Concept of Mobile Application for Mobility As a Service Based on Autonomous Vehicles

sustainability

Article Concept of Mobile Application for Mobility as a Service Based on Autonomous Vehicles

Yinying He * and Csaba Csiszár

Department of Transport Technology and Economics (KUKG), Faculty of Transportation Engineering and Vehicle Engineering (KJK), Budapest University of Technology and Economics (BME), 1111 Budapest, Hungary; [email protected] * Correspondence: [email protected]; Tel.: +36-7055-314-42

Received: 22 July 2020; Accepted: 15 August 2020; Published: 20 August 2020

Abstract: Mobility as a service (MaaS) is proposed to encourage travelers to choose sustainable mobility options and reduce use of individual car. In the future, mobility services based on autonomous vehicles (AVs) are also incorporated into MaaS. The objective of our work is to elaborate the concept of mobile application, aiding the MaaS based on AVs. We applied a system engineering process-oriented approach to determine the information system components, the functions as well as input and output data. Functions of back-end information system operation and front-end interface of application have been identified, as well as the information flows have been modeled. We highlighted the main differences between MaaS and MaaS based on AVs. We found that recording of event-based points and feedback management are regarded as pivot functions in this self-travel service. Our results facilitate the development of smartphone application for the MaaS based on AVs.

Keywords: mobility as a service; autonomous vehicle; smartphone application; concept; function

1. Introduction In the mobility as a service (MaaS) concept, cooperation between public and private transport service providers are managed by the MaaS operator. According to the proposed ideal solution, all kinds of mobility services can be ‘accessed’ via a single smartphone application by travelers. Considering the typical existing MaaS services, the following mobility services or modes are involved: public transport (PT), taxi, car/bike-sharing, ridesharing, ride-sourcing, car rental, scooter sharing. The MaaS based on autonomous vehicles (AVs) is to be envisaged as a more ‘mature’ MaaS service. The automated or autonomous PT (A-PT) service is proposed for large volume passenger transit; the services of shared AVs (SAVs) are proposed for first/last mile supplementary purpose. Since AV is an intelligent machine, information management is essential in entire travel. The travel planning and transfer processes are significantly supported by transport informatics. The mobility service is based on interactions between travelers and smartphone applications. ‘By the support of online smartphone application, travelers arrive at their destination via a low-carbon emission, environment friendly, and priceworthy multimodal travel chain from departure point by themselves.’ It is identified as the goal of the self-travel service of MaaS based on AVs. The objective of our work is to elaborate the concept of smartphone application for the MaaS based on AVs. Travel related functions are identified regarding the main system components, where the operation of application-related functions is highlighted. Towards the back-end information system analysis, information flow (input and output data groups) of functions regarding each travel phases, e.g., before, during, and after travel, are presented. In addition, the front-end interface functions of application are introduced and compared with the benchmarking ‘Whim (https://whimapp.com/)’ application. The correspondences between the back and front -end functions have been modeled too.

Sustainability 2020, 12, 6737; doi:10.3390/su12176737 www.mdpi.com/journal/sustainability Sustainability 2020, 12, 6737 2 of 16

Two premises are pre-deﬁned as follows:

1. The services of SAVs are grouped into two categories: vehicle sharing and vehicle-seat sharing. Small or medium sized vehicles are applied. The former one is similar as the car-sharing service and the later one as the small group ride-sharing service; namely, the A-PT works as the large volume vehicle-seat sharing transit. Reservation based or on-demand service types are not distinguished in our work. In addition, parking issues of vehicles are also not considered. 2. The role of public or private MaaS operators is widely discussed in existing publications. In our work, the ﬂeet operator of SAVs is preferred to be the operator of MaaS based on AVs, considering that the most complicated task coordination is managed by this operator.

The A-PT service will still be the schedule and route-based service; however, the management of AV fleet is much more complicated than management of the public transportation. Accordingly, automated operational management is proposed in the MaaS based on AVs system. Most of the real-time data are generated from AV fleets. In the case the operator of PT service belongs to the operator of AV fleets, the data are shared and operated more efficiently. We assume that the main AV fleet operator is appointed to be the operator of this MaaS based on AVs service. Several smartphone applications for existing MaaS services have been developed by various MaaS operators, but the concept of envisaged mobile application in MaaS based on AVs have not been elaborated. This is identiﬁed as the research niche. Accordingly, our research questions are:

What is the information system architecture? • What is the back-end operational functions and front-end user interface functions? • What are the data flows among components and functions? • The multimodal travel chain generation and traveler-vehicle identification are the pivot functions in autonomous mobility. The former one is to balance the demand and supply; the later one is needed for the fare calculation. In addition, feedback management affects the quality of service. The remainder of the paper is structured as follows. State of the art is summarized in Section2. Sections3 and4 are to present the back-end operation of application. Section5 is to introduce the front-end user interface. In Section3, function groups of travel regarding main system components are determined. The information flow of interacted functions according to the travel chain is modeled in Section4. In Section5, the functions on application interface are summarized and new functions are highlighted, the correspondences between front-and back-end functions are modeled. The paper is completed by the concluding remarks in Section6.

2. State of the Art The literature is reviewed under topics of MaaS, shared services based on AVs, and mobile application related papers. The structure is shown by Figure1. Not all reviewed papers contributed to our work directly, however, they have been used as stimulation during our work. Transport (or mobility) is already not only an activity to move travelers from point A to B, travelers participate in the travel process more actively and act as a moving information collection and management points. Individuals have their consciousness and requirements [1], this is why transport or mobility should be provided as a service. MaaS is a mobility service which is provided by an integrated transportation system, stakeholders such as MaaS operator, service providers, and users are interacted via a single application [2]. In addition, combined mobility monthly plans are introduced which are available by subscription. Towards MaaS based on AVs, the intelligent vehicles are to be considered as an essential component of the MaaS system, and the simpliﬁed service structure requires a new interface to conduct such an interaction. Sustainability 2020, 12, 6737 3 of 16 Sustainability 2020, 12, x FOR PEER REVIEW 3 of 18

Smartphone MaaS Application [3, 4, 5, 6] Interaction Travel Platform behaviour [14, 15, 16, 17, 18, 19, 20]

AV SAV Concept [3, 4, 5, 6, 21, 22, [8, 9, 10, 11] [12, 13] 23, 24]

Figure 1. StructureStructure of literature review review..

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[21], airport Several [22], electromobility papers focus [ 23on], andtravel AV behavior baseddemand-responsive analysis as the consequence transport of [24 in].formation The relevant provision system [15–19], architecture e.g., how and the operational usage of functionsmobility application are modelled influence with detailed the travel input behavior. and output Customized data groups. and The personalized specific additional functions, functions as well of servicesas dynamic are developed information, in detail. and Questionnairefeedback opportun surveysities regarding are emphasized user expectation regarding have beenthe concept conducted of inmobility [21,22 ],application in order to [14]. elaborate Customized on user-centric functions smartphonerequire input application. of users’ preferences The function manually. of charging By spotcontrast, reservation personalized is introduced functions with apply calculation artificial equation intelligence; in [23 users’]. A concept preferences of smartphone are set automatically, application considering collected, analyzed behavior and habit data. Besides, gamification is also proposed to be embedded when considering how to attract travelers to be more willing to use mobility application Sustainability 2020, 12, 6737 4 of 16 is elaborated comparing several existing applications, where the new functions based on AVs are highlighted [24]. The research problem, methodology, and main ﬁndings of reviewed papers are summarized in Table1. The key points supported in our work are highlighted with a grey background.

Table 1. Summary of reviewed papers.

Research Question Method Main Finding Literature review MaaS is an ongoing topic; crowdsourcing information [2] Summary, comparison of MaaS among travelers are expected to be involved. A framework for Literature analysis, Review MaaS concept; public sector may significantly [3] MaaS policies case study facilitate development of MaaS. Low technology adoption and individual vehicle Barriers and drivers to [4] Survey, cluster analysis ownership feeling are the barriers. adopt MaaS Multimodal recipients are willing to accept MaaS. Barriers to adopt MaaS are analyzed; A decision Preference of mobility [5] Stated survey analysis supporting system is developed based on customer packages willingness to pay. The concept of modal efficiency is illustrated through a [6] Overview of MaaS paper Modelling conceptual framework, a government-contracted model for MaaS is proposed. The comprehensive reviews of the foreseen impacts are Categorization analysis, [8] Review of SAV services categorized into seven groups; An SAV typology typology is presented. SAV services are simulated as the alternative during An integrated PT-AV [9] Agent-based simulation system morning peak hour community transport. The integrated system performs well. Encouraging a consumer to form a psychological The influential factors Survey, structural [12] ownership with an AV may be an effective strategy for to use AVs equation modeling promoting the use of AV. Appropriately encourage morning commute Extended bottleneck the ridesharing behaviors in SAVs and control [11] problem with SAVs model parking capacity may contribute to reduce road congestion. Experimental results show that using integrated transit Optimal integration Linear program, [10] decreases total system travel time, especially with SAVs with PT greedy algorithm small sizes of SAV fleet. Encourage ridesharing with in-advance requests and demand-supply of Systematic approach, [13] PT-SAV system explicit modeling combine fare facilitate service integration as well as sustainable travel. Customization to the user, information and feedback , Travel behavior, [15] Conceptual model commitment and appealing design are essential in mobile application smartphone applications. People’s mobile media usage and intensive phone use Modality cues, social [14] Survey, data analysis interacted as social responses, cues of phone user interface design is important. Ages 16–34 are more likely to use smartphones Mobile application, Discrete choice model, [17] for trip planning. Social networking facilitates travel decision survey the usage of mobility application. Smartphone application usage tends to decrease Application usage, [18] logit model, survey mobility choices vehicle kilometers traveled, new place visits and planned group trips. Barriers exist in smartphone analysis including Smartphone use, [19] Pilot study sampling problems, limitations in big data travel behavior analyses and technological issues. Participants walk more encouraged by the developed Gamification in mobility Survey, an application [20] game-based application , especially those with service interface intensive competitive spirit. Sustainability 2020, 12, 6737 5 of 16

To conclude from the literature, a concept of smartphone application for the MaaS based on AVs is identiﬁed as a research niche. Accordingly, we model and elaborate this concept from the operator’s point of view (back-end information management), and the travelers’ point of view (front-end interface functions).

3. Information System Architecture and Functions A mobile application is supported by the back-end information system and the front-end user interface; namely, user request from the interface is accomplished by the solution provision from information system operation. The integrated mobility services are provided by complex systems, e.g., traffic control and network, management of infrastructure and service; all are interconnected with each other. Since we focus on the information management and the smartphone application, several other sub-systems or system components are not discussed in detail. Accordingly, the following main system components are considered: T: traveler with smartphone acts as the end-user of mobile application. M: MaaS operator based on AVs. The information system and mobile application are operated by M. To: transport service operators or providers. Other service operators are involved as well, e.g., intelligent infrastructure operator, such as smart stop operator; additional data source operator; the food and drink e-sale platform operator. We focus on the information management tasks of transport service operators. AV: autonomous vehicles; they are regarded as the intelligent machines running on the road. A large number of data are generated in a connected transportation environment. The available online big data resource is coming from various sensor devices installed on vehicles and infrastructures, from the remote sensing systems that monitor and supervise the transportation network, from the social networks or smartphones of travelers, as well as from the electronic cash flow transactions in mobility services [25]. The characteristics of big data are to be met in the MaaS based on AVs: volume, variety, velocity, veracity, and value [26]. Although several challenges, like the collection, quality, reliability, soundness, storage, security of data still exist, such amounts of data can be handled using the scalable and online cloud services. For example, data analytics methods are supported by various advanced algorithms: e.g., artificial neural networks algorithm, deep learning algorithm, times series algorithms [27]. As well, the data fusion technology is proposed to fuse data from multiple sensors and human-machine interfaces, to improve the quality of collected data and supplement the deep learning process of the system. In addition, autonomous driving is coming in a promising blueprint. The society is optimistic that the AVs could improve traffic safety by reducing the number of collisions due to errors and fatigue made by human drivers [26,27]. To establish the information system architecture for MaaS based on AVs, especially regarding mobile phone application, the system components have been identified first. M acts as the highest third-party organizational role; it is placed between T and To. This mobility service will be managed by cloud-based solution, the operation of mobile application is assigned to M. A vast amount of data is collected and processed by M, in order to reduce the consumption of data transfer and storage among each component. Two major types of services are provided: large volume transit and small group or individual rapid transit. Application interface is used by T; the so called ‘user experience’ is delivered by them. Conventional vehicles without cognitive ability are simply transportation tools in the mobility system, the drivers’ decision and reaction are more relevant; in this sense, conventional vehicles are not really considered as a system component. Involving AVs in the mobility system, AV is identified as a component between T and To. They are available to ‘sense’ the surrounding environment and make decision supported by technologies. AV is an interactive transfer machine; the vehicle itself is considered as one system component. Thus, one stream is ‘T- M- To’, and the other is ‘T -AV- To’, which are placed on the four sides of a rectangle. These four sides of the rectangle are linked by the flow of information. Sustainability 2020, 12, x FOR PEER REVIEW 6 of 18 algorithm, times series algorithms [27]. As well, the data fusion technology is proposed to fuse data from multiple sensors and human-machine interfaces, to improve the quality of collected data and supplement the deep learning process of the system. In addition, autonomous driving is coming in a promising blueprint. The society is optimistic that the AVs could improve traffic safety by reducing the number of collisions due to errors and fatigue made by human drivers [26,27]. To establish the information system architecture for MaaS based on AVs, especially regarding mobile phone application, the system components have been identified first. M acts as the highest third-party organizational role; it is placed between T and To. This mobility service will be managed by cloud-based solution, the operation of mobile application is assigned to M. A vast amount of data is collected and processed by M, in order to reduce the consumption of data transfer and storage among each component. Two major types of services are provided: large volume transit and small group or individual rapid transit. Application interface is used by T; the so called ‘user experience’ is delivered by them. Conventional vehicles without cognitive ability are simply transportation tools in the mobility system, the drivers’ decision and reaction are more relevant; in this sense, conventional vehicles are not really considered as a system component. Involving AVs in the mobility system, AV is identified as a component between T and To. They are available to ‘sense’ the surrounding environment and make decision supported by technologies. AV is an interactive transfer machine; the vehicle itself is considered as one system component. Thus, one stream is ‘T- M-Sustainability To’, and2020 the, 12 other, 6737 is ‘T -AV- To’, which are placed on the four sides of a rectangle. These6 four of 16 sides of the rectangle are linked by the flow of information. i The back-end information system architecture is modelled, the information function groups i Fc The back-end information system architecture is modelled, the information function groups Fc of of each involved system component (c) and interacted functionsi f i between interacted components each involved system component (c) and interacted functions fic betweenic interacted components (ic) (areic) are presented presented in Figure in Figure2. 2.

1,2,3,4,5 FM

MaaS operator 1,2,3 (AV fleet operator) 1,2,3,4 fMT fToM

Application f 1,2,3,4 1,2,3 TM operation fMTo 1,2,3,4,5 1,2 FT FTo Transport Traveler operator Autonomous or automated Services of large volume shared AVS PT service (SAV) A-PT (A-PT) operator

Application interface SAV 1,2 FAV operator f 1 f 1 AVT AV ToAV

(machine 1 1,2,3 fAVTo fTAV component) Other …

Figure 2. InformationInformation system system architecture architecture..

The function groups F are assigned to each component; it shows that the information activity is majorly performedperformed by by this this component. component. The interactedThe interacted functions functionsf are assigned f are toassigned each two to components, each two components,which indicates which that theindicates detailed that information the detailed tasks information are accomplished tasks byare them. accomplished The direction by isthem. indicated. The directionThe back-end is indicated. subsystem The isback-end operated subsystem and maintained is operated by the and MaaS maintained operator; by thethe dataMaaS source operator; is open the dataand sharable.source is open The users and sharable. of the front-end The users application of the front-end interface application are the travelers. interface are the travelers. Five function groups F are determined for T and M, respectively.respectively. The significantsignificant information interactionsinteractions are are performed performed by by these these two two components components through through entire entire travel. travel. Since Since AVs AVs are are connected connected into the information system, information exchange between AVs and other components are available for M, two function groups F are determined for AV and To. Interacted functions f are assigned on two ‘circles’, inner circle is identified as ‘T M To AV T ‘, the outside circle is identified as → → → → ‘M T AV To M‘. Travel request is announced by T and is responded by M accordingly. → → → → i i 1 2 3 In order to simplify the indication in the figure, Fc and fic are not listed individually as Fc , Fc , Fc ... and 1 2 3 1,2,3, 1,2,3, fic, fic, fic ...; instead the combined solution are presented as Fc ··· and fic ···. AVs are not only a transport tool in MaaS anymore; they ‘participate’ in the travel because of its cognitive ability. From a traveler point of view, their travel movement from departure point A to destination point B is involved in the information system, they not only complete their travel but also act as crowdsourcing information collector to optimize the performance of the mobility system. Travelers, together with intelligent vehicles, provide enormous dynamic data to information system in MaaS based on AVs. The system is optimized bidirectionally; a seamless, efficient, and comfortable travel is to be met by travelers. Pay-as-you-go and monthly mobility plan subscription as fare collection solutions have been introduced in the MaaS. Since travel processes are more advanced and automated in MaaS based on AVs, the ‘recording’ of travel points is significant, e.g., boarding and alighting of each travel leg are essential for the dynamic price accounting in our model. Two types of traveler-vehicle checking are Sustainability 2020, 12, 6737 7 of 16 involved: travelers with service of A-PT and SAVs. First case works as ticketless checking, second case is to open and use the vehicle. Bidirectional recognition is recommended. Dynamic price-based fare collection solution facilitates travelers to pay for ‘what they really used’. Peak and peak-off time travel are to be charged with different prices. A combination of time and distance-based solutions is considered. For example, the time and distance of A-PT use of a traveler is recorded—the travel cost is calculated ‘when’ (peak or peak-off time period) and ‘how far’ (how many bus/metro stops are taken?). For an individual vehicle sharing user, the time usage-based charging is more appropriate, i.e., during which time period and for how long a time is it used? The information function groups regarding each component are summarized in Table2.

Table 2. Function groups of components.

Function Group of the Traveler Function Group of MaaS Operator 1 1 FT Multimodal travel planning request FM Travel plan/route generation for T 2 2 FT Booking/Reservation FM Automated demand-capacity coordination 3 F3 FT Traveler-vehicle identiﬁcation M Ticket completion 4 4 FT Payment FM Travel cost and price calculation 5 5 FT Evaluation FM Feedback handling Function Group of the Vehicle Function Group of Transport Operator 1 1 FAV Traveler-vehicle boarding matching FTo Check of vehicle capacity 2 2 FAV Communication FTo Check of virtual ticket

1 FT,To,M are the function groups in the multimodal travel chain generation process. Travelers announce the travel demand, relevant transport service operators check the available capacity, MaaS operator provide the multimodal travel options. A relevant service is booked by travelers, e.g., vehicle sharing. Demand-capacity is automatedly coordinated and announced by the information system, as every component is connected. Accordingly, the electronic ticket for various modes involved in the travel chain is generated. The travel chain can be interpreted by function groups in the time sequence shown in Figure3. Sustainability 2020, 12, x FOR PEER REVIEW 8 of 18

F 1 F1 F1 F 2 F 2 F3 ( F 2 F 3 F1 ) F2 F4 F 4 F 5 F 5 T To M T M M To , T , AV AV M T T M Figure 3. Travel chain regarding function groups in time sequence. Figure 3. Travel chain regarding function groups in time sequence.

Since the the entire entire travel travel chain chain is is highly highly automated, automated, an andd self-service self-service is isavailable, available, the the entire entire travel travel is tracked,is tracked, but but the the ‘event’ ‘event’ points points are are recorded recorded specifically, specifically, e.g., e.g., boarding/alighting boarding/alighting point. point. The The bracket 22313 1 FFFTo,, T AV  is to present the traveler-vehicle identification, in order to record the boarding process. FTo, FT, FAV is to present the traveler-vehicle identification, in order to record the boarding process. ‘Communication’ hashas a dia ffdifferenterent meaning meaning in the inenvironment the environment of connected of connected AVs, information AVs, information exchange exchangebetween vehicle between and vehicle,vehicle vehicleand vehicle, and infrastructure, vehicle and vehicle infrastructure, and users—such vehicle interactions and users—such optimize the performance of the mobility system. F4 is introduced to indicate4 the total cost of travel regarding interactions optimize the performance of theM mobility system. FM is introduced to indicate the total costthe calculationof travel regarding and payment the calculation process. The and fare payment is automatically process. The calculated; fare is automatically payment is handledcalculated; by 5 MaaS operator. Feedback and its handling F play an essential role5 in a traveler-centric service. payment is handled by MaaS operator. FeedbackT,M and its handling F play an essential role in a The MaaS based on AVs, is an integrated service of ‘services’ connected inTM, a relatively open information traveler-centricsystem—involving service. travelers’ The MaaS recommendations based on AVs, in is service an integrated improvement service is of proposed. ‘services’ connected in a relativelyThe majoropen information information system—involving flows of specific travel travelers’ are to recommendations be presented by thein service interacted improvement functions is proposed. between the components (in Figure4). The major involved components ( csct) in one specific information The major informationj = j =flowsj of specific travel are to be presented by the interacted functions task are shown by fc fcsct fcs ct . between the components (in Figure→ 4). The major involved components (csct) in one specific information task are shown by ffjj f j. cccccst s t

j fc Traveller MaaS operator Transport operator Autonomous Vehicle

1 f journey request 1 T-AV TM fTAV identification 2 fTM booking 2 virtual ticket T fTAV checking f 3 payment TM 3 T-AV 4 fTAV interaction fTM feedback travel options f 1 1 virtual ticket MT provision fMTo checking f 2 virtual ticket 2 T-AV M MT provision fMTo identification 3 complaint f 3 travel cost, fMT handling MTo price forwarding

f 1 current situation f 1 virtual ToM of network ToAV ticket data f 2 current situation To ToM of vehicle 3 recording fToM boarding 4 recording fToM alighting f 1 AV-T 1 AVT identification f AVTo dynamic information AV (cleanness, capacity, battery level, etc)

Legend: Self-management Indirect interaction

Figure 4. Interacted functions between components.

Each information component manages their sub-information system. As the M is introduced, the interaction between To and T are eliminated. Vehicle fleet information is managed by the fleet provider. The information is shared with M and M manages the service; the interactions between AV and M are indirect. The information tasks are assigned to each component pairs, in order to improve the efficiency of information sharing and service management. 3 Furthermore, fMTo is addressed in the case that M handles the calculation of total travel cost. The usage of specific modes is recorded by each To; only the most relevant information is forwarded to the M to calculate the total travel cost. In addition, the paid amount is distributed to each To according to these recording data as well. Sustainability 2020, 12, x FOR PEER REVIEW 8 of 18

F 1 F1 F1 F 2 F 2 F3 ( F 2 F 3 F1 ) F2 F4 F 4 F 5 F 5 T To M T M M To , T , AV AV M T T M Figure 3. Travel chain regarding function groups in time sequence.

Since the entire travel chain is highly automated, and self-service is available, the entire travel is tracked, but the ‘event’ points are recorded specifically, e.g., boarding/alighting point. The bracket 231 FFFTo,, T AV  is to present the traveler-vehicle identification, in order to record the boarding process. ‘Communication’ has a different meaning in the environment of connected AVs, information exchange between vehicle and vehicle, vehicle and infrastructure, vehicle and users—such 4 interactions optimize the performance of the mobility system. FM is introduced to indicate the total cost of travel regarding the calculation and payment process. The fare is automatically calculated; 5 payment is handled by MaaS operator. Feedback and its handling FTM, play an essential role in a traveler-centric service. The MaaS based on AVs, is an integrated service of ‘services’ connected in a relatively open information system—involving travelers’ recommendations in service improvement is proposed. The major information flows of specific travel are to be presented by the interacted functions Sustainabilitybetween2020 the, 12 , 6737components (in Figure 4). The major involved components (csct) in one specific8 of 16 information task are shown by ffjj f j. cccccst s t

j fc Traveller MaaS operator Transport operator Autonomous Vehicle

Legend: Self-management Indirect interaction

FigureFigure 4. 4.Interacted Interacted functions functions between between components components..

EachEach information information component component manages manages theirtheir sub-information system. system. As Asthe theM isM introduced,is introduced, the interactionthe interaction between betweenTo Toand andT areT are eliminated. eliminated. VehicleVehicle fleet fleet information information is managed is managed by the by fleet the fleet provider. The information is shared with M and M manages the service; the interactions between AV provider. The information is shared with M and M manages the service; the interactions between AV and M are indirect. The information tasks are assigned to each component pairs, in order to improve and M are indirect. The information tasks are assigned to each component pairs, in order to improve the efficiency of information sharing and service management. the efficiency of information3 sharing and service management. Furthermore, f is addressed in the case that M handles the calculation of total travel cost. Furthermore, f 3 MisTo addressed in the case that M handles the calculation of total travel cost. The usage of specificMTo modes is recorded by each To; only the most relevant information is forwarded To The usageto the of M specific to calculate modes the is total recorded travel bycost. each In addition,; only thethe mostpaid relevantamount is information distributed isto forwardedeach To to the Maccordingto calculate to these the totalrecording travel data cost. as Inwell. addition, the paid amount is distributed to each To according to these recording data as well.

4. Information Flow Integrated mobility management or control centers are not involved in system components. On the one hand, MaaS operator handles this role efficiently by coordination of dynamic demand and capacity. On the other hand, MaaS operator is already the highest organizational role. Fewer mobility system components may facilitate the operational efficiency and service quality. Information management is regarded as the backbone of this integrated intelligent mobility service; thus input and output data groups are determined as significant elements of information transfer process. The main data groups are summarized and presented in Table3. Static data (s) are rarely modified data; they are used to store basic information and the historical data. The historical data are used as the input of travel behavior and habit analysis by the machine system. Monthly or yearly updating is appropriate. Semi-dynamic data (sd) are changeable and event-based data recording. Updating cycle could be hourly or daily. Several dynamic data (d) are collected as ‘tracking data’ and updated every minute, for example, location and communication data, but major dynamic data are event-based—more frequently the update is required, thus belonging to dynamic data, e.g., data of vehicle condition, task coordination. How do the components interact with each other during travel? What are the information flows between components in a travel process? In order to answer these questions, the input and output data of functions which interact between component pairs are determined and presented according to Sustainability 2020, 12, 6737 9 of 16 the travel phases, e.g., phases of before, during, and after travel. We introduce Figure5 to show one example of a multimodal travel chain indicated with travel phases.

Table 3. Data groups of components.

Static (s) Semi-Dynamic (sd) Dynamic (d) D1 data of credit card D1 current position D1 basic data of user account T,Sd T,d T,S D2 customized D2 personalized T (e.g., name, gender, birthdate) T,Sd T,d D2 historical travel data preference setting recommendation T,S D3 ticketing data D3 travel tracking data T,Sd T,d 1 D1 historical travel data D ticket/identification data M,S D1 data of mobility package M,d (e.g., origin-destination, M,Sd D2 matched travel data D2 booking data M,d M time of matched travel) M,Sd (e.g., T-AV data) 2 (e.g., position and time of 3 DM,S feedback data D travel options matched travel) M,d D3 payment transfer D4 M,S M,d calculated price D1 occupancy of vehicle D1 basic transport To,d D1 data of transport To,Sd To,S D2 service price data To d vehicle position operators (e.g., name, fleet data) , D2 operator involved in D3 vehicle condition To D2 transport network data To,Sd To,d To,S (e.g., cleanness, battery) (e.g., station, line, route) specific request (e.g., the offered vehicle, D4 ticket/identification data D3 To,d To,S historical data fleet information) D5 network condition To,d D1 ticket/identification data D1 basic data of vehicle D1 vehicle condition AV,d AV,S AV,Sd D2 communication data AV (e.g., capacity, brand, color) (capacity, battery level, cleanness) AV,d 2 2 (e.g., from connected Sustainability 2020D , 12historical, x FOR PEER data REVIEW D ticketing data 10 of 18 AV,S AV,Sd vehicles, travelers)

Time Sequence

1 1 1 2 2 3 2 3 1 2 4 4 5 5 FT FTo FM FT FM FM ( FTo , FT , FAV ) FAV FM FT FT FM

Journey planning Booking and Vehicle-seat Public Vehicle Public Walking Payment Feedback ticketing small group transport sharing transport or bike- sharing (bus) (metro) sharing

Before During After

Legend:

i F function i of recording point travel tracking phase of travel c component c (event-based) Figure 5. AnAn example example of of multimodal multimodal travel chain indicating travel phases.

The information flow ﬂow is generated by the involved functions in the time sequence; input and output data keep the information fl ﬂowow in real-time. The information process of ‘before the travel’ is presented in Figure6 6.. Travelers announce their travel demand. By applying the information of the updated current situation of network and vehicles, available travel chain options are provided by the MaaS operator. 1 1 3 2 1 2 1 D 1 3 1 4 1 D AV, s DTo, d D D DM ,d DTo, sd D D D D The provisionTs, of combination options is theTs, pivotMs, function in ‘beforeTs, M ,d the travel’Ts, To phase., d D InTo, sd order

2 1 1 to provide personalized5 optimalD combination2 solutions,2 D historical1 1 travel1 data of2 travelers and2 their DTsd, DTo, d To, d DTsd, DM ,s DTo, s AV, s DM ,sd DAV, s DM ,sd D relevant recording, e.g., feedback, the manual input of customized preference setting regardingTo, specificsd 2 2 2 2 1 3 2 2 1 1 5 D D DTo, d D D D D D D D travel, theTd personalized, To, s preference captures,Td, e.g.,M the,sd To automated, s AV, s travelM ,sd AV habits, sd analysisM ,d results,DTo, d are the major input data groups. After a traveler selects an option, then booking is confirmed, and virtual f 1 f 1 , f 2 f 1 f 2 2 1 ticket orTM identificationToM code areToM forwardedMT to traveler and vehicle.TM fMT fToAV

3 2 2 3 The information2 process interpretation of ‘during the travel’ phase2 is presented1 in Figure1 7. D D DAV, s D D D Tsd, To, s Ts, M ,d Msd, DTs, DMsd,

2 3 4 D 1 D D 2 D2 Ts, DM ,s To, s M ,d DM ,sd AV, sd

1 1 D D 2 3 M ,s AV, s DAV, sd DTsd,

Legend: Interacted function Data group Input Output Time sequence

Figure 6. Information flow of ‘before the travel’ phase.

Travelers announce their travel demand. By applying the information of the updated current situation of network and vehicles, available travel chain options are provided by the MaaS operator. The provision of combination options is the pivot function in ‘before the travel’ phase. In order to provide personalized optimal combination solutions, historical travel data of travelers and their relevant recording, e.g., feedback, the manual input of customized preference setting regarding specific travel, the personalized preference captures, e.g., the automated travel habits analysis results, are the major input data groups. After a traveler selects an option, then booking is confirmed, and virtual ticket or identification code are forwarded to traveler and vehicle. The information process interpretation of ‘during the travel’ phase is presented in Figure 7. Sustainability 2020, 12, x FOR PEER REVIEW 10 of 18

Time Sequence

1 1 1 2 2 3 2 3 1 2 4 4 5 5 FT FTo FM FT FM FM ( FTo , FT , FAV ) FAV FM FT FT FM

Journey planning Booking and Vehicle-seat Public Vehicle Public Walking Payment Feedback ticketing small group transport sharing transport or bike- sharing (bus) (metro) sharing

Before During After

Legend:

i F function i of recording point travel tracking phase of travel c component c (event-based) Figure 5. An example of multimodal travel chain indicating travel phases.

The information flow is generated by the involved functions in the time sequence; input and output data keep the information flow in real-time. The information process of ‘before the travel’ is Sustainability 2020, 12, 6737 10 of 16 presented in Figure 6.

1 3 2 1 2 1 1 1 3 1 4 1 D DAV, s DTo, d D D D DTo, sd D D Ts, Ts, Ms, M ,d DTs, M ,d DTs, To, d DTo, sd

2 1 2 2 1 1 D D5 D D D D D D1 D1 D2 2 Tsd, To, d To, d Tsd, M ,s To, s AV, s M ,sd AV, s M ,sd DTo, sd

2 2 2 2 1 3 2 2 1 1 5 D D DTo, d D D D D D D D Td, To, s Td, M ,sd To, s AV, s M ,sd AV, sd M ,d DTo, d f 1 f 1 , f 2 f 1 f 2 2 1 TM ToM ToM MT TM fMT fToAV

3 2 2 3 2 2 1 1 D D DAV, s D D D Tsd, To, s Ts, M ,d Msd, DTs, DMsd,

2 3 4 D 1 D D 2 D2 Ts, DM ,s To, s M ,d DM ,sd AV, sd

1 1 D D 2 3 M ,s AV, s DAV, sd DTsd,

Legend: Interacted function Data group Input Output Time sequence

Sustainability 2020, 12, x FOR PEERFigure REVIEW 6. Information ﬂow of ‘before the travel’ phase. 11 of 18 Figure 6. Information flow of ‘before the travel’ phase.

Travelers announce1 2 their3 travel3 demand. By1 applying3 the information1 of 1the 2updated1 current2 D D 1 3 1 3 D AV, sd AV, d DTsd, DTsd, DAV, d DTsd, DAV, d DTsd, DAV, s DTsd, D DTs, AV, d DTs, DTo, d situation of network and vehicles, available travel chain options are providedTs, by the MaaS operator. D2 D1 D1 D1 1 D2 1 3 1 The provision of Tocombination, sd M ,d optionsM ,d is theM ,dpivot fuDTdnction, AV, sd in ‘beforeD theTd, travel’DTd, phase.D InTd, order to

provide personalized3 optimal4 combination4 4 solutions,D1 historical1 travel2 data of2 travelers3 and their DTo, d DTo, d DTo, d DTo, d Msd, DAV, d DTo, d DTo, d DTd, 1 relevantfToM recording, e.g., feedback, the manual input of customized preference setting regarding specific[ travel, 1the personalized1 preference2 1 captures,2 e.g., fthe1 automated) 3 travel habits3 analysis4 results, , fAVTo ] ( fMTo , fMTo , fTAV , fTAV , AVT fToM fTAV fToM are the 2major input data groups. After a traveler selects an option, then booking is confirmed, and f 2 ToM D3 D1 D1 D2 D2 D1 D2 D1 D D1 virtual ticket or identificationTo, d Td, code Tdare, forwardedTo, d M ,d to travelerM ,sd AVand, s vehicle.M ,s Ts, M ,s

The informationD2 process3 interpretation3 Dof2 ‘durinDg3 the travel’D2 phaseD 2is presentedD2 in Figure 7. To, sd DTd, DTd, AV, s Td, To, sd M ,d AV, s

2 D2 2 DM ,d M ,d DM ,d

Legend:

Interacted Time sequence [] Re-check process () Same time point function Data group Input Output

FigureFigure 7. 7.InformationInformation flow ﬂow of of‘during ‘during the the travel’ travel’ phase. phase.

BeforeBefore the the travel started,started, thethe real-time real-time information information of transportof transport network network and vehicles and vehicles was updated; was updated;in case needed, in case theneeded, travel the chain travel route chain could route be re-planned could be accordingre-planned to updatedaccording data, to updated e.g., in an data, emergency e.g., inor an disruption emergency situation. or disruption The function situation. of the The traveler function ticket ofonboard the traveler checking ticket or onboard traveler-vehicle checking (T-AV) or traveler-vehicleidentification works (T-AV) actively identification as driver works is eliminated. actively They as driver are the is essentialeliminated. tracking They and are farethe calculationessential trackingpoints. and After fare ticket calculation checking points. or bidirectional After ticket ch identification,ecking or bidirectional the boarding identification, is recorded. the Duringboarding the istravel, recorded. smartphone During the application travel, smartphone is used by application traveler to ‘communicate’is used by traveler with to surrounding ‘communicate’ connected with surroundingvehicles, or travelerconnected interacts vehicles, with or vehicletraveler by interact the touchs with screen vehicle on vehicles. by the touch ‘Connected’ screen AVson vehicles. have two ‘Connected’meaning in AVs this have sense, two the meaning small vehicle in this body sense, can the connect small withvehicle each body other, can or connect the AVs with are connectedeach other, in orinformation the AVs are system, connected information in information sharing system, and interaction information are available.sharing and The interaction latter is considered are available. in our Thework. latter Travelers is considered accomplish in our their work. travel Travelers in a more accomplish self-service their type travel by in themselves. a more self-service When the type traveler by themselves.leaves the vehicle,When the the traveler alighting leaves point the is recordedvehicle, the as well.alighting point is recorded as well. TheThe information information process process of of ‘after ‘after the the tr travel’avel’ phase phase is is presented presented in in Figure Figure 8.8 .

1 D2 D1 D1 1 D1 1 DTs, To, sd Tsd, To, sd DTs, AV, S DTs,

3 3 D2 D2 DTd, DTd, Md, To, sd

4 4 D2 1 DM ,d DM ,d To, sd DAV, s

f 3 3 4 3 MTo fTM fTM fMT

1 4 2 2 DTsd, DMd, DM ,s DM ,s

3 D3 D 2 To, s M ,s DTs,

Legend: Interacted Data group Input Output funtion Time sequence Figure 8. Information flow of ‘after the travel’ phase.

After the travel, the travel cost calculation, payment, feedback and its handling are general procedures. Dynamic price is available in MaaS based on AVs; travelers pay exactly what they used. For the monthly mobility plan, the approach of MaaS is that MaaS operator provides the mobility plan options, and travelers select one. In the case of MaaS based on AVs, the monthly plan should be tailored for the specific traveler, namely, according to the commuting travelers’ real use, the operator of MaaS based on AVs is responsible to price appropriately for the personalized monthly plan. Instead of providing the stable plans, this operator just calculates the price for the traveler customized Sustainability 2020, 12, x FOR PEER REVIEW 11 of 18

D1 D2 D3 3 1 3 D1 3 1 3 1 1 D2 1 2 AV, sd AV, d Tsd, DTsd, DAV, d DTsd, AV, d DTsd, DAV, s DTsd, DTs, DTs, AV, d DTs, DTo, d

D2 1 1 1 1 D2 1 3 1 To, sd DM ,d DM ,d DM ,d DTd, AV, sd DTd, DTd, DTd,

3 4 4 4 D1 1 2 2 3 DTo, d DTo, d DTo, d DTo, d Msd, DAV, d DTo, d DTo, d DTd, 1 fToM [ 1 1 2 1 2 f 1 ) 3 3 4 , fAVTo ] ( fMTo , fMTo , fTAV , fTAV , AVT fToM fTAV fToM 2 f 2 ToM D3 1 1 2 2 D1 D2 1 D1 To, d DTd, DTd, DTo, d DM ,d M ,sd AV, s DM ,s DTs, M ,s

D2 3 3 D2 D3 D2 D2 D2 To, sd DTd, DTd, AV, s Td, To, sd M ,d AV, s

2 D2 2 DM ,d M ,d DM ,d

Legend:

Interacted Time sequence [] Re-check process () Same time point function Data group Input Output

Figure 7. Information flow of ‘during the travel’ phase.

Before the travel started, the real-time information of transport network and vehicles was updated; in case needed, the travel chain route could be re-planned according to updated data, e.g., in an emergency or disruption situation. The function of the traveler ticket onboard checking or traveler-vehicle (T-AV) identification works actively as driver is eliminated. They are the essential tracking and fare calculation points. After ticket checking or bidirectional identification, the boarding is recorded. During the travel, smartphone application is used by traveler to ‘communicate’ with surrounding connected vehicles, or traveler interacts with vehicle by the touch screen on vehicles. ‘Connected’ AVs have two meaning in this sense, the small vehicle body can connect with each other, or the AVs are connected in information system, information sharing and interaction are available. The latter is considered in our work. Travelers accomplish their travel in a more self-service type by Sustainabilitythemselves.2020 When, 12, 6737 the traveler leaves the vehicle, the alighting point is recorded as well. 11 of 16 The information process of ‘after the travel’ phase is presented in Figure 8.

1 D2 D1 D1 1 D1 1 DTs, To, sd Tsd, To, sd DTs, AV, S DTs,

3 3 D2 D2 DTd, DTd, Md, To, sd

4 4 D2 1 DM ,d DM ,d To, sd DAV, s

f 3 3 4 3 MTo fTM fTM fMT

1 4 2 2 DTsd, DMd, DM ,s DM ,s

3 D3 D 2 To, s M ,s DTs,

Legend: Interacted Data group Input Output funtion Time sequence FigureFigure 8. 8.Information Information flow ﬂow of of ‘after ‘after the the travel’ travel’ phase. phase.

AfterAfter the the travel, travel, the the traveltravel costcost calculation,calculation, payment, feedback feedback and and its its handling handling are are general general procedures.procedures. Dynamic Dynamic price price is is availableavailable in MaaS based based on on AVs; AVs; travelers travelers pay pay exactly exactly what what they they used. used. ForFor the the monthly monthly mobility mobility plan, plan, thethe approachapproach of MaaS is is that that MaaS MaaS operator operator provides provides the the mobility mobility planplan options, options, and and travelers travelers select select one. one. InIn thethe case of MaaS MaaS based based on on AVs, AVs, the the monthly monthly plan plan should should be be tailoredtailored for for the the specific specific traveler, traveler, namely, namely, according according to to the the commuting commuting travelers’ travelers’ realreal use,use, thethe operator of of MaaS based on AVs is responsible to price appropriately for the personalized monthly plan. MaaS based on AVs is responsible to price appropriately for the personalized monthly plan. Instead of Instead of providing the stable plans, this operator just calculates the price for the traveler customized providing the stable plans, this operator just calculates the price for the traveler customized choice. For the pay-as-you-go tariff type, the payment process is required after each travel. ‘Traveler management’ is significant in the traveler-centric approach, operator contact with their travelers and build the ‘service loyalty’. Thus, functions of feedback from travelers and its appropriate, efficiency handling enhance the service quality. Operator should really care about travelers’ involvement.

5. Interface Functions of Smartphone Application The functions of back-end mobile application operation are activated according to functions of interface responded to by travelers. The application interface functions are introduced in this section; the correspondences between back and front -end functions are modelled as well. Interface functions are defined as the functions embedded or displayed on an interface, travelers are available to manage input and receive output of functions, e.g., touch screen to make choice, voice commands, read messages. The ‘Whim’ is identified as the benchmarking application of MaaS. We introduce the interface functions of application for MaaS based on AVs by comparison with Whim’s. The MaaS Global was established in 2016 in Finland, and accordingly the smartphone application ‘Whim’ was introduced. Together with the Ubigo project of Sweden, Whim and Ubigo are recognized as the first successful MaaS trials [28]. The monthly mobility plan subscription solutions were introduced with the ‘born’ of Whim. The private company MaaS global worked well as the third party MaaS operator; its operational area has been extended to the West Midlands, Antwerp, Vienna, Tokyo, and Singapore. The services of urban PT, taxi, bike/car/e-scooter sharing, car-rental, and train are available to be used with the ‘Whim’ application. Application functions of travel planning, mapping, booking, payment, and ticketing are available. Manually, customization settings are provided, and value-added functions such as saved favorites and service alters are involved as well. Pay-as-you-go and three types of monthly subscription plans are introduced as the tariff structure. Compared with the ‘Whim’, the smartphone application concept is envisaged and introduced for the MaaS based on AVs regarding the available interface functions in Table4. Furthermore, Bi indicates basic a/b/c setting function. In addition, Ji indicate the function i of before/during/after (a/b/c) travel phase. Sustainability 2020, 12, 6737 12 of 16

Table 4. Functions on interface compared with the benchmarking Whim.

Notation Function Detail Whim New B Operation area chosen global basic 1 B2 Language option local language; selectable a J1 Journey planning multimodal a J2 Booking public transport, SAV, seat a J3 Ticketing for boarding, electronic Before travel a J4 Service alterations current situation a J5 Customization setting preferences a J6 Personalization Recommendation mode, route, seat position a J7 Vehicle condition battery states, cleanness, a J8 Travel pattern and habits statistical analysis b J1 Ticket validation boarding identification b J2 Mapping/navigation between public and other modes; in facilities b Boarding supporting J3 for disabilities, elders, children, etc. Jb Baggage reminder before alighting During travel 4 b J5 Entertainment e.g., games on application b Availability to communicate with surrounding vehicles J6 connected vehicle environment b Emergency situation J7 detection, reminder, call b J8 Voice communication command with vehicle b Crowdsourcing opportunity J9 available on the map similar like the bus (SAV) b Charging point reservation J10 instant booking c J1 Feedback in time crowdsourcing purpose c J2 Fellow passenger rating group shared, small sized AV c J3 Lost and found one specific function After travel c J4 Additional information and supplementary service e.g., discounts with food/drink purchase c J5 CO2 consumption report motivation purpose c J6 Energy consuming report motivation purpose c J7 Satisfaction investigation long-term users c J8 Statistical data reports monthly, quarterly, yearly New functions are identified from the mobility service point of view. Functions in bold letters are already embedded in several existing MaaS applications, but output of functions do not fully fulfill the aim we mentioned in application of the MaaS based on AVs. Sustainability 2020, 12, 6737 13 of 16

‘Whim’ is already recognized as the top MaaS application and continuously under further implementation [29]. However, compared with the concept of an ‘ideal’ MaaS application, several development aspects and functions are to be introduced. Multimodal options are available with Whim, but ‘seamless’ or ‘one-stop-shop’ service experience is not fully available. For example, if the planned travel chain contains the service of car-sharing, then travelers reserve cars separately. In the most extreme case, if no vehicle is available, the ‘help center’ of Whim recommends that the traveler orders the car-sharing service with an additional company on their own, and ‘Whim’ will equally compensate the cost later with invoice certification (https://helpcenter.whimapp.com/hc/en-us/articles/360024480 233-Whim-Weekend#h_f1c592ad-470d-48b1-9132-5ea44e645902). Such a situation often happens at weekends. The separated reservation announcement is needed in the taxi service as well. Moreover, several transitional modes, e.g., ridesharing, ride-sourcing, chauffer service, are not involved because of the inconvenience to manage the private drivers. However, the situation is improved with the service of MaaS based on AVs. Basic information of vehicles is widely available in existing applications, such as brand, capacity, and pictures of vehicles are shown on the application, but dynamic information of vehicles are not Sustainability 2020, 12, x FOR PEER REVIEW 14 of 18 available yet. For example, vehicles of SAV services are major electric vehicles, the real-time data of batteryavailable level yet. are bothFor example, relevant vehicles for operator of SAV and services traveler, are themajor vehicle electric is chargedvehicles, inthe advance real-time by data operator of or duringbattery thelevel travel are both by travelers.relevant for Thus, operator the and dynamic traveler, battery the vehicle level informationis charged in advance is available by operator in the new application.or during Along the travel with by artificial travelers. intelligence-based Thus, the dynamic personalization battery level information analysis, travelis available pattern in the and new habits of travelersapplication. are deeplyAlong investigatedwith artificial by intelligence-based MaaS operator. Travelerspersonalization are informed analysis, about travel their pattern travel and habits andhabits are possible of travelers to shift are todeeply a sustainable investigated mobility by MaaS pattern, operator. e.g., Travelers CO2-central are informed mobility about with walkingtheir andtravel cycling habits more. and Cyclingare possible routes to shift and to infrastructure a sustainable mobility are displayed pattern, e.g., in the CO new2-central application mobility with as well. Severalwalking direct and supports cycling more. are recommended Cycling routes for and travelers infrastructure with disabilities, are displayed such in the as voice-embeddednew application as GPS well. Several direct supports are recommended for travelers with disabilities, such as voice- guiding to find the vehicle, as special vehicles are not needed for blind people. A traveler-oriented embedded GPS guiding to find the vehicle, as special vehicles are not needed for blind people. A service put the individuals in the center; such a baggage rechecking reminder before alighting is traveler-oriented service put the individuals in the center; such a baggage rechecking reminder before highly proposed. Seat reservation is available in a short distance travel, in order to provide the alighting is highly proposed. Seat reservation is available in a short distance travel, in order to personalizedprovide the service. personalized service. TheThe connected connected vehicle vehicle environment environment isis expectedexpected in in the the future, future, functions functions of ofinformation information ‘communication’‘communication’ between between connected connected vehicles vehicles andand surroundingsurrounding environments environments are are identified identified as novel as novel functions,functions, travelers travelers and and vehicles vehicles are are active active information information components. ForFor the the small small group group ride-sharing ride-sharing service,service, opportunitiesopportunities to to rate rate or or provide provide feedback feedback of fellow of fellow passengerspassengers are are necessary, necessary, in in order order to to enhance enhance serviceservice quality and and improve improve the the comfort comfort of ofindividual individual traveltravel experience. experience. On On the the assumption assumption that that individualsindividuals concern concern travel travel environment environment more more in the in thefuture, future, suchsuch energy energy and and emission emission report report analyses analyses facilitatefacilitate travelers to to turn turn to to more more sustainable sustainable and and green green mobility.mobility. From From the the traveler-centric traveler-centric point point ofof view,view, travelertraveler satisfaction satisfaction analysis analysis and and report report function function attractattract travelers travelers to use to ause service a service more. more. The feedbackThe feedba fromck from the operator the operator works works as a bidirectional as a bidirectional response, notresponse, as before, not as only as before, travelers as only provide travelers their feedback.provide their The feedback. aim is to The attract aim travelers is to attract to ‘wish’ travelers to use to the ‘wish’ to use the service of MaaS based on AVs, not only because they ‘have to’ choose it as they need service of MaaS based on AVs, not only because they ‘have to’ choose it as they need to be transported. to be transported. The correspondences between back- and front-end functions are modelled with Figure9. The correspondences between back- and front-end functions are modelled with Figure 9.

f 2 1 2 1 MTo fToM fToM fAVTo f1 4 TAV fToM

1 1 2 1 2 2 1 1 2 1 3 3 3 3 4 3 fTM fToM fToM fMT fTM fMT fToAV fMTo fTAV fAVT fToM fTAV fMTo fTM fTM fMT

1 1 1 2 2 3 2 3 1 2 4 4 5 5 FT FTo FM FT FM FM ( FTo , FT , FAV ) FAV FM FT FT FM B b 1 J J a J a J a J a J a J b J b J b 4 J c J c J a 7 2 3 1 4 1 3 4 1 2 1,5,6,8 J b J c a a a a a 5,6,7,8,9,10 3,4,5,6,7,8 B2 J1 J 4 J6 J7 J7

Legend: Time sequence Relation between interacted functions Relation between interface functions Interface function Preliminary setting and main function groups and main function groups FigureFigure 9. Correspondences9. Correspondences between between front-endfront-end and ba back-endck-end functions functions inin time time sequence. sequence.

Taking data flows into account, the information flow between back-end and front-end functions are determined in time sequence. The interface functions are available on the application; the functionalities are realized by touching the screen from users’ operation. Travel demand is announced by travelers; input data is generated from several components. On the surface, the travel is guided or initiated at each step by the operation of front-end functions from travelers; facing the truth, the route generation and travel tracking such core functions are accomplished by the operation of back-end functions from MaaS operator. The active response between front- and back-end functions, namely the information flow, guide the traveler to accomplish the self-travel. Since we discuss and focus on grey background new functions, the identified input and output data groups are assigned to the new functions too, which are summarized in Table 5.

Table 5. Input and output data groups of new functions.

New Input Data Groups Output Data Groups Function Sustainability 2020, 12, 6737 14 of 16

Taking data flows into account, the information flow between back-end and front-end functions are determined in time sequence. The interface functions are available on the application; the functionalities are realized by touching the screen from users’ operation. Travel demand is announced by travelers; input data is generated from several components. On the surface, the travel is guided or initiated at each step by the operation of front-end functions from travelers; facing the truth, the route generation and travel tracking such core functions are accomplished by the operation of back-end functions from MaaS operator. The active response between front- and back-end functions, namely the information flow, guide the traveler to accomplish the self-travel. Since we discuss and focus on grey background new functions, the identified input and output data groups are assigned to the new functions too, which are summarized in Table5.

Table 5. Input and output data groups of new functions.

Input Data Groups New Function Output Data Groups D1 , D2 , D1 a D2 AV,S AV,S AV,Sd J7 AV,S D1 , D2 , D2 , D2 , D3 a D2 , D2 T,S T,S T,Sd T,d T,d J8 T,S T,d D3 , D1 , D2 , D2 , D4 , D1 , D2 , D1 b D1 , D4 , D2 , D3 , D1 , D3 , D2 T,Sd M,Sd To,Sd To,d To,d AV,Sd AV,Sd AV,d J3 AV,d To,d M,d T,d M,S To,S AV,S D1 , D3 , D2 b D3 , D2 T,S T,d AV,d J4 T,d AV,d D2 , D2 , D2 b D2 , D2 , D2 T,Sd T,d AV,d J5 T,S AV,S T,S D2 b D2 , D2 AV,d J6 AV,d AV,S D1 , D1 , D3 , D2 , D3 , D2 b D2 , D2 , D3 , D2 T,S T,d T,d To,d To,d AV,d J7 AV,d AV,S To,S T,S D1 , D3 , D2 b D2 T,d T,d AV,d J8 T,S D1 , D2 , D3 b D3 , D5 , D2 T,d T,d T,d J9 M,d To,d AV,d D1 , D3 , D1 , D1 b D2 , D2 T,S T,d T,d AV,Sd J10 AV,S T,S D1 , D2 , D3 , D2 c D2 , D2 , D3 , D2 T,S T,S M,d To,Sd J1 M,S T,S To,S AV,S D1 , D2 , D2 c D2 , D2 T,S T,S M,d J2 T,S M,S D1 , D2 c D2 , D2 T,S M,d J3 T,S M,S D1 D2 D1 D2 c D2 , D2 T,S, T,S, M,S, M,S J7 T,d T,S D1 D2 D1 D2 c D2 T,S, T,S, M,S, M,S J8 T,S

6. Conclusions The MaaS is proposed to facilitate the service integration and sustainable mobility. AVs as intelligent machines are incorporated into MaaS, we elaborated the concept ‘MaaS based on AVs’ in our work focusing on mobile application. System engineering top-down and process-oriented approaches were applied. The main system components were determined, and the main function groups of components were introduced. As information management is the backbone of this service, the back-end information flows of application were identified and presented, considering input and output data groups in interacted functions for each travel phase (before, during, after). In addition, the front-end application interface functions were devised considering the existing MaaS application. The correspondences between back and front -end functions were also modelled. We considered both the MaaS operator’s and traveler’s aspects. The main contributions are: information system architecture model and identified functions, • operational and information flow model, • model of correspondences between back-end and front-end functions. • We have found that: as the MaaS based on AVs is a highly automated self-service, recording event-based points is • significant for travel fare calculation, e.g., boarding and alighting, feedback management is the pivot function. Travel habits and behavior of travelers are more • relevant for operator to analysis service performance and user satisfaction, Sustainability 2020, 12, 6737 15 of 16

new traveler-centric functions are to be developed, e.g., baggage reminder function, fellow • passengers rating.

A lesson learnt in this study was that the available literature on our topics is rather limited. Many researchers worked on travel behavior analysis of smartphone application aiding mobility, however, very few works with systematic approaches revealed the information management of the application. Our further research direction is to extend the topic on gamification inserted into mobile application, in order to investigate the factors affecting the change of travel behavior. Several gamification-oriented mobility approaches exist in either mobile application or real-life practice, and the following research questions have been identified. What are the major influence factors regarding gamification aiding mobility? How do travelers consider points, badges, leadership in gamification embedded application? How can social networks aid gamification in mobility services? An international online questionnaire survey will be conducted, and statistical analysis results will be addressed to answer these questions. The research aim is to support the software development for such gamification-oriented applications, considering the MaaS based on AVs service. MaaS is not only a concept that is relevant for passenger transport, the freight transport is to be incorporated as well. Our other further research direction is to elaborate a parcel delivery service concept embedding in MaaS, based on AVs framework. Taking this Coronavirus-19 epidemiological situation into consideration, contactless delivery may work appropriately, not only in emergency situation, but also in case of one traveler sharing the vehicle space with one ‘the same way’ parcel, applying this traveler-parcel combination transport form to balance empty vehicle redistribution tasks, in order to optimize the resource allocation of society.

Author Contributions: Conceptualization, Y.H. and C.C.; methodology, Y.H. and C.C.; validation, Y.H. and C.C.; writing—original draft preparation, Y.H.; writing—review and editing, Y.H. and C.C.; supervision, C.C. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Acknowledgments: The research reported in this paper was supported by the EFOP-3.6.3-VEKOP-16-2017-00001: Talent management in autonomous vehicle control technologies—The Project is supported by the Hungarian Government and co-financed by the European Social Fund. The research reported in this paper and carried out at the Budapest University of Technology and Economics was supported by the “TKP2020, Institutional Excellence Program” of the National Research Development and Innovation Office in the field of Artificial Intelligence (BME IE-MI-FM TKP2020). Conflicts of Interest: The authors declare no conflict of interest.

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