Automated Vehicles and Maas: Removing the Barriers

ISBN-13: 9781119765349 / Angielski / Twarda / 2021 / 288 str.

Bob Williams

Spis treści

1. The promise and hype regarding automated driving and MaaS 61.1 The promise 61.2 What do we mean by the term 'automated driving'? 91.3 The hype 112 Automated Driving levels 272.1 SAE J3016 272.2 The Significance of Operational Design Domain (ODD 382.3 Deprecated terms 392.4 No relative merit 402.5 Mutually Exclusive Levels 402.6 J3016 Limitations 412.7 Actors in the automated vehicle paradigm 422.8 Other functions 492.8.1 Regulation data access 493 The current reality 513.1 UNECE WP 29 513.2 Social acceptance 533.3 SMMT 533.4 Other observations 543.5 The European Commission 553.6 Legislation 563.7 Subsidiarity 573.8 Viewpoints 574 Automated Driving Paradigms 604.1 OECD 604.4 Communications evolution 604.2 Cooperative ITS 624.3 The C-ITS Platform 654.5 Holistic approach 674.6 It won't happen quickly 684.7 Implications of fully automated vehicles 695 The MaaS Paradigm 815.1 Purist definition for MaaS 815.2 Vehicle manufacturer perspective for MaaS 815.3 Traditional transport service provider perspective for MaaS 825.4 MaaS from the perspective of the MaaS Broker 825.5 MaaS as a tool for Social Engineering 875.6 MaaS experience to date 895.7 MaaS and Covid-19 896 Challenges facing automated driving 937 Potential problems hindering the instantiation of MaaS 987.1 Root causes of obstacles 987.2 Level of community readiness 987.3 Level of Social Engineering readiness 997.4 Perception of risks 1017.5 Level of market readiness 1017.6 Level of Software solution readiness 1037.7 Training 1037.8 Timing 1037.9 Institutional & Governance 1038 Potential solutions to overcoming barriers to automated driving 1068.1 Vehicle manufacturers flawed paradigm of the automated vehicle 1068.2 Vehicle manufacturers using different paradigms for competitive advantage 1078.3 Road operator's responsibilities 1108.4 New modes of transport and new mobility services must be safe and secure by design 1188.5 How other road users interact with AVs 1198.6 Automated vehicles will have to be able to identify and consistently respond to different forms of communication 1198.7 AV's by themselves will not necessarily be smarter than conventional vehicles 1228.8 Congestion levels will not drop significantly 1248.9 Automated vehicles will release unsatiated demand 1258.10 Safety and some operational data must be freely shared 1288.11 Mixed AV and conventional traffic 1288.12 AV Acceptability 1298.13 Low latency communication 1308.14 Roads could be allocated exclusively to AVs 1338.15 Automated and connected vehicles bring new requirements 1358.16 Cybersecurity 1368.17 Changing speed limits and even getting signs put up can take years 1418.18 Political decisions needed 1428.19 Role of government 1438.20 Fallback to driver 1498.21 Range of services supported 1568.21.1 Services that can be instantiated without the support of the local infrastructure 1578.21.2 Services that can only be provided using data/information from the local infrastructure 1588.21.3 Services that can be enhanced/improved/extended by using data/information from the local infrastructure 1588.21.4 The HARTS architecture with reference to C-ITS platform Day/Day 1.5 services 1608.22 Young drivers and experience 1978.23 Liability 1988.24 Level 5 may take a long time to instantiate 2039 Potential solutions to overcoming barriers to MaaS 2059.1 Addressing General issues 2059.2 Essentials to enable MaaS 2069.2.1 Trust 2079.2.2 Impartiality 2079.2.3 Cooperation 2089.2.4 Integration services 2089.2.5 Commercial agreements 2099.2.6 Data protection 2109.2.7 Solid Governance model 2119.3 Removing Obstacles to MaaS 2179.3 Innovative enablers for MaaS 21810 The C-ART innovation 22010.1 Overview 22010.2 Policy context 22110.3 Key conclusions 22210.4 C-ART scenarios 22310.4.1 Short to medium term scenario (2020-2030): C-ART 2030 22310.4.2 Medium to long term scenario (2030-2050): C-ART 2050 22410.4.3 Town planning as a consequence of C-ART 22410.4.4 An assessment of C-ART 22510.4.5 Technology principles and architecture behind C-ART 22510. 4.6 The C-ART framework 22810.4.7 Some observations on Project C-ART 23111 Potential solutions to instantiate AVs and MaaS: Managed Architecture for Transportation Optimisation (MOAT) 23311.1 Managed not controlled 23311.2 High level Actors in the MOAT architecture 23511.2.1 Traveller Group (Traveller) 23511.2.2 Subscriber (Subscriber) 23511.2.3 Travel Service Provider (TSP) 23611.2.4 AV operator (AVO) 23611.2.6 Travel Information Provider (TIP) 23611.2.7 Traffic Management Centre (TMC) 23611.2.8 Travel Optimisation Service (TOS) 23611.3 MOAT from the subscriber / user perspective 23711.4 MOAT from the Travel Service Provider perspective 23911.4.1 Operate user interface (UI) 23911.4.2 Receive request from subscriber 23911.4.3 Characterise request options 23911.4.4 Calculate viable travel options 23911.4.5 Confirm options to subscriber 23911.4.6 Receive subscriber selection 24011.4.7 Fulfil travel arrangements 24011.4.8 Provide confirmation to subscriber 24011.4.9 Monitor/Manage progress of journey 24011.4.10 Acknowledge end of journey 24011.4.11 Process administration requirement 24011.4.12 Delete personal data 24011.5 MOAT from the road operator perspective 24011.6 MOAT from the AV operator (AVO) perspective 24111.7 MOAT from the Travel Optimisation Service (TOS) perspective 24211.8 MOAT from the Traffic Management Centre (TMC) perspective 24311.9 MOAT from the Travel Information Provider (TIP) perspective 24311.10 MOAT and privacy 24311.11 The MOAT overview architecture 24311.12 The MOAT systems architecture 24412 The Business Case for MaaS 24712.1 The Challenge 24712.3 The Solution 24712.4 The Outlook 24813 The Business Case for Automated Vehicles 24813.1 The Challenge 24813.3 The Solution 24913.4 The Outlook 25014 Timescales to successful implementation 25114.1 Caveat 25114.2 Phased MOAT 25214.3 Timescales MaaS 25314.4 Timescales for Automated Vehicles 25314.5 The first half of the Twentieth Century 25514.6 The second half of the twentieth Century 25514.7 2000 - 2009 25614.8 2010-2019 25714.9 2020 - 2029 25914.10 2030 - 2039 26014.11 2040 - 2050 26014.12 2050-2060 26114.13 In summary 261 Bibliography 262

O autorze

Bob Williams, PhD, FCMA, CGMA, FIoD is internationally recognized as one of the world's leading independent data capture consultants specializing in wireless technologies. He has nearly 40 years experience in Intelligent Transport Systems (ITS), Radio Frequency Identification (RFID), and Bar Coding. He provides support to many of the world's leading companies and governments and is the architect and editor of over one hundred International Standards deliverables for ITS and RFID.