Experiments on Autonomous and Automated Driving: an Overview 2015
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Innovation in Ecosystem Business Models: an Application to Maas and Autonomous Vehicles in Urban Mobility System
Innovation in ecosystem business models : An application to MaaS and Autonomous vehicles in urban mobility system Rodrigo Gandia To cite this version: Rodrigo Gandia. Innovation in ecosystem business models : An application to MaaS and Autonomous vehicles in urban mobility system. Economics and Finance. Université Paris-Saclay; University of Lavras, UFLA (Brésil), 2020. English. NNT : 2020UPASC018. tel-02895349 HAL Id: tel-02895349 https://tel.archives-ouvertes.fr/tel-02895349 Submitted on 9 Jul 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Innovation in Ecosystem Business Models: An Application to MaaS and Autonomous Vehicles in Urban Mobility System Thèse de doctorat de l'université Paris-Saclay École doctorale n° 573 Interfaces : approches interdisciplinaires, fon- dements, applications et innovation (Interfaces) Spécialité de doctorat : Ingénierie des systèmes complexes Unité de recherche : Université Paris-Saclay, CentraleSupélec, Laboratoire Genie Industriel, 91190, Gif-sur-Yvette, France. Référent : CentraleSupélec Thèse présentée et -
Autonomous Vehicle, Sensing and Communication Survey 1 Introduction
Autonomous Vehicle, Sensing and Communication Survey Edited and submitted by Shraga Shoval Prepared by Shlomi Hacohen and Oded Medina Department of Mechanical Engineering, Ariel University, Ariel, Israel. August 2020 Abstract Autonomous vehicles introduce dramatic changes to the way in which we travel. This technology has the potential to impact the transportation across a wide array of categories including safety, congestion, and travel behavior. In this report we review the main issues involved in autonomous driving as discussed in the literature and shed light on topics that we believe require further development. 1 Introduction The challenges in autonomous driving require a combination of many capabilities, among them: localization, motion planning, vehicle’s systems control (steering, acceleration/deceleration, signaling, etc.), road perception, prediction of other road-users behavior, awareness of dangers, etc. These capabilities have a various level of importance for various levels of driving automation. Even though the first autonomous vehicle (AV) was experimented in 1926 [104], a real-modern autonomous vehicle was first presented in 1986 by a team from Carnegie Mellon University [58]. Since 2010, many major automotive manufacturers, such as GM, Mercedes Benz, Ford, Toyota, and many more are developing AVs [90]. A demonstration of AV equipped with numerous sensors and communication systems was presented by Toyota in 2013 [10]. In 2016, Google’s AV has passed over one million kilometers. These events present a glimpse to the landmarks in the development of AV that, due to the complexity of the task, progresses slowly with considerable amount of attention to safety and reliability. AVs need a large amount of data for reliable decision making. -
How to Make Use of Data in a Car: Connected Cars, Payment Tech, Analytics, and Other Opportunities
HOW TO MAKE USE OF DATA IN A CAR: CONNECTED CARS, PAYMENT TECH, ANALYTICS, AND OTHER OPPORTUNITIES Andrew Ray David Monteiro May 13, 2020 Tess Blair @MLGlobalTech © 2018 Morgan, Lewis & Bockius LLP Morgan Lewis Automotive Hour Webinar Series Series of automotive industry focused webinars led by members of the Morgan Lewis global automotive team. The 10-part 2020 program is designed to provide a comprehensive overview on a variety of topics related to clients in the automotive industry. Upcoming sessions: JUNE 10 | Employee Benefits in the Automotive and Mobility Context JULY 15 | Working with, or Operating, a Tech Startup in the Automotive and Mobility Sectors AUGUST 5 | Electric Vehicles and Their Energy Impact SEPTEMBER 23 | Autonomous Vehicles Regulation and State Developments NOVEMBER 11 | Environmental Developments and Challenges in the Automotive Space DECEMBER 9 | Capitalizing on Emerging Technology in the Automotive and Mobility Space 2 Table of Contents Section 01 – Introductions Section 02 – Market Overview Section 03 – Data Acquisition and Use Section 04 – Regulatory and Enforcement Risks 3 SECTION 01 INTRODUCTIONS Today’s Presenters Andrew Ray David Monteiro Tess Blair Washington, DC Dallas Philadelphia Tel +1.202.373.6585 Tel +1.214.466.4133 Tel +1.215.963.5161 [email protected] [email protected] [email protected] 5 SECTION 02 MARKET OVERVIEW 7 Market Overview • 135 million Americans spend 51 minutes on average commuting to work five days a week. • Connected commerce experience represents a $230 billion market. • Since 2010, investors have poured $20.8 billion into connectivity and infotainment technologies. Source: “2019 Digital Drive Report,” P97 / PYMNTS.com; “Start me up: Where mobility investments are going,” McKinsey & Company. -
Connected Car
Connected Car [email protected] 1 Confidential – © 2019 Oracle Internal/Restricted/Highly Restricted I've always been asked, „What is my favorite car?” and I've always said „The next one”. Carroll Shelby Source: Wikipedia 2 Confidential – © 2019 Oracle Internal/Restricted/Highly Restricted Connected Car or Autonomous Car Connected vehicles can exchange information wirelessly with other vehicles and infrastructure, but also with the vehicle manufacture or third-party service providers. Automated vehicles, on the other hand, are vehicles in which at least some aspects of safety- critical control functions occur without direct driver input. 3 Confidential – © 2019 Oracle Internal/Restricted/Highly Restricted The Race is On to Capture In-Vehicle Commerce By 2020, there will be 250 Million connected vehicles on the road globally Gartner & Connected Vehicle Trade Association 82% of new cars will be connected to Internet in 2021 Business Insider Connected car commerce will zoom to $265 billion by 2023 Juniper Research Automakers align with tech firms Voice technology will prevail Source: Business Insider 4 Confidential – © 2019 Oracle Internal/Restricted/Highly Restricted Car Data Facts • What are the risks of allowing direct access to car data? • How do vehicle makers and third party providers protect my personal data and privacy? • Why share car data? • What is the safest and most secure way to share car data? • Will vehicle data be available to all service providers and under the same conditions? • What kind of data can my car share? 5 Confidential – © 2019 Oracle Internal/Restricted/Highly Restricted Car Data • Diverse data types • Speed, Engine RPM, Throttle, Load, Pressure, Gear, Braking, Torque, Steer, Wheels rotations and many more (eg. -
Using Fuzzy Logic in Automated Vehicle Control
Intelligent Transportation Systems Using Fuzzy Logic in Automated Vehicle Control José E. Naranjo, Carlos González, Ricardo García, and Teresa de Pedro, Instituto de Automática Industrial Miguel A. Sotelo, Universidad de Alcalá de Henares ntil recently, in-vehicle computing has been largely relegated to auxiliary U tasks such as regulating cabin temperature, opening doors, and monitoring Automated versions fuel, oil, and battery-charge levels. Now, however, computers are increasingly assum- of a mass-produced ing driving-related tasks in some commercial models. Among those tasks are vehicle use fuzzy logic • maintaining a reference velocity or keeping a safe nomous robots and fuzzy control systems and the distance from other vehicles, Universidad de Alcalá de Henares’s knowledge of techniques to both • improving night vision with infrared cameras, and artificial vision. (The “Intelligent-Vehicle Systems” • building maps and providing alternative routes. sidebar discusses other such projects.) We’re devel- address common oping a testbed infrastructure for vehicle driving that Still, many traffic situations remain complex and includes control-system experimentation, strategies, challenges and difficult to manage, particularly in urban settings. and sensors. All of our facilities and instruments are The driving task belongs to a class of problems that available for collaboration with other research groups incorporate human depend on underlying systems for logical reasoning in this field. So far, we’ve automated and instru- and dealing with uncertainty. So, to move vehicle mented two Citroën Berlingo mass-produced vans procedural knowledge computers beyond monitoring and into tasks related to carry out our objectives. to environment perception or driving, we must inte- into the vehicle control grate aspects of human intelligence and behaviors Automated-vehicle equipment so that vehicles can manage driving actuators in a Figure 1 shows two mass-produced electric Cit- algorithms. -
Anna University:: Chennai 600 025 University Departments Curriculum – R 2013 B.E. (Part – Time) – Automobile Engineering
ANNA UNIVERSITY:: CHENNAI 600 025 UNIVERSITY DEPARTMENTS CURRICULUM – R 2013 B.E. (PART – TIME) – AUTOMOBILE ENGINEERING I – VII SEMESTERS CURRICULA & SYLLABI SEMESTER I SL. CODE NO. COURSE TITLE L T P C NO. THEORY 1 PTMA8151 Applied Mathematics 3 0 0 3 2 PTPH8151 Engineering Physics 3 0 0 3 3 PTCY8152 Engineering Chemistry 3 0 0 3 4 PTGE8153 Engineering Mechanics 3 0 0 3 5 PTGE8151 Computing Techniques 3 0 0 3 TOTAL 15 0 0 15 SEMESTER II SL. CODE NO. COURSE TITLE L T P C NO. THEORY 1 PTAU8201 Electrical and Electronics Engineering 3 0 0 3 2 PTAU8202 Manufacturing Processes 3 0 0 3 3 PTAU8203 Measurement System for Automobiles 3 0 0 3 4 PTAU8204 Thermodynamics and Thermal Engineering 3 0 0 3 5 PTMA8251 Numerical Methods 3 0 0 3 TOTAL 15 0 0 15 SEMESTER III SL. CODE NO. COURSE TITLE L T P C NO. THEORY 1 PTAU8301 Automotive Chassis 3 0 0 3 2 PTAU8302 Automotive Electrical and Electronics 3 0 0 3 3 PTAU8303 Automotive Petrol Engines 3 0 0 3 4 PTAU8304 Solid Mechanics 3 0 0 3 5 PTAU8305 Theory of fuels and Lubricants 3 0 0 3 TOTAL 15 0 0 15 1 SEMESTER IV SL. CODE NO. COURSE TITLE L T P C NO. THEORY 1 PTAU8401 Automotive Diesel Engines 3 0 0 3 2 PTAU8402 Automotive Transmission 3 0 0 3 3 PTAU8403 Two and Three Wheeler Technology 3 0 0 3 4 PTPR8351 Kinematics and Dynamics of Machines 3 0 0 3 PRACTICAL 5 PTAU8411 Automotive Engine and Chassis Components 0 0 3 2 Laboratory TOTAL 12 0 3 14 SEMESTER V SL. -
Human Centred Design of First and Last Mile Mobility Vehicles
Coventry University DOCTOR OF PHILOSOPHY Human centred design of first and last mile mobility vehicles Wasser, Joscha Award date: 2020 Awarding institution: Coventry University Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of this thesis for personal non-commercial research or study • This thesis cannot be reproduced or quoted extensively from without first obtaining permission from the copyright holder(s) • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Download date: 11. Oct. 2021 Human Centred Design of First and Last Mile Mobility Vehicles by 1,2,4 Joscha Wasser A thesis submitted in partial fulfilment of the University’s requirements for the Degree of Doctor of Philosophy. Supervisors: Andrew Parkes1, Cyriel Diels3, Michael Tovey1 and Anthony Baxendale2 1 The National Transport Design Centre, Swift Road, Coventry CV1 2TT, UK 2 HORIBA MIRA Ltd, Watling Street, Nuneaton, Warwickshire, CV10 0TU, UK 3 Royal College of Art, Kensington Gore, Kensington, London SW7 2EU, UK 4 Fraunhofer FKIE, Fraunhoferstraße 20, 53343 Wachtberg, Germany Content removed on data protection grounds 2 3 4 5 6 Content removed on data protection grounds 7 Content removed on data protection grounds 8 Content removed on data protection grounds 9 10 Acknowledgements I would like to express my sincere gratitude to Dr. -
On Processing Personal Data in the Context of Connected Vehicles and Mobility Related Applications
Guidelines 1/2020 on processing personal data in the context of connected vehicles and mobility related applications Version 1.0 Adopted on 28 January 2020 Adopted - version for public consultation 1 Table of contents 1 INTRODUCTION ................................................................................................................................ 3 1.1 Related works ........................................................................................................................... 4 1.2 Applicable law .......................................................................................................................... 5 1.3 Scope ........................................................................................................................................ 6 1.4 Definitions ................................................................................................................................ 9 1.5 Privacy and data protection risks ........................................................................................... 10 2 GENERAL RECOMMENDATIONS..................................................................................................... 12 2.1 Categories of data .................................................................................................................. 12 2.2 Purposes ................................................................................................................................. 14 2.3 Relevance and data minimisation ......................................................................................... -
Connected Car Is Talking
Your connected car is talking. Who’s listening? Moving the data-driven user experience forward with value, security and privacy @YourCar: Feeling extra #chatty today. kpmg.com @YourCar: “Monday. 8:23 a.m. 37 degrees. Pulling out of the driveway with Passenger Alex and heading to the office at 123 Main Street.” © 2016 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. The KPMG name and logo are registered trademarks or trademarks of KPMG International. NDPPS 604896 Contents About the authors 1 A message from Gary Silberg 3 Securing the high value of data 5 Big data speaks volumes 8 The risky road ahead 14 A closer look under the hood 19 Cybersecurity in a connected car 22 Reaching your data destination 24 About KPMG 28 © 2016 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. The KPMG name and logo are registered trademarks or trademarks of KPMG International. NDPPS 604896 About the authors Gary Silberg is KPMG LLP’s (KPMG) national sector lead partner for the automotive industry. With more than 25 years of business experience, including more than 15 years in the automotive industry, he is a leading voice in the media on global trends in the automotive industry. He advises numerous domestic and multinational companies in areas of strategy, mergers, acquisitions, divestitures, and joint ventures. -
Connected and Autonomous Vehicles: Implications for Policy and Practice in City and Transportation Planning
Connected and Autonomous Vehicles: Implications for Policy and Practice in City and Transportation Planning by Charles Ng supervised by Laura Taylor A Major Paper submitted to the Faculty of Environmental Studies in partial fulfillment of the requirements for the degree of Master in Environmental Studies York University, Toronto, Ontario, Canada December 8, 2017 Acknowledgments This paper could not have been completed without the help and support of the caring individuals that I am thankful to have in my life. I would like to thank and acknowledge my mother, Maria, and my sister, Ka Lang for providing me with love and support; my advisor, Peter Timmerman, and my supervisor, Laura Taylor, for providing me with academic and non-academic support; and my invaluable friends that I have made in the MES program for their encouragement, support and relief. i Foreword My Area of Concentration for my Plan of Study is sustainable transportation planning for growth management. Connected and Autonomous Vehicles will change the urban landscape, the roles of governments and present new challenges to planners. This paper has allowed me to view transportation planning through the lens of emerging technologies and how this affects cities in the short and long term. There are many sustainability and growth management implications with Connected and Autonomous Vehicles. For example, automated vehicles can foster decentralization because it easily enables travel however, if utilized correctly, automated vehicles can also compliment local transit systems to support intensification. This is especially important in Ontario (Canada’s first province to allow testing of autonomous vehicles on public roads) as it directly relates to the goals and policies related to sprawl and sustainability as outlined in Ontario’s four provincial land use plans: The Growth Plan for the Greater Golden Horseshoe (GGH), The Greenbelt Plan, The Oak Ridges Moraine Conservation Plan and the Niagara Escarpment Plan. -
Driving Security Into Connected Cars: Threat Model and Recommendations
Driving Security Into Connected Cars: Threat Model and Recommendations Numaan Huq, Craig Gibson, Rainer Vosseler TREND MICRO LEGAL DISCLAIMER The information provided herein is for general information Contents and educational purposes only. It is not intended and should not be construed to constitute legal advice. The information contained herein may not be applicable to all situations and may not reflect the most current situation. Nothing contained herein should be relied on or acted 4 upon without the benefit of legal advice based on the particular facts and circumstances presented and nothing herein should be construed otherwise. Trend Micro The Concept of Connected Cars reserves the right to modify the contents of this document at any time without prior notice. Translations of any material into other languages are intended solely as a convenience. Translation accuracy is not guaranteed nor implied. If any questions arise related to the accuracy of a translation, please refer to 10 the original language official version of the document. Any discrepancies or differences created in the translation are Research on Remote Vehicle Attacks not binding and have no legal effect for compliance or enforcement purposes. Although Trend Micro uses reasonable efforts to include accurate and up-to-date information herein, Trend Micro makes no warranties or representations of any kind as to its accuracy, currency, or completeness. You agree 20 that access to and use of and reliance on this document and the content thereof is at your own risk. Trend Micro Threat Model for Connected Cars disclaims all warranties of any kind, express or implied. Neither Trend Micro nor any party involved in creating, producing, or delivering this document shall be liable for any consequence, loss, or damage, including direct, indirect, special, consequential, loss of business profits, or special damages, whatsoever arising out of access to, 26 use of, or inability to use, or in connection with the use of this document, or any errors or omissions in the content thereof. -
Scenarios for Autonomous Vehicles – Opportunities and Risks for Transport Companies
Position Paper / November 2015 Scenarios for Autonomous Vehicles – Opportunities and Risks for Transport Companies Imprint Verband Deutscher Verkehrsunternehmen e. V. (VDV) Kamekestr. 37–39 · 50672 Cologne · Germany T +49 221 57979-0 · F +49 221 57979-8000 [email protected] · www.vdv.de Contact Martin Röhrleef üstra Hannover, Head of the Mobility Association Department Chairman of the VDV working group “Multimodal Mobility” T +49 511 1668-2330 F +49 511 1668-962330 [email protected] Dr. Volker Deutsch VDV, Head of the Traffic Planning Department T +49 221 57979-130 F +49 221 57979-8130 [email protected] Dr. Till Ackermann VDV, Head of the Business Development Department T +49 221 57979-110 F +49 221 57979-8110 [email protected] Figure sources Title, page 18 VDV Page 5 VDA Page 9 Morgan Stanley Summary: Autonomous vehicles: opportunities and risks for public transport The development and operation of fully automated, driverless vehicles (“autonomous vehicle”) will have a disruptive impact on the transport market and thoroughly mix up the present usage patterns as well as the present ownership and business models. The autonomous vehicle is a game changer, not least because the traditional differences between the various modes of transport become indistinct as an autonomous vehicle can be everything, in principle: a private car, a taxi, a bus, a car-sharing vehicle or a shared taxi. To express it dramatically: the autonomous vehicle could be part of the public transport system – but it could also seriously threaten the existence of today’s public and long-distance transport: The autonomous vehicle can threaten the existence of public transport because it makes driving much more attractive.