D1.3 Technology Knowledge Base and Observatory

Ref. Ares(2017)5327673 - 31/10/2017

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Grant Agreement No 636148.

Project Title: Optimodal European Travel Ecosystem Acronym: EuTravel Start date of project: 01/05/2015 Duration: 30M Due date of deliverable: 30/04/2016 Actual submission date (version v.1.0): 23/11/2016 Resubmission date: (version v.2.0): 30/10/2017 Organisation name of lead contractor for this deliverable: NCSRD Final [v 2.0]

Dissemination Level Public, fully open PU 

Confidential, restricted under conditions set out in Grant Agreement to CO  consortium members and the Commission Services.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 Table of Contents

1. EXECUTIVE SUMMARY ...... 11 2. OBJECTIVES OF WORK-PACKAGE AND TASK ...... 12 3. CLASSIFICATION OF ITS TECHNOLOGIES AND EUTRAVEL FOCUS ...... 14 4. STATE OF THE ART OVERVIEW OF KEY TECHNOLOGIES (EUTRAVEL FOCUS) ...... 16

4.1 INTRODUCTION ...... 16 4.2 JOURNEY PLANNERS ...... 16 4.2.1 Knowledge Based Travel Planners - Travel Recommender Systems (TRS) ...... 17 4.2.2 Personalized Collaborative Recommendations ...... 18 4.2.3 Current Travel Recommender Systems ...... 20 4.2.4 Multi-stage and multi decision travel recommenders ...... 20 4.2.5 Collaborative filtering approaches for travel recommendation ...... 21 4.2.6 Software agent based systems for travel advice ...... 21 4.3 OPTIMISATION - ROUTE SEARCH ALGORITHMS AND THE MULTI OBJECTIVE PATH SEARCH PROBLEM ...... 22 4.4 LOCATION AND CONTEXT AWARE SERVICES FOR TRAVELLERS ...... 24 4.4.1 Geolocation services for travel routing ...... 25 4.5 E-PAYMENT SOLUTIONS ...... 28 4.6 MOBILE & WEARABLE TRAVEL TECHNOLOGY ...... 30 4.7 TRAVEL APIS ...... 33 4.8 TASK MODELS AND ONTOLOGIES FOR TRAVELLERS ...... 35 4.8.1 Travel & Traveller Knowledge Representation - Travel Ontologies ...... 36 4.8.2 Schema extension for Travel Domain ...... 41 4.8.3 Semantic enrichment of travel and tourism data and systems - Semantic annotations ...... 42 4.8.4 Semantic search for travel portals / travel planners ...... 43 4.9 CLOUD COMPUTING, CLOUD-BASED ENTERPRISE SYSTEMS AND VIRTUALISATION ...... 43 4.10 CUSTOMER RELATIONSHIP MANAGEMENT – USER PROFILING ...... 47 4.11 BIG DATA PROCESSING AND ANALYTICS ...... 47 4.12 CURRENT LIMITATIONS IDENTIFIED AND EUTRAVEL APPROACH ...... 50 4.12.1 Journey Planners...... 50 4.12.2 Optimisation Route search algorithms and the multi objective path search problem ...... 51 4.12.3 Travel Recommender systems and Geolocation techniques...... 53 4.12.4 Travel APIs ...... 54 4.12.5 e-payment solutions ...... 56 4.12.6 Task models and travel ontologies ...... 56 4.12.7 User Profiling ...... 56 4.12.8 Big Data processing and analytics ...... 57 4.13 DISCUSSION ON RESULTS AND SELECTION OF TECHNOLOGIES TO BE USED AND TO BE MONITORED (TECHNOLOGIES LIBRARY) 58 5. ITS DEVELOPMENTS ACROSS EUROPE AND REFERENCE PROJECTS ...... 62 5.1 OPTI-TRANS ...... 62 5.2 WISETRIP ...... 63 5.3 SHIFT2RAIL (S2R) ...... 64 5.4 IT2RAIL ...... 66 5.5 TAP-TSI ...... 67 5.6 FULL SERVICE MODEL INITIATIVE (FSM) ...... 68 5.7 COOPERATIVE CITIES (CO-CITIES) ...... 69 5.8 OPENTRANSPORTNET ...... 70 5.9 MOBINET ...... 70 5.10 MODELS FOR OPTIMISING DYNAMIC URBAN MOBILITY (MODUM) ...... 70 5.11 STREETLIFE ...... 71 5.12 DESIGN FOR ECO-MULTIMODAL MOBILITY (DECOMOBIL) ...... 71 5.13 COLOMBO ...... 71

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

5.14 EUROPEAN DIGITAL TRAFFIC INFRASTRUCTURE NETWORK FOR INTELLIGENT TRANSPORT SYSTEMS (EDITS) ...... 72 5.15 CIVITAS (2MOVE2) ...... 72 5.16 POSSE (PROMOTING OPEN SPECIFICATIONS AND STANDARDS IN EUROPE) ...... 73 5.17 ECOMPASS ...... 73 5.18 TRANSFORUM ...... 74 5.19 COMPASS ...... 75 5.20 ONTIME ...... 76 5.21 INSTANT MOBILITY ...... 77 5.22 ALL WAYS TRAVELLING (AWT) ...... 78 5.23 1ST SMART MOBILITY CHALLENGE ...... 81 5.24 OPTICITIES ...... 81 5.25 NEW TOOLS FOR DESIGN OF URBAN TRANSPORT INTERCHANGES (NODES) ...... 83 5.26 INTERCONNECTION BETWEEN SORT AND LONG DISTANCE TRANSPORT NETWORKS (INTERCONNECT) ...... 83 5.27 INTELLIGENT TRANSPORT SYSTEM FOR OPTIMISED URBAN TRIPS (I-TOUR) ...... 84 5.28 TOURPACK ...... 85 5.29 BYTE ...... 86 5.30 LDCT ...... 86 6. ONGOING RELATED ITS CLUSTER HORIZON 2020 PROJECTS ...... 87

6.1 MAAS4EU ...... 87 6.2 BONVOAYAGE ...... 88 6.3 COOPERATIVE ITS DEPLOYMENT COORDINATION SUPPORT (CODECS) ...... 88 6.4 DOOR TO DOOR INFORMATION FOR AIRPORT AND AIRLINES (DORA) ...... 88 6.5 EUROPEAN TRAVELLERS CLUB (ETC) ...... 88 6.6 ITS OBSERVATORY ...... 89 6.7 MOBILITY BASED ON AGGREGATION OF SERVICES AND APPLICATIONS INTEGRATION (MASAI) ...... 89 6.8 MULTI-SOURCE BIG DATA FUSION DRIVEN PROACTIVITY FOR INTELLIGENT MOBILITY (OPTIMUM) ...... 89 6.9 OPEN SOCIAL TRANSPORT NETWORK FOR URBAN APPROACH TO CARPOOLING (SOCIALCAR) ...... 89 6.10 ENHANCED REAL TIME SERVICES FOR OPTIMIZED MULTIMODAL MOBILITY (TIMON) ...... 90 7. EUTRAVEL KNOWLEDGE BASE AND OBSERVATORY ...... 91

7.1 ONLINE EUTRAVEL OBSERVATORY ...... 91 7.2 EUTRAVEL OBSERVATORY SYSTEM – USER VIEW ...... 92 7.2.1 How to login ...... 92 7.2.2 Main Page ...... 93 7.2.3 Dropdown Lists ...... 93 7.2.4 Upload Files ...... 94 7.2.5 Navigation Tree ...... 95 7.2.6 Glossary Terms ...... 97 7.2.7 Events ...... 98 7.2.8 Journals ...... 98 7.2.9 Experts ...... 99 7.3 EUTRAVEL OBSERVATORY SYSTEM – ADMIN VIEW ...... 101 7.3.1 How to login ...... 101 7.3.2 Main Page ...... 101 7.3.3 Dropdown Lists ...... 102 7.3.4 Upload Files ...... 102 7.3.5 Modules ...... 103 7.3.6 Templates ...... 105 7.3.7 Navigate Tree...... 106 7.3.8 Subject Categories ...... 108 7.3.9 Glossary Terms ...... 111 7.3.10 Events ...... 112 7.3.11 Journals ...... 113 7.3.12 Experts ...... 113 7.3.13 Registrations ...... 114 7.4 EUTRAVEL OBSERVATORY – PUBLIC SITE ...... 115 7.4.1 Welcome Page ...... 115 7.4.2 Subject Info Page ...... 119

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

8. CONCLUSIONS ...... 123 9. REFERENCES ...... 124 10. ANNEX 1 ...... 132

10.1 SERVICE AGGREGATION APIS ...... 132 10.2 SINGLE SERVICE PROVIDER APIS ...... 133 10.3 TRAVEL RELATED INFORMATION APIS ...... 134 10.4 TRAVEL ITINERARY PLANNING APIS ...... 135 10.5 TRAVEL COLLABORATION APIS ...... 136

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 Document Summary Information

Abstract

EuTravel aims to support the EU agenda towards an open and single market for mobility services by enabling travellers to organise a multimodal trip in accordance with their own criteria including environmental performance and providing multimodal travel service providers an effective way to deliver customised services. Optimodal travel implies that itineraries are constructed according to user preferences including environmental performance and providing a seamless end-user experience.

The project demonstrates a way to present to travellers what their options are when they want to go from location A to location B in a way that does not penalise or ignore some options in favour of others and secondly allow them to book and manage all the legs of their trip from within a single application. The case of people with mobility problems is also taken into account to the design of the EuTravel solutions. Key to the realisation of the projects’ vision is the EuTravel Optimodality Framework, which integrates processes, data, and systems in a manner that eliminates interoperability barriers. The proof of concept of the framework is realised through the implementation of the Optimodality platform, which is the backbone of the EuTravel ecosystem, an open innovation foundation that promotes openness, scalability and easy participation for transport and travel stakeholders. The platform enables travel and transport organisations to easily publish content and develop both business-to-business and business-to-consumer distribution services, enabling travellers to make an informed choice, using multiple modes of transport. Key part of the platform is the “Super Travel API” or “API of APIs” which helps overcoming interoperability barriers in the transportation and travel-related industry. To realize the “API of APIs”, EuTravel developed a Common Information Model (CIM) for the travel domain and the semantic version of it i.e. the EuTravel Unifying Ontology. These artefacts are providing the foundation for the EuTravel ecosystem solution delivering a unifying, global view over a multitude of travel APIs and formats and enabling seamless integration of European travel data and services. This report identifies leading edge technologies, passenger travel related ITS developments, reference projects and initiatives, consolidated in the initial project knowledge base, leading to the selection of technologies used in developing the EuTravel solutions. This research is documented herein and resulted in a collection of technologies and projects to be published via the EuTravel Technology Knowledge Base and Observatory web portal. From optimization algorithms to travel recommendation systems, the report gives an overview of the technologies needed in order to develop Optimodal processes and services in the context of EuTravel. Reference projects provide a baseline knowledge-base for further research in EuTravel in terms of identified issues to be addressed. The EuTravel Knowledge Base and Observatory, presents the selected technologies and related projects via the web portal throughout the duration of the project and beyond.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Keywords Intelligent Transportation Systems, Journey Planning, Ontologies

Authors and contributors

Initials Name Organisation Role EG Eftichia Georgiou NCSRD Lead Author NA Nikos Argyreas NCSRD Author SC Stelios Christofi eBOS Author KP Kyriakos Petrou eBOS Author IF Ioanna Fergadioti INLECOM Author GT Georgia Tsiochantari INLECOM Author SE Spyros Evangelatos INLECOM Author DG David Griffiths BMT Author BK Bill Karakostas VLTN Author IT Ioan Toma STI Author

Quality control Role Who Date Deliverable leader EG 12.04.2016 Quality Manager DG 30.04.2016 Project manager IF 22.11.2016, 28/02.2017, 30/10/2017

Disclaimer The content of the publication herein is the sole responsibility of the publishers and it does not necessarily represent the views expressed by the European Commission or its services. While the information contained in the documents is believed to be accurate, the authors(s) or any other participant in the EuTravel consortium make no warranty of any kind with regard to this material including, but not limited to the implied warranties of merchantability and fitness for a particular purpose. Neither the EuTravel Consortium nor any of its members, their officers, employees or agents shall be responsible or liable in negligence or otherwise howsoever in respect of any inaccuracy or omission herein. Without derogating from the generality of the foregoing neither the EuTravel Consortium nor any of its members, their officers, employees or agents shall be liable for any direct or indirect or consequential loss or damage caused by or arising from any information advice or inaccuracy or omission herein.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 Abbreviations

API Application Programming Interface BPaaS Business Process as a Service CER Community of European Railway and Infrastructure Companies C-ITS Cooperative Intelligent Transportation Systems CRS Computer Reservation System DMS Destination Management Systems IaaS Infrastructure as a Service ITS Intelligent Transportation Systems TRS Travel Recommender System CEN European Committee for Standardization CENELEC European Committee for Electro-technical Standardisation CER Community of European Railway and Infrastructure Companies CIM Common Information Model CRM Customer Relationship Management CRS Computer Reservation System DaaS Information/Data as a Service EA Evolutionary algorithm ETSI European Telecommunications Standards Institute FSM Full Service Model GA Genetic Algorithm GDS Global Distribution System GNSS Global Navigation Satellite System GPS Global Positioning System GTFS General Transit Feed Specification ICT Information and Communications Technology IR Infrared Radiation ITIF Information Technology & Information Foundation ITS Intelligent Transport Systems KPI Key Performance Indicator MMTIPs Multimodal Travel Information and Planning Services OTA Online Travel Agent OWL Web Ontology Language

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

PaaS Platform as a Service POI Point of Interest PT Public Transportation RF Radio Frequency RSSI Received Signal Strength Indicator SaaS Software as a Service SERA Single European Rail Area SCORM Sharable content object reference model SMIL Synchronized Multimedia Integration Language TAP Telematics Applications for Passenger services TDoA Time Difference of Arrival ToA Time of Arrival TRS Travel Recommender Systems TSA Travel Service Advisor TSI Technical Specification for Interoperability WG Working Group XML eXtensible Markup Language

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 List of Figures

FIGURE 2.1: WP1 DELIVERABLES RELATIONSHIP ...... 12 FIGURE 2-2: WORKPLAN RATIONAL ...... 13 FIGURE 4.1: SEASONAL GROWTH OF MOBILE BOOKINGS. SOURCE: CRITEO: TRAVEL. FLASH REPORT. SEPTEMBER 2014...... 30 FIGURE 4.2: INITIAL CLASSIFICATION OF TRAVEL RELATED APIS ...... 34 FIGURE 4.3: THE CLASSES IN TRAVEL ONTOLOGY ...... 35 FIGURE 4.4: CLASSES OF TRAVEL ONTOLOGY FROM SWAT PROJECT ...... 36 FIGURE 4.5: CLASSES OF GTFS ...... 37 FIGURE 4.6: CLASSES OF TRAVEL BUSINESS ONTOLOGY FROM TAGA ...... 38 FIGURE 4.7: CLASSES OF TRAVEL ONTOLOGY FROM TRAVEL GUIDES ...... 39 FIGURE 4.8: CLASSES OF KM4C ...... 40 FIGURE 4.9: MOVEACTION PLAN OF SCHEMA.ORG ...... 41 FIGURE 4.10: RELATED CLASSES FOR MEANS OF TRANSPORTATION ...... 42 FIGURE 4.11: RELATED CLASSES FOR RELATIVELY SHORT STAYS IN BETWEEN MOVEMENTS ...... 42 FIGURE 4-12 : SUPPORTED MODES OF TRANSPORT OF EXISTING TRAVEL PLANNERS ...... 50 FIGURE 4-13 : SUPPORTED CAPABILITIES OF EXISTING TRAVEL PLANNERS ...... 51 FIGURE 4.14: SEMANTICS TRANSFORMATION COMPONENT ...... 58 FIGURE 4.15: DATA FUSION COMPONENT ...... 59 FIGURE 4.16: SEMANTIC GRAPH COMPONENT ...... 59 FIGURE 4.17: RELATED CLASSES FOR MEANS OF TRANSPORTATION ...... 60 FIGURE 4.18: INDICATIVE USE CASE WORKFLOW ...... 60 FIGURE 5.1: SHIFT2RAIL – INNOVATION PROGRAMMES ...... 65 FIGURE 5.2: FSM WORKING GROUPS ...... 69 FIGURE 5.3: AWT FRAMEWORK [121] ...... 79 FIGURE 5.4: AWT WORKFLOWS [121] ...... 80 FIGURE 5.5: EARLY EUTRAVEL ARCHITECTURE DESIGN (1) (2015) ...... 80 FIGURE 5.6: EARLY EUTRAVEL ARCHITECTURE DESIGN (2) (2015) ...... 81 FIGURE 7.1: KNOWLEDGE PLATFORM...... 91 FIGURE 7.2: SPECIFIC TOPIC IN OBSERVATORY - STANDARDISATION ...... 92 FIGURE 7.3: SPECIFIC TOPIC IN OBSERVATORY – KEY TECHNOLOGIES ...... 92 FIGURE 7.4: EUTRAVEL OBSERVATORY ADMIN - LOGIN PAGE ...... 93 FIGURE 7.5: EUTRAVEL OBSERVATORY ADMIN - MAIN PAGE...... 93 FIGURE 7.6: EUTRAVEL OBSERVATORY ADMIN - DROPDOWN LIST ...... 93 FIGURE 7.7: EUTRAVEL OBSERVATORY ADMIN - UPLOAD AND DOWNLOAD FILE BUTTONS ...... 94 FIGURE 7.8: EUTRAVEL OBSERVATORY ADMIN - UPLOAD FILE POPUP ...... 94 FIGURE 7.9: EUTRAVEL OBSERVATORY ADMIN - NAVIGATE TREE ...... 95 FIGURE 7.10: EUTRAVEL OBSERVATORY ADMIN - NAVIGATE TREE ACTIONS ...... 96 FIGURE 7.11: EUTRAVEL OBSERVATORY ADMIN - SUBJECT INFO FORM ...... 96 FIGURE 7.12: EUTRAVEL OBSERVATORY ADMIN - GLOSSARY TERMS FORM ...... 97 FIGURE 7.13: EUTRAVEL OBSERVATORY ADMIN - GLOSSARY COMMENTS ...... 98 FIGURE 7.14: EUTRAVEL OBSERVATORY ADMIN - EVENTS FORMS ...... 98 FIGURE 7.15: EUTRAVEL OBSERVATORY ADMIN - JOURNALS ...... 99 FIGURE 7.16: EUTRAVEL OBSERVATORY ADMIN - EXPERTS ...... 100 FIGURE 7.17: EUTRAVEL OBSERVATORY ADMIN - LOGIN PAGE ...... 101 FIGURE 7.18: EUTRAVEL OBSERVATORY ADMIN - MAIN PAGE ...... 102 FIGURE 7.19: EUTRAVEL OBSERVATORY ADMIN - DROPDOWN LIST ...... 102 FIGURE 7.20: EUTRAVEL OBSERVATORY ADMIN - UPLOAD AND DOWNLOAD FILE BUTTONS ...... 102 FIGURE 7.21: EUTRAVEL OBSERVATORY ADMIN - UPLOAD FILE POPUP ...... 103 FIGURE 7.22: EUTRAVEL OBSERVATORY ADMIN - EDIT MODULE ...... 103 FIGURE 7.23: EUTRAVEL OBSERVATORY ADMIN - PORTAL MODULES ...... 104 FIGURE 7.24: EUTRAVEL OBSERVATORY ADMIN - MODULE ON EUTRAVEL PORTAL ...... 104 FIGURE 7.25: EUTRAVEL OBSERVATORY ADMIN - PORTAL TEMPLATES ...... 105 FIGURE 7.26: EUTRAVEL OBSERVATORY ADMIN - TEMPLATES' FORM ...... 105 FIGURE 7.27: EUTRAVEL OBSERVATORY ADMIN - NAVIGATE TREE ...... 106 FIGURE 7.28: EUTRAVEL OBSERVATORY ADMIN - NAVIGATE TREE ACTIONS ...... 106 FIGURE 7.29: EUTRAVEL OBSERVATORY ADMIN - SUBJECT INFO FORM ...... 107

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

FIGURE 7.30: EUTRAVEL OBSERVATORY ADMIN - SUBJECT CATEGORIES ...... 108 FIGURE 7.31: EUTRAVEL OBSERVATORY ADMIN - EDIT SUBJECT CATEGORY ...... 108 FIGURE 7.32: EUTRAVEL OBSERVATORY ADMIN - SUBJECT AREAS ...... 109 FIGURE 7.33: EUTRAVEL OBSERVATORY ADMIN - EDIT SUBJECT AREAS ...... 109 FIGURE 7.34: EUTRAVEL OBSERVATORY ADMIN - SUBJECT TOPICS ...... 110 FIGURE 7.35: EUTRAVEL OBSERVATORY ADMIN - SUBJECT INFO ...... 110 FIGURE 7.36: EUTRAVEL OBSERVATORY ADMIN - EDIT SUBJECT TOPIC ...... 110 FIGURE 7.37: EUTRAVEL OBSERVATORY ADMIN - GLOSSARY TERMS FORM ...... 111 FIGURE 7.38: EUTRAVEL OBSERVATORY ADMIN - GLOSSARY COMMENTS ...... 112 FIGURE 7.39: EUTRAVEL OBSERVATORY ADMIN - EVENTS FORM ...... 112 FIGURE 7.40: EUTRAVEL OBSERVATORY ADMIN - JOURNALS ...... 113 FIGURE 7.41: EUTRAVEL OBSERVATORY ADMIN - EXPERTS ...... 114 FIGURE 7.42: REGISTRATIONS FORM ...... 114 FIGURE 7.43: EUTRAVEL OBSERVATORY - WELCOME PAGE ...... 115 FIGURE 7.44: EUTRAVEL OBSERVATORY - CUSTOMISED HOMEPAGE ...... 116 FIGURE 7.45: EUTRAVEL OBSERVATORY - EDIT MODULES ...... 116 FIGURE 7.46: EUTRAVEL OBSERVATORY - ADD/REMOVE TOPICS ...... 117 FIGURE 7.47: EUTRAVEL OBSERVATORY - DRAG AND DROP MODULES (BEFORE) ...... 118 FIGURE 7.48: EUTRAVEL OBSERVATORY - DRAG AND DROP MODULES (AFTER) ...... 118 FIGURE 7.49: EUTRAVEL OBSERVATORY – SUBJECT INFO WEBPAGE (A) ...... 119 FIGURE 7.50: EUTRAVEL OBSERVATORY – SUBJECT INFO WEBPAGE (B) ...... 120 FIGURE 7.51: EUTRAVEL OBSERVATORY - EUTRAVEL INDEX TREE ...... 120 FIGURE 7.52: EUTRAVEL OBSERVATORY - LOGIN BUTTON ...... 121 FIGURE 7.53: EUTRAVEL OBSERVATORY - LOGIN FORM ...... 121 FIGURE 7.54: EUTRAVEL OBSERVATORY - SEARCH RESULTS ...... 122

List of Tables

TABLE 2-1: DELIVERABLE’S ADHERENCE TO EUTRAVEL WORK PLAN ...... 13 TABLE 4-1: GEOLOCATION TECHNIQUES ...... 26 TABLE 4-2: WORLDWIDE WEARABLE DEVICE SHIPMENTS, YEAR-OVER-YEAR GROWTH AND CAGR BY PRODUCT CATEGORY, 2014, 2015, AND 2019 (UNITS IN MILLIONS), SOURCE: INTERNATIONAL DATA CORPORATION (IDC) WORLDWIDE QUARTERLY WEARABLE DEVICE TRACKER ...... 30 TABLE 4-3: EUTRAVEL ECOSYSTEM PARTICIPANTS ...... 33 TABLE 4-4: IMPORTANT ASPECTS IN TRAVEL DOMAIN...... 41

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

1. Executive Summary

New technologies and models of transportation service delivery transform the way people plan their travel and move around the globe and within cities. Mobility needs and patterns evolve fast and new transport and travel services emerge. New intermodal and multimodal services in passenger transport are offered by mobility service providers by either organising the transport chain for the users or by providing the means to users to organise their own journeys [1]. On the other hand, transportation technologies aim to become more environmentally-efficient. The existing transport sector's structure and governance is challenged, calling for changes in technology adoption, business processes and the regulatory framework.

Intelligent Transport Systems (ITS) is being identified as a domain of high potential to tackle many challenges in the Transport sector both within each of the modes and most importantly in creating interfaces and facilitating integration across the modes [2]. ITS describe information and communication technologies applied to transport and infrastructure to transfer information between systems for improved safety, productivity, environmental performance and mobility management. This includes stand-alone applications such as traffic management systems, travel information management systems, systems installed in individual vehicles, as well as cooperative ITS (C-ITS) applications involving vehicle to infrastructure and vehicle-to-vehicle communications.

EuTravel research focuses on technologies related to advanced Travel Information Services, thus technologies adopted to enable well-informed travel decisions (pre-trip) and information provision during the journey. This category involves also route optimisation algorithms. On the other hand, technologies facilitating modes integration and the realisation of intelligent transport networks (ecosystems) managed with data, such as existing APIs have been examined. Last, data and insight (knowledge discovery) technologies have been considered for the development of added value services for all travel stakeholders.

This report suggests a classification of ITS technologies in order to identify the EuTravel focus areas from a technology perspective (Chapter 3), identifies related leading-edge technologies (Chapter 4), passenger travel related ITS developments, reference projects and initiatives across Europe (Chapters 5 & 6) consolidated in the initial project knowledge base of technologies used and monitored.

This report is complemented by the online knowledge base and observatory (Chapter 7) which can be viewed at: http://www.eutravelproject.eu/Observatory.

The report elaborates on reference project’s outcomes, and current limitations of existing technologies within the scope of EuTravel (library of related technologies) and discusses further work envisioned in the project that advances the state-of the-art. The way these technologies are utilised within the project, is elaborated in the technical deliverables:

D1.4 EU Optimodality Framework D2.1 Technology Ecosystem Architecture D2.2 Ecosystem Specification and Prototype Implementation D2.3 One-stop, cross-device multilingual interface D2.4 EuTravel Value Added Services D3.2 Living Lab Setup

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

2. Objectives of work-package and task

The overall objective of WP1 is to ensure that the research and development undertaken in EuTravel is driven by stakeholder needs and requirements for achieving the EuTravel objectives, taking into account technology advancements in the travel and transport industry and key reference projects and research initiatives.

The key outcome of WP1 is the Optimodality Framework, which sets the principles of the work carried out in all other work packages, taking into account existing technology drives and opportunities on the one side, and the stakeholder’s capacity, priorities and constraints on the other. This deliverable is complementary to deliverables 1.1 and 1.2; all three deliverables will contribute to the Optimodality Framework development (Figure 2.1).

Figure 2.1: WP1 deliverables relationship

This report consolidates the research outcomes of Task 1.3: Technology assessment (ST1.3.1 Produce classification of key technologies for each stakeholder group, ST1.3.2 Technology review and selection of technologies to be used and to be monitored), and builds the EuTravel Knowledge Base and Observatory, presenting in the deliverable and online a library of leading edge technologies (ST1.3.3 Develop a library on selected technologies), monitored through the online knowledge base during the lifetime of the project (ST1.3.4 Set up the EuTravel observatory).

The deliverable is closely related to Task T1.4 Optimodality Framework and Impact Assessment which sets the co-operation framework between interacting parties and incentivises, and describes the Common Information Model (CIM) for the travel domain and the semantic version of it i.e. the EuTravel Unifying Ontology. It is also linked to all deliverables of WP2 (see Figure 2-2) which defines the architecture, methods and services establishing the EuTravel ecosystem, and to task T3.3 Living Lab operation learning, refinements and reporting, that will conclude learning outcomes and conclusions of the testing and validation of the solutions, which will be published via the Technology Knowledge Base and Observatory web portal. Besides the technologies and the

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Knowledge Base Observatory, the document includes an extensive report on past and ongoing projects which served as a knowledge baseline for EuTravel.

Figure 2-2: Workplan Rational

The following section is extracted from the project’s Description of Action (DoA) and demonstrates how each sub task of T1.3 Technology assessment, EuTravel Knowledge Base and Observatory is addressed in this deliverable.

Table 2-1: Deliverable’s adherence to EuTravel Work Plan Main sub-task activities as described in DoA Document Reference ST1.3.1 Produce classification of key technologies Chapter 3: Classification of ITS for each stakeholder group (T1.1) (NCSRD, BMT). technologies and EuTravel focus ST1.3.2 Technology review and selection of Chapter 4: State of the Art Overview of Key technologies to be used and to be monitored Technologies (EuTravel focus) (NCSRD, BMT, VLTN, STI; review workshop ILS). For review workshop see Section 4.12: Current limitations identified and EuTravel approach ST1.3.3 Develop a library on selected technologies Section 4.13 Discussion on results and (NCSRD). selection of technologies to be used and to be monitored (Technologies Library)

ST1.3.4 Set up the EuTravel observatory based on Chapter 7: EuTravel Knowledge Base and assigning team members to monitor specific Observatory including entries on: initiatives, projects and technologies and on Section 5.3 Shift2Rail automatic acquisition of relevant content (EBOS, Section 5.5 TAP-TSI EUL and contribution by the other Task Participants). Initiatives to be monitored from the outset will be TAP-TSI and SHIFT²RAIL.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

3. Classification of ITS technologies and EuTravel focus

Emerging technology trends in the travel and transportation industry can be seen in areas such as: • Smart infrastructures, including sensors and devices that allow more efficient capacity and traffic management. • Travel information management, including a. digital and social, personalised engagement with customers using online interactive channels in real time, b. Smart payment services so travellers can quickly board services or validate an entitlement without managing multiple cards or accounts; c. Mobility-as-a-Service platforms that facilitate shared or personal transport on demand, d. Dynamic demand management systems that help match capacity with demand. • Data and insight technologies, including advanced analytics and real-time decision support tools that generate insights from smart network infrastructure and customer service systems. • Vehicle technologies, including connected and automated vehicles, personal mobility devices that offer new options for first- and last-mile travel and alternatively fuelled vehicles.

The above information and communication technologies (Intelligent Transport Systems - ITS), are applied to transport and infrastructure to transfer information between systems for improved safety, productivity, environmental performance and mobility management. Several approaches in classifying ITS technologies and their applications exist.

The ITS Directive [3] priority areas include: 1 Optimal Use of road traffic and travel data 2 Continuity of traffic and freight management ITS Services 3 ITS road safety and security applications 4 Linking the vehicle with the transport infrastructure

Priority Action A of the ITS Directive the European Commission has specified the requirements for making “EU-wide multimodal travel information services accurate and available across borders to ITS users” in terms of availability of information and data, facilitating electronic data exchange between stakeholders across borders, and timely updating of information as well as the need for equitable rights to access, use and present data.

Furthermore, the recent EU delegated Regulation of the 31st of May 2017, supplementing Directive 2010/40/EU of the European Parliament and of the Council with regard to the provision of EU-wide multimodal travel information services [139], sets the necessary requirements to make EU-wide multimodal travel information services accurate and available across borders. The regulation establishes the specifications necessary to ensure the accessibility, exchange and update of travel and traffic data and distributed journey planning for the provision of multimodal information services in the European Union. The Annex introduces the categorisation of transport modes in scheduled (air, rail including high speed rail, conventional rail, light rail, long-distance coach, maritime including ferry, metro, tram, bus, trolley-bus), demand-responsive (shuttle bus, shuttle ferry, taxi, car-sharing, car-pooling, car-hire, bike-sharing, bike-hire) and personal (car, motorcycle, cycle). In the same Annex, related data are categorised in static travel data and dynamic travel and traffic data, while three different service levels are defined. Member States that are prompted to start digitising static and dynamic travel and traffic information of different transport modes that can be used for multimodal travel information services are encouraged to start with the data defined in level of service 1.The AECOM Study on KPIs for ITS [4], also discussed in deliverable D1.1: EuTravel Stakeholder Requirements Specification, introduces a hierarchical taxonomy of ITS, mapping the ITS priority areas to 2DECIDE [5] categories and categories introduced in PIARC ITS handbook (2011) [6] Handbook on Intelligent Transport Systems.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

ERTICO’s taxonomy as implemented in the ITS Observatory [7] identifies the following ITS application domains: 1 Traveller Information 2 Traffic management & control 3 Freight & logistics 4 Smart vehicles 5 Mobility services 6 Public transport

Alberta Transportation (2014) divides ITS applications into the following major functional categories: 1 Traveller Information Services 2 Traffic Management Services 3 Public Transport Services 4 Commercial Vehicle Operations 5 Electronic Payment Services 6 Vehicle Safety and Control Systems 7 Information Warehousing Services

The Information Technology & Information Foundation (ITIF) categorizes ITS applications into five primary groups: 1 Advanced Traveller Information Systems 2 Advanced Transportation Management Systems 3 ITS-enabled Transportation Pricing Systems 4 Advanced Public Transportation Systems 5 Fully integrated ITS Systems

EuTravel focuses on technologies related to advanced Travel Information Management, thus technologies adopted to enable well-informed travel decisions (pre-trip) and information provision during the journey (on-trip). This category involves also route optimisation algorithms. On the other hand, technologies facilitating modes integration and the realisation of intelligent transport networks (ecosystems) managed with data have been also examined. Data and insight (knowledge discovery) technologies have been considered for the development of added value services for all travel stakeholders. In that terms, EuTravel mostly monitors advancements in the highlighted ITS categories above.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

4. State of the Art Overview of Key Technologies (EuTravel focus)

4.1 Introduction Effective travel information systems have an obvious and very significant role for both travellers and operators. Operators to run their systems and reduce the costs involved when interacting with travellers, while travellers are enabled to: • Make easy, well-informed transport choices based on their personal needs and preferences. • Have more transport services delivered more reliably. • Get from door to door more easily with flexible transport connections and seamless transfers. • Fulfil their mobility needs efficiently and sustainably. • Manage their mobility costs and pay for services simply and conveniently.

Delivering a personalised transport experience requires a new era of highly interactive customer service attuned to each person’s individual patterns of mobility and individual preferences. There is a growing need for systems that provide tailored journey plans, early disruption notifications, and trip advice that reflects location, time of day, and the customer’s own travel preferences. Sections 4.2 - 4.6 present an overview of the state-of-the art in advanced Travel Information Services and related ICT applications and solutions. Section 4.7 presents a landscape of APIs for the travel industry. Section 4.8 focus on semantics and the role of ontologies in developing travel services. For completion, the other sections of Chapter 4 present advancements in data and insight (knowledge discovery) technologies related to travel. Section 4.12-Current limitations identified and EuTravel approach, summarises the current limitations in technologies within the scope of EuTravel and envisioned advancements in alignment with the EuTravel approach and the DoA.

4.2 Journey Planners Journey planners have been widely used in the travel industry since the 1970s by booking agents accessed through a user interface on a computer terminal, in order to support call center agents providing public transport information. A multimodal journey planner is an IT system able to propose a set of one or more transport services answering at least the question “How can I go from location A to location B at a given departure/arrival date and time and under which conditions”. The most common point of access is via a specific web service.

Many Journey planners are already available on the Internet providing a wide variety of services in terms of geographical convergence, modes used, multimodality, type of information used, media used, itinerary planning capabilities. The development tendencies that influence the quality of journey planning are the following:

• Multimodality, • Real-time data, • Location based services, • Personal preferences.

The evaluation study of multimodal Journey Planners conducted by Domokos Esztergar – Kiss and Csaba Csiszar [8] considering a) urban journey planners such as the Hungarian BKV, the TfL in London, the RATP in Paris and the Austrian AnachB, b) railway journey planners such as the Hungarian Elvira, Raileurope, the system of the German railways (DB) and the solution of the Austrian railways (ÖBB), called SCOTTY, c) low-cost and service-independent solutions airline journey planners such as Wizzair, Lufthansa and Skyscanner, and d) systems with international

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 relations and multimodal planning options such as the German Bayerninfo, the French Eco- comparateur, the EU-Spirit (its realization is VBB), the Swiss RouteRANK and the international WiseTrip, indicated that: • multimodality is rather typical for the journey planners, • real-time data and personalized preferences turn up only partially and, • location based services are mostly missing.

Existing commercial systems for journey planning are adequately providing such services i.e. at a regional level (e.g. within a city) or on the basis of a single transport mode, but the combination of multilevel information at a wider scale and the delivery of dynamic personalised data has not been yet properly addressed.

A more theoretical approach on journey planners’ characteristics supports that transferability is highly desired. To achieve transferability, the initial design must take into account all factors that may diverge between locations, including existing modes of transport, the availability of required data, the technological habits of users, etc. In consequence, a highly transferable system is difficult and expensive to develop and maintain. A very flexible initial design, one ensuring low-cost adaptability of the system for different cities, regions, or countries, might not be cost-effective. The process of changeability assessment (e.g., transferability) is examined in light of the goals of journey planning from the point of view of different stakeholders: travellers, private developers, and transport authorities. The analysis demonstrates how tradespace exploration [9] can also be used to identify specific designs that bridge the gap between the public and private sectors and provide value over time to all parties. Moreover, when specific concerns of public authorities are not met, tradespace exploration can reveal measures the public sector can take (financial or others) for making their preferred design attractive to the private sector as well.

Another key factor regarding journey planner’s performance is network analysis. An innovative method was conducted predicting the distribution of passenger throughput across stations and lines of a city rapid transit system by calculating the normalized betweenness centrality of the nodes (stations) and edges of the rail network. The method is evaluated by correlating the distribution of betweenness centrality against throughput distribution which is calculated using actual passenger ridership data. The correlation is improved significantly when the data points are split according to their separate lines, illustrating differences in the intrinsic characteristics of each line. The aforementioned simple procedure shows that static network analysis of the structure of a transport network [10] can allow transport planners to predict with sufficient accuracy the passenger ridership, without requiring dynamic and complex simulation methods.

4.2.1 Knowledge Based Travel Planners - Travel Recommender Systems (TRS) Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. The suggestions provided are aimed at supporting their users in various decision- making processes, such as what items to buy, what music to listen, or what news to read. In the travel domain, capturing the feedback of the user along with analytics on the travel planners use and preferences, makes it possible for a knowledge base to be constructed. Therefore, there can be a single point of reference in case a new request reaches the journey planner core algorithm in order to return a personalized and customized reply/solution.

One of the key factors to evaluate the recommendation algorithm is the accuracy. If the recommendation list made by the system is very different from the users’ interests, the users will lose his/her confidence in the system and probably ignore the future information provided by the system. The system makes recommendations based on the users’ records, which should be as personalized as possible so that the users’ requirements can be sufficiently satisfied.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

To examine the potential of such a system, the casual relationship between controlled factors, which are the independent variables, and multiple analyzed responses, which are the dependent variables, were identified and measured. A number of controlled factors were identified that were relevant to the evaluation of an expert system for the TRS. The factors which also can be defined as key components of an expert system are: Multi-Dimensional Coverage, Experience, Filtering Methods and a Complexity of a Task. Each of these factors were set at only two extreme values, a low value (-1) and a high value (+1), as the experimental designs is to test for the significance of main effects and combinations of main effects. Using comparatively few treatment runs, the researcher determined which factor or factors cause significant changes in the performance measure.

In tourism recommendation systems, the number of users and items is very large. But traditional recommendation system uses partial information for identifying similar characteristics of users. Collaborative filtering is the primary approach of any recommendation system. It provides a recommendation, which is easy to understand. It is based on similarities of user opinions like rating or likes and dislikes. So the recommendation provided by collaborative cannot be considered as quality recommendation. Recommendation after association rule mining is having high support and confidence level. So that will be considered as strong recommendation. The hybridization of both collaborative filtering and association rule mining can produce strong and quality recommendation even when sufficient data are not available. This paper combines recommendation for tourism application by using a hybridization of traditional collaborative filtering technique and data mining techniques [11].

Recommender systems are commonly defined as applications that e-commerce sites exploit to suggest products and provide consumers with information to facilitate their decision-making processes [12]. They map user requirements and preferences, through appropriate recommendation algorithms, and convert them into recommendations of a small subset of products/services out of a very large set. Knowledge about the products/services and consumers is extracted from either domain experts (in content- or knowledge- based recommendation approaches) or the analysis of previous purchase and recommendation histories (collaborative- based approaches). Furthermore, the recommendations are presented to the user/consumer together with a rationale for the underlying recommendation.

Recommenders can help to increase online sales; analyst Jack Aaronson of the Aaronson Group estimates that investments in recommenders bring in returns of 10 to 30 percent, thanks to the increased sales they drive [13]. There is potential for further utilisation of recommender systems.

4.2.2 Personalized Collaborative Recommendations Although several recommendation algorithms have been devised, these days, the most prevalent one is collaborative filtering. All major ecommerce and social media sites such as Amazon, Netflix, and Facebook’s employ some variant of collaborative filtering techniques. They are “personalized” because they track the user’s behaviour—pages viewed, purchases, and ratings— to produce recommendations. The approach is called “collaborative” because it treats two items (products/services (as being related based on the fact that lots of other customers have purchased or stated a preference for those items, rather than by analysing sets of product features or keywords.

Personalized collaborative recommender systems have been around since the early 1990s. Some of the early recommenders include the GroupLens project [14], targeting movie recommendations, and MIT’s Ringo for music recommendations. Both GroupLens and Ringo use a simple collaborative algorithm that computes the “distance” between pairs of users based on how much they agree on items they have both rated. Users whose tastes are relatively “near” each other according to these calculations are said to be in the same “neighbourhood.”

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

However, user similarity recommendations tend to suffer from problems such as the lack of sufficient data sets because most pairs of users have only a few ratings in common or none at all. However, it is not always easy to form neighbourhoods that make sense. Most recommendation systems today rely on item distance algorithms, which calculates the distance between each pair of items according to how closely users who have rated them agree. Distances between pairs of items, which may be based on the ratings of thousands or millions of users, tend to be relatively stable over time, so recommenders can precompute distances and generate recommendations more quickly. Both Amazon and Netflix use variants of an item-item algorithm. One problem with both user-user and item-item algorithms is the inconsistency of ratings. Users often do not rate the same item the same way if offered the chance to rate it again (subjective evaluation is a weakness of rating systems). The larger the populations using the rating systems, the more accurate the results may be. Researchers therefore are trying different ways to incorporate such variables into their models; for example, some recommenders will ask users to rerate items when their original ratings seem out of sync with everything else the recommender knows about them.

Both content and collaborative filtering algorithms are too inflexible as they can detect people who prefer the same item but they can miss potential pairs who prefer very similar items.

A method to compute the similarity of items is the dimensionality reduction that reduces the potentially very large number of features (feature space) to a smaller representative subset. This method is however more computationally intensive than the other recommendation algorithms, as the time it takes to factor the matrix grows quickly with the number of customers and products. This more general representation allows the recommender to detect users who prefer similar yet distinct items. And it substantially compresses the matrix, making the recommender more efficient.

To calculate the customer’s similarity to other customers, the recommender has to take in mind the customer’s preferences. There are many methods to achieve that, for example by asking customers to rate their purchases. The recommender uses the user’s navigation history through its website and items clicked on to suggest complementary items, and it combines purchase data with user ratings to build a profile of user’s long-term preferences.

Recommenders also utilise business rules that help ensure its recommendations are both helpful to you and profitable for the retailer.

To build trust, the more sophisticated recommender systems strive for some degree of transparency by giving customers an idea of why a particular item was recommended and letting them correct their profiles if they don’t like the recommendations they’re getting. Explanations like these let users know how reliable a given recommendation is.

There is active research on recommendation algorithms that improve different parameters, as different recommendation systems can target different performance goals. The effectiveness of an algorithm can be determined by comparing its predictions and the actual ratings users give. Sellers care much more about errors on highly rated items than errors on low-rated items, because the highly-rated items are the ones users are more likely to buy. Another performance measure is the extent to which recommendations match actual purchases. Such measures should however take into account that sometimes users purchase items irrespectively of the recommendations made.

Given the shortcomings of current approaches, research in recommendations has started to focus not at accuracy but also at other attributes, such as serendipity and diversity. Serendipity approaches try to produce unusual recommendations, particularly those that are valuable to one user but not as valuable to other similar users. A diverse list of recommendations is one that does

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 not recommend products services in a single class but also in diverse classes. For example, if the user is browsing books, the recommender will also suggest music and computer games.

Recommendation research today are considering to what extent a recommender should help users explore parts of a site’s collection they haven’t looked into—Recommenders could also help expose people to new ideas [15].

4.2.3 Current Travel Recommender Systems For travel and tourism, the two most successful recommender system technologies are Triplehop’s TripMatcher and VacationCoach’s expert advice platform, Me-Print (used by travelocity.com). TripleHop’s TripMatcher is a recommendation software based upon artificial intelligence and human knowledge that advises travellers on the destinations that best match their needs and preferences. Both of these recommender systems try to mimic the interactivity observed in traditional advice provided by travel agents, when users search for advice on a possible holiday destination. From a technical viewpoint, they primarily use a content-based approach, in which the user expresses his needs, benefits, and constraints using predefined features/attributes. The system then matches the user preferences with travel services in a catalogue of destinations. VacationCoach exploits user profiling by explicitly asking the user to classify himself/herself in one of predefined traveller profiles, which induces implicit needs that the user doesn’t provide. The user can even input precise profile information by completing the appropriate form.

TripleHop’s matching engine guesses importance of attributes that the user does not explicitly mention. It then combines statistics on past user queries with a prediction computed as a weighted average of importance assigned by similar users.

Recent recommender systems add multimedia content to recommendations. For example, by using the Sharable content object reference model (SCORM) a standard that collates content from various Web sites, and content object repository discovery and registration/resolution architecture. The information related to the recommendation (photos, videos) collected is stored in the form of an XML file. This XML file can be visualised by either converting it into a Flash movie or into a synchronized multimedia integration language (SMIL) presentation.

4.2.4 Multi-stage and multi decision travel recommenders The interactions between the user and the recommender system in a basic recommendation process (moving from needs to products with explanations), is not always linear and straightforward.

While some systems e.g. used by Amazon produce non-interactive recommendations, others such as www.activebuyersguide.com involves a user searching for a vacation in a multistage interaction. First, the site asks about the vacation’s general characteristics (type of vacation, activities, accommodation, and so forth). Second, it asks for details related to these characteristics, then for trade-offs between characteristics. Finally, it recommends destinations. It is argued that an interactive approach, where questions are fine-tuned as the human–machine interaction unfolds, has more potential (Ricci, 2002) [12].

Researchers have therefore argued that recommender systems should support multiple decision styles. The DieToRecs recommender (Ricci et al, 2006) [16] supports these decision styles by letting the user enter the system through: iterative single-item selection, complete travel selection, and inspiration-driven selection. Iterative single-item selection allows experienced users to efficiently navigate in the potentially overwhelming information space. The user can select whatever products he or she likes and in the preferred order, using the selections done up

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 to a certain point (and in the past) to personalize the next stage. For example, if the user selects a particular destination, that destination is used to recommend a particular accommodation.

Complete travel selection gives to the user the option to select a personalized travel plan that bundles items by reusing the structure of travels built by other users in similar sessions. Finally, inspiration-driven selection lets the user choose a complete trip by means of a simpler user interface and a short interaction. This approach integrates case-based reasoning with interactive query refinement. Interactive query refinement allows a more flexible dialogue management that handles failures due to over- or under-specified user needs, suggesting precise repair actions. Case based reasoning therefore provides the framework to cast a recommendation session into a case and similarity-based ordering of both complete trips and single services (Ricci et al 2006) [16].

As Ricci et al (2006) [16] argued that an effective travel recommender system should not only notice the user’s main needs or constraints in a top-down way but also allow the exploration of the option space and support the active construction of user preferences (in a bottom-up way). Recent research has emphasized this change of perspective, defining it as navigation by proposing. In this approach, the system shows the user examples of products, selected from those that the initial query retrieved. The user can choose a product as the current best choice, which updates the initial query and lets the recommender identify a new set of suggestions. These approaches use the concept of relevance feedback, used in information retrieval in a conversational, multistage interaction, in a dialog that interleaves needs elicitation with products. In conclusion, recommender systems for travel must carefully manage the human–machine dialogue to achieve usability and acceptance by the users.

4.2.5 Collaborative filtering approaches for travel recommendation Recommender systems are applications that suggest products and provide consumers with information to facilitate their decision-making processes. They map user requirements and preferences, through appropriate recommendation algorithms, and convert them into recommendations of a small subset of products/services out of a very large set. Knowledge about the products/services and consumers is extracted from either domain experts (in content or knowledge-based recommendation approaches) or the analysis of previous purchase and recommendation histories (collaborative-based approaches). Furthermore, the recommendations are presented to the user/consumer together with a rationale for the underlying recommendation. Collaborative and content-based filtering are two paradigms used by recommender systems. Collaborative filtering exploits correlations between ratings across a population of users, Content-based filtering is an alternative paradigm that has been used mainly in the context of recommending items such as books, web pages, news, etc. Some travel oriented recommender systems have been proposed, for example using travellers’ GPS tracks to predict popular places and activities near the current location of the user [17]. Other work has focused on the recommendation of specific types of locations. An item-based collaborative filtering method was used to recommend shops, similar to a user’s previously visited shops [18] [19] and a user-based collaborative filtering was proposed to generate restaurant recommendations through users with similar taste.

4.2.6 Software agent based systems for travel advice Software agents which are software entities that have autonomous behaviour have been applied in many business domains over the past decades. Software agents are capable of cooperation, negotiation, learning, planning and knowledge sharing. Travel is an information intensive industry and travel products increasingly rely on information availability at the time of booking but also during consumption, i.e. for the duration of the travel. A software agent for travel can remove some of the burden of information seeking and processing from the traveller by actively seeking information, vetting it, filtering it and presenting it to the

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 traveller. Some applications of software agents to travel have been reported, for example in Tariq et al [20] to help tourists to choose the right destination and tour company from the wide variety on offer.

Their travel service advisor (TSA) agent supports travellers by providing up-to-date information about travel companies’ performance and help them to advice right decision according to their requirement and preferences. Other agent approaches include: • applications for rapid and cost-efficient of an online pre-trip travel advisory service; • agent mediated e-commerce application to automate the hotel reservation process; • multiagent travel planning system for e-tourism domain; • multiagent tourist advisor system to construct personalized tours, select package tours and handle the underlying information.

4.3 Optimisation - Route search algorithms and the multi objective path search problem Route search algorithms try to find unique, optimal paths, from origin to destination. For the simple shortest path search problem formulation, the network is usually represented as a directed graph. The most important algorithms for solving this problem are listed below: • Dijkstra algorithm [21] solves the problem of finding the shortest path from a point in a graph (the source) to a destination. The algorithm finds the shortest paths from a start point to every other point in the graph, producing a shortest path tree. The algorithm, at each step examines the node with the lowest distance from the start. The node is marked "closed", and all nodes adjacent to it are added to the open set if they have not already been examined. The process ends as soon as a path to the destination has been found. • Bi-directional search is a graph search algorithm that finds a shortest path from an initial point to a goal point in a directed graph. It runs two simultaneous searches: one forward from the start, and one backward from the goal, stopping when the two meet in the middle [22]. • A* is a computer algorithm that is widely used in path finding. A* solves problems by searching among all possible paths to the solution for the one that incurs the smallest cost (least distance travelled, shortest time, etc.), and among these paths it first considers the ones that appear to lead most quickly to the solution. A* assigns A* assigns a weight to each open node equal to the weight of the edge to that node plus the approximate distance between that node and the finish. The approximate distance is found by the heuristic, and represents a minimum possible distance between that node and the end. When the heuristic evaluates to zero, A* is equivalent to Dijkstra's algorithm [23].

For multi-objective optimization problems, such as the multi-modal routing problem, there is usually no single optimal solution. Instead, such problems tend to be characterized by a set of alternative solutions, which should be considered equivalent in the absence of further information regarding the relative importance of each objective in the solution vectors. The purpose of multi-modal route planning is to provide the traveller with an optimal, feasible, and personalized route between origin and destination, which may involve public and private transportation modes. The problem of efficiently computing multi-modal journeys, presents several algorithmic challenges and has been an active area of research in recent years due to a strong practical interest and an increasing data availability. The Multi-Objective Path Search Problem is based on the simple shortest path search but it considers not only one weight label, but a weight vector for each link. Due to the presence of many criteria that might come into

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 conflict with each other, not only one optimal path is searched, but a set of paths with acceptable trade-offs among the routing criteria. Multi-objective path search problem is an application topic of Multi-objective optimization theory. Known algorithms for the Multi-Objective Path Search Problem cannot resolve the optimal solutions set in polynomial time, as it is a NP complete problem. In fact, it is intractable because the size of the Pareto frontier grows exponentially with the number of nodes of the network [24]. In this sense, Multi-Objective Optimization algorithms do not intend to build a complete optimal set, but an approximation of it, that represents the whole range of choices [25].

The Multi-Objective Transit Routing is an application case of the Multi-objective path search problem in the area of transportation systems. It consists in finding optimal paths for passengers traveling along a public transport network. Passengers’ preferences and the characteristics of the specific public transport system must be considered. Thus, typically the optimal transit route search deals with the problem of giving the passenger a solution that represents a tradeoff between different objective functions. Common considered objective functions to minimize in optimal transit routing studies are travel time, number of transfers, walk time, and, in some cases, the fare cost.

In computer science and operations research, a genetic algorithm (GA) is a meta- heuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). The genetic algorithm repeatedly modifies a population of individual solutions relying on bio-inspired operators, such as mutation, crossover, and election [26]. The EA are commonly used to generate high-quality solutions to optimization and search problems. Genetic algorithms (GA) were proposed in order to solve the multi-modal route planning problem [27]. Variable length chromosomes with several parts (subchromosome) are utilized to represent routes in multi-modal travel environment, where each part describes a kind of transportation mode. Crossover and mutation operators are redefined in single mode; two new operators, hypercrossover and hypermutation, are defined as inter-mode operation. A multi- criteria evaluation method using a p dimensional vector to represent multiple criteria is adopted in the fitness function for selecting the optimal solutions. The multi-objective ranking method usually consumes much running time. The performance of the proposed approach in dynamic environment has not been tested.

Delling et al [28] studied multi-criteria journey planning in metropolitan multimodal networks. The authors argued that users of such networks optimize three criteria: arrival time, costs, and convenience. The proposed algorithms compute a full Pareto set and then score the solutions in a post-processing step, using techniques from fuzzy logic, which can quickly identify the most significant journeys. The full Pareto set is too large and includes many unnatural journeys. Multi- criteria heuristics can be used in order to find similar journeys. The experiments showed that this approach enables the computation of high-quality multimodal journeys on large metropolitan areas, and is fast enough for practical applications.

Müller-Hannemann and Weihe [29] carried out a study on bi – criteria shortest path search on a scenario with real schedule information of the German train system. The objective was to determine if the Pareto optimal set size could be set to a polynomial size or not. The approach identifies key characteristics on the scenario that lead to a smaller number of optimal solutions which practically makes the problem tractable, instead of getting an exponentially growing solution size in the worst case. The method sets restrictions to paths according to an edge model classification and discards node labels that are dominated by labels at the destination node. Subsequently, a prototype solution based on a multi – criteria generalization of Dijkstra’s algorithm has been implemented and tested on the German train system time – depended

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 network (Disser et al.) [30], providing fair average execution time (below 1sec). In this implementation, nodes have multidimensional labels which can be expanded multiple times during the path search. Each label represents an optimization objective and includes a reference to its predecessor on the path. New labels are compared to the complete list of previously revised node labels, a list of non-dominated labels is updated, and dominated labels are removed.

Furthermore, Müller-Hannemann and Schnee [31] presented a model with three main optimization objectives: travel time, fare, and transfer number minimization. This model introduces the concept of Relaxed Pareto Dominance, in order to find potentially attractive routes without discarding “near optimal” solutions. A relaxation function is applied, accounting other travel aspects, not originally considered in the main optimization objectives. Routes that are attractive in respect to these travel aspects are set incomparable. In that way, these attractive routes are not suppressed by the normal route dominance comparison. The reported performance surpasses the journey planner of the Deutsche Bahn AG, which collaborated for the scenario of the German public railroad network.

In a similar way, Delling et al. [32] presented a routing algorithm for flight networks (with nodes representing airports) which reduces the network complexity in comparison to road (or railway) networks. In contrast to railway networks, fight networks contain (almost) exclusively direct connections between airports (unlike trains, planes do not stop at many airports on a route). Because of this fact, all routes between airports are conveniently pre-calculated and stored in tables (queries retrieve routes in microseconds). The classic Dijkstra’s algorithm has poor performance on very large graphs such as continent – size road networks, thus, several speedup techniques have been proposed based on graph preprocessing. Such an algorithm is SHARC [33] and its extension for multi-criteria routing [34]. SHARC creates graph partitions and pre-calculates paths to them with a generalized Dijkstra method. Then, links that lead to certain partitions are flagged. After that, an iterative process contracts the graph selecting only relevant nodes. Finally, the arc-flags refinement introduces several reasonable constraints to prune unattractive paths, both during pre-processing and queries. The Multi-Objective Path Search approach includes the following: A multi-criteria version of Dijkstra algorithm operates on the prepared graph. In order to be able to reduce the Pareto set and so also to deal with real big scenarios, travel time is set as main dominance criterion. Other paths are considered in the optimal set, only if they do not represent a big bad impact on time optimization. The effect of speed-up techniques on performance is reported in a Western Europe network scenario test, in which pre-processing lasted for 5 hours, and a route query was resolved in 8 ms.

During the last decade, novel graph pre-processing techniques have been proposed, such as contraction hierarchies [35], transit node routing [36], and Hierarchical Hub Labeling [37], thus, providing enormous speedup for both data pre-processing and query execution time (for European size continental road graph combining of tens of millions of nodes and edges, we can achieve pre-processing time less than 2 hours and query execution time less than 10ms. Their potential extension for supporting the multi-criteria routing problem, could over-perform typical (without pre-processing) path finding methods, and be capable of handling continental size transport networks for multimodal journey planning.

4.4 Location and context aware services for travellers Travel and tour planning is a process that involves searching, selecting, grouping and sequencing destination related products and services including attractions, accommodations, restaurants, and activities. Location-based services focus on providing information based on users’ current positions. Based on travellers’ current location and time, as well as personal preferences and

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 needs, location services make recommendations regarding sightseeing spots, hotels, restaurants, and packaged tour plans. Location based services are quickly gaining popularity due to affordable mobile devices and ubiquitous Internet access. Websites like Foursquare, Gowalla, Google Latitude and Facebook show that people want to share their location information and get accurate location recommendations at any time and place. In return for sharing their location data, users can be matched to products, venues, events or local social relations and groups. Accurate predictions of the user’s preferred locations can simultaneously aid the user itself, advertisers of products specific to the recommended place and service providers (e.g. transportation to the recommended location). To provide these recommendations, location based services needs to have an accurate way to find similarities between locations or people.

4.4.1 Geolocation services for travel routing Geolocation is the determination of the physical location of an object (for example a mobile device, a laptop etc.) using various technological methods such as Global Positioning System (GPS), Radio Frequency (RF) location methods, etc. Common uses of Geolocation systems are: • Detecting Points of Interest (POI) on users’ maps. In case of traveling and tourism, POIs can be museums, monuments, entertainment places, etc. Geolocation systems detect users’ location and then they assist them in selecting a POI, based on proximity, and then provide navigation services. • Making annotations based on location. Users can express themselves either by providing comments, or photos, or videos, etc. Geolocation systems detect users’ position and combine users ‘actions with their location. These annotated media can be analyzed in further, to discover places with high popularity, common routes, favourite POIs, etc. • User navigation. • User notification about local information based on users’ location.

Geolocation techniques The techniques that are used, are divided in four categories: Proximity methods, Triangulation methods, Dead Reckoning and Fingerprinting (Table 4-1) [38], [39].

Proximity based methods usually consists of a wireless sensor network which is divided into clusters. The location of each cluster is known. In proximity methods, each user (through his terminal) sends a signal to each cluster’s head node, and becomes assigned to the nearest cluster. The user location approximately corresponds to the location of the cluster that he/she is assigned to. This method has the drawback that large range of cluster’s head node corresponds to lower accuracy.

Triangulation method consists of a wireless sensor network as well. In this method each user sends a signal to several network’s nodes, and then receives the signals back with altered strength and in different times. According to triangulation methods, the user calculates his relevant position to the network’s position. The three most common methods are: (a) the Angle Based Localization, (b) the Range Based Localization and (c) the Distance Based Localization

• Angle based localization uses the angle of the received signals in order to calculate each user’s orientation and distance to the cluster’s head. This method, although it is more accurate than the previous one, it is much more expensive because it requires special antennas.

• Range based Localization uses the range (signal strength or time of signal’s arrival to users’ terminal) in order to calculate users’ orientation and distance to the cluster’s head. This method consists of three approaches based on the kind of metric it uses (signal strength or signal’s time of arrival): (a) the Received Signal Strength Indicator (RSSI), (b)

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

the Time of Arrival (ToA), and (c) the Time Difference of Arrival (TDoA). Range based techniques have the drawback that accuracy is significantly influenced by link reliabilities and noise interferences.

• Distance based Localization uses the hop distance between the sender and the receiver node in order to estimate the relevant location of user, compared to the cluster’s node location. However, accuracy in this method is reliable only if the network is dense.

Dead Reckoning (DR) methods make predictions of users’ location based on previous estimated users’ position. These methods do not use any other external information source (e.g. Signal from network nodes), but depend on users’ terminal’s built-in sensors such as gyroscopes, accelerometers etc. This method however suffers from accumulative accuracy error which comes from the accumulation of insignificant sensor measurements’ errors. Fingerprinting methods aim to collect (via built-in sensors, antennas, cameras, etc.) features of the environment that are distinctive for the location and orientation of the user, and then match these features (fingerprints) to known fingerprints in order to determine user’s location and orientation. These methods do not require any external or specialized hardware other than the built – in hardware of mobile terminals. However, these methods depend highly on environmental features which must be maintained and updated constantly for each location.

Table 4-1: Geolocation Techniques Method Measurement Indoor Coverage Line of Affected Cost Notes Type accuracy Sight/ by non Multipath line of sight Proximity Signal Type Low to Good Both No Low (1) Accuracy can be High improved by using additional antenna, However, it will increase the cost. (2) Accuracy is on the order of the size of the cells Direction Angle of Medium Good LOS Yes High (1) Accuracy (AoA) arrival depends on the antennas angular properties (2) Location of antenna must be specified Time (ToA, Time High Good LOS Yes High (1) Time TDoA) Difference of synchronization arrival needs (2) Location of antenna must be specified Fingerprnting Received High Good Both No Medium (1) Need Heavy signal strength calibration (2) Location of antenna is not necessary Dead Acceleration, Low to Good NLOS Yes Low Inaccuracy of the reckoning Velocity Medium process is cumulative, so the deviation in the position fix grows with time

Technologies used in Geolocation: The most prominent state – of – the art technologies used for geolocation are the following:

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• Global Positioning System (GPS) [40] is the most used technology for outdoor localization. GPS provides continuous positioning and timing information. Because it serves an unlimited number of users as well as being used for security reasons GPS is a one way ranging passive system. That is only users can receive the satellite sites [41]. Although for outdoor localization this technology is satisfying, it is inefficient in environments with large obstacles or indoor locations because the electromagnetic waves transferred between satellites and indoor receiver are attenuated by the buildings and the outdoor obstacles.

• Infrared Radiation (IR) positioning systems are based on line-of-sight devices that use infrared radiation for communication. This technology is usually used for indoor localization for detecting or tracking objects or persons and is available in mobile phones, PDAs, TVs, etc. The main advantage of this technology is that it is small and lightweight. However, this technology has the following disadvantages: it demands line – of – sight, it has security and privacy issues and it is highly influenced by fluorescent light and sunlight [42][43].

• Radio frequency positioning systems are based on radio waves which have the advantage of being capable to penetrate obstacles like building walls and human bodies. These systems are used for a variety of sizes of coverage areas, depending on the frequency of radio waves. As a result, we have narrow band RF systems (RFID, Bluetooth, WLAN and FM) and wide band systems. Moreover, there is the ZigBee technology which provides solutions for short and medium range communications [44].

• Ultrasound positioning systems are based on ultrasound waves, which imitate the bats’ perception system. These systems use ultrasound signals to estimate the position of the emmiter tags from the receivers. These systems have low level accuracy and suffer a lot of interference from reflected ultrasound signals [45].

• Inertial measurement positioning systems are based on measures of velocity, orientation and gravitational forces using a combination of accelerometers and gyroscopes and sometimes magnetometers. These systems although they are independent of any external hardware and signal, they suffer from accumulated error, because for each location estimation it is added small errors due to measurements, which however accumulate and lead to larger errors after several estimations. As a result, these systems demand that after some estimations, the system must acquire (using another method apparently), a correct measurement of location which resets the position and error values. • Hybrid methods [46]: Combination of the aforementioned technologies in order to reduce each one’s disadvantages and enhance their advantages.

Commercial Geolocation solutions Apple, Google and Microsoft are the prevailing tech players in localization and navigation technologies, which have implemented hybrid systems that are mainly a combination of GPS (outdoor), Wi-Fi/WIMAX and Bluetooth technologies. Moreover, in indoor localization there are companies that are dedicated to a specific technology:

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• Locata: Australian company that offers beacons that send out signals that cover large areas and can penetrate walls. • Nokia: They use beacons that send out Bluetooth signals • Navizon, Skyhook, TruePosition: use Wi-Fi technology • ByteLight: They use flickering light patterns from a LED light transmitter, and a terminal receiver (camera on a mobile phone) reads the pattern and sends it to a server where it is compared to other light fingerprints in order to find a match. • IndoorAtlas: Their devices survey buildings for their internal magnetic cap which corresponds to a fingerprint for each location and orientation.

4.5 E-payment Solutions The payment methods can be categorized in conventional and alternative/ emerging methods. Credit Cards, cash, check, electronic funds transfer, and debit cards are the most common payment methods in the travel industry. It seems though that new ways of payment such as account based ticketing, virtual cards, online wallets, mobile payment, NFC based mobile and cash on delivery are emerging, because of the need of making the payment methods as simple as possible for the end- users by simplifying the travel experience.

Online banking is a very common payment method. The customers of a financial institution are able to conduct financial transactions through the website operated by the financial institution. The customer can execute online a purchase. The payment must be confirmed and after that the amount will be debited from his account. The bank informs the travel agency (in case that the customer bought a ticket) for the payment, and the ticket is sent to the customer.

Smart cards. In public transport card based systems often use smart cards. Smart cards are devices designed to store and, in most cases, process data. Smart cards can store info such as monthly pass, discount rights and tickets. Tickets can be pre-paid or Pay-As-You-Go.

Mobile payment and Digital wallet. Mobile payments is a new and rapidly adopting alternative payment method. The digital wallet allows users to store holder’s credentials and payment information within a device such as a mobile device. This can include purchasing items on-line with a computer or using a smartphone to purchase something at a store [47]. The biggest players in the market are Apple and Google. Some of the companies in the travel industry that have already embedded wallet payments in their applications are Priceline, Airbnb, Booking.com, Uber and Expedia [48]. The Apple Pay mobile-payment and digital-wallet system which was announced in September 2014, lets the consumers with NFC-enabled iPhone 6, iPhone 6 Plus, and Apple Watch devices pay in stores at contactless terminals and buy goods using apps that support the service [49]. Moreover, PayPal is investing towards this direction by purchasing Paydiant [50].

Towards the same direction, Samsung in February 2015 purchased LoopPay which is a company that provides mobile wallet solutions. Visa Inc. announced in February 2015 that it has partnered with several leading financial institutions around the world to offer new mobile payment services. BBVA and Cuscal launched new issuer-branded mobile payment applications for mobile devices running on the Android operating system. Additionally, Banco do Brazil, PNC Bank, N.A., and U.S. Bank intend to launch similar capabilities in the near future [51]. Virtual cards. A digital / virtual card, unlike a plastic card, doesn't require any physical representation in the first place as it is fully virtual and hosted online. Usually a maximum charge for the virtual number is set in order to further protect users’ transactions.

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Cloud Based Ticketing - Acount Based Ticketing In the next years it is estimated that the payment methods will move towards the cloud. In the white paper “Cloud based ticketing – Next generation fare collection” [52] published by the university of Limerick, UL presents its vision about the next generation of ticketing. The Acount Based Ticketing means that the customer will be able to use any means of the transport network rail, bus, ferry etc. and pay with any means of payment such as a card, a pre-paid wallet, mobile or a smart wearable. The customer must have a unique id which will be used for his identification. The terminals of the travel providers have their own ID The payment will link with their account residing out there in the cloud. The cloud which consists of communication networks and server technology will have a big impact in the travel industry. The three areas that are going to be affected by the new technologies and are related to the fare collection are the identification, the fare calculation and the payment.

The European Travellers Club (ETC) [131] which is an initiative of several European e-Ticketing Schemes in Public Transport, the Open Ticketing Institute and the University of Limerick are working towards the creation of a trusted, easy and seamless Account-Based System across Europe. According to the ETC’s white paper through the account based ticketing the monthly passes, the discount rights are not stored on devices but are stored in a back-office. Moreover, through Account-Based Ticketing new chances for cooperation between authorities, financial institutions, and services providers emerge. As stated in the report travellers in the future will be able to connect their account to cards such as a bankcard, an ID-card or devices such as a mobile phone or a wearable device, which can be used for the payment needs. It will be possible for the travellers to pay before or after their travel. Below are some examples of account based ticketing, based on the white paper of the European Travellers Club project.

London contactless cards public transportation [54]: In London contactless cards can be used in public transport (bus, Tube, tram, DLR, London Overground, TfL Rail and most National Rail services in London.). The cards are used in the same way as Oyster card, the user must touch the card flat on the yellow card reader when he enters and leaves a station but the way of payment is different. This is because the traveller doesn’t add credit before the travel. Payment is affected afterwards, after the end-of-day closing. The total cost of all the journeys that have been made in one day are calculated. The calculations are done in the back-office and a daily cap is applied to the user’s contactless payment card account.

OV-Chipkaart, Netherlands, and Mobility Passes: Several mobility providers in the Netherlands such as the Dutch Railways, offer account-based travelling. This may include parking, bike or car rental, etc. An indicator that is an active account based card is contained in the business cards. After end-of-day closing, all transactions are routed through a back-office where also the discount arrangements are applied. Invoices are paid afterwards.

M-Kaart, Luxemburg, and additional services: In Luxemburg, the national transport authority, Verkéiersverbond, has launched a new version of its national e-ticket: the M-Kaart. Travelling itself will be predominantly card-centric on the basis of Germany’s VDV-KA standard. But Verkéiersverbond has started a project with OTI and VDV e-Ticket Service, to test whether the integration with travel information and other government (sponsored) services can best be implemented account-based.

Euregio, Maastricht-Aachen-Liege, and cross-border travelling: In the Euregio, the introduction of three different national e-Ticketing standards has not made life easier for cross-border travellers. In the Netherlands they need to have an OV-Chipkaart, in Germany a VDV-card and in Belgium a MOBIB card. With the support of the European Union, the partners in the region (led by the Aachener Verkehrsverbund) have started a project with OTI and VDV e-Ticket Service to explore strategies to make travelling easier for cross-border travellers. These include readers that

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 can read several cards, smart cards or mobile phones that can contain the data of several cards, and a single account.

4.6 Mobile & Wearable Travel Technology According to the travel flash report Online travel’s never looked so mobile, mobile bookings are growing faster than desktop (Figure 4.1). As it is stated in the report in the first six months of 2014, mobile bookings were up to 20%. Moreover, the average booking value for air was 21% higher on mobile devices than on desktops and 13% higher for car rentals [55].

Seasonal growth of mobile bookings worldwide in H1 2014 150

100

0 January February March April May June

Mobile index Desktop index

Figure 4.1: Seasonal growth of mobile bookings. Source: Criteo: Travel. Flash report. September 2014.

The world of wearable technology is also moving fast (Table 4-2). There has been an upward trend in the market of wearables in the first quarter of 2015 as new vendors, including Apple, prepared to enter the market. Based on the new forecast from the International Data Corporation (IDC) Worldwide Quarterly Wearable Device Tracker it is estimated that 72.1 million wearable devices will be shipped in 2015, up to 173.3% in comparison to the 26.4 million units shipped in 2014. According to the same report, the shipment volumes are expected to reach the 155.7 million units in 2019. The annual growth of the shipment is expected to be 42.6% over the five-year forecast period (2014-2019) [56].

Table 4-2: Worldwide Wearable Device Shipments, Year-Over-Year Growth and CAGR by Product Category, 2014, 2015, and 2019 (Units in Millions), Source: International Data Corporation (IDC) Worldwide Quarterly Wearable Device Tracker 2015 Year- Product of 2014 2015 2019 2014 - 2019 Over-Year Category Shipments Shipments Shipments CAGR Growth Basic 22.1 39.0 66.3 76.0% 24.5% Wearables Smart 4.2 33.1 89.4 683.0% 84.1% Wearables All Wearables 26.4 72.1 155.7 173.3% 42.6%

Categories of wearable devices The term wearable devices refers to advanced technologies incorporated into items which can be worn on the body, such as clothing and accessories. These wearable devices can perform many of the same computing tasks as mobile phones and laptops. Wearable technology comes in different forms in order to cover head, back, waist, arms, body, wrist and legs. The wearable devices tend to be more sophisticated than mobile and laptops on the market today, because

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 they can provide sensory and scanning features not typically seen in the aforementioned devices, such as biofeedback and tracking of physiological function [57]. The most common wearable devices in use, are the following: • Smart glasses • Smart watches • Smart bracelets • Smart rings • Smart clothes • Smart cards

Applications of wearable devices Wearable technologies have been mostly applied in the following areas: • Entertainment • Gaming • Industry • Personal health and fitness management: o Activity trackers o GPS monitoring o Devices for fitness management (e.g. improper posture notifications) • Management of disease within healthcare: o Remote management of patient status o Ongoing updates regarding patient status o Feedback to patients o Empowers patient to self-manage • Performance enhancement in elite sport: o Sports performance enhancement o Chemical Sensors in Sports

Wearable Technologies and Travel Wearable Technologies – such as smart watches and heads-up devices like Google Glass – could bring about real step-change in the way businesses market and sell travel, and the way consumers experience it. With technology and gadgets already a critical part of travel, wearable technology is predicted to become the biggest thing since the release of the smart phone. Companies should find ways in order to incorporate wearable technology in the travel industry. The companies should consider why consumers want technology connected to their bodies and how it could augment their lives. The travel industry as stated in different reports is ready to adopt wearable technology in their business cycle. Amadeus which is a leading provider of advanced travel technology solutions, highlights some of features and functionalities of the wearable technology and the opportunities it presents for the travel industry [58] [59].

Virgin Atlantic is another industry that recognised the opportunities for the travel industry of wearable devices and launched their wearable technology pilot scheme in February 2015. The staff of the company used Google Glass or a Sony SmartWatch2 to greed the company’s passengers arriving at the Upper Class Wing at Heathrow airport. The cutting edge technology was developed in collaboration with the air transport IT specialist SITA. The passengers were greeted by name and the personnel wearing the Google glasses or smart watches was able to start the check in process. Moreover, the personnel was able to provide to the passengers information regarding their flight, as well as regarding the weather and events at their destination. The wearable technology can provide a unique personalized experience to the customers and in future the devices could provide info regarding passengers’ preferences to the staff, in order to enhance passengers' travel experiences, increase efficiency and exceed consumer expectations [60]. The prototype Google Glass Flight search app is another application developed by the global technology company Sable, which has been showcasing potential uses

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 and applications for wearable devices in travel. As stated in the description of the app, the application can find flights based on a user’s simple voice command: “Ok Glass, find a flight from London Heathrow to the beach in December” [61].

For travel, smartwatches basically become a mini-screen that would perform many of the same functions as a phone. Weather, boarding pass reminders, gate updates, reservation information, QR codes, and all of the related information that fuels a traveller’s trip, would be available right there on the wrist. Directions are also a very useful area for smartwatches. Rather than having to stare down on a phone, travellers can simply use the watch – and a Bluetooth headset – to get the necessary directions. This would also reduce the likelihood of a distraction-related injury or a handset snatching thief. Another implication would be battery life. Theoretically the watch should have a better battery life, and offload some smartphone interactions – thus increasing range of batteries during travels. Based on the Delphi study of the project Guide2Wear: mobile devices for the future traveller [62], wearable devices can be used in the following services: • Intermodal routing • Car/bike sharing bookings • Local navigation • Location based services • Access to public transport • E-ticketing/payment

Based on the same report the smartphones, followed by smartwatches and glasses will be the optimal device for finding intermodal routes in the future.

Virtual journeying The virtual reality technology has been mostly used in games, but now it seems that the travel industry is exploring how to use this technology as a marketing tool in order to sell more effectively. Virtual travel is in its infancy but it seems that it will become a new form of selling experiences. The travel industry has seen the potential of virtual reality technology, as it can be used as a 3D taste of a destination that will in the end, convince travellers to buy that taste.

Thomas Cook, Qantas Airways, and Destination British Columbia in Canada are some of the companies that are using this technology in their own promotional VR videos.

Thomas Cook, In August 2014, announced a trial pilot in which they placed virtual reality headsets at one of its stores in England that allowed visitors to explore the Sentido Resorts, as well as virtually experience a flight with Thomas Cook Airlines [63]. As stated by the company’s Chief Innovation Officer, Marco Ryan, the company sees the virtual reality technology as an innovation which will change the travel business, moreover he added that "The closer you get to the destination, the more excited you are to have that experience"—i.e., enhance the shopping experience.

Destination British Columbia has just launched The Wild Within VR Experience, using Oculus Rift technology. The Wild Within VR Experience is an interactive video used as a marketing tool in order to promote the destination. The users can experience British Columbia in an interactive way. Marsha Walden, CEO of Destination BC stated that “We think virtual reality is a great fit for tourism marketing. It lets our travel trade and media partners experience our destination in a new and unique way that has not been possible before. And, as the headsets become more widely available to consumers, virtual reality gives them a ‘360’ experience – immersing them in the extraordinary travel opportunities that British Columbia offers, from raw wilderness to refined cities.” [64]

The idea behind the use of virtual technology in travel is not that it will replace real-world travel. As it seems nobody in the travel industry would be interested in that. As it is stated in the

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Scyscanner’s Future of travel 2024 report in the future virtual reality headsets will offer travel companies the opportunity to provide virtual ‘try-before-you-buy’ holidays [65].

Moreover, virtual reality technology will let travellers explore digitally rendered hotels before booking their stay or get previews of local landmarks before deciding on a holiday location. In 10 years’ time, a traveller will be able to take a virtual reality walk through the hotel he is planning to book in real time, says Nik Gupta, Director of Hotels at Skyscanner. ‘He will be able to watch staff preparing his room as it happens, see the staff in action and watch chefs cooking his favourite food. That will be ground-breaking an incredibly powerful tool for building engagement and trust between the traveller and the brand [66]. In this way the traveller will be better informed and he would be able to evaluate the hotel in a more personalized way.

4.7 Travel APIs Businesses are moving beyond traditional industry silos and coalescing into networked ecosystems, creating new opportunities for innovation alongside new challenges for many enterprises. Ecosystems typically bring together multiple players of different types and sizes in order to create, scale, and serve markets in ways that are beyond the capacity of any single organization—or even any traditional industry. Their diversity—and their collective ability to learn, adapt, and, crucially, innovate together—are key determinants of their longer-term success. In Eutravel, apart for the travel end users (travellers and businesses that buy travel services) several other key ecosystem stakeholders are considered (Table 4-3).

Table 4-3: EuTravel Ecosystem Participants Transport Transport Service Travel Service Infrastructure Providers Authorities Providers Providers Global Distribution Rail Infrastructure Mobility Management Rail Operators System Service Providers/ Managers Authorities Providers (GDSs) Travel Agents Air Carriers, Airline (Retailers), PT Administration Airport Operators Operator Travel Management Authorities Companies (TMCs) Fleet Owners, Online Travel Agents Environmental Port/Terminal Ferry Operators (OTAs) (Retailers) Authorities Operators Infrastructure Urban/Public Transport Car Rental Service Cross Border Managing Maintenance Service Operators (PT) Providers Authorities Providers Hotels/ Hospitality Toll Operators Coach Operators Customs Providers Ticket Vendors - Travel Insurance ITS Solution Providers Retailers (third parties, Service Providers apart from operators)

Ecosystems formulation are facilitated by the growth of APIs. With the proliferation of Application Programming interfaces (APIs) available both privately and publicly, it becomes very difficult to monitor the latest developments in this area. This is partially alleviated by recently established public registries of APIs where their developers/owners are encouraged to register information about them. The API registry used in this research was the Programmable Web [67] that claims to be the world’s largest repository (registry) for APIs, containing in excess of 14,000 API entries at the time of writing this report. To retrieve travel related APIs the category ‘travel’ was used to retrieve relevant APIs from the Programmable Web repository. This approach however is not guaranteed

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 to return the whole list of travel related APIs, nor only APIs that are relevant to travel, as some travel APIs could possibly have been classified incorrectly. The number of results however, (in excess of 300) indicates that (a) the Programmable Web is a useful source of API information and (b) the proliferation of travel related APIs. Also, although the search opted to exclude deprecated APIs, there is no absolute certainty that the APIs found are still actively used/supported by users and their developers.

The next step in the process involved the filtering out of APIs that were deemed to have a narrow geographical coverage, i.e. covering travel information within a city or region- but not country or continent level, as EuTravel has a pan-European scope.

The number of travel APIs in the filtered list obtained in this manner was still too high and therefore not useful to provide patterns, trends and insides into the current travel related API market. As the purpose of EuTravel is to develop an ‘API of APIs’ it was considered important to define the breadth of coverage and scope of such API. This would require some classification of existing travel APIs however. As such classification did not currently exist, we decided to propose one that is empirically derived by analysing the descriptions of the discovered APIs and identifying common themes that appear across them. Thus, this is not a strict classification as APIs may straddle several themes and some APIs may appear to not belong to any of the proposed themes. Instead this classification was proposed in an attempt to scope the planned ‘API of APIs’. The classification visualised in Figure 4.2 proposes the following five themes:

Figure 4.2: Initial classification of travel related APIs

• APIs oriented towards developers that want to integrated/aggregate existing travel services (e.g. to create portals. Mashups, for travel aggregators). These also cover multiple travel modes (sea, land, air) and facilities (e.g. car and hotel hire). These APIs have transactional capability (e.g. create bookings). • APIs oriented towards one type of service/travel mode (e.g. air travel) and/or one provider (e.g. one particular airline only). These APIs also may have transactional capability. • APIs that provide travel related but static information (e.g. about locations such as places to visit or airports) but they do not (normally) support itinerary planning as timetabling and dynamic travel information is not included • APIs that provide timetable-like information such as bus or flight arrival information, flight tracking, for single or multi-mode but (normally) no booking functionality. • APIs that allow the sharing of information or resources between travellers, such as recommendations about visiting places, travel routes and trails etc.

An indicative list of APIs from the Programmable Web registry have been categorized as above and listed in the tables in Annex 1 of this report.

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4.8 Task models and ontologies for travellers Most travel service providers use XML based schemas to describe their services so that they are amenable to automated discovery by search engines and interpretation by software agents on the Web. For such organisations, the addition of ontological descriptions and semantics is the next logical step that can help to improve the traveller experience and relevance of search results, both within the booking engine and on general purpose search engines like Bing, Google and Yahoo!. A travel ontology is a conceptualization and formalization of the travel domain using ontology languages such as RDF and OWL. Travel ontologies conceptualise: • Travel processes and the entities that participate in them such as holidays, journeys, people, geographical features, etc.; • Physical and abstract things such as land, countries and regions; • Material and immaterial things such as buildings, vehicles and journey plans; • Attributes of things used for classification purposes such as long journeys, fast vehicles, etc. • Roles / functions of things involved in travel (traveller, booking party, travel agent, etc).

Figure 4.3: The classes in Travel Ontology

Figure 4.3 shows a sample travel ontology as proposed by Chang Choi et al [68]. It defines an upper ontology consisting of key concepts such as accommodation, activity, food and transportation that can be further specialised. Logical descriptions are further used to define the meaning of the concepts and of their relationships. Currently, only experimental, small scale travel ontologies have been created [69] . They define class hierarchies of concepts such as hotel, restaurant, sports, specialisations such as luxury hotel, bed and breakfast, services and activities such as safari, hiking, spa treatment, sunbathing, sightseeing, accommodation rating (three stars, etc.), campground, surﬁng, consisting of primitive deﬁnable classes, their relations, properties, domains and ranges as well as individual entities.

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4.8.1 Travel & Traveller Knowledge Representation - Travel Ontologies A travel ontology has been proposed by the SWAT Project (Figure 4.4) [70]. The current version (v26) of the ontology consists of 146 classes, 64 object properties, and 8 data properties.

Figure 4.4: Classes of Travel Ontology from SWAT Project

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GTFS [71] which has been superceeding the Transit vocabulary [72] is a translation of the General Transit Feed Specification [73] as an open standard data format for public transport schedules (Figure 4.5).

Figure 4.5: Classes of GTFS

TAGA is an agent framework for simulating the global travel market on the web [74]. The framework provides several ontologies: Travel Business; Auction; FIPA OWL content language; TAGA Query language (Figure 4.6). The travel business ontology contains 34 classes and 16 object properties.

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Figure 4.6: Classes of Travel Business Ontology from TAGA

Travel Guides [75] utilizes Semantic Web technologies to decrease the maintenance efforts required for existing e-Tourism systems and ease the process of searching for vacation packages. It provides a travel ontology as an extension of the PROTON Ontology, contains 67 classes, 19 object properties and 3 data properties (Figure 4.7).

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Figure 4.7: Classes of Travel Ontology from Travel Guides

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Knowledge Model for City and Mobility KM4C is a knowledge model to describe a smart city, that interconnects data from info mobility service, Open Data and other source (Figure 4.8) [76].

Figure 4.8: Classes of KM4C

To summarize the survey on Travel Ontologies, three important aspects in the travel domain are examined: 1. Capability to describe activity of moving from one location to another. a. Describe who is travelling. b. Describe the original location. c. Describe the final location. 2. Capability to describe means of transportation used when moving from one place to another.

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3. Capability to describe activity to stay for a relatively short time in between movements.

An estimation value from 0…1 is assigned to each aspect, where 0 means the aspect does not supported completely and 1 means highly supported (Table 4-4).

Table 4-4: Important aspects in travel domain. Aspect Aspect Aspect No Ontology Name #1 #2 #3 1 Travel Ontology of SWAT Project 1 1 0 2 General Transit Feed Specification 0 0.2 0 3 Travel Agent Game in Agent cities 0 0.2 0.2 4 Travel Guides 1 1 1 5 Knowledge Model for City and Mobility 0.2 1 0.4

4.8.2 Schema extension for Travel Domain Schema.org consists a wide variety of classes and properties [77]. Specifically for travel activity as the movement of people between distant geographical locations [78], we found a highly related class in Schema.org so called “MoveAction” as shown in Figure 4.9.

Figure 4.9: MoveAction Plan of Schema.org “MoveAction” is the act of an agent relocation to a place, where the agent can be “Person” or “Organization”. This action requires two “Place” as original and final location respectively. It consists of three sub-classes: 1. “ArriveAction” as the act of arriving at a place, 2. “DepartAction” as the act of departing from a place, 3. “TravelAction” as the act of traveling from a location to a destination.

“MoveAction” has two specific properties, “fromLocation” depicts the original location and “toLocation” as the final location. “TravelAction” itself has property “distance” depicts the distance travelled.

Another important aspect for travel activity is it requires a mean of transportation to be able to move from the original to final location. This mean of transportation might be foot, bicycle, train, airplane, etc.

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Figure 4.10: Related classes for means of transportation

As shown in Figure 4.10, variety means of transportation classes have been available in the class “Intangible” which is a utility class that serves as the umbrella for a number of ‘intangible’ things 79]. Travel could also include stays for a relatively short time between successive travel movements. For example, waiting for another mean of transportation, taking a short rest, etc.

Figure 4.11: Related classes for relatively short stays in between movements

As shown in Figure 4.11 several types for short stay in between movements are available in Schema.org in class “CivicStructure” which is a sub-class of “Place”. These types of place do not cover for long stay, for example to eat at Restaurant, to stay at Hotel, etc.

4.8.3 Semantic enrichment of travel and tourism data and systems - Semantic annotations Semantic Web technologies are expected to influence the next generation of Destination Management Systems by providing interoperability, reusability, and shareability among modular and service-oriented Destination Management Systems. The Semantic Web is a concept that enables better machine processing of information on the Web, by structuring documents written for the Web in such a way that they become understandable by machines. The Semantic Web allows users and travel agents to make specific queries and infer knowledge quickly and accurately. The major components of the Semantic web framework are the ontologies, the ontology languages, the semantic annotations, the software agents and the applications/services. The field of using semantics in tourism is not new. The SATINE project [80] by Dogac et al. describes how to deploy semantically enriched travel Web services and how to exploit semantics through Web service registries. Jakkilinki, Georgievski, and Sharda proposed an ontology based

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 on e-Tourism Planner AuSTO [81] that enables users to create an itinerary in one single application by this intelligent tool that builds on semantic web technologies.

In the specific field of using semantics to provide better information for travellers there have been relevant and recent efforts in the literature. For example, García Crespo et al. proposed a semantically enriched recommendation platform [82] for tourists on route, later expanded to DMS.

4.8.4 Semantic search for travel portals / travel planners The introduction of semantic search during the online search phase of a travel booking is becoming a game changer, even though it is still in its infancy regarding the travel industry. Semantic search enables the traveller to focus his search priorities within an open search text box. Now days, a growing number of websites, including travel sites, are moving towards semantic search. The reason is simple: the travel industry does not have much choice. Travel search based on traditional search takes a lot of effort and requires time and patience, and time- consuming solutions are not what internet users are after.

An important issue that is addressed in the context of the semantic search, is the fact that there are a massive number of searches that go on today using online booking engines that are ultimately booked using a call center or reservation service due primarily to the lack of pertinent search data available online. Hotel companies, CRS platforms and OTA’s must now be able to give the travelling public exactly what they want in order to be pertinent. The introduction of semantic search will enable the travel experience to evolve constantly and get continuously better.

Recently, semantic search has become relevant to e-commerce sites, including travel ones. One of the world’s top websites in online travel industry, Expedia.com, is working on the semantic search tools for customers that seek travel products. A beta version of a semantic search service has also been launched on Cheapair.com. Another travel site going semantic is Adioso.com. ZapTravel.com is yet another example of a travel website, which took up the challenge. The creators of the site ensure that their search engine responds to queries in natural language.

4.9 Cloud computing, cloud-based enterprise systems and virtualisation Cloud computing is a kind of Internet – based computing that relies on sharing computing resources instead of local servers. It enables ubiquitous, on demand access to a pool of configurable computing resources. Cloud computing is similar to grid computing, which corresponds to a network of computers as well, but it is based on sharing unused processing cycles of these computers. Mainly cloud computing serves three tasks: “application”, “storage” and “connectivity”. Each task serves a different purpose and provides different contribution to businesses and individuals around the world [83] [84] [85].

One of the benefits of using cloud computing by companies is the potential to reduce IT operational costs by outsourcing hardware and software maintenance to the cloud providers. The latter allows companies to outsource many of their IT related task to the service (cloud) provider including upfront infrastructure and IT equipment maintenance costs and focus on projects that differentiate their businesses instead of on IT infrastructure [86]. Cloud computing utilizes large server networks that run low-cost consumer PC technology with specialized connectivity capabilities, however the core technologies behind cloud computing are: (i) the hardware virtualization which allows the end user to exclusively use a set of virtual resources and (ii) the service oriented architecture model which makes it easier for software components on computers connected over a network to cooperate. The standards for connecting the computer systems and the software needed to make cloud computing work, are not strictly

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 defined, which provides the flexibility to the companies to define their own cloud computing technologies.

Cloud computing promises several attractive benefits for businesses and end users such as [87]: • Services on demand: Service catalogue and specific SLAs • Acceleration of services: end users can accelerate their processing tasks by using cloud's computing resources on demand. • Adaptability: companies can scale up as computing needs increase and scale down as demands decrease. • Security, Risk management, compliance: Standardization and automation of these procedures • Incident management and fails management: Monitoring and filtering of events by the service providers • Business Model: users pay only for the resources and workloads they use.

Cloud computing has become a popular approach in corporate data centers as it enables them to operate like the Internet through the process of enabling computing resources to be accessed and shared as virtual resources in a secure and scalable manner. Small and medium size business (SMEs), benefit from cloud computing as well, as there are able to save time and money by investing in cloud computing for certain applications. The adoption of cloud computing can help SMEs in growing revenue, reducing long-term IT cost, attracting new customers, improving cash flow, maintaining profitability, and, increasingly importantly, reacting to ever-changing market conditions. Using cloud computing, SMEs can access remote resources and expand or shrink services as business needs change [88]. Cloud computing provisions can be categorized in two ways based on two criteria: deployment models and service models.

Deployment models Based on the NIST categorization (National Institute of Standards and Technology), cloud computing can be divided into four types [89]: • Private Cloud: In this case the cloud infrastructure is operated solely for an organization, even if it may be managed by the organization or a third part and may exist on premise or off-premise. Private cloud gives an organization the benefits of cloud computing without the restrictions of bandwidth, security exposures and legal issues that could be entailed by using external resources. However, this model is very costly and usually it is much time consuming for a company to establish a usable cloud. • Community Cloud: In this case the cloud infrastructure is shared by several organizations and supports a specific community that has similar concerns (e.g. mission, security requirements, and policy and compliance considerations). While the burden of building the cloud is lifted from the shoulders of each community member, this must be done by the community as a whole. • Public Cloud: In this case the cloud infrastructure is available to the general public or a large industry group and is owned by an organization selling cloud services. The main benefit of this model is easy and inexpensive to set-up, because the work needed for the cloud establishment is done by the cloud services provider. • Hybrid Cloud: This is a combination of two or more of the above mentioned types of clouds that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability.

Service models Based on the aforementioned report published by NIST [89] the service models applied in cloud computing are the following: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). • Software as a Service (SaaS): The service offers the consumer the capability to use the

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provider’s applications which run on the cloud. A thin client interface such as a web browser (e.g., web-based email) allows the accessibility to applications from various client devices. • Platform as a Service (PaaS): The service offers the consumer the capability to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure. • Infrastructure as a Service (IaaS): The service offers the consumer the capability to process storage, networks, and other fundamental computing resources where the consumer is able to deploy and run software, including operating systems and applications. The consumer in this case too does not manage or control the cloud infrastructure.

Moreover, the following services models are suggested [90]: • Business Process as a Service (BPaaS) The service offers the consumer the capability to manage an entire business process as a service in the cloud. Generally, the underlying capabilities of a BPaaS platform (i.e., software, technology, infrastructure resources, etc.) are owned and managed by the Cloud Service Provider. Examples of business processes could be: payroll, CRM, billing, HR, order taking, information delivery etc. The main difference of this model with the SaaS model is that the former includes services partly performed by people and not just by the applications software as in the case of SaaS. • Information/Data as a Service (DaaS) The service offers the consumer the capability to set information/data and associated metadata using one or more established standards. This type of service is especially useful for large and complex data.

Commercial Applications As mentioned above cloud computing is used mainly for three purposes: optimizing applications performance, storing large volume of data and connectivity purposes. Many companies choose to build their own clouds in order to maintain security, secure legal issues that are entailed by using external resources, and keep control of the infrastructure and the resources that will be used for their purposes. However, there are many examples of organizations that prefer to use a public cloud in order to avoid the cost and time consuming of the establishment of the cloud. These organizations address to external cloud services providers. Popular examples of public cloud providers are: • Infrastructure as a Service: in this case providers supply a virtual server instance and storage as well as APIs that let users (organizations) migrate workloads to a virtual machine. ◦ Amazon Web Services ◦ Microsoft Azure ◦ IBM/SoftLayer ◦ Google Compute Engine • Platform as a Service: in this case providers host development tools on their infrastructures. Users access those tools over the Internet using APIs, Web portals or gateway software. ◦ Salesforce.com ◦ Amazon Elastic Beanstalk ◦ Google App Engine • Software as a Service: in this case providers deliver software applications over the Internet ◦ Microsoft Office 365

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Cloud computing in transportation Cloud computing is used by early adopters in the transportation industry. The data shows that the market growing fast. In 2008, total transit ridership reached an estimated 10.5 billion unlinked trips. The main solution the companies ask from in the sector of transport lies in bringing various measurements together into one useful dashboard. The connection directly to the cloud of transport services can bring multiple pieces of data together which become available, in near real- time, allowing managers to make quick adjustments for better service [91].

The Device Cloud Many vendors provide online hosting or software-as-a-service (SaaS) models to transportation organizations. SaaS essentially allows the customer to rent the software and access it online for a monthly fee. While these tools can benefit the business side of the transportation industry, the real value comes when the cloud intersects directly with fleet management devices. Bypassing SaaS and simply passing data directly from the device to the cloud saves time and also money. It typically takes long, to plan, procure and deploy IT infrastructure to connect embedded transportation devices to the network and capture valuable data. Transportation agencies use GPS devices, passenger counters, fare collectors and other devices to capture key data. Traditionally, these devices are plugged into a hard-wired Internet connection, and the data is downloaded onto a local PC connected to a network. The data is downloaded at specified intervals, such as each night or once per week. Many times, data is either never used, or analyzed once per month or even once per year to make service changes. The device cloud is a term coined by Eurotech, to describe how organizations can bring data from device to business application with an integrated solution to turn bits of data into valuable and actionable information. By storing device data in the cloud, both public and private transportation agencies can access data in near real-time. The device cloud is also scalable, secure and many times more cost-effective than traditional infrastructure for transportation IT departments. As cloud computing becomes more mainstream, transportation agencies are evaluating whether a cloud solution can be an efficient alternative to traditional computing networks.

Simplifying the Dashboard using more useful data Using cloud computing for storing transportation data could beneficiary for travel/transport providers and agencies. Currently, the last ones collect various measurements ranging from travel time to fare collection. Then, the management of this data is done by different departments in these organizations. When all of these measures are stored in the cloud, transportation executives can access the data anytime and anywhere through a secure online portal. The creation of specific dashboards that extract the data needed, in considered to be invaluable in analyzing data. With a cloud computing infrastructure, the cloud service can pull information from all of the different databases and sources of information together into one simple and secure dashboard. At any given moment, the person in charge can generate a report containing both data such as fare collection and passenger counting with a single click. The elimination of operational times spent on processing data from different sources gained from cloud computing can minimize the personnel ‘s recurring time used to generate the same reports month after month, year after year [92].

Making Quick Decisions with Faster Data through the Cloud In addition to minimizing personnel’s effort with regards to data manipulation with a simple dashboard, cloud computing can also provide the benefit of more immediate, near real-time data. Since data is sent to the cloud almost continuously, organizations can see realistic snapshots at any given moment.

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4.10 Customer Relationship Management – User Profiling A customer profile is a description of a customer or set of customers that includes demographic, geographic, and psychographic information, as well as data about buying patterns, creditworthiness, and purchase history, collected from different marketing and transaction systems. Such information is usually managed by Customer Relationship Management (CRM) systems. In the context of travel industry, a customer profile is a record that contains useful information about a traveller, company, or agency. Many large GDSs and travel marketing companies have attempted to identify general traveller profiles.

CIC China conducted a detailed study on the Chinese travel industry by analysing about 30 million items of content related to and about 1.5 million Weibo tweets. The study primarily focused on five types of Chinese travellers: business, package, self-driving, backpackers, and luxury shopping travellers. The first highlight from the report illustrates traveller types in terms of their willingness to spend more time versus willing to spend more money.

The four key attributes for business travellers in order of priority were found to be flight time, ticket price, brand reputation and loyalty program/membership. Another type of travellers, are typically middle-aged people prefer self-driving trips due to reasons such as making friends, freedom, family and enjoying driving. A third category is package tourists that focus on services (travel agency, attraction tickets, tourist guide, one stop services, travel bus, optional expenses). They lack the travel experience and usually make no detailed plans. A final category, the backpackers want to experience the local culture, long for freedom, and explore the world and themselves. User-generated content is the most important factor for this group of travellers.

4.11 Big data processing and analytics Today’s processing power allows for the analysis of big data to find hidden correlations, consumer information and other business-relevant insights. With developments in cloud services, the capabilities of data analysis are increasing at the same time as progress in the field of artificial intelligence such as deep learning (The Economist, 2016). A number of technologies make big data processing possible: 1. Cloud computing —provides significant computing scale without huge capital investment. 2. Hadoop – a framework for running applications on a large cluster of commodity software. 3. MapReduce – runs on Hadoop and reduces large applications into smaller elements of work. 4. Logical data warehouse – data can be stored in many disparate places; shopping data may be separate from purchasing data. The logical data warehouse would see and treat these data sites as one, making analysis much easier. 5. NoSQL –provides an excellent database structure for big data processing. 6. In-memory databases: To achieve maximum performance, database processing is best done with data already in the computer’s memory, which cuts out the time it takes the computer to read data off a disk.

Machine learning allows computers to crunch vast amounts of data, recognise patterns – including real time image recognition of shared photos – and get better at what they do with experience. This has the potential to disrupt many aspects of consumer purchases

Companies across the various travel and transportation industry segments, such as airlines, airports, railways, freight logistics, hospitality and others, have been handling large amounts of data for years, but until recently have not always had the capability to turn that raw data into insights.

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In today's instrumented and interconnected world, unprecedented amounts of data are captured from almost every kind of system or event - and much of it is unstructured data. From passenger name records, transaction history and pricing data to customer feedback surveys, call centre logs and Twitter feeds, travel and transportation companies now have access to a lot of data on all aspects of their business operations and customer interactions.

At the same time, consumers are becoming smarter shoppers with a variety of choices via various channels - phone, web, kiosk, counter, 3rd party agency, etc. Travellers are becoming more demanding in the quality and variety of services available, as a result of rewards systems or loyalty programmes. The "empowered," or "always connected," consumer has particularly profound implications for the way that the travel and transportation industry manages travellers, requiring new approaches in responding to greater expectations of (for example) being kept informed and able to amend travel plans at short notice.

In order for travel and transportation organizations to capitalize on these and other challenges in the industry, they need ways to collect, manage and analyse a tremendous volume, variety, velocity and veracity of data. Organizations who can tackle the big data challenge will differentiate from competitors, gain market share and increase revenue and profits with innovative new services.

Currently, the travel and transportation industry as a whole is perceived as generally lagging behind other sectors in terms of how data is used, according to a recent IBM Center for Applied Insights study [93]. According to the study, for example, travel and transportation companies are surprisingly behind in predictive modelling, simulations and next best action modelling – all areas necessary to run operations efficiently and target customers effectively. According to an article [94] in Engineering News Record, a survey by a big data analytics company specializing in transportation planning underscored this picture of sluggish adoption of technology and age bias towards the potential of new technology.

This represents a huge opportunity for travel and transportation companies to derive more insights from their data, according to a recent Forbes article [95]. The article presents some examples of ways in which the travel and transportation industry can create value from big data and analytics are shown below.

For Customer analytics and loyalty marketing, data analytics has the potential to help companies create a comprehensive 360-degree view of the customer, dramatically improving customer interaction at every touch point and across the end-to-end passenger or traveller experience. This enables greater personalization and relevance to increase marketing effectiveness, improve customer service and drive loyalty.

The ability to analyse more historical information with higher frequency — in near real time — allows for more dynamic and smarter pricing actions, optimized capacity planning and effective yield management.

Predictive, proactive and sensor-based analytics can help companies achieve operational efficiencies and improve performance outcomes. By capturing and analysing more complete operational data, big data and analytics can help organizations manage and maintain their assets to improve safety, performance and equipment life. This enables asset optimization to shift from reactive repairs to preventative maintenance. Total cost of asset ownership is reduced, asset life and operational capacity is increased, and on-time performance is improved.

The travel and transportation industry is now seeking to emulate other sectors in deriving greater insights from the newly-available and manageable data it now has access to. In an era in which it

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 is possible to predict a new retail trend or customer retention patterns for cellular phones, similar types of analytics are providing insights that can predict flight delays and better understand customer decisions and behaviours. For example, as reported in another recent Forbes article 96], IBM is working with Lufthansa on a research project to develop automated systems to learn and interact naturally with airline operators so they can more precisely respond to weather conditions, minimizing the ripple effect of flight disruptions. The goal is a more proactive flight scheduling system to help boost operational efficiency and customer service. It could also help avoid costly downtime, and reduce maintenance and services costs for the airline.

In summary, areas where big data analysis could apply to travel distribution include: 1. Providing real-time transparency of operational data: enabling companies to see look-to- book ratios, responses to new promotions, reaction to new user interfaces, performance against plan, individual agent conversion rates, online abandonment, call center talk time, volume of help calls referred to a higher level, user satisfaction, and response to crisis events. 2. Determining relevant content to be displayed based on stage of the trip, location, device, psychographic profile, purchase and conversion histories (of a specific traveller or ones with similar profiles), and purpose of the trip. 3. Leveraging location based services: Location based services can be used for route optimization, understanding traveller behavior, developing new transportation facilities and tourist venues, and reducing gas consumption. 4. Defining the next generation of travel products and services based on behaviors throughout the travel distribution value chain. 5. Providing real-time operational traveller support services throughout the integration of the Internet of Things– real-time sensors that monitor the environment, transportation facilities, hotel rooms, etc. 6. Improving operations management: correlating service and preventative and restorative maintenance to reduce cost and increase efficiency, particularly in aircraft maintenance.

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4.12 Current limitations identified and EuTravel approach The following sections summarize the limitations identified in the ICT applications and services discussed in sections 4.2 – 4.11 and the EuTravel’s approach is presented. The following table summarizes the ICT categories and the relevant applications / solutions discussed in the aforementioned sections. The identified ICT solutions and technologies have shown significant potential in favouring seamless transport solutions. In addition, ICT solutions represent the key instruments to communicate the relevant information to the passengers for making a seamless trip possible: from the information on timetables, delays and interconnections to the availability of smart ticketing.

4.12.1 Journey Planners A research of Multimodal Journey Planners was performed in deliverable D2.3: One stop cross device multilingual interface. The Planners analysed were the following: Google Maps, RouteRANK, Rome2Rio, Vivanoda, Waymate, Wanderio, TripHobbo, and Expedia. Additional Travel Portals were examined in D2.4: EuTravel Value Added Services Research on Multimodal Planners (Annex 2) in order to extract useful data, such as the most successful practices, rising trends and possibly any service that is needed but has not been implemented yet.

The conclusions of the aforementioned analysis are the following (in summary in Figure 4-12 and Figure 4-13).

Current limitations: • The majority of Journey Planners offer booking, ticketing and payment services but users are redirected to related booking systems to carry out their respective bookings. To the best of our knowledge, there is no built-in mechanism within the existing portals giving to the user the ability to have multi-mode bookings through one single ticket. • The combination of multilevel information at a wider scale and the delivery of dynamic personalised data has not been yet properly addressed. • A significant number of Journey planners do not offer re-planning / re-routing neither alerts about disruptions during the travelling period. • Some portals are limited only for desktop resolution and they cannot be viewed from tablets or smartphones • Language Limitations

Figure 4-12 : Supported modes of transport of existing travel planners

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Figure 4-13 : Supported capabilities of existing travel planners

EuTravel Approach: The EuTravel Journey Planner outperforms the portals examined in all aspects such as booking, ticketing, payment, alerts about disruptions, cross device capability and multilingual interface. The lack of the alerts and replanning-rerouting functionality from almost all other portals gives to the EuTravel portal an enormous advantage over the others. As other portals provide booking, ticketing and payment mechanism through externals APIs, EuTravel has a customized, built-in mechanism giving to the portal user the ability to have multi-mode bookings through one single interaction. Overall, EuTravel offers new sub-services that improve the journey planning and booking experience. Another advantage of the EuTravel portal is that it supports both multilingualism and cross device capabilities, and along with the easy and smooth user experience gives to the users a complete solution for their trip planning. Overall EuTravel delivers a multimodal travel planner that: • supports several modes of transport (air, rail, bus/coach, ferry) and door-to-door segments, • is user friendly following latest user interface trends, • is accessed through multiple devices, • is implemented based on the latest web technologies and, • returns personalized results.

4.12.2 Optimisation Route search algorithms and the multi objective path search problem Current limitations: For multi-objective optimization problems, such as the multi-modal routing problem, there is usually no single optimal solution. For example, the quickest solution is not always the best one for a user since someone might be willing to accept a longer journey granted that the ticket is cheaper. Such problems tend to be characterized by a set of alternative solutions, which should be considered equivalent in the absence of further information regarding the relative importance of each objective in the solution vectors. Multi-criteria searches yield too many solutions, so it is needed to introduce reasonable constraints for pruning solutions that do not fit travellers’ preferences and provide unattractive paths. Due to the presence of many criteria that might come into conflict with each other, not only one optimal path is searched, but a set of paths with acceptable trade-offs among the routing criteria. Common path-finding methods cannot be applied efficiently to typical transport graphs that include road networks, although these graphs are ideal for road navigation systems due to the excessive number of included nodes and edges (tens of millions for continent-size level). Speedup techniques that require several hours of pre-

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 processing have been introduced. Expanding such graphs with public transport route information and timetables, adds complexity in both graph size and pre-processing effort.

Moreover, the restrictions due to data availability can affect the optimisation algorithm’s performance. Specifically, the route optimization for the geographical scale of Europe is strongly dependent to the quality of the available data (GIS data, schedulers, cost information, etc.). However, until now, the complete geographical representation of the European railway network is incomplete. Some railway routes are not available on digital format. The geocoding of the majority of stations is poor, and the schedulers may be not available. Thus, the route optimization has to be flexible enough and capable to operate with a minimal dataset. Also, it has to be expendable enough to incorporate new datasets that may be available in the future. However, new data source migration is (at most cases) a non-automated procedure due to poor standardization of such data. Other restrictions pertain to legal restrictions for traveling aboard, for example travelling from one country to another by using a private car that cannot be represented onto a typical transportation graph.

EuTravel approach: Instead of using a standard directed graph, EuTravel introduces a restricted graph which is the result of the transformation of the initial transportation graph into a minimal transit network graph consisted of unique trips and their topological relation, in which the basic structural element is the “trip”, as it has been introduced by Google Transit and the General Transit Feed Specification: “A Trip represents a journey taken by a vehicle through Stops. Trips are time-specific - they are defined as a sequence of StopTimes, so a single Trip represents one journey along a transit line or route. In addition to StopTimes, Trips use Calendars to define the days when a Trip is available to passengers.” Each trip, which is also a graph by itself, is a single vertex for our graph, thus, each solution produced by the journey planner is a finite sequence of adjacent trips. Regarding the intermediate legs of this sequence (the transit stops have not been selected by the user as initial preferences as the user has selected only the origin and the destination location) they are adjacent to each other (the distance between transit stations is minimal, less than 1km) so there is no need to use some private transportation mean (i.e. car / taxi) for moving between them. The traveler is provided with door to door information for the first and the last leg of the journey (urban directions on departure and arrival based on OPTI-TRANS results - see section 5.1).

The transformation to a minimal transit network graph reduces the total number of vertices for a continent scale transit network to a few thousands. Besides the reduction of the graph size (>99%) and its impact to the runtime and storage size requirements the transformation (pre- processing) time is reduced from several hours to a few minutes, thus, it is possible to be dynamically updated while running in a production environment. Additionally, the graph is “built- in”, compliant to the GFTS standard, thus, updating data from GTFS sources is a one-step procedure. Each solution produced by the journey planner is a finite sequence of adjacent trips. To minimize the number of trip interchanges (a trip with more than 4 or 5 means changes is not preferred), we perform early stopping on the path-finding algorithm, in order to achieve: • Further speedup • Solution space restriction (all solutions that include >5 interchanges are ignored) • Minimization of the number of used means (least number of changes optimization) In terms of the solution ranking apart from the applied least-changes optimization criterion, the solution set can be sorted based on other (countable) criteria, such as travel duration, CO2 emissions, and price, in order to eliminate non-optimal solutions and extract the top K ones based on the selected criterion.

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The available EuTravel data set is only a subset of European-wide transportation data (less than 10% of trains and bus routes). It is assumed that the performance measurements would remain (practically) the same if a complete data set was available.

4.12.3 Travel Recommender systems and Geolocation techniques. Current limitations: To the best of our knowledge existing systems do not support the user in building a personalised multi-stage trip that consists of multimodal travel, accommodation and visiting of cultural and other touristic attractions. Therefore, such systems only help the users decide the destination of their travel. To make effective recommendations, factors that influence destination choice need to be identified; these include both personal features and travel features. The first group contains both socioeconomic factors (such as age, education, and income) and psychological and cognitive ones (personality and attitudes towards travel). The second group might include travel purpose, travel-party size, and length of travel, distance, and transportation mode. These various factors affect all stages of the traveller’s decision-making process, which is a complex constructive activity [12]. Another reason why these systems focus on destination selection relates to the content- based approach they employ. To apply the same filtering technology to other tourism concepts, e.g. hotels, the system would have to create a knowledge base of hotels containing the features considered by the algorithm. Thus, Ricci (2002) [12] argues that this approach does not scale without a costly knowledge-engineering activity for each travel product type. Currently, the focus is on destinations because they are rather stable, reusable concepts, i.e. corresponding to major geographical regions, resorts, cities etc. While collaborative filtering approaches do not suffer from this problem, Ricci (2002) argues that they suffer from another critical problem, which is the availability of sufficient data for comparison. Two trips are very unlikely to be similar under all considered parameters- unlike other less complex products such as music and books. Hybrid approaches that combine content and collaborative-based approaches are therefore more likely to succeed. It has been suggested however, that most of the existing recommender systems only provide location-centric recommendations to travellers about ‘things to do’, once they get to their destination.

Some advanced recommenders, like SAMAP [145] and PaTac [146], are even capable of analysing the connection possibilities between the activities using different means of transport i.e., on foot, by bike, by car, or by public transport. This category of recommenders has similarities to automated travel planners. However, travel planners mainly rely on domain knowledge about routes and their properties, such as available travel modes, online timetables, knowledge of the average travel times and so on. Such knowledge is hard to acquire, integrate and maintain. On the other hand, travel knowledge elicited directly from the travel users themselves, maybe easier to acquire, due to the proliferation of travel related web sites such as forums. This knowledge may be less accurate and more subjective than the knowledge employed by travel planners, but that is compensated by the large volumes of available data.

Finally, another feature that travel planners are lacking is critiquing user proposed routes. Often users have a particular route in mind that they want to follow, but they want other user’s opinion as to whether their route represents a good choice. A recommender system augmented with critiquing capabilities can comment on user proposals by comparing the users’ routes (or the routes’ legs, modes of transport etc), with what other users have recommended.

In the same context, geolocation services seem to be of great interest to travel management companies and travel providers and they are taking steps towards the adoption of such services. The traveller experience plays a major role in the travel industry, whether it concerns proactive destination information, help in an emergency situation, multichannel access or personalized services. For example, hotels are using geolocation apps to fill up empty rooms with last minute travellers and some of them track their customers’ position in order to inform them with

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 pertinent details for their room number and procedures, when close to the hotel. Geolocation apps providing promotion amenities in terms of restaurants, retail shops etc. based on personalisation are considered of great interest in the tourism industry as they might have a direct impact on the bottom lines of the specific industry.

EuTravel approach: As described in detail in deliverable D2.4, EuTravel Value Added Services (VAS) consist of integrated tools within the EuTravel ecosystem that extend the usability of the ecosystem's core functionality by providing additional travel services to a variety of stakeholder groups, such as transport infrastructure and service providers, travel service providers, and authorities, as well as to consumers themselves (travellers). Their main purpose is to customise, combine (aggregate) or otherwise add value to existing travel services. The Travel Diary mobile application that will be incorporated in the EuTravel ecosystem, consists of a door-to-door information system with the ability to associate places with notes and photos, and also to enhance travel experience with personalised recommendations and feedback. In addition, it provides incentives to encourage multimodal travelling options through several gamification approaches, such as “Achievements”. The “API of APIs” is used for the collection of valuable metadata through the information produced by the usage of the mobile app by the consumers, e.g., likes, existing trips, user profiling and behaviour, etc. This app-generated content has the potential to enrich the existing knowledge of the Optimodality Framework, producing more sophisticated and accurate information about possible POIs, places and/or products. This enhanced information is retrieved by the mobile app using the “API of APIs”, increasing the performance of its operation towards the fulfilment of consumers’ needs.

Regarding advancing the state-of-the-art in recommender systems, EuTravel presented an awarded paper in the Ninth International Conference on Advances in Databases, Knowledge, and Data Applications, in Antwerp (Karakostas, 2017) [142]. The paper presents a travel route recommender and critique that does not rely on objective travel knowledge such as travel timetables, travel times and distances but on user recommendations. The system is capable of recommending the most popular means of transport between two locations. This differs from the typical travel planner’s ability to find the best route between two places based on criteria such as travel time or cost (full paper in the Annexes of D4.4: Dissemination Strategy, Communication Plan and Evaluation Report).

4.12.4 Travel APIs Current limitations: The key barriers to interoperability and wide adoption of door-to-door mobility solutions as identified by the European Commission in the Draft Delegated Regulation on the provision of EU- wide multimodal travel/transport information services European Commission [139] are summarised below: 1. Insufficient accessibility of travel and traffic data Without access to full range of datasets across Europe from public and private sources, services will remain limited in scope, both in a geographical (all urban and inter-urban parts of Europe) and modal (all available transport modes) sense. At present, access to the full range travel and traffic data is still limited and technically speaking there are no appropriate data sharing mechanisms widely available across the Member States. 2. Lack of travel and traffic data interoperability The ability to easily exchange and integrate multiple sources of data of different transport modes is essential. However, at present there is no single data format for all modes: instead, a large variety of data formats and exchange protocols are used amongst the various transport modes making it increasingly costly and time consuming for travel information service providers to manage and integrate various data sources. This gap is seen as a key barrier in the provision of full door-to-door mobility.

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3. Lack of travel information service interoperability Many travel/transport information services exist at city, regional and national level. However, the interoperability between such services remains limited. The lack of commonly accepted and standardised application programming interfaces (APIs) of operators is considered one of the key barriers. Furthermore, as discussed in section 4.7: Travel APIs, there is a large number of heterogeneous APIs with different functionalities. The EuTravel classification of APIs as proposed in the aforementioned section is not actually a strict classification as APIs may straddle several themes and some APIs may appear to not belong to any of the proposed themes. Instead this classification was proposed in an attempt to scope the planned ‘API of APIs’.

4. Insufficient travel and traffic data quality The quality of travel and traffic data in terms of being accurate, up to date etc. are fundamental for the widespread and uptake of multimodal travel information services. However, quality levels, especially those for real-time information, are varied across the EU and consistency of such data quality is essential.

EuTravel approach: As discussed in deliverable D2.3: One-stop, cross-device multilingual interface, the main purpose of API of APIs is to overcome interoperability barriers in the transportation and travel-related industry. The development of the proposed API of APIs will allow unifying all heterogeneous APIs under a common collaboration ground. It contains all the methods that operate under the Optimodality Framework. Thus, the API of APIs can be conveniently used by front-end application templates to communicate indirectly with all necessary heterogeneous APIs in a unified, homogeneous manner. In addition, the clients of the API of APIs do not require semantic processing capabilities, as the information is returned in a common format (e.g. XML) suitable for lightweight clients, such as mobile and tablets devices. The “API of APIs” operates as the only required intermediate between both consumers and different stakeholders, enabling in this way the interoperability of services across the EuTravel Ecosystem. This is where our solution, the Optimodality Platform comes in. It is a cloud solution aiming to unify all these channels under a single data model, namely CIM, so that seamless communication can be achieved between Ecosystem participants. The Optimodality Platform is designed to manage the end-to-end information flow from timetables, to planning, shopping and booking along with any Value-Added Services that can be offered.

Essentially, the project belongs to the class of “aggregator” systems, by integrating and supplying multiple proprietary and heterogeneous APIs from a single endpoint. This indicates that the challenges the team had to overcome began with indexing and semantically classifying the available datastores in terms of quality and quantity, studying the data and the surrounding documentation in order to enable numerous systems to interoperate under a single, open and extensible domain model in the form of the Common Information Model, orchestrating the data flows in a service-oriented approach and finally exposing them via a single API, the “API of APIs”. This functionality was developed as multiple software modules, cumulatively forming the core of the ecosystem. In summary, the EuTravel approach addresses the following issues: 1. APIs hard-wired to the applications of operators and other systems. 2. Heterogeneity in API data structures. 3. Information about travel itineraries is scattered across different domains/means of transport and different companies, thus, different databases. This information needs to be transformed in a uniform manner (Common Information Model -CIM), in order to be able to optimally and timely serve multimodal itineraries. 4. Data overlapping between different sources.

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4.12.5 e-payment solutions Current limitations: Despite the availability of the implemented technologies, a) booking is still handled separately for each journey leg, and b) booking as a process is not separated from the payment systems in available solutions on the market. EuTravel approach: A single account payment is envisioned for all the chosen journey legs, in a way that there is no need to purchase separate travel tickets. This is further elaborated in Deliverable D1.4: EU Optimodality Framework.

4.12.6 Task models and travel ontologies Current limitations: There are several domain ontologies for travel and transport that describe the specialised vocabulary of concepts in the particular domain. These ontologies were developed in isolation from each other and present lack of compatibility and overlapping leading to interoperability barriers. EuTravel approach: In EuTravel, ontologies from different transport domains and modes are integrated by alignment to the Optimodal Unified ontology. This will provide a common foundation for classes and relations in multimodal transport (Deliverable D1.4: EU Optimodality Framework). Furthermore, Karakostas and Kalamboukis (2017) introduced a method for the semantic annotation of APIs, towards enhancing the utility of APIs in delivering travel information in mashups [140]. An API annotation engine was created, using semantic descriptions of established open Ontologies (WordNet, ConceptNet). The annotation engine parses API descriptions in XSD, JSON, and other hierarchical formats, and subsequently uses the linguistic constructs (nouns, verbs etc.), that describe API data and operations), to map them to concepts of the ontology hierarchy. This method has been implemented as a semi-automatic data mapping engine. A unified graph data model for travel was created, holding travel related concepts from different ontologies. Namespaces were defined for different ontologies, allowing APIs to be annotated in a consistent and uniform way (see also deliverable D2.2: Ecosystem Specification and Prototype Implementation and full paper in the Annexes of D4.4: Dissemination Strategy, Communication Plan and Evaluation Report).

4.12.7 User Profiling Current limitations: A customer profile is a description of a customer or set of customers that includes demographic, geographic, and psychographic information, as well as data about buying patterns, creditworthiness, and purchase history, collected from different marketing and transaction systems. In the era of multimodal travel solutions, designing personalized services according to the users’ criteria may be challenging, as this information needs to be shared with multiple back- end booking systems to retrieve accurate responses on availability and prices.

EuTravel approach: As described in deliverable D2.3 3 One-stop, cross-device multilingual interface and more specifically in section 4.21: Front-end Interface, the traveller needs to enter some information in order to begin the journey planning and to get personalised results. Some fields are mandatory and some optional. The data that needs to be inserted include the arrival/departure location, departure date and number of travellers, along with the option of choosing one or two-way trips. The EuTravel User Profile is divided into three major sections: Personal Info, Account Info and Preferences. Under the Personal Info section as illustrated in the following figure, the traveler will be able to add personal data such as full name, gender, address, date of birth, phone number,

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 passport details etc. This user-specific information can be used for the booking, ticketing processes and statistical purposes. Under the Preference section the traveller will be able to pre- define some parameters/filters in order to get personalised results, including: travel duration, distance, special assistance, and journey carbon footprint. The API of APIs back-end orchestration layer, performs data combination, fusion and aggregation, and by contacting GDS’ and operators’ APIs gets current prices for specific itinerary segments (D2.2: Ecosystem Specification and Prototype Implementation – Section 5.2.3 Orchestration).

4.12.8 Big Data processing and analytics Current limitations: Presently, travel organizations have deployed data warehouses and OLAP technologies for these purposes. However, these approaches suffer from the following issues:

1. Data availability. Data warehouses are built incrementally and there is always a list of subject data waiting to be added. Typically, a steering committee made up of marketing, IT and other stakeholders prioritizes what data subjects must be included and in what order. This involves a constant cycle of evaluating the business value, cost and feasibility of processing the data. Survey data, for instance, might be considered of lower value and feasibility when compared to retail data. However, it could be one of the most powerful tools for understanding a customer’s engagement and sentiment. 2. Very large volumes of data. Decisions need to be made around what data to store in the data warehouse and how long to maintain it. However, filtering and pruning customer data can stand in the way of getting the full picture of the situation. Also, typically, these decisions are made by Information Technology (IT) based on infrastructure costs, rather than business people. 3. Unstructured data. Data of this type is very difficult to model in a relational database, and correspondingly in a conventional data warehouse. If this data is structured and conformed, much of its original value can be lost. In general, a good amount of the raw data is discarded as a tradeoff for storing it in a more useable form. Additionally, much of the unstructured world is comprised of text. Analyzing and gaining insight from this data in the relational world is quite challenging and the toolset is relatively thin, especially when dealing with high volumes.

EuTravel approach: The Common Information model (D2.2: Ecosystem Specification and Prototype Implementation) deals with the modelling challenges of travel data. Additionally, in D2.4: EuTravel Value Added Services, an Analytics and Business Intelligence Dashboard for developing and displaying multimodal travel-related reports and analytics to stakeholders is presented, utilising big volumes of data for improved insights.

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4.13 Discussion on results and selection of technologies to be used and to be monitored (Technologies Library) The initial results of task T1.3 and specifically the design decisions related to the technologies to be used for further development of the EuTravel prototype, were discussed in the Innovation & Exploitation Boards Meeting and side-demonstration/workshop in London on the 29th of July 2015.

Apart from project partners, the Association of British Travel Agents and Tour Operators (ABTA) participated in the meeting (representative: Mrs Susan Parsons).

The key topics discussed in the meeting were: • The updated EuTravel Solution Architecture/Implementation Approach (evolution of initial design presented at the kick-off meeting) and related technologies. • The infrastructural key components including the Common Information Model. • Reflection on the live demonstration of initial back-end prototype, including the first version of an interactive map powered by a knowledge graph. The prototype supported multimodal searching capabilities from city A to city B (worldwide) and a visual representation of alternative itineraries using color code for different modes. • Indicative Use Case Process Workflows • Decisions on project boundaries and next steps regarding the implementation path.

The following diagrams (Figure 4.14 to Figure 4.18) were discussed in detail during the meeting.

Figure 4.14: Semantics Transformation Component

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Figure 4.15: Data Fusion Component

Figure 4.16: Semantic Graph Component

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Figure 4.17: Related classes for means of transportation

Figure 4.18: Indicative Use case workflow

Based on this preliminary research, baseline knowledge base and related projects outcomes (Chapters 5 and 6), project scope and meeting discussions, specific technologies were identified as core to the EuTravel solutions development (library of selected technologies monitored throughout the project). It was considered important for EuTravel to utilise and advance the state-of-the-art on technologies related to: • Journey Planners and Advanced Travel Information Services, • Route optimisation, • Travel Ontologies,

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• Data integration and harmonisation (of data provided through APIs by different service providers across different modes), • Data and insight (Knowledge discovery) technologies for the development of added value services for all travel stakeholders.

The way these technologies are utilised and advanced within the project, is elaborated in the technical deliverables: • D1.4 EU Optimodality Framework • D2.1 Technology Ecosystem Architecture • D2.2 Ecosystem Specification and Prototype Implementation • D2.3 One-stop, cross-device multilingual interface • D2.4 EuTravel Value Added Services • D3.2 Living Lab Setup

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5. ITS Developments across Europe and Reference Projects

This chapter presents completed and on-going projects and initiatives related to EuTravel. Even if many of them focus on urban mobility, outcomes and deliverables provided a baseline knowledge base for further research.

5.1 OPTI-TRANS OPTI-TRANS [97] is a multimodal Journey Planner that allows travellers to plan their trip efficiently by making optimal use of public and private transport while taking into account their preferences (shortest transport time, minimum cost etc). It also incorporates Dynamic Car Sharing and Taxi- on-Demand options and provides information about traffic congestion, strikes, and points of interests. The OPTI-TRANS mobile GNSS application has been supported by the EU under FP7- Galileo 2007 - GSA Call 1 finished in March, 2011. It is currently available for Athens, Madrid, Rome, Barcelona, London, Brussels, Prague, Oslo, New York and Boston, and expanding rapidly to other cities across the Globe. OPTI-TRANS interface with existing database systems provides public transport information (timetables, routes, etc.) so as to give the most optimal multi-modal solutions for the commuters' requirements. It incorporates Transport-on-Demand through the Car Pooling services and Passenger-on-the-Curb facilities that allow privately owned vehicles to be shared with others subscribed to the service. The OPTI-TRANS project fully met the objectives in demonstrating the potential for Location Based Services and GNSS technology both to the general public and the public transport authorities The objectives of the OPTI-TRANS project were as follows: • To provide an innovative, multi-modal personal navigation mobile location based services (LBS) application which will interface with a core platform providing an optimum combination of use of public transport and carpooling facilities to the commuter. • To develop the highly intuitive OPTI-TRANS platform consisting of the Location Based Ad- Hoc Group (LBAG) algorithm which will combine information from various sources (public transport DBs, personal commuter profiles, car-pooling services, etc.) in order to provide optimum routing and co-modal transportation to the commuter/traveller. • To support the status of LBS as a key technology for implementing transport policies with the implementation of the OPTI-TRANS platform and the mobile LBS application which will demonstrate the feasibility of a dynamically updated, location-aware pedestrian and public transport route planning tool. • To endeavour to standardise interfaces to Public Transport Authority databases in order to allow applications such as the OPTI-TRANS solution to be utilised across Europe (and consequently traversing border beyond Europe), thus providing seamless roaming to the users of the OPTI-TRANS solution. • To assess the user requirement, evaluate and determine the adoption of available state- of-the-art technology enablers (LBS services and applications) and derive the technical specifications of the OPTI-TRANS platform while taking into consideration the early study performed on the technical feasibility of the overall system. • To determine the specification of the OPTI-TRANS representative test cases and pilot scenarios, define concrete and measurable validation criteria and to define the architecture specification of the OPTI-TRANS platform and GNSS-enabled mobile LBS application. The user-defined test cases and technological evaluation results will be acquired during the evaluation phase of the project. The participation of the Europe-wide leading players will ensure the importance of the OPTI-TRANS user-defined test cases and demonstrations. • To conduct market surveys and develop a business model in order to determine the most efficient, functional and user-acceptable operational model for the system as well as to demonstrate the commercial feasibility of the end product. The business model pertaining to the commercial exploitation of the OPTI-TRANS system will be defined from

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the perspectives of the various players involved in the concept (network operators, public transport authorities, end users, etc.), and to assess the various socio-economic and ethical aspects that are involved. The OPTI-TRANS concept will be measured and the system's added value will be demonstrated by conducting extended user trials, representative of the user-defined test cases. • To effectively facilitate and encourage the dissemination (i.e. organisation of workshop embracing awareness sessions, presentations, feedback, etc) in order to promote awareness of the OPTI-TRANS solution, and advance exploitation of existing and emerging expertise and practices in the field of Location Based Services, and active participation in workshops, forums, tradeshows, etc. • To build on previous FP6 work, namely to extend the Taxi-on-Demand system developed within the context of the FP6 IST project LIAISON, and to provide the appropriate experience for building this LBS solution to the Mass Market utilising work and findings from the FP6-Galileo project AGILE.

For the needs of the EuTravel project, NCSRD adjusted and expanded its multi-modal Journey planner (OPTI-TRANS) in order to offer the EuTravel door-to-door service. The door-to-door service provides optimal multimodal door to door navigation instructions to the end user, for combinatorial use of public transport from a point of departure to a destination, including walking. It provides a detailed description of all intermediate stops along the route on the map or in text format. The core algorithm which is based on the graphhopper1 libraries is a fast and lightweight implementation of the bidirectional2 A* algorithm. By making use of the open standards such as the GTFS3 format and the OpenStreetMap4 data the algorithm can support many different cities without the need of any modifications. For the needs of the EuTravel project the door-to-door service will support the following cities: Athens, Rome, Barcelona, London, Brussels, Prague, Madrid and Oslo. The main features of the door-to-door functionality are the following: • Quick calculation of optimal route. • Calculation of time and alternative routes. • Combination of all means of transport. • Selection of origin/destination point through GPS. • Detailed description of route on map. • Timetables, News & Traffic info where available • Favorite routes & POIs.

5.2 WiseTrip WISETRIP [98] is an FP7 project finished in November 2010 that demonstrated an effective way to integrate different Journey Planning engines, covering different geographical areas, to form a unified multi-modal planner for international journeys. WISETRIP has addressed the issue of personalized trip services. The user can configure his personal data and trip preferences before and during the trip though the seven categories of personalization services offered: My preferences, Scheduled notifications, Trip Disturbances Alerts, Trip Segments Validations, Automatic Trip Reschedules, My Reminders and My Bulletin. The main problem faced by WISETRIP is the wide variance in the level and quality of information provided by national journey planning systems and the fact that the requirements of user groups with population on-growth should be accommodated. Moreover, social media and mobile extensions will increase usability within certain scenarios. European-wide Journey Planning should become attractive to the public as a personal trip assistant, rather than a traditional Journey Planner. Integrated ticketing should

1 https://graphhopper.com/ 2 https://en.wikipedia.org/wiki/Bidirectional_search 3 https://developers.google.com/transit/gtfs/reference/ 4 https://www.openstreetmap.org

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 become a closer vision practically in place rather than a vision [99]. Enhanced WISETRIP (finished in February 2014) aimed at building on the knowledge and results achieved within WISETRIP to provide efficient and green planning international multimodal trips. More specifically the project aimed at improving the following aspects of the WISETRIP project: Content and modal extension (geographical, multi-modal coverage), pricing and ticketing information, alerts and re-planning options, concern about elderly and disabled users, concern about green routes, and mobile applications for new generation devices. The Enhanced Wisetrip web interface, is not currently available, so based on the final project’s report summary published in EU Cordis portal the project enhanced WISETRIP’s multimodality aspects by covering a limited number of international and national routes (Greece, Finland, UK, Italy and China). WiseTrip content was expanded with five additional Journey Planners. Additionally, the modal extension was partially addressed in Enhanced WISETRIP by including international air routes, Adriatic Ferries, static rail routing data and public transport mode for the region of Toscana. Alerting, re-routing, consideration about elderly and disabled and CO2 emissions, were taken into consideration by the proposed Enhanced WISETRIP Itinerary planning algorithm. It is not clear if the project provided integrated ticketing.

EuTravel addresses the aforementioned issues including: personalisation services, green planning international multimodal trips based on CO2 emissions and unified booking. In EuTravel journey planning, a traveler can choose not only between cheapest or shortest itineraries but also itineraries based on the least greenhouse gas modes. Each solution produced by the journey planner is a finite sequence of adjacent trips. Apart from the applied least-changes optimization criterion, the solution set can be sorted based on countable criteria, such as travel duration, CO2 emissions, and price.

Regarding the unified booking phase, the EuTravel system acts as a “single point of interaction” between the user and all transport / travel operators involved in the multi-modal travel solution, giving the user the possibility to perform a single booking request for all the involved operators and complete the booking process in one step only. Thus, it puts in place a user-friendly booking process, allowing the user to perform a single booking request and save time. Therefore, the booking stage completely changes the current interactions and processes, overcoming fragmentation (Deliverable D2.2 - Ecosystem Specification and Prototype Implementation).

The EuTravel’s Travel Diary mobile application, as described in deliverables D2.3 One-stop, cross- device multilingual interface and D2.4 EuTravel value added services, consists of a door-to-door information system with the ability to associate places with notes and photos, and also to enhance travel experience with personalised recommendations and feedback.

5.3 Shift2Rail (S2R) The European Commission is working towards the creation of a Single European Railway Area and has promoted a modal shift from road to rail in order to achieve a more competitive and resource- efficient European transport system. However, the share of rail on the European freight and passenger transport markets is still not satisfactory. EU research and innovation must therefore help rail play a new, broader role in global transport markets, both by addressing pressing short- term problems that drain rail business operations, and by helping the sector to achieve a stronger market position.

The Shift2Rail Joint Undertaking [100] is a public-private partnership in the rail sector, providing a platform for cooperation that intends to drive innovation in the years to come. The Shift2Rail Joint Undertaking pursues research and innovation activities in support of the achievement of the Single European Railway Area (SERA) and improve the attractiveness and competitiveness of the European rail system.

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Shift2Rail fosters the introduction of better trains to the market (more comfortable, quieter and more reliable, etc.), operating on innovative rail network infrastructure in a reliable way from the first day of service introduction, at a lower life cycle cost, with more capacity to cope with growing passenger and freight mobility demand. All this will be developed by European companies thereby increasing their competitiveness on the global marketplace.

Shift2Rail contributes to: • Cutting the life-cycle cost of railway transport (i.e. costs of building, operating, maintaining and renewing infrastructure and rolling stock) by as much as 50%; • Doubling railway capacity; • Increasing reliability and punctuality by as much as 50%. and its impact can be seen on all segments of the rail market: High Speed/Mainline, Regional, Urban/Metro & Suburban, and Freight and make daily life easier for millions of European passengers and rail freight users. The work conducted within the Shift2Rail framework is structured around five asset-specific Innovation Programmes (IPs) (Figure 5.1), covering all the different structural (technical) and functional (process) sub-systems of the rail system, namely:

• IP1: Cost-efficient and Reliable Trains, including high capacity trains and high speed trains; • IP2: Advanced Traffic Management & Control Systems; • IP3: Cost-efficient, Sustainable and Reliable High Capacity Infrastructure; • IP4: IT Solutions for Attractive Railway Services; • IP5: Technologies for Sustainable & Attractive European Freight.

These five Innovation Programmes are not just a simple “package” of programmes that are independent of one another. On the contrary, they form a whole assembly of the railway system, with a number of common cross-cutting themes and the R&I activities of the Joint Undertaking have to be managed in the most efficient way to allow the full coverage of all areas while ensuring a high degree of efficiency in the management of the technical activities.

Figure 5.1: Shift2Rail – Innovation Programmes

The Joint Undertaking Shift2Rail (S2R) was created to respond to the objectives defined in the White Paper and in the Fourth Railway Package, namely the goal of strengthening the role of rail in the transport system, given its inherent advantages in terms of environmental performance, land use, energy consumption and safety. A key initiative in achieving this goal is also the creation

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 of a Single European Railway Area (SERA). It is recognised that there is need for significant progress to be made by the sector in terms of efficiency, reliability, sustainability and more generally, user friendliness and attractiveness. The initiative has led to an increased visibility of rail research and improved the coordination of many technical aspects. However, there are some concerns on the multi-modal aspects. From a number of interviews concerns were expressed that having all rail research being ‘organised’ by the rail sector increased the exclusivity of rail and reduced opportunities for inter/multi-modal solutions and innovation. The rail sector seen from the outside is often perceived as being individualistic. [144].

The initiative is monitored throughout the EuTravel project and also discussed in deliverables D1.1: EuTravel Stakeholder Requirements Specification and D.1.2: Policy, Legal and Standardisation Requirements Analysis Report (see specifically Section 5.4 IT2Rail Project that follows).

5.4 IT2Rail The IT2Rail -Information Technologies for Shift2Rail project, is a first step towards the long term IP4 -“IT Solutions for Attractive Railway Services” [101], one of the Shift2Rail Joint Undertaking’s Innovation Programmes, which aims at providing a new seamless travel experience, giving access to a complete multimodal travel offer which connects the first and last mile to long distance journeys. This is achieved through the introduction of a ground breaking Technical Enabler based on two concepts:

• The traveller is placed at the heart of innovative solutions, accessing all multimodal travel services (shopping, ticketing, and tracking) through its travel-companion. • An open published framework is providing full interoperability whilst limiting impacts on existing systems, without prerequisites for centralized standardization.

The project is funded under European Union’s Horizon 2020 programme and its main objective is to enable the development of solutions providing a seamless travel experience by giving access to a complete multimodal travel offer, which connects the first and last mile of long distance journeys. IP4’s vision should lead to a dramatic increase in “rail attractiveness”, generating sufficient growth in demand to support a major shift to rail, through a seamless travel experience, and a seamless access to all travel services by innovative digital technologies.

IT2Rail looks into a complete door-to-door intermodal journeys encompassing distinct modes of transportation, combining air, rail, coach and other services. It integrates diverse existing and future services for planning, one-stop-shop ticketing and booking transactions, along with real- time re-accommodation.

Through the introduction of radical new technologies and solutions, the European citizen’s global travel interactions will be transformed into a fully integrated and customised experience. It will further render the entire European transportation system a natural extension of citizens work and leisure environments, across all modes, local and long-distance, public and private.

Although IT2Rail seems very similar with the EuTravel project, it is heavily focused on promoting the rail sector of a multimodal journey. Additionally, a different approach regarding the interoperability of different services (and their respective APIs) is being followed in terms of semantic heterogeneity. Discussions with IT2Rail project towards cross-fertilising projects results are described in deliverable D4.4. -Communications Programme.

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5.5 TAP-TSI The European Commission has adopted a regulation on standards in the field of telematics applications for rail passenger services (Commission Regulation (EU) No 454/2011 of 5 May 2011 on the technical specification for interoperability relating to the subsystem ‘telematics applications for passenger services’ of the trans-European rail system). These standards, known to the rail sector as "technical specifications for interoperability" (TSI) relate to the subsystem "telematics applications for passengers" (TAP) of the trans-European rail system and define how stakeholders must interact with travel-related data in the field of rail transport.

The main objective of TAP-TSI is to facilitate planning, reservations and travelling by train in Europe. It will also strengthen passengers’ protection and enhance informed consumer choice by making it possible for rail companies and ticket vendors to fulfil their obligations under Regulation (EC) No 1371/2007 on rail passengers’ rights and obligations.

The standards define how stakeholders must interact with rail travel data. The data exchange covers timetables, tariffs, information on conditions of carriage before and during the journey, as well as other data. Part of the standard is the definition of a standard rail data exchange architecture with definitions of key data content and approved standards of exchange with other modes.

The TAP-TSI standard is of high importance for the further development of any European multimodal service. The computerised information and reservation systems that will be developed on the basis of these standards will not necessarily supply "integrated tickets", meaning a single ticket for a trip involving more than one transport mode. However, based on these standards, suitable communication systems between rail companies and ticket vendors will be developed, while rail data will be made available to all players, such as rail companies, infrastructure managers and ticket vendors. They will have at their disposal harmonised travel data, which they can use to develop IT tools and applications. For example, the data could be used to book tickets for international rail journeys, plan a European journey crossing national borders, or display the latest information on the internet or in the train itself.

As already stated above, TAP-TSI prescribes the protocols needed for the data exchange of Timetables, Tariffs, Reservation, Fulfillment etc. Identically, standard information content on timetables, (aside from departure and arrival time) is defined as: • Basic principles of train variants • Representation of a train, • Different possibilities to represent days of operation, • Train category / Service mode. • Transport service relationships • Coach groups attached to trains, • Joining to, splitting from, • Through connections (connecting to), • Through connections (Service number change). • Details of transport services • Stops with traffic restrictions, • Overnight trains, • Time zone crossings, • Pricing regime and Reservation details, • Information Provider, • Reservation Provider, • Service Facilities,

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• Accessibility of the train (including scheduled existence of priority seats, wheelchair spaces, universal sleeping compartments) • Service extras, • Connecting - Timing between transport services. • Station list. • This reflects the complexity of rail travel.

TAP/TSI and its attributes have already been used in the EuTravel project so as to be aligned with the EC initiatives regarding the offered services for rail passengers (Discussed also in deliverables D1.1: EuTravel Stakeholder Requirements Specification and D.1.2: Policy, Legal and Standardisation Requirements Analysis Report). A complete and detailed analysis of TAP/TSI is made available to the public through a White Paper from the EuTravel consortium (deliverable D1.4 – Optimodality Framework, Annexes).

5.6 Full Service Model Initiative (FSM) Full Service Model (FSM) [102] is an initiative by rail industry stakeholders, aiming to develop and implement technical specifications for the interoperability of telematics applications for passenger services (TAP-TSI) and to fill in potential gaps. The FSM aims to put in place an industry standard for rail data exchange, including door-to-door travel throughout Europe and promote further cooperation between railway operators and ticket vendors.

FSM concentrates on the functional requirements and specifications for an open, interoperable IT framework designed to be used by a wide number of applications. More choice and information for passengers and additional business opportunities for both rail operators and ticket vendors are expected to be the main outcomes of the initiative.

The following organisations have an advisory role to FSM:

CER [103]: The Community of European Railway and Infrastructure Companies brings together more than 70 European railway undertakings and infrastructure companies. CER represents the interests of its members towards the European institutions as well as other policy makers and transport actors. CER’s main focus is promoting the strengthening of rail as essential to the creation of a sustainable transport system which is efficient, effective and environmentally sound.

ECTAA [104]: The European travel agents’ and tour operators’ associations regroups the national associations of travel agents and tour operators of 30 European countries, of which 26 are within the European Union, and represents some 70.000 enterprises.

ETTSA [105]: The European Technology and Travel Services Association, was established in 2009 to represent and promote the interests of global distribution systems (“GDSs”) and online travel agencies (“OTAs”) towards policy-makers, opinion formers, consumer groups and all other relevant European stakeholders.

Through the involvement of ETTSA (representing GDSs), FSM’s work contributes towards the integration of rail and air travel solutions and the harmonisation of information.

Implementation is carried out in parallel for all process steps including shopping, booking, fulfilment and payment (Figure 5.2). More specifically, due to the size and scope of the FSM, it was decided to divide the entire traveller process into several Traveller Stages: 1. Pre-purchase customer information & decision support 2. Look – Timetables 3. Look – Fares and auto price

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4. Purchase/Book 5. Ticket Fulfilment 6. Payment 7. Post-purchase customer support 8. Pre-journey information (delays, cancellations etc.) 9. In-journey customer information & support 10. Post-journey Customer support 11. Set-up aspects in necessary for TVs and RUs 12. Settlement methodology 13. Back office activities 14. Supplier sales reporting

Figure 5.2: FSM Working Groups

FSM early results were taken into consideration in deliverable D1.1: EuTravel Stakeholder Requirements Specification. FSM along with IATA NDC initiatives (also discussed in deliverable D.1.2: Policy, Legal and Standardisation Requirements Analysis Report), have an ambition to improve multi-modal integration. The question remains when FSM will reach a level maturity that will lead to a change for customers. According to the final report of the All Ways Travelling project [143], FSM and NDC are considered as enablers as they lower barriers towards multimodality. If lowering barriers as such will be sufficient for different actors to adopt new standards and further invest into collaboration, remains a key question. It is likely that further investment on a larger scale, by multiple actors, will depend on actual customer demand and/or competitive advantage achieved by ‘first movers’. This has been a challenge elaborated by the EuTravel project as well.

5.7 Cooperative Cities (Co-Cities) Co-Cities [106] was a pilot project funded by the EC in the ICT PSP Programme that ended in December 2013. The project addressed the lack of fast and reliable traffic information for travellers and professional users when on the move in the cities and urban areas. Co-cities provided travellers with traffic information using the Co-cities App, but also it developed a dynamic ”feedback loop’’ from mobile users and travellers to the cities’ traffic management centres, giving to end users the opportunity to comment on the received services, but most importantly to submit new information about congestion events or delays. The information provision and feedback loop is based on the Commonly Agreed standardised Interface (CAI), which is a standardized access layer to local data servers and to multimodal traffic data and services. The cities/regions that have already implemented the CAI are Bilbao, Florence, Reading, Munich, Vienna, Oslo, Prague, and Bucharest. The EuTravel consortium studied the Co-Cities mobile app when investigating ways to alert the user in case of disruptions in a planned journey,

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 though this would imply taping into the actual APIs collecting and sharing data related to disruptions. Such services were not available among project participants. Future research could investigate integrating such APIs in the Optimodality Platform (Deliverable D2.2) and the design of additional Value-Added Services (Deliverable D2.4).

5.8 Opentransportnet OpenTransportNet (OTN) [107] was a European project co-funded by the Competitiveness and Innovation Framework Programme that ended in January 2017. The primary aim of OTN was to support the reuse of geographic information (GI) as an important component of public sector information. This was achieved through cooperation with key stakeholders and development of data hubs which served for multiple use. The OTN project focused on transport data and transport related applications and it was developing collaborative virtual service hubs that aggregate, harmonize and visualize open transport-related data to drive the rapid creation of innovative applications and services. OpenTransportNet was validated in four pilot locations the UK, Belgium, France and the Liberec Region and the proposed solution used a Social Enterprise Freemium business model. OTN Lite was an open service that provided access to open data sets and an innovation environment, while OTN Premium was available for a fee enabling users' access to business incubation. In this scope, the EuTravel consortium studied the project outcomes and investigated the possibility of incorporating traffic related services such as accidents and traffic congestion services from the aforementioned cities so as to enhance further its disruption alert module. Such services were not available among project participants. Future research could investigate integrating such APIs in the Optimodality Platform (Deliverable D2.2) and the design of additional Value-Added Services (Deliverable D2.4).

5.9 Mobinet Mobinet [108] was an EU co-funded project under the Seventh EU Framework Programme that ended in August 2016 and aimed to develop, deploy and operate the technical and organizational foundations of a multi-vendor, open access platform for Europe-wide mobility services. It offered a business-to-business marketplace where commercial and public-sector providers of mobility data and services could publish and exchange their products or find other business services to extend their own offer. The most highlighted services, included a uniform middleware environment that enabled transparent and intelligent connectivity management along with tools for service providers to assist them in developing innovative transport and mobility services with cross-device interoperability deployed in any geographic area. The EuTravel consortium investigated the Mobinet business cases; future research could the possibility of incorporating some tools and components from the e-marketplace in the Optimodality Platform (Deliverable D2.2) and the design of additional Value-Added Services (Deliverable D2.4).

5.10 Models for Optimising Dynamic Urban Mobility (MODUM) The EU FP7 Project MODUM [109] that ended in December 2014, developed a system that provided on the one hand commuters with up-to-date urban multi-modal travel information, and on the other hand local administrations with the means for more efficient traffic management within their cities, leading to improvement of the quality of life in urban environments. In order to accomplish all this, the MODUM system was composed of various interrelated core components: There was a microscopic traffic flow simulator at the heart of the application which provided a complete view of traffic conditions on the transport network. Additionally, it was queried by two other services: one of them was responsible for gathering information on the fastest and greenest routes throughout the transportation network, including not only private road traffic but also public transportation (such as buses, trams, metro, and trains). The other

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 service was centred around predicting road traffic travel times for short periods of up to 30 minutes to 1 hour into the future. The interaction of these three components made MODUM an innovative player in the field of personal mobility assistance, as it not only calculated for example the fastest commuting route, but it also took into account the predicted travel time in the future. The MODUM project not only provided a useful app for commuters and an informative system for traffic managers, but its system was also backed by dedicated server infrastructure that can be deployed anywhere. MODUM’s prototype was validated by real-life experiments in Sofia (BG) and Nottingham (UK), which were evaluated by the relevant traffic management structures within the traffic control centres of these cities. The EuTravel consortium investigated the MODUM’s approach for pro-active demand-responsive traffic management that enables energy-efficient multi-modal transport choices, promoting the reduction of CO2 emissions and the improvement of the quality of life in urban environments. Future research in the urban context could investigate the possibility of integrating traffic data sources (APIs) in the Optimodality Platform (Deliverable D2.2).

5.11 StreetLife The EU Project STREETLIFE [110] that ended September 2016, developed a multimodal urban mobility information system that provided mobile information services to end users in order to promote sustainable transport alternatives. Emphasis was given not only on personalized information to access mobility and efficient, integrated mobility planning but also on the reduction of carbon emissions in cities by lowering the number of car trips. This was achieved either by informing commuters about the existing transport alternatives and their value in terms of cost, time and carbon footprint or by enhancing public transport to meet the needs of both citizens and cities. EuTravel considered the developments of the StreetLife project concerning services that promote the eco-friendly nature of multimodal travel but followed a different implementation approach.

5.12 Design for Eco-Multimodal Mobility (DECOMOBIL) DECOMOBIL [111] project ended in September 2014 and aimed at developing and widely disseminating knowledge in the area of human centred design of information and communication technologies for sustainable transport. Expected impacts of DECOMOBIL were the widening of the market for information and communication technologies based mobility and transport services and the contributing to the development and the widespread of user-friendly innovative nomadic services, impacting bicycles, public transport and car-sharing use. The project set up several design recommendations for the next generation of cooperative systems and for the improvement of integrated road transport system.

The activities in DECOMOBIL provided understanding on acceptability and usability of information and communication technologies for the population. The project organized several scientific seminars and international conferences, defined road mapping for future research priorities that reflect on joint research initiatives, and contributed to the eSafety forum. The DECOMOBIL work was focused on cleaner and safer mobility through identification, discussion and dissemination of updated know-how in human-machine interaction and human centred design areas towards the intelligent transportation systems community at European and international level. The aforementioned design areas have been considered by EuTravel but a different implementation approach was followed.

5.13 COLOMBO Urban traffic control systems aim at enabling safe and efficient passing of the ever-increasing road traffic flows at intersections and elsewhere. This requires determining the situation on the

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 roads. Emerging cooperative techniques like vehicle-to-infrastructure communication increase the estimation accuracy of the traffic situation and open new channels for delivering information to traffic participants. However, most cooperative applications require large penetration rates in order to assure their functionality, making the first steps towards their deployment unattractive. The COLOMBO project that ended in October 2015 was based on overcoming this hurdle by delivering a set of modern, self-organizing traffic management components being applicable even at penetration rates below 10%, asserting their usability from the very beginning of deployment on.

The COLOMBO working objectives were summarized below • Delivered proven traffic management algorithms for traffic surveillance and advanced traffic light control components. • Extended and implemented well-established simulation software for vehicular pollutant emissions (PHEM), traffic (SUMO), and vehicular communication (iTETRIS and ns-3). • Cost-efficiency and the reduction of vehicular emissions were the project’s key targets. The COLOMBO project used several simulation software packages to emulate the real world environment in which the traffic management solutions were embedded as Software-in-the-Loop but not real time solutions. As its outcome is a simulation tool with not any real-life data, EuTravel could not fully embed this component in the Multimodal Travel Planner.

5.14 European Digital Traffic Infrastructure Network for Intelligent Transport Systems (EDITS) EDITS [112] was an EU co-funded project under the umbrella of the Central Europe (CE) Programme that ended in December 2014. The purpose of the project was to go beyond the local and regional journey planners and to focus on enabling cross-border multimodal travel information. The project demonstrated an effective way to improve accessibility to interoperable and multimodal Real Time Traffic and Travel Information (RTII) services based on a harmonised platform for data and information exchange. In this way no centralised system was developed, rather existing structures were improved, updated and harmonized. Central part in EDITS was the adoption of a specified EDITS Graph Integration Platform (EDITS-GIP) and commonly agreed EDITS-GIP-Interface to allow the exchange of traffic related information among regions. The EDITS services have been implemented in three demonstration areas, including CENTROPE (Austria, Slovakia, Czech Republic and Hungary), the triangle area between Austria, Italy and Slovenia as well as the Italian bordering provinces of Modena and Ferrara. EDITS created an urban journey information system that did not include planning, booking or ticketing as for the case of the EuTravel project.

5.15 CIVITAS (2MOVE2) The CIVITAS initiative was launched in 2002 and ended in November 2016, to redefine transport measures and policies in order to create cleaner, better transport in cities. 2Move2 [113] was an EU project under the CIVITAS PLUS II programme, which aimed at improving urban mobility by advancing or creating sustainable, energy-efficient urban transport systems in the participating European cities (Stuttgart, Malaga, Brno, and Tel Aviv – Yafo). More specifically, the project focused on planning and implementing measures for e-mobility (clean, energy efficient vehicles and integrated transport systems for personal, collective applications), freight and the deployment of ICT and ITS for traffic management (vehicle guidance, accident avoidance, passenger information and travel planning, road pricing and smart payment systems). Linking the proposed measures with the Sustainable Urban Mobility and urban development plans was also being emphasized.

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The CIVITAS initiative has already made transport more eco-friendly in over 60 European metropolitan areas, including a public transport ticketing system in Tallinn, Estonia, a 100% clean bus fleet in Toulouse, France, waterborne goods transport in Bremen, Germany and a new traffic control system in Bologna, Italy. Future research could investigate the possibility of integrating CIVITAS modules such as traffic management, vehicle guidance and accident avoidance to enhance the EuTravel Ecosystem services.

5.16 POSSE (Promoting Open Specifications and Standards in Europe) The POSSE project [114] that ended in December 2014, focused on the facilitation of exchange and sharing of knowledge on how to develop, implement and maintain open specifications and standards for ITS and traffic management. The development of good practice guidelines required for the specification and implementation of open ITS systems and standards took place covering the processes and considerations required. POSSE answered questions regarding Good Practice Guidelines such as where to start in developing a procurement environment based around open specifications and standards, as well as how to deal with a mixed vendor environment. In addition, it provided implementation plans setting out how Transfer Sites should look to implement or further develop Open Specifications and Standards after the project. The outcomes of POSSE have been considered in the EuTravel project during the design of the CIM described in deliverables D1.4 - Optimodality Framework and D2.2 - Ecosystem Specification and Prototype Implementation, and the standards used for the API of APIs aiming at the successful integration of various transportation data sources.

5.17 eCOMPASS The eCOMPASS project (finished in December 2014) [115] introduced new mobility concepts and established a methodological framework for route planning optimization following a holistic approach in addressing the environmental impact of urban mobility. eCOMPASS aimed at delivering a comprehensive set of tools and services for end users to enable eco-awareness in urban multi-modal transportations. It involved a generic architecture that considered all types and scenarios of human and goods mobility in urban environments minimizing their corresponding environmental impact. First, the project focused on the design and development of intelligent on-board and centralized vehicles’ fleet management systems; the fundamental objective of eco-awareness was addressed through employing intelligent traffic prediction and traffic balancing methods, while also taking into account driving behaviour and considering the option of car drivers transferred to means of public transportation at suitable locations. Second, eCOMPASS developed web and mobile services providing multi-modal public transportation route planning, taking into account contextual information (such as location and time) as well as various restrictions and/or user constraints. Recommended routes will be optimized mainly in terms of the transports’ environmental footprint, although additional objectives were also - considered. An important objective of eCOMPASS was the development of novel algorithmic solutions and the delivery of the respective services to familiar end-user mobile devices. The methodology of using a common (unified) graph which includes the entire network is not time efficient for a continent scale graph as the one examined in EuTravel. The estimated execution time if such a unified graph was to be used it would be too high per query (> 1 minute). Instead of using the standard directed graph, EuTravel introduces a restricted graph which is the result of the transformation of the initial transportation graph into a minimal transit network graph consisted of unique trips and their topological relation, in which the basic structural element is the “trip”

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5.18 TRANSFORuM TRANSFORuM (finished in January 2015) [117] was a research project funded under the Seventh Framework Programme of the European Commission. The project contributed to the transformation of the European transport system towards more competitiveness and resource- efficiency. During the project, key stakeholders were engaged in carefully moderated forum activities and through other consultation measures in order to identify their views about the challenges, barriers, trends, opportunities and win-win potentials in shaping the future European transport system. The TRANSFORuM project contributed to this transformation process, in particular to the implementation of the following four key goals of the Transport White Paper:

• Clean Urban Transport and CO2‐free city logistics • Shift of road freight to rail and waterborne transport • Complete and maintain the European high‐speed rail network • European multimodal information, management and payment (MMIP) system

The project’s key outputs are a set of the following documents, all of which are based on stakeholder input:

• Roadmaps show feasible pathways for reaching short‐ to mid‐term goals (to 2030). Their target audience includes companies, technology platforms, research and innovation communities, public sector organisations and the European Commission itself as an important catalyst for action. They provide: o an analysis of the status quo o descriptions of measures to be taken o timetables with milestones o indicators of progress/success o actors to be involved o required resources and financing schemes o remaining open issues to be solved in further activities. • Recommendations to translate the technical and thematic information of the roadmaps into concrete steps to be taken by policy makers, industry leaders, NGOs and other decision makers. • A detailed strategic outlook with a long-term perspective (2030‐2050). It replicates the structure of the roadmaps but has a “vision” character, illustrating a possible European transport system of 2050.

EuTravel considered the Transforum’s roadmap “Multimodal Transport Information Management (MMIP) and payment systems”5. As described in the specific report the key challenges for the creation of the European MMIP, which EuTravel faces too, are the following:

o Legal challenge: existing legal obligations, requirements and restrictions vary between the European and the national policy level and across member States o Data availability: making transport data complete with regard to geographical coverage, rea time, transport modes etc. and ensure high quality, reliability and validity as well as traceability and transparency. o Access to travel data especially real time and fare data. Lack of interoperable data formats, protocols and interfaces. Fare data is the most difficult to obtain.

5http://www.transforum-project.eu/fileadmin/user_upload/08_resources/08- 01_library/TRANSFORuM_Roadmap_MIMP.pdf

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o Trust between the different actors and users in relation to financial transactions when buying tickets including payments between operators.

EuTravel addressed the issue of clean transport as a traveler can choose not only between cheapest or shortest itineraries but also itineraries based on the least greenhouse gas modes. Regarding the unified booking phase, the EuTravel system acts as a “single point of interaction” between the user and all transport / travel operators involved in the multi-modal travel solution. It puts in place a user-friendly booking process, allowing the user to perform a single booking request and save time.

5.19 COMPASS COMPASS (finished in November 2013) [118] was a research project funded under the Seventh Framework Programme of the European Commission. COMPASS looked at the existing information available on passenger journeys in Europe, drawing extensively on work that has been undertaken in previous European-funded projects. Existing sources of information and data were used to identify and describe the key trends in mobility patterns in the 21st century, based on current and future passenger needs. Existing sources of travel survey data were exhaustively researched, with a particular focus on the role of ICT in data collection and management, and recommendations were made on improving data collection in passenger transport to meet future needs.

COMPASS identified ICT-based solutions that had the potential to improve co-modality in passenger transport and these potential solutions were assessed through a number of case studies. The assessment of ICT solutions for improved co-modality was based on a framework that emphasised the contribution of each solution to reduced carbon emissions. There was also an investigation into how best to present solutions for improved co-modality to those stakeholders in transport operations and planning who would be responsible for their implementation, to ensure the best possible take-up of recommended solutions.

The key objectives of the COMPASS project were to:

• identify key trends (demographic, societal, economical, policy etc.) that will affect mobility now and in the future and thus to identify the mobility needs of current and future travellers, • identify the potential role of ICT in promoting co-modality and data collection, • identify the information that would be needed from data in order properly understand mobility, to optimise a future co-modal transport system and to assess the impact of new solutions, • analyse existing surveys with regard to data available concerning long-distance, rural and urban travel, • identify solutions to improving behavioural data (from ICT or elsewhere) and needs and opportunities for harmonisation of the data collected, in particular in the various national surveys (this also includes new definitions of accessibility indicators), • identify and investigate ICT solutions to influence mobility patterns for long-distance, rural and urban travel towards increased co-modality, • develop business models that enable and promote these solutions in practice, • assess the potential impact of the solutions identified both on local and on European level, in particular with regard to carbon emissions, • derive conclusions and recommendations for national and EU transport policy and actions, • disseminate the findings widely amongst policy makers and other stakeholders as well as researchers and the transport industry.

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At the core of the COMPASS project was the identification of technologies that will help integrate and optimise the transport system. Each of these technologies was analysed in depth with regard to, amongst others, costs, impact on mode choice and travel time and impact on emission reduction. Important enabling applications were smart ticketing options combining tariff information of several transport modes (smart cards) and traveller information systems, informing transport users on timetables and travel time (multi-modal traveller information systems)6

5.20 ONTIME The ON-TIME [119] was a joint research project funded under the Seventh Framework Programme (FP7 2011-2013) of the European Commission. The overall aim of the ON-TIME project was to improve railway customer satisfaction through increased capacity and decreased delays both for passengers and freight. This was achieved through new and enhanced methods, processes and algorithms. The main objectives of the project were: • To improve management of the flow of traffic through bottlenecks to minimise track occupancy times. • To reduce overall delays through improved planning techniques that provide robust and resilient timetables capable of coping with normal statistical variations in operations and minor perturbations. • To reduce overall delays and thus service dependability through improved traffic management techniques that can recover operations following minor perturbations as well as major disturbances. • To improve the traffic flow throughout the entire system by providing effective, real-time information to traffic controllers and drivers, thus enhancing system performance. • To provide customers of passenger and freight services with reliable and accurate information that is updated as new traffic management decisions are taken, particularly in the event of disruptions. • To improve and move towards the standardisation of the information provided to drivers to allow improved real-time train management on international corridors and system interoperability; whilst also increasing the energy efficiency of railway operations. • To better understand, manage and optimise the dependencies between train paths by considering connections, turn-around, passenger transit, shunting, etc. in order to allocate more appropriate recovery allowances, at the locations they are needed, during timetable generation. • To provide a means of updating and notifying actors of changes to the timetable in a manner and to timescales that allows them to use the information effectively. • To increase overall transport capacity by demonstrating the benefits of integrating, planning and real-time operations.

Among the innovation actions of the project the following results were extracted: Under Innovation 1: The development of standardised definitions and methods that can be used to create interoperable processes and tools that facilitate consistent, standardised and cross- border planning and real-time traffic management. Under innovation 2: Improved Methods for timetable constructions, the methods developed in the project have been applied to a high-capacity mixed-traffic network around the railway node at Hertogenbosch in the Netherlands including the synchronized corridors Utrecht – Eindhoven and Tilburg - Nijmegen. The ON-TIME timetabling approach was applied to the Dutch case study and the resulting timetable was tested and evaluated using the HERMES simulation tool, showing improvements on all performance indicators.

6 http://cordis.europa.eu/result/rcn/141737_en.html

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Under innovation 3: Real-time traffic control algorithms, the algorithm applied for real time traffic management on the East Coast Main Line (ECML) in the UK ECML is the Differential Evolution Junction Rescheduling Model (DEJRM) developed by The University of Birmingham. It optimally reschedules train timings at junctions in the event of minor perturbations. Under innovation 4: Improved Decision support – Handling major Perturbations. The case study area was an important of the Dutch railway network. The network is bounded by Utrecht Central in the northwest, Tilburg in the southwest, Eindhoven in the southeast and Arnhem in the east. On this network, about 90% of the trains are domestic passenger trains operated by Nederland’s Spoorwegen (NS). In this action the only parameters considered were the following: the timetable, rolling stock and crew schedule of these trains. The disruption scenarios were the i) accident with person near Rosmalen and ii) Signalling problem near Culemborg. The experimental results show that the disruption management module computes feasible resource schedules in a couple of minutes. Such solution times are acceptable in practice. This shows that the iterative algorithm can be applied in a practical setting for the disruption management process. Under innovation 5: Centrally Guided Train Operation (CGTO). ON-TIME proposed an XML- interface data format supporting three different architectures (i.e DAS-C: mainly central intelligence, DAS-I: distributed intelligence, DAS-O: mainly on-board intelligence) which also supported bidirectional communication between central and on-board components. The project has delivered a demo-implementation of CGTO including this standardized interface. Since all of the particular functions of the designed CGTO system have been validated, the ON-TIME project team was strongly convinced that the CGTO based on this standardized interface can be used in the future. Nevertheless, the goal to evaluate the whole CGTO system in closed loop could finally not be achieved within ON-TIME and should therefore be addressed in future projects. Under innovation 6: Process and information architecture. The actual ON-TIME Architecture was a collection of .NET components, and it was based on three modules: a subscription service, a data provider, a security layer and a dashboard. Tests simulated 10 clients with a number of parallel requests, ranging from 1000 to 10000 each. The tests certified the ability of the architecture to receive about 3500 messages per node per second. The average size of the messages was approximately 5 KB. The architecture revealed fairly good scalability: adding nodes proportionally improves the ability to handle more messages.

ON_TIME developed new methods and processes for timetable planning and real-time railway traffic management to maximize capacity on the railway network and improve railway customer satisfaction through increased capacity and decreased delays both for passengers and freight. EuTravel recognises that reliability, service characteristics and cost competitiveness can progress significantly through the improvement of real-time information to customers and better data exchange between the involved parties in the intermodal transport chain. These key improvements are explicitly addressed inside the EuTravel Optimodality framework, connecting the recent advances in the rail sector with valued added services provided to the traveller. Taking into account the rail competition with road transport, it is important that future rail solutions should be developed to optimize the overall transport time; all innovation activities within EuTravel framework, ensure that rail is able to better operate in conjunction with other modes, in order to maximise the utilisation of existing networks.

5.21 Instant Mobility Instant Mobility [120] (Multimodality for people and goods in urban areas) was part of the FI-PPP initiative, co-funded by the European Commission 7th Framework Programme (FP7-2011-ICT-FI) that ended in March 2013.

The project set out to pave the way for the mobility revolution, through five main steps:

• Create and analyse a set of innovative Future Internet-based “lead scenarios” and constituent services corresponding to the needs of five key stakeholder groups:

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- multimodal travellers, - car drivers and passengers, - public and other collective transport operators, - truck fleet operators and the distribution industry, - road operators and traffic managers. • Define and specify essential “enablers”, i.e. generic and transport-specific technologies and components needed to support the Instant Mobility services • Integrate the enabler specifications into a conceptual prototype demonstrating a simplified Transport and Mobility Internet and some scenario services as examples • Investigate key societal issues for potential Instant Mobility deployment, including security and privacy, acceptability, business models, etc. • Dialogue with stakeholders in potential candidate cities for deployment, creating a plan for a network of pilot implementation sites in the next stage of the Future Internet - Public Private Partnership (FI-PPP)

In the Instant Mobility vision, every journey and every transport movement is part of a fully connected and self-optimising ecosystem. Whatever the traveller's situation (office, home, on- trip) Instant Mobility will deliver useful Future Internet enabled information and services.

The outcomes of Instant Mobility have been considered in the EuTravel project in D1.1: EuTravel Stakeholder Requirements and in the design of the CIM as described in deliverable D1.4 - Optimodality Framework.

5.22 All Ways Travelling (AWT) According to the White Paper on transport policy from 2011, the multimodal travel system will be a core element of future sustainable passenger transport. The European Commission has addressed this subject by several studies and legal acts elaborating on the desirable attributes and certain issues of a multimodal travel system and their consequent benefits for the traveller.

Against this background, DG MOVE had been seeking external expertise “to develop and validate a European passenger transport information and booking interface across transport modes”, and the consortium “All Ways Travelling” (completed in June 2014) was selected to advise the European Commission on this topic via a service contract.

The consortium delivered a study [121] on the framework conditions for a European passenger transport information and booking interface across transport modes – Multi-Modal Information and Ticketing Systems (MMITS) - which gave insights into the prerequisites for the possible future development of information and booking systems, and presented a set of recommendations for future action of the European Commission.

The study concluded that the establishment of a well-functioning marketplace for MMITS will significantly contribute to achieving the ambitions of the White Paper on Transport. Comprehensive and unbiased MMITS that provide location-independent search, booking, payment, and trip entitlement issuance, are highly likely to be attractive for users, in turn providing an attractive marketing and sales channels for travel providers.

The key drivers of MMITS were identified as:

• Industry collaboration through initiatives such as FSM and Shift2Rail IP4. • Further deregulation of the rail sector in the EU. • EU intervention to support industry initiatives and innovation programmes like Shift2Rail • EU regulations to ensure non-discriminatory access to travel information.

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• Clarification of multimodal conditions of carriage and passenger rights in a multimodal journey. • Improvement of the physical connectivity and infrastructure to facilitate connections and transfers between transport modes, increasing the number of available and attractive travel options. • Availability and development of technologies that enable the establishment of MMITS solutions with reasonable investment levels, including new search and mobile internet technologies.

Key Findings of the study were:

• Three kinds of information have to be available for planning a journey via MMITS: Schedules, fares, and availability. Furthermore, real time information is necessary during the journey. • Comprehensive and unbiased information is necessary for MMITS to be attractive. • Information provision is only feasible for commercial carriers if no sensitive data is published. Therefore, schedule information may be published as raw data while dynamic information, like yield-managed pricing, may be accessed via API access. • Information provision and distribution (selling tickets through intermediaries) are very different, and should be regarded separately.

Figure 5.3: AWT Framework [121]

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Figure 5.4: AWT Workflows [121]

The early outcomes of AWT (2015 report) (Figure 5.3 and Figure 5.4) [121] have been considered in the EuTravel project in D1.1: EuTravel Stakeholder Requirements and in the design of the CIM as described in deliverable D1.4 - Optimodality Framework. Specifically, this report has been the basis for the early architecture designs of the EuTravel Solution (Figure 5.5 and Figure 5.6) that have been developed in the architecture described in detail in deliverables D2.1 Technology Ecosystem Architecture and D2.2 Ecosystem Specification and Prototype Implementation.

Figure 5.5: Early EuTravel architecture design (1) (2015)

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Figure 5.6: Early EuTravel architecture design (2) (2015)

5.23 1st Smart Mobility Challenge The 1st Smart Mobility Challenge (2011-2012) was organised to raise awareness of the broad public and different stakeholders about multimodal journey planning. In response to the Challenge, 22 submissions of journey planners were received, out of which 12 were shortlisted to be put to the vote by the public [122].

The winners of the challenge were:

• Byebyehello Journey planner combines planning the trip (according to time, budget, environment preferences), booking and paying with one click. It uses a distributed approach with A* routing algorithm (Penelope Ventures GmbH). • Mytripset is a vision of a journey planner that wants to move from a classic functional tool to an open and intuitive service available on all devices (SNCF). • The right architecture for a European multimodal journey planner is a distributed system with standardized API (Application Programming Interface) (CHAPS). • Le Frecce journey planner that will be launched in 2012-2013 will be a four-layer abstraction model with layer-specific interoperability protocol (Trenitalia).

The outcomes of the 1st Smart Mobility Challenge have been elaborated in D1.1: EuTravel Stakeholder Requirements.

5.24 Opticities OPTICITIES [123] was a 3-year project running from 1 November 2013 to 31 October 2016.

OPTICITIES developed a collaborative approach between public and private stakeholders. In this vision European cities consolidate all mobility data available at local level and provide it to service operators through a standardised gateway.

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The key assets of this approach are:

• A geographical and modal urban mobility data completeness thus reinforcing services’ quality • Deploying truly multimodal services, supporting the diversity of services’ offer, sustaining high value services • Ensuring coherency between user-oriented services and urban mobility public policies

OPTICITIES aimed to associate major cities, groups and SMEs at the forefront in these fields in Europe to develop:

• Genuine multimodal solutions. For once ITS solutions will not be a juxtaposition of mono- modal approaches exclusively focused on public transport. Multimodal solutions will be based on reliable data for every mode and combination, with optimised end-user HMI, and will involve the car industry as well as public transport and soft mode actors. • A contractual framework on data access and exchange policy allowing enlarged access to high quality data. This policy aims at amplifying the development of information services by centralising (or accessing local databases) and disseminating all private and public data available at the scale of the conurbation, in line with urban mobility public policies. • European interoperability of urban mobility data and mobility solutions. Based on an open ITS system, the standards developed in OPTICITIES will provide cost effective and seamless multimodal services. • Enhance network operators’ supervision capacity and management efficiency thus allowing for smart and adapted decision-making processes. • Develop, try out and assess high-level innovative multimodal information and transport management services. These services will target transport managers, travellers and freight transport users or fleet managers. • Enhance users’ accessibility to mobility services through the display of coherent and highly reliable multimodal information.

OPTICITIES aimed to achieve these objectives through the following major breakthroughs in terms of innovation:

• New monitoring devices and sources: data collection through users, new means for urban freight data collection, real-time road works data collection, multimodal real time data collection; • Building of a standardised Urban mobility dataset and access portal: definition of a European standard for the Multimodal Urban Dataset and its interfaces between public authorities and service providers; development of a contractual architecture between private and public actors for data access, data exchange and service provision. • Developing innovative services for multimodal and predictive management of urban networks: optimisation of urban networks exploitation through the development of traffic prediction tools and their integration into traffic management systems; integrated multimodal management allowing better allocation of means to support mobility demand. • Developing innovative services for end-users ensuring service continuity between vehicles and smartphones: deployment of multimodal urban navigator on smartphones in the partner cities; service continuity between in-vehicle navigation system and the multimodal urban navigator. • Developing innovative services for urban logistic: urban freight navigator; tools for urban freight management.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

OPTICITIES’ innovations focused on the urban environment. EuTravel had a different focus, prioritising mostly the integration of long distance modes. Future research (link in currently running project MaaS4EU [147], could investigate the possibility of integrating EuTravel and OPTICITIES solutions.

5.25 New Tools For Design of Urban Transport Interchanges (NODES) NODES [124] is a three-year research European project, focusing on the efficient integration of public transport services. NODES has developed a Toolbox to allow practitioners (public authorities, public transport operators, infrastructure managers…) to assess their public transport interchanges and to improve their performance. As interchanges play a key role in the integration of the urban mobility system and in enabling good intermodal solutions, their efficiency is essential to achieving sustainable transport objectives.

The main outcomes of the project are:

• Measuring the performance of a transport interchange

The first steps of the project consisted of defining the future user needs and system requirements. Key performance indicators have been identified to enable practitioners to better understand the performance of their transport interchange. These indicators were worked on in order to develop the so called “NODES Benchmark tool” which will be unveiled at the project’s final conference. With this online tool, the practitioners just have to enter the main figures of their interchange and answer specific questions to be provided with a performance evaluation of their interchange.

• Improving performance thanks to the NODES Toolbox

Once a practitioner obtains the strong and weak points of his interchange, they are pointed towards the NODES Toolbox, a list of tools (software, methods, techniques, models, regulations, materials) that will allow them to improve its performance.

The indicators as well as the tools cover the five key areas related to transport interchanges:

• Strategies for integrated land use planning with urban passenger infrastructure planning • Innovative approaches relating to the design of efficient transport interchanges • Intermodal operations and information provision • Management and business models (the interchange as a business case for the local economy and itself) • Energy-efficient and environmentally-friendly interchanges

In order to validate the efficiency of the tools that were identified, they were tested in nine reference sites distributed around Europe. EuTravel obtained insights about transportation means in several cities from the Benchmark tool that has been developed in the NODES project and especially for the environmental impact in multimodal travel solutions.

5.26 Interconnection between Sort and Long Distance Transport Networks (INTERCONNECT) The INTERCONNECT (Interconnection between Short and Long-Distance Transport Networks) project [125] ran from June 2009 to May 2011. It examined the role of local and regional interconnections in the context of longer distance passenger journeys in Europe, in order to address the potential for greater economic efficiency and reduced environmental impact. Factors

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 investigated in the project include integration, co-operation and, where appropriate, competition in the provision of local connections across all transport modes.

Effective interconnection between trip legs is a necessary feature of a growing proportion of passenger journeys, particularly of those which contribute most to regional and national economies. Such effective interconnection requires the provision of integrated networks and services which are attractive to potential users and this is likely to require co-operation between a range of authorities and providers in the public and private sectors and may necessitate a wider vision than might otherwise prevail.

INTERCONNECT addressed the potential for greater efficiency and reduced environmental impact of passenger transport through encouragement of integration, co-operation and, where appropriate, competition in the provision of these local and regional connections.

INTERCONNECT focused, in particular, on those journeys that might benefit from more effective interconnections between different transport modes and services, and on those journeys where effective interconnection is currently hampered by institutional barriers, lack of investment, or failure to innovate. By identifying examples of good practice from Europe and elsewhere, INTERCONNECT has shown how local and regional transport interconnections could benefit from a more enlightened approach. This is a paradigm investigated in the EuTravel project for designing best practices use case scenarios for the LL test procedures.

The range and applicability of specified solutions that were tested in the project case studies took into account legal and institutional issues and made use of policy measures like integrated pricing, and ticketing, improved links and interchanges, infrastructure pricing, strategic planning, information and marketing.

While promoting take-up of organisational, administrative and technical best practice and coordination among policy makers, INTERCONNECT also made a contribution to the wider use of analytical tools that are appropriate to this field at both European and local level.

5.27 Intelligent Transport System for Optimised Urban Trips (i-TOUR) I-TOUR [126] project, which ran from February 2010 – January 2013, was designed to promote the use of public transport by encouraging sustainable travel choices and by providing rewarding mechanisms for users choosing public travel options.

The objective of I-TOUR was to develop an open framework to be used by different providers, authorities and citizens to provide intelligent multi-modal mobility services. I-TOUR aimed to support and suggest (in a user-friendly way) the use of different forms of transport: bus, car, rail road, tram, etc., taking user preferences into account, as well as real-time information on road conditions, weather and public transport network conditions.

The main project objectives are grouped below in five high-level goals:

• Development of a reliable and secure data collection approach capable to benefit both from measures of real-time conditions on public transport load and from information provided by the citizens. For this reason, a trust-based mechanism would be developed to ensure reliability of the uploaded content and accuracy of the consumed content, ensuring at the same time the highest level of privacy. • Development of a modular infrastructure based on standard open technologies that can be adopted by public transport providers to expose harmonised transport-related services.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

• Development of a personalised multi-modal transport information system capable of providing user-tailored travel choices and capable to learn incrementally from the users' preferences. • Development of a user-friendly travel information system, promoting sustainable travel choices based on multi-modal public transport. • An additional goal of I-TOUR was the identification of new business models based on real- time personalised LBS (Localisation Based Services) of interest for urban travellers.

The project promoted a user friendly reliable travel information system for optimal multi-modal passenger trips based on novel data collection techniques capable to promote and award sustainable travel choices. I-TOUR predicated an approach whereby citizens can benefit from a wide range of Location Based Services. These are based on the widespread availability low-cost portable localisation technologies, including GPS and forthcoming GALILEO services, as well as on the ubiquitous availability of wireless network connections (e.g. UMTS, Wi-Fi) at the urban and rural level. This vision is in line within the priorities set by the EU ICT for Mobility Strategic Research Agenda which advocates the use of info-mobility service, including pre-trip, on-trip and post-trip information. The i-Tour project developed an urban traveller information system that provides information regarding the user’s routes for multimodal trips. i-Tour aimed to manage a wide range of real- time information coming from several public transport providers. The main objective of the i- Tour project is to monitor the activities of users and alerts them when conflicts or opportunity arise, such as changing a route. Also, the system provides recommendations on an existing route based on a comprehensive representation of user’s preferences. Furthermore, it incorporates a learning model which makes it possible to incrementally learn user’s preferences each time it receives feedback on the travel choice a potential user makes. This way the portal will help users to plan their trip according to their preferences and needs. This is very helpful especially for users with special needs. As a consequence, the system provides improved user experience through adaptability and context awareness. Additional, the system provides not only a multimodal travel- information and planning, but also a multimodal ticketing service. This would serve the purpose of promoting and furthering a considerably larger utilization of multimodal travel by travel users in Europe.

The scope of EuTravel is extended beyond the urban context, serving also long-distance journey planning, and utilising both cached and real-time data, with respect to synchronisation between modes, passenger experience, passenger rights and environmental performance. After studying the outputs of the i-tour project, a similar approach was adopted in EuTravel with regards to user access to the available services (through the user interface). EuTravel like i-tour, uses two primary user types: a) registered users and b) guests. Both projects manage the degree of access offered to users based on authentication. Non-registered travel users (guests) have limited capabilities. On the other hand, in both projects, user’s preferences are connected to the perception and needs of the traveller. For registered users, their historic interaction with the system and storage of their preferences facilitate both the personalisation of results for each query and their future interactions.

5.28 TourPack TourPack was an Austrian project (ended in 2016), that created a linked data - empowered system for touristic service packaging in order to provide the optimal travel experience to its users. The aim of TourPack was to design a production system that creates “on demand” touristic packages catering to the individual touristic service consumer needs and preferences. The abundance and variety of travel services and the restricted time the travellers typically have on vacations or in business trips, touristic service search, selection and combination requires a lot of effort from the service consumer, when aiming at an optimal travel experience.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Also, as in many service-oriented businesses nowadays, the touristic service consumers want individualized experiences and no longer want the “one-size fits all” touristic packages. It is obvious that travel is an integrated part of such a package. EuTravel solutions could be extended in the future, by utilising the packaging/composition solution that TourPack developed to serve travellers needs such as Travel Packs, i.e. combining different travel modes in a package, including accommodation.

5.29 Byte Byte [127] aims to deliver big data roadmaps by capturing the positive externalities and diminishing the negative externalities associated with big data. One of the seven use cases Byte is using is smart cities, where public transport/travel plays a major role. This case study is focused on the macro view of the creation of value from potentially massive amounts of urban data that emerge through the digitalized interaction of a city's users with the urban infrastructure of resources, such as transportation and administrative services. Obviously, central train stations and airports can be considered as information hubs. The aforementioned transportation infrastructure can be seen as a multimodal resource flow network where the roads, railways lines etc. can be considered as the different modes of transportation.

. New data available to the project, are expected to be obtained not only from the existing resources but also from the infrastructure utilized in the city. Additionally, data from EuTravel could possibly enhance the citizen and visitor experience. The most valued resource a person/visitor has is time and everyone wants to avoid waiting or queuing when he can spent his time doing something creative.

5.30 LDCT LDCT [128] was a collaboration project between Austria and France that deals with the integration of touristic and cultural data using linked data technologies. Integration of travel data and APIs is a core aspect in EuTravel. EuTravel solutions could be extended by utilising LDCT results on data integration. For example, cultural events that may interest the traveller and can be aligned to touristic offers can be considered as an input API to EuTravel. LDCT has also benefited from early EuTravel results, more precisely the part of EuTravel Unifying Ontology dealing with terrestrial transport within cities boundaries (as presented in Deliverable D1.4 EU Optimodality Framework).

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

6. Ongoing Related ITS Cluster Horizon 2020 Projects

The ITS cluster is a group of H2020 projects settled in the ITS & connected vehicles domain of H2020 programme, dealing with different aspects of ICT research and operation in multimodal traffic and transport. The common goal is to accelerate ITS deployment in Europe for safer, more efficient, comfortable and seamless traffic and transport. The key objectives of this cluster are:

• Exploiting synergies between projects to increase impact on ITS research and deployment • Enhancing visibility of C-ITS related state-of-the-art and future research needs • Reaching complementarity in implementations • Regular information exchange • Joint dissemination activities.

Some of the projects that participate in the ITS Cluster and have a related or complementary focus with EuTravel were also present in the EuTravel conference that took place in Barcelona, in October 2016 (http://eutravel.eu/Conference/) (see also D4.4.-Communications Programme).

The scope of these ongoing projects is outlined here and are presented in the Online Observatory (see Section 7.1).

6.1 Maas4EU End-to-End Approach for Mobility-as-a-Service tools, business models, enabling framework and evidence for European seamless mobility (MaaS4EU) [147], is a research and development project funded by the Horizon2020 research and innovation programme bringing together 17 partners from several sectors and backgrounds to provide viable evidence and solutions about the MaaS concept. MaaS4EU started in June 2017 and will provide quantifiable evidence, frameworks and tools to remove the barriers and enable a cooperative and interconnected EU single transport market for the MaaS concept, by addressing challenges under four pillars:

1. Business models: MaaS4EU designs prototype Business Models (BM) for a cross-company MaaS enterprise involving multiple actors within the EU single market. These BM demonstrate the value, the benefits, the potential and viability of the MaaS concept. Several MaaS products are designed based on users’ needs and are tested to assess the advantages and disadvantages of each case. 2.End-Users: MaaS4EU explores the needs, preferences, demand and acceptance of various end- user groups for MaaS services and products via MaaS living labs and real life demonstrations. 3.Technology: MaaS4EU designs and develops the open MaaS4EU platform by bringing together (existing and new) well-defined technologies, processes, interfaces for plugging-in disparate data sources enabling urban and cross-border multimodal planning, booking, ticketing and payment. Any Mobility Service Provider could accommodate its data and any MaaS operator could use the platform to test, develop and scale its services. 4. Policy: MaaS4EU proposes the required “MaaS Policy Framework” that provides guidelines for a co-operative transport ecosystem regarding financing, technology, privacy and security, passenger rights, and regulations to enable the implementation of MaaS across Europe.

MaaS4EU aims to solve research questions related to several technological areas in order to provide seamless mobility in the urban context. The goal is to homogenize and use mobility- related data in a unified manner, by introducing a common format to facilitate the consolidation of all available data structures and semantics. To address this challenge, MaaS4EU, builds directly on the EuTravel project outcomes. The proposed EuTravel API of APIs approach and Optimodality Framework will be adopted and extended to unify heterogeneous APIs under a common collaboration ground in the urban context, including public transportation and new modes of

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 transport such as car-sharing. Specification will be developed to allow transport service providers to generate and share common, reliable, resilient data (exposed via APIs), capable to be used/consumed by a Mobility as Service Operator.

6.2 BONVOAYAGE The BONVOYAGE project [128] (From Bilbao to Oslo, intermodal mobility solutions and interfaces for people and goods, supported by an innovative communication network) aims at designing, developing and testing a platform optimizing multimodal door-to-door transport of passengers and goods.

6.3 Cooperative ITS Deployment Coordination Support (CODECS) CODECS [129] supports the European Commission and the manifold stakeholders involved in C- ITS deployment in finding strategic and technical policy solutions and processes for a consolidated C-ITS roll-out. CODECS serves as hub for transparent information and knowledge transfer on function approaches, experiences and lessons-learned by stakeholders active in the initial deployment. To ensure European-wide seamless (cross-border) interoperability and end-user experiences, CODECS develops a harmonised standards profile supporting a growing amount of C-ITS services. To address key organisational and technology related issues, CODECS will derive a strategic common road map from preferences of the involved stakeholders, giving direction for innovation, testing, standardisation and deployment beyond Day One. CODECS also supports future C-ITS common deployment by achieving a clear understanding on policies, roles and responsibilities. CODECS does convey these insights to the C-ITS deployment platform initiated by the European Commission and also to the Amsterdam Group.

6.4 Door to Door Information for Airport and Airlines (DORA) The DORA [130] project is aiming at the design and establishment of an integrated information system that helps passengers to optimise travel time from an origin of the travel to the airplane at the departing airport as well as from the arrival airport to the final destination. With it, the DORA integrated information system, which will be created within the project together with necessary software platforms and end user applications, is aiming at the reduction of overall time needed for a typical European air travel including necessary time needed for transport to and from the airports.

6.5 European Travellers Club (ETC) The European Travellers Club - Account-Based Travelling across the European Union [131], is a programme by and for European transport ticketing schemes or operators, travellers organizations and technology providers to create seamless Account-Based Traveling across the European Union, funded under the Horizon 2020 Transport Programme.

The programme is traveller-centric, meaning that the travellers will be in control of their preferences and privacy. While it includes innovative technological concepts, it is expressly designed to work with existing e-ticketing infrastructures in member states (Calypso, VDV, ITSO etc.) as well as new possibilities (such as EMV-contactless, smart tokens etc.). The "eco-system" will be open for all potential suppliers through an open architecture with clear interfaces and standardized protocols. The architecture is such that it allows for a smooth integration with travel planning and booking tools, journey information and integration with other uses of e-identity, e- payment and e-ticketing.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

6.6 ITS Observatory The ITS Observatory [7] aims at providing easily accessible and understandable information on Intelligent Transport Systems. The main objectives of the ITS Observatory are to bridge knowledge fragmentation across Europe, support ITS deployment by creating an intelligent software platform, create an efficient user-friendly decision-making tool which will enable fact based policy making and to create a common EU Library for ITS projects, research, pilots and implementation. The ITS Observatory comprise three main elements; • a database of projects that have been completed or are underway, predominantly those with Commission funding/co-funding, • a mechanism for capturing factual up to date information about projects and • a front-end to allow users to make a range of inquiries.

6.7 Mobility Based On Aggregation Of Services And Applications Integration (MASAI) The vision of the MASAI project [133] is to satisfy the overall requirements for services dreamed by each mobile citizen: a tailor-made aggregation of features (information, payment, ticketing) offering a seamless travel experience. MASAI delivers the appropriate solution easily plugging multiple (existing or not) services through an open, cost-effective HUB. The MASAI HUB composed of centralized components but also of distributed agents and an APIs layer acts as a service aggregator itself, through an open and public modular and flexible application. This approach builds on state of the art IT concepts, on existing and upcoming standards and on the use of commonly accepted personal digital media and interfaces.

6.8 Multi-source Big Data Fusion Driven Proactivity For Intelligent Mobility (OPTIMUM) OPTIMUM’s vision is to provide the required interoperability, adaptability and dynamicity in modern transport systems for a proactive and problem-free transportation system. OPTIMUM will establish a largely scalable, distributed architecture for the management and processing of multisource big-data, enabling continuous monitoring of transportation systems needs and proposing proactive decisions and actions in an (semi-) automatic way. OPTIMUM [134] follows a cognitive approach based on the Observe, Orient, Decide, Act loop of the big data supply chain for continuous situational awareness. OPTIMUM's goals will be achieved by incorporating and advancing state of the art in transport and traffic modelling, travel behavior analysis, sentiment analysis, big data processing, predictive analysis and real-time event-based processing, persuasive technologies and proactive recommenders. The proposed solution will be deployed in real-life pilots in order to realise challenging use cases in the domains of proactive improvement of transport systems quality and efficiency, proactive charging for freight transport and Car2X communication integration.

6.9 Open Social Transport Network for Urban approach To Carpooling (SocialCar) SocialCar [136] is an Intelligent Transport System based on an innovative approach to transport demand management, and more specifically to carpooling in urban and peri-urban areas. SocialCar’s main objective is developing a new communication network for intelligent mobility, sharing information of car-pooling integrated with existing transport and mobility systems. This will be achieved by means of powerful planning algorithms and integration in a liveable environment of big data related to public transport, carpooling and crowdsourcing in order to provide the final user with a simplified travel experience allowing comparison and choice between multiple options/services.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

6.10 Enhanced real time services for optimized multimodal mobility (TIMON) The main objective of TIMON project [137] is to increase the safety, sustainability, flexibility and efficiency of road transport systems by taking advantage of cooperative communication and by processing open data related to travel through a cooperative open web based platform and mobile application, developed for the purpose of delivering information and services to drivers, businesses and vulnerable road users in real time.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

7. EuTravel Knowledge Base and Observatory

7.1 Online EuTravel Observatory Overview The EuTravel Observatory can be found online at http://www.eutravelproject.eu/Observatory (Figure 7.1). It consolidates content from the current deliverable (Figure 7.3) with special focus on the library of selected technologies to be monitored throughout the project as described in paragraph 4.13, but also includes content from other deliverables such as Information on related standards from D.1.2: Policy, Legal and Standardisation (Figure 7.2). Lasts it lists and links to the reference projects (Chapter 5) and the ITS Cluster projects (Chapter 6).

Content has been periodically updated throughout the project by EBOS with the contribution of all partners and reviewed by the project coordinator. The observatory will be supported by ILS and EBOS after the project for at least two years and will be updated with related content from other projects such as MaaS4EU and other new initiatives.

Figure 7.1: Knowledge Platform

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Figure 7.2: Specific topic in Observatory - Standardisation

Figure 7.3: Specific topic in Observatory – Key Technologies

7.2 EuTravel Observatory System – User View This section provides general information on the system of the EuTravel Observatory Knowledge Admin side from the user point of view. The system is a web based system and accessible from anywhere. It is built on the EuTravel Knowledge Platform utilising the .NET Framework and powered by the SQL Database engine.

7.2.1 How to login In order to login you have to click on the link provided in the email sent to you with your registration, or type in the address bar of your browser http://www.ebos.com.cy/shopadminv99 and the page shown in Figure 7.4 will open. Type the login information that was sent to you by email when you make your registration and click login button. You have the option to select a different language if you wish.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Figure 7.4: EuTravel Observatory Admin - Login Page

7.2.2 Main Page At the top is the navigation menu where you can make a choice to display the data in the middle of the screen. In the middle of the Welcome screen there are the most important quick links that the user can select and navigate to. At the very top right on the main page there is the option to change your password or log off from the system (Figure 7.5).

Figure 7.5: EuTravel Observatory Admin - Main Page

7.2.3 Dropdown Lists In various pages you will see a dropdown list (Figure 7.6) that allows you to select an object from the list.

Figure 7.6: EuTravel Observatory Admin - Dropdown List

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

• The first button allows the addition of a new object in the list. • The second button allows the user to edit the selected object from the list. • The third button allows only the projection of the selected object from the list. • The buttons provide access depending on the user’s level.

7.2.4 Upload Files In various pages you will see the buttons in Figure 7.7. These buttons allow you to upload or download a file.

Figure 7.7: EuTravel Observatory Admin - Upload and Download file buttons

Figure 7.8 shows the popup window that will open when you click on the upload button. Click on the select button and choose the file that you want to upload on the site. Finally click on the upload button and wait for the file to be uploaded on the server.

The same applies to the View Button. Once you have clicked the View button you will be able to download and view the file.

Figure 7.8: EuTravel Observatory Admin - Upload File Popup

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

7.2.5 Navigation Tree By clicking on the top menu, under menu item “Index”, you select the link Navigate Tree. Figure 7.9 shows the Navigate Tree page.

Here you can see a navigation tree that is assigned to the EuTravel Portal. • The first level is the Subject Categories. • The second level is the Subject Area. • The third level is the Subject Topic. • The fourth level is the Subject Info. Registered members have access to add or edit only at the third and fourth level.

Figure 7.9: EuTravel Observatory Admin - Navigate Tree

When you click on a node from the third and fourth level, the left Toolbar (Figure 7.10) will appear with the buttons that will allow you to edit the selected Subject Topic or add Subject Info related to this topic.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Figure 7.10: EuTravel Observatory Admin - Navigate Tree Actions

In Figure 7.11you can see the Subject Info form. Here you can write all the information you want to be displayed on the EuTravel Observatory Portal.

Figure 7.11: EuTravel Observatory Admin - Subject Info Form Fields Explanation: • Subject Area/Subject Topic: These fields will be added automatically proportionally by the tree choice. However, you can choose another if you wish. • Title: This is the title of the Subject Info. • Author: The name of the Subject Info author. • Overview: In this text editor you can write the overview of the Subject Info that will be displayed in the centre of the EuTravel Observatory Portal. • Study Filename: Here you can upload the file of the Subject Info that will be available on the website for download as show. • URL: In this field you can write a website URL that has more information about this subject info.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

At the left of the Subject Info form, as shown in figure 7.8, you can see the tabs with all the related subjects. In order to add any related “subjects”, click on the tab and then on the Add new record. These subjects exist on the right side of the EuTravel Observatory Portal.

Tabs explanation: • Subject Info Comments: Here are the comments that users can add from the website link. • Subject Articles: Here you can add all the related documents of the Subject Info. • Subject Policies: Here you can add all the related subjects from the Policy Directory. • Subject Stakeholders: Here you can add all the related stakeholders of the Subject Info. • Subject Projects: Here you can add all the related subjects from the Projects Directory. • Expert Info: Here you can add all the related Experts of the Subject Info. • Subject Events: Here you can add all the related Events of the Subject Info. • Subject News: Here you can add all the news related to the Subject Info. • Subject Glossary: Here you can add the glossary related to the Subject Info. • Subject Journals: Here you can add the journals related to the Subject Info. • Subject Info Sources: Here you can add all the related Information Sources of the Subject Info.

7.2.6 Glossary Terms In Figure 7.12 you can see the Glossary Terms form. Here you can add the term, its definition and the Wikipedia link.

Figure 7.12: EuTravel Observatory Admin - Glossary Terms Form

Also, you can add comments, or see the comments that users add from the website as illustrated in figure 7.13.

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Figure 7.13: EuTravel Observatory Admin - Glossary Comments

7.2.7 Events Here you have to write the event name, date and the details of the Event. Also you can write the URL where the user can find some more information. There is also the option to upload a file name together with the event details (figure 7.14).

Figure 7.14: EuTravel Observatory Admin - Events Forms 7.2.8 Journals Here you can write the name, description and the URL of the Journal. Also you can choose whether you want the journal to be visible or not, and in which order you want them to be displayed (Figure 7.15).

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Figure 7.15: EuTravel Observatory Admin - Journals

7.2.9 Experts Here you can suggest an Expert including his/her contact details along with the category that is specialised. An email will be sent to admin to check if the information you have provided is correct (Figure 7.16).

EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0

Figure 7.16: EuTravel Observatory Admin - Experts

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7.3 EuTravel Observatory System – Admin View This section provides general information on the system of the EuTravel Observatory Knowledge Admin side from the Admin point of view. The system is a web based system and accessible from anywhere. It is built on the EuTravel Knowledge Platform utilising the .NET Framework and powered by the SQL Database engine.

7.3.1 How to login In order to login to the EuTravel Observatory System you have to type in the address bar of your browser http://www.eskema.eu/skemaknowledgeadmin/eLogin.aspx and the page shown in Figure 7.17 will open. Type the login information that was sent to you by the super admin. You have the option to select a different language if you wish.

Figure 7.17: EuTravel Observatory Admin - Login Page

7.3.2 Main Page At the top is the navigation menu where you can make a choice to display the data in the middle of the screen. In the middle of the Welcome screen there are the most important quick links that the user can select and navigate to. At the very top right on the main page there is the option to change your password or log off from the system (Figure 7.18).

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Figure 7.18: EuTravel Observatory Admin - Main Page

7.3.3 Dropdown Lists In various pages you will see a dropdown list (Figure 7.19) that allows you to select an object from the list.

Figure 7.19: EuTravel Observatory Admin - Dropdown List • The first button allows the addition of a new object in the list. • The second button allows the user to edit the selected object from the list. • The third button allows only the projection of the selected object from the list. • The buttons provide access depending on the user’s level.

7.3.4 Upload Files In various pages you will see the buttons in Figure 7.20. These buttons allow you to upload or download a file.

Figure 7.20: EuTravel Observatory Admin - Upload and Download file buttons

Figure 7.21 shows the popup window that will open when you click on the upload button. Click on the select button and choose the file that you want to upload on the site. Finally click on the upload button and wait for the file to be uploaded on the server.

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Figure 7.21: EuTravel Observatory Admin - Upload File Popup

The same applies to the View Button. Once you have clicked the View button you will be able to download and view the file.

7.3.5 Modules By clicking on the top menu, under Menu item “Modules”, you can find the “Portal Module” link. This page displays a list of modules assigned to this portal as shown in Figure 7.22.

Figure 7.22: EuTravel Observatory Admin - Edit Module

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Figure 7.23: EuTravel Observatory Admin - Portal Modules By selecting one of the modules and clicking on the “Edit Record” on the left hand side you have the option to change the information entered for that module as illustrated in Figure 7.23.

Fields Explanation: • Name: This is the name of the module. • Description: Here you can add the description of the module that will be displayed on the EuTravel Portal as shown in the Figure 7.24. • Position, Column: Here you can specify the position of the module on the Portal • Object: From this field you can select in which category this module belongs • Level: Here you can write all the Subject Area levels that belong to this module, and they will appear on the EuTravel Portal as show in Figure 7.24. • Has Childs: Select this field if there are children under this module. • Visible: Select this field if you want to be displayed on the EuTravel Portal. • Web Role: Select this field if you want to give specific permissions to specific roles.

Figure 7.24: EuTravel Observatory Admin -

Module on EuTravel Portal

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7.3.6 Templates

By clicking on the top menu, under Menu item “Modules”, you can find the “Templates” link. This page displays a list of templates assigned to this portal as shown in Figure 7.25. The purpose of these templates is that it gives the flexibility to the admin to change the look and feel of different sections of the portal easily.

Figure 7.25: EuTravel Observatory Admin - Portal Templates By selecting one of the templates and clicking on the “Edit Record” on the left hand side you have the option to change the information entered for that template as illustrated in Figure 7.26.

Figure 7.26: EuTravel Observatory Admin - Templates' Form Fields Explanation: • Type: The name of the template. • Template: Here you can make the design of the template that will show on the EuTravel portal.

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7.3.7 Navigate Tree By clicking on the top menu, under menu item “Index”, you select the link Navigate Tree. Figure 7.27 shows the Navigate tree page. Here you can see a navigation tree that is assigned to the EuTravel Portal. • The first level is the Subject Categories. • The second level is the Subject Area. • The third level is the Subject Topic. • The fourth level is the Subject Info. Registered members have access to add or edit only at the third and fourth level.

Figure 7.27: EuTravel Observatory Admin - Navigate Tree

When you click on a node from the third and fourth level, the left Toolbar (Figure 7.28) will appear with the buttons that will allow you to edit the selected Subject Topic or add Subject Info related to this topic.

Figure 7.28: EuTravel Observatory Admin - Navigate Tree Actions

In Figure 7.29 you can see the Subject Info form. Here you can write all the information you want to be displayed on the EuTravel Observatory Portal.

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Figure 7.29: EuTravel Observatory Admin - Subject Info Form Fields Explanation: • Subject Area/Subject Topic: These fields will be added automatically depending on the tree choice. However you can choose another if you wish. • Title: This is the title of the Subject Info. • Author: The name of the Subject Info author. • Overview: In this text editor you can write the overview of the Subject Info that will be displayed in the centre of the EuTravel Observatory Portal. • Study Filename: Here you can upload the file of the Subject Info that will be available on the website for download. • URL: In this field you can write a website URL that has more information about this subject info.

At the left of the Subject Info form, as shown in Figure 7.29, you can see the tabs with all the related subjects. In order to add any related subject, click on the tab and then on the Add new record. These subjects exist on the right side of the EuTravel Observatory Portal.

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7.3.8 Subject Categories By clicking on the top menu, under Menu item “Index”, you can find the “Subject Categories” link. This page displays a list the Subject Categories assigned to this portal as shown in Figure 7.30.

Figure 7.30: EuTravel Observatory Admin - Subject Categories By selecting one of the subject categories and clicking on the “Edit Record” on the left hand side you have the option to change the information entered for that category as illustrated in Figure 7.31.

Figure 7.31: EuTravel Observatory Admin - Edit Subject Category

Fields Explanation: • Index No: Here you can write the Index level of the Category. • Name: Here you can write the name of the Subject Category.

On the left hand side of the Subject Category form you can see the Subject Areas link. By clicking this link you will be redirected to the Subject Areas of this Subject Category. In Figure 7.32 you can see the Subject Areas.

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Figure 7.32: EuTravel Observatory Admin - Subject Areas

By selecting one of the subject areas and clicking on the “Edit Record” on the left hand side you have the option to change the information entered for that Area as illustrated in Figure 7.33.

Figure 7.33: EuTravel Observatory Admin - Edit Subject Areas

Fields Explanation: • Subject Category: This field will be added automatically proportionally by the tree choice. However you can choose another if you wish. • Index No: Here you can write the Index level of the Subject Area. • Level: This is the Index No of the Subject Category. You can add the level together with the index no to the Modules form in the field level. • Name: The name of the Subject Area. • Position: The position of the Subject Area on the EuTravel Portal. • Visible: Select this if you want the Subject Area to be displayed on the EuTravel portal.

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The same way, on the left hand side of the Subject Area form you can see the Subject Topics and Subject Info links. By clicking on these links you will be redirected to the respective screenshots as shown in Figures 7.34 and 7.35 respectively.

Figure 7.34: EuTravel Observatory Admin - Subject Topics

Figure 7.35: EuTravel Observatory Admin - Subject Info

By selecting one of the subject topics and clicking on the “Edit Record” on the left hand side you have the option to change the information entered for that Topic as illustrated in Figure 7.36.

Figure 7.36: EuTravel Observatory Admin - Edit Subject Topic

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Fields Explanation: • Subject Area: This field will be added automatically proportionally by the tree choice. However you can choose another if you wish. • Index No: Here you can write the Index level of the Subject Topic. • Level: This is the Index No of the Subject Area. • Name: The name of the Subject Topic. • Position: The position of the Subject Topic on the EuTravel Portal. • Visible: Select this if you want the Subject Topic to be displayed on the EuTravel Portal.

7.3.9 Glossary Terms In Figure 7.37 you can see the Glossary Terms form. Here you can add the term, its definition and the Wikipedia link.

Figure 7.37: EuTravel Observatory Admin - Glossary Terms Form

Also you can add comments, or see the comments that users add from the website as illustrated in Figure 7.38.

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Figure 7.38: EuTravel Observatory Admin - Glossary

Comments

7.3.10 Events Here you have to write the event name, date and the details of the Event. Also you can write the URL where the user can find some more information. There is also the option to upload a filename together with the event details (Figure 7.39).

Figure 7.39: EuTravel Observatory Admin - Events Form

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7.3.11 Journals Here you can write the name, description and the URL of the Journal. Also you can choose whether you want the journal to be visible or not, and in which order you want them to be displayed (Figure 7.40).

Figure 7.40: EuTravel Observatory Admin - Journals

7.3.12 Experts Here you can suggest an Expert including his/her contact details along with the category that is specialised. An email will be sent to the admin to check if the information you have provided is correct (Figure 7.41).

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Figure 7.41: EuTravel Observatory Admin - Experts

7.3.13 Registrations Last but not least, in Figure 7.42 you can see the registrations form. Here you can add the personal information of the members. Also you can edit, view or delete the members that have been registered from the EuTravel portal registration form and to add new Subject Info.

Figure 7.42: Registrations Form

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7.4 EuTravel Observatory – Public Site This section of the report describes in detail the EuTravel Observatory Knowledge Portal. This portal has been designed taking into consideration the colour and themes of the EuTravel Project website. The technology engine is powered by the EuTravel knowledge based Platform which has been developed as part of the EuTravel Project. The EuTravel Observatory content is being updated on a bi-weekly basis.

7.4.1 Welcome Page Figure 7.43 illustrates the EuTravel Observatory Welcome Page. The welcome page contains all modules/topics that are available for the EuTravel Portal. These modules can be customised according to user requirements.

Figure 7.43: EuTravel Observatory - Welcome Page

Customised homepage The user can choose the modules they prefer to be displayed on the EuTravel welcome page. When you click on the link “Customised Homepage” the list of all the modules is shown. Unselect the modules you want to remove from the front page and then click the “Save” button in order

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EuTravel - D1.3 Technology Knowledge Base and Observatory – Version 2.0 to save your changes. The “Reset Default” button clears the changes that the user made and rearranges the EuTravel welcome page to the original form. Figure 7.44 shows the customised homepage.

Figure 7.44: EuTravel Observatory - Customised Homepage

Edit Modules The user can select and display from each module only the areas that interest him. When the user clicks on the “Edit” button, next to the title, the list of the related areas appears. Unselect the areas you want to remove from the front page and then click “Save” button in order to save your changes. Figure 7.45 shows the list of the areas.

Figure 7.45: EuTravel Observatory - Edit Modules

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Add/Remove topics Under each area there are a number of topics. The user can increase or decrease the number of the topics they want to be shown on the welcome page by clicking on the icons. Figure 7.46 shows how to increase and decrease the number of topics to be displayed for each area.

Figure 7.46: EuTravel Observatory - Add/Remove Topics

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Drag and Drop Modules Another feature of the EuTravel Observatory Portal is that the user can also change the position of the modules. You can click on the title of a module and drag it to any position you want on the Portal. Figure 7.47 shows how the “Travel Regulatory Framework” module, before moves and Figure 7.48 after moves from the left column of the page to the right column.

Figure 7.47: EuTravel Observatory - Drag and Drop Modules (before)

Figure 7.48: EuTravel Observatory - Drag and Drop Modules (after) 118

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When the user makes some changes on the appearance of the page these changes will be saved automatically and the next time the user visits the EuTravel Observatory Portal from the same computer these changes will apply.

7.4.2 Subject Info Page

When the user clicks on a specific area topic, a new page with all the information will open. In Figure 7.49 you can see how the subject info page looks.

Figure 7.49: EuTravel Observatory – Subject Info webpage (a)

Overview of the subject info On the centre of the page (Figure 7.50) there is an overview about the selected subject. On the right hand side of the overview, there are some related links that are relevant to the Subject Info page. For example there are “Subject News”, “Linked Topics”, “Related Documents”, “Lessons Learned”, “Information Source”, “Related Projects”, “Related Policies” and “Related Products”. Furthermore, at the bottom of the Overview page (see Figure 7.47), the users have the ability to write comments for the article and read comments from other users. Under the overview there is a glossary term section. The Subject Info page has been designed in such a way in order that all relevant information will be on one page with easy navigation and reading of all relevant information. Under the overview and the glossary terms there is some additional information for the selected topic

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Figure 7.50: EuTravel Observatory – Subject Info webpage (b)

EuTravel Index Tree The navigation tree always appears on the left side of the page (Figure 7.51) with the EuTravel Index information. There is a four level tree with all the subject categories, topics and articles of the EuTravel Observatory portal. By clicking on one of the tree nodes, the user will be automatically redirected to the selected subject information webpage. This tree helps the user to navigate to other subject categories that are part of the same Subject Area.

Figure 7.51: EuTravel Observatory - EuTravel Index Tree

Related Subjects On the right side of the page there is a column with subjects related to the topic in the middle of the page. On the top there is news linked to the related subject and below there are two linked topics. There are also some related documents, lessons learned and information sources for reading in more depth about the specific subject. On the bottom there are also the related projects, and policies.

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Access to Restricted Modules In order for the users to have access to restricted modules on the Portal, they need to. Click at the Login button at the top of the Portal (see Figure 3.3.3) in order to open the login page.

Figure 7.52: EuTravel Observatory - Login Button

After the pop up Login page appears Figure 3.3.4, user will enter the username and password (received by email) and click on the Login button. Now the user will be able to view more modules that are only available to registered members.

Figure 7.53: EuTravel Observatory - Login Form

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Advanced Search Another important functionality of the EuTravel Observatory Portal is the ability of the users to easily search all the above information using an advanced search component. For the purpose of the example, the keyword “security” is entered into the box above and the button “go” is clicked. Once it is clicked, the search results appear as illustrated in Figure 7.54. The results are categories by type of information i.e. document, news, events etc. The user has the ability to filter the results by selecting the filtering options above the results page.

Figure 7.54: EuTravel Observatory - Search Results

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8. Conclusions

Advances in technology are revolutionising the way consumers around the world search, shop, book, share and compare their holidays and the way operators and other service providers utilise collected data. The adoption and applications of these technologies are shaped by a range of factors beyond technology maturity, such as social acceptance, cost to end users and government interventions.

Several projects have been addressing challenges of improving the traveller’s experience, integrating modes, managing and optimising the capacity of the transport network, improving flows, better utilising resources, enabling better decision making, and improving the overall quality of services to the European citizen.

This deliverable summarises the results of the preliminary research on such projects and the state-of-the art technologies that fall within the project scope and identifies limitations and areas for advancement. The deliverable contributes to WP1 objectives and the development of the Optimodality Framework by analysing the existing technology drives in the context of multimodal travelling.

A classification of ITS and travel related technologies was attempted, in order to specify the EuTravel focus areas from a technology perspective. EuTravel builds on technologies related to advanced Travel Information Management, thus technologies adopted to enable well-informed travel decisions (pre-trip) and information provision during the journey (on-trip). This category involves also route optimisation algorithms. On the other hand, technologies facilitating modes integration and the realisation of data-driven intelligent transport networks (ecosystems) managed with data have been examined. Data and insight (knowledge discovery) technologies have been considered for the development of added value services for all travel stakeholders.

After the technology review and analysis, it was considered important for EuTravel to utilise and advance the state-of-the-art in the following areas: • Journey Planners and Advanced Travel Information Services, • Route optimisation, • Travel Ontologies, • Data integration and harmonisation (of data provided through APIs by different service providers across different modes), • Data and insight (knowledge discovery) technologies for the development of added value services for all travel stakeholders.

The EuTravel online knowledge base and observatory consolidates the outcomes of this deliverable and is available to the public.

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[92] View at http://www.masstransitmag.com/article/10286925/cloud-computing-in- transportation-increasing-efficiency-by-connecting-devices-to-the-cloud [93] Inside the Mind of Generation D: What it means to be data-rich and analytically driven. IBM Center for Applied Insights, 2014. [94] Drawing Transportation Planning Inferences From Big Data, by Tom Sawyer. ENR: Engineering News-Record; 9/22/2014, Vol. 273 Issue 8, p1 [95] Why Big Data Means Big Opportunity For The Travel Industry, by Shannon Adelman. – Forbes, 9 July 2015 [96] Making Summer Air Travel Less Stressful With Big Data and Mobile Technology, by Raimon Christiani. Forbes, 15 July 2015 [97] View at http://www.optitrans-fp7.eu/index.php/project, http://optitrans.net/? [98] View at http://www.wisetrip-eu.org/ [99] WISETRIP – International multimodal journey planning and delivery of personalized trip information. Vasssilis Spitadakis, Maria Fostieri. Procedia p Social and Behavioral Sciences 48 (2012). SciVerse Science Direct. [100] View at http://www.shift2rail.org/ [101] View at http://www.it2rail.eu/ [102] View at http://www.cer.be/press/press-releases/press-releases/taking-rail-ticket- distribution-to-the-next-level-railways-and-ticket-vendors-launch-the-full-service-model- initiative/. [103] View at www.cer.be [104] View at www.ectaa.org [105] View at www.ettsa.eu [106] View at http://co-cities.eu/ [107] View at http://opentransportnet.eu/ [108] View at http://www.mobinet.eu/ [109] View at http://modum-project.eu/ [110] View at http://www.streetlife-project.eu/ [111] View at http://www.transport-research.info/project/support-action-contribute- preparation-future-community-research-programme-user-centered [112] View at http://edits-project.eu/ [113] View at http://www.civitas.eu/content/2move2 [114] View at http://www.posse-openits.eu/ [115] www.ecompass-project.eu [116] View at http://smile-einfachmobil.at/ [117] View at http://www.transforum-project.eu

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[118] View at http://www.fp7-compass.eu/ [119] View at http://www.ontime-project.eu/ [120] View at http://instant-mobility.com/ [121] View at http://www.allwaystravelling.eu/documents.aspx [122] View at http://ec.europa.eu/transport/its/multimodal-planners/index_en.htm [123] View at http://www.opticities.com [124] View at http://www.nodes-interchanges.eu/ [125] View at http://www.interconnect-project.eu/ [126] View at http://cordis.europa.eu/project/rcn/93951_en.html [127] View at http://byte-project.eu/ [128] View at http://bonvoyage2020.eu/ [129] View at http://www.codecs-project.eu [130] View at https://dora-project.eu/ [131] View at http://www.openticketing.eu/ [132] View at http://hights.eu/ [133] View at http://masai.teleticketing.eu/ [134] View at http://www.optimumproject.eu/ [135] View at http://roadart.eu/ [136] View at http://socialcar-project.eu/ [137] View at http://www.timon-project.eu/ [138] View at http://ldct.sti2.at/ [139] C(2017) 3574 final, COMMISSION DELEGATED REGULATION (EU) …/... of 31.5.2017 supplementing Directive 2010/40/EU of the European Parliament and of the Council with regard to the provision of EU-wide multimodal travel information services and ANNEX [140] Karakostas, B., & Kalamboukis, Z. (2017). API mashups: How well do they support the travellers’ information needs? Procedia Computer Science, 109, 204-209. Karin de Regt, Oded Cats, Niels Van Oort and Hans van Lint (2017). Investigating Potential Transit Ridership by Fusing Smartcard and Global System for Mobile Communications Data, Transportation Research Record: Journal of the Transportation Research Board [141] Evangelatos, S., Kalampoukis, Z., Fergadioti, I., Christofi, S., Karakostas, B., & Zorgios, Y. (2017, July). Service availability analysis of a multimodal travel planner using Stochastic Automata. In Computers and Communications (ISCC), 2017 IEEE Symposium on (pp. 146- 151). IEEE. [142] B.Karakostas, D. Kardaras, A Knowledge Graph for Travel Mode Recommendation and Critiquing, DBKDA 2017: The Ninth International Conference on Advances in Databases, Knowledge, and Data Applications, Antwerp, Belgium

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[143] AWT (All Ways Travelling) Final Report - Phase 2 - Proofs of Concept (POCs), Contract MOVE/C2/SER/2012 489/SI2.646722, 2016 [144] Eric Fontanel, Roderick Smith, Heather Allen, Michael Dooms, Interim Evaluation of Shift2Rail Joint Undertaking (2014-2016), June 2017 [145] L. Castillo, et al., “Samap: A user-oriented adaptive system for planning tourist visits” Expert Systems with Applications, 34, 1318–1332, (2008). [146] L. Ceccaroni, V., Codina, M., Palau, and M. Pous, “PaTac: Urban, ubiquitous, personalized services for citizens and tourists,” In Third international conference on the digital society (ICDS 2009), February 1–7, 2009. [147] MaaS$EU project, viewed at http://www.maas4eu.eu/

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Annex 1

10. Annex 1

The tables below present indicative APIs classified under the five different themes. For each API its name and URL pointing to more information about it is listed. A short description about the API is also provided, based on the information presented on Programmable Web. APIs are listed alphabetically, and no relative significance or chronological order is assumed about the APIs in the lists.

10.1 Service Aggregation APIs Allmyles Developers can use the Allmyles API to integrate http://www.allmyles.com services for booking flights, hotels and car rental. Avinode Market The Avinode Marketplace APIs allow developers to use http://www.avinode.com/ air charter information to create search engines, design unique marketplaces, and attract more business to their sites or applications. CAVAL CAVAL is an initiative for developing open standards Htttp://caval.travel for data interoperability in the travel and tourism industry. Cleartrip Hotel It supports booking for flights, hotels and trains, as http://www.cleartrip.com/ well as other travel services across the world. The Cleartrip Hotel API provides developers access to the hotel search and bookings. CostaClick CostaClick is the portal for travel agents provided by http://www.costacruise.com/ Costa Cruises, a booking service for cruises around the world. Cyrus Recharge Travel Portal API The Cyrus Recharge Travel Portal API allows http://www.cyrusrecharge.com developers to integrate methods for real time booking of buses, flights, cabs, and more into their own websites and applications. FlitWays With FlitWays API, travel suppliers such as Airline, https://flitways.com Hotels, Car Rentals, Cruises, Travel Consolidators, Aggregators. mTrip http://business.mtrip.com/ mTrip develops mobile solutions for the travel industry. The mTrip API can be used by tour operators, travel agencies, and their partners to sync client-side data. Rezdy new Rezdy is an online booking and reservation platform. http://hotelscombined.com Users can accept reservations and bookings online through their websites with Rezdy feature. SilverRail Journey Planner Jeppesen provide charts, maps and planning solutions http://ww1.jeppesen.com/ for aviation, marine and rail operators. The Jeppesen Journey Planner API lets developers integrate public transit information into their own. TourCMS Marketplace TourCMS provides a full website and reservation http://www.tourcms.com management system for small and medium sized tour operators.

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Travel Connectivity XML The Travel Connectivity XML API solution enables 3rd http://www.travelconnectivity.com / party developers to utilize existing TC products and deliver them in their own presentation. Travel IQ Travel IQ is an online travel booking service. The Travel http://travel-iq.com IQ API offers developers programmatic access to the functionality of the booking service. Travel portal The Travel Portal API provides programmatic access to http://www.topscripts4you.com functions that allow customers to book hotels, flights, cars, and tours from the developer's websites. TravelFusion The Travelfusion Direct Connect XML API allows http://www.travelfusion.com/ authorised travel partners direct and easy access content from more than 170 low cost and scheduled airlines. Travelisense OpenDistribution The service provides unified access travel information http://www.travelisense.com from a distributed partner network of separate systems specializing in information about flights, hotels, car rental, etc. Travelport Travelport Universal API is the global distribution http://www.travelport.com/ system (GDS) industry’s first truly universal API, giving you access to a world of content and functionality through a single API connection. Triptelligent Shore Excursions Triptelligent is a shore excursion marketplace for http://www.triptelligent.com/ travellers on cruise ships. Cruise guests are connected with tour operators, local guides, and personalized service. ValueCommerce Travel The Travel API allows users to aggregate airfare, hotel http://www.valuecommerce.com and tour data from top merchants in Japan. Waynaut http://waynaut.com/en/ Waynaut API provides a RESTful JSON interface to implement mapping features around Europe. Yahoo Travel From their site: Yahoo! Travel is also launching API http://developer.yahoo.com/travel/ access to trip planner data through a REST-like interface. Zilyo Vacation Rental Zilyo is an online company that provides travellers a https://zilyo.com/ way to find places to stay from around the world. The Zilyo Vacation Rental API lets developers integrate its services with their applications.

10.2 Single Service Provider APIs http://www.bestparking.com/ Parking data (garages and lots open to the public). British Airways British Airways (BA) is a full service global airline with www.ba.com an extensive global route network based out of the United Kingdom. British Airways offers developers a REST API. Click A Taxi The service provides automated ordering of taxi clickataxi.com service in 5000 European and North American cities. EAN Cancel Reservation The EAN Cancel Reservation API allows developers to http://developer.ean.com/ integrate the Expedia database into their applications, enabling their users to cancel an existing reservation for a single room. EAN Hotel List EAN Hotel List API allows developers to integrate the http://developer.ean.com/ Expedia hotel list database into their applications, enabling their users to search for hotels by location or

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by hotel id. EAN Itinerary Request The EAN Itinerary Request API allows developers to www.expedia.com integrate the Expedia database into their applications. EasyToBook Easytobook provides hotel bookings for more than http://www.easytobook.com/ 120,000 hotels in over 9,000 cities. Expedia (www.expedia.com) Expedia EAN Developer Hub gives developers free access to a set of APIs that power websites, mobile apps, and more. Google Maps Roads The Google Maps Roads API allows developers to https://developers.google.com identify the roads a vehicle was traveling along and provides additional metadata about those roads, such as speed limit. Google QPX Express The Google QPX Express API allows developers to http://www.google.com access information on global airline pricing and availability. Instamanager Instamanager is a cloud-based vacation rental http://www.instamanager.com/ software provided by Bookt. SITA Boarding Pass SITA's 2D Boarding Pass API creates and delivers an http://www.sita.aero/ IATA and TSA standard compliant 2D boarding pass image based on information and boarding pass delivery. TripAuthority XML API from Alliance Reservations Network for hotel http://tripauthority.com/hotel.asmx availability, rate details, bookings, and cancellations. Uber https://www.uber.com/ Using the Uber API, developers can integrate Uber taxi booking service into 3rd party applications. WuBook Wired http://wubook.net/ WuBook is an online booking service allowing hotels to support online booking and sync Internet Distribution Services.

10.3 Travel related Information APIs AwardWallet API for a service that lets users manage their reward http://awardwallet.com/ balances and travel itineraries. Bing Traffic www.bing.com The Bing Traffic API provides information about traffic incidents and issues, such as construction sites and traffic congestion. CicerOOs Semantic Graph CicerOOs is an Italian travel search engine and virtual http://www.ciceroos.it tour guide. CicerOOs exposes its service through the CicerOOs Semantic Graph API. Currency Converter API The Currency Converter API allows users to get Providerhttp://www.currencyconv exchange rates between over 60 currencies with just 1 ertapi.com line of code. Findery https://findery.com Findery is a destination discovery application. Hotwire Rental Car Shopping The Rental Car Shopping API delivers data describing http://hotwire.com rental car shopping results similar to those that can be obtained when shopping for rental car rates on Hotwire.com. Lodgix Vacation Rental The Lodgix Vacation Rental API allows users to access http://www.lodgix.com the booking calendars, availability data, property images, marketing copy, and amenities and rate information for the properties. MarineTraffic API MarineTraffic provides data on millions of daily vessel http://www.marinetraffic.com/ positions, which users may integrate with their

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applications or websites using the RESTful API. MonitorHotels Rate Shopping Data The MonitorHotels Rate Shopping Data API provides https://monitorhotels.com/ users all the data used for displaying charts on this site and much more. Mountain News Provides information about activities useful for winter http://www.mountainnews.com/h sports enthusiasts and vacation travel planners. API ome.html methods support specification of a location or region to receive listings of ski resorts etc. Outpost.Travel Outpost.Travel helps users find affordable vacation Publichttp://outpost.travel/ rentals, rideshares, and local activities all around the world. PilotOutlook This API provides geo-coordinates, city, state, epoch, http://pilotoutlook.com runway and other information for about 40,000 airports. Planyo http://www.planyo.com Planyo is a flexible online booking system for resources such as hotels, holiday apartments, yacht rentals, driving schools, tennis courts, doctor appointments, events etc. Qalendra Predictions Qalendra Predictions API provides long-range https://qalendra.com predictions for travel and hospitality. RestFul Web Services Airport The RestFul Web Services Airport API allows users to http://www.restfulwebservices.ne retrieve detailed information about a given airport code.

10.4 Travel Itinerary planning APIs

SITA iTravel This is an API for a web service that provides developer access to air travel shopping, booking, http://www.sita.aero/ check-in, loyalty, baggage tracking, and flight and airline information. FlightCaster FlightCaster predicts flight delays, often hours before http://www.flightcaster.com the airlines. Flightwise http://flightwise.com/ Flightwise's Flight Data API and PlaneXML allow developers to pull near real-time flight tracking. FlightAware http://flightaware.com Using the FlightXML API, programs can query the FlightAware live flight information and historical datasets. ExpertFlyer The ExpertFlyer API provides access to real time flight http://www.ExpertFlyer.com data. Airport Transfer Worldwide It allows users to avoid long waits at airports or having http://www.taxi2order.com/ to travel on public transit. FlightView FlightView's API includes dozens of attributes to http://corporate.flightview.com/ describe the status and location of more than 130,000 commercial and general aviation flights every day around the world. Flight Routing API Flight Routing is an API hosted by Mashape. It lets https://mashable.com/flight-routin users get flight routing options, currently covering European and US airspace. HitchHiker Flight The Flight API as a basis to create your own travel http://www.hitchhiker.net booking platforms for travel agencies or end- consumers. TripIt http://www.tripit.com API allows users to access the TripIt's information about travel and itineraries.

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Flextrip http://www.flextrip.com Flextrip offers APIs which allow online travel companies to create and catalyze financial opportunities through a wide and diverse selection of tours and activities. Airport Transfers Transfers API is a tool for developers representing http://www.airportransfers.gr travel agencies, companies, and websites affiliated with tourism services. Rome2rio Rome2rio is an API to discover travel itineraries from http://www.rome2rio.com/ all around the world. i2space http://www.i2space.com I2space technologies is a travel portal platform that provides the i2space API which allows users to facilitate Bus Booking. Rutamina http://en.rutamina.com The Rutamina API provides data from a database of routes, so any application can get, search and display routes on maps. Rutamina is a community focused on walking routes, cycling. ViaMichelin http://viamichelin.com The ViaMichelin APIs provide users with access to high quality maps, car and pedestrian itineraries, proximity and integrated booking search engine. Waze http://www.waze.com/ Waze is a social mobile application providing free turn- by-turn navigation based on the live conditions of the road. INFOBUS INFOBUS is an online booking company that lets its http://www.infobus.eu customers to browse and book bus, train, or flight tickets to their destinations. INRIX Provides mapping of road systems with congestion http://www.inrix.com/ reports to estimate travel times and suggest the quickest routes. Route4me The service is designed to reduce travel time, save on http://www.route4me.com vehicle expense. The Route4me API allows users to plan a route, view routes, check the distance. aboutPLACE The aboutPLACE RESTful API allows developers to http://www.urban4m.com/ integrate place-based data into interactive maps. BagJourney http://www.sita.aero/ SITA BagJourney API presents passengers the option to track baggage in real time using mobile devices. Hotwire Hotel Shopping The Hotel Shopping API delivers data describing hotel http://hotwire.com shopping results similar to those that can be obtained when shopping for hotel rates on Hotwire.com. CTA Bus Tracker The CTA Bus Tracker API provides a gateway into near- http://www.transitchicago.com real-time CTA bus locations and estimated arrival times.

10.5 Travel Collaboration APIs NileGuide NileGuide API makes most of their original travel http://www.nileguide.com content to make relevant suggestions that make for more rewarding travel experiences. TripSay TripSay is a travel website where users share their http://www.tripsay.com/ trips and connect with traveling friends to exchange insider tips. Add To Trip The Add to Trip API lets users manage a social travel https://addtotrip.co network including user creation/authentication, social notifications, geolocation searches, trip itineraries etc.

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Unofficial Free Waze It is offered to developers interested in https://www.mashape.com/best implementation of travel, mapping, and social apps. api/free-waze-route-calculation Myallocator.com Allows users to update their accommodations and http://www.myallocator.com information on many online travel sites. The Myallocator.com API allows developers to access and integrate the functionality of Myallocator.com. Pocket Village It offers a platform for users to search and compare http://www.pocketvillage.com/ travel experiences, activities and tours. HotelsCombined No public API documentation is available for this API, http://hotelscombined.com but access to documentation is available when you register to the affiliate program (free). eTravelSmart etravelsmart.com Use this API to manage all aspects of online bus reservation in India. G Adventures G Adventures provides small group tours around the http://www.gadventures.com/ globe with a focus on delivering authentic adventures in a responsible and sustainable manner. DealAngel DealAngel is a hotel rate search engine. DealAngel http://www.dealangel.com allows users to search for hotels by location, retrieving pricing and reservation information for booking hotel. hubermedia eTourist Hubermedia is a website for facilitating the exchange http://hubermedia.de/ of information useful to tourists and the tourism industry. eTourist is one of hubermedia's services. 3.0 Trippin' in It provides attraction recommendations via API. http://www.trippinin.com My Trails My Trails offers users four API choices. The Location www.mytrails.com.au Based Search API returns information on shared trails and markers for latitude/longitude inputs from the My Trails database.

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