From AI to Autonomous and Connected Vehicles: Advanced Driver-Assistance Systems (ADAS)

288 Pages·2021·38.512 MB·English

by  Abdelaziz Bensrhair (editor), Thierry Bapin (editor)

From AI to Autonomous and Connected Vehicles

Digital Sciences Set
coordinated by
Abdelkhalak El Hami
Volume 2
From AI to Autonomous and
Connected Vehicles

Advanced Driver-Assistance Systems (ADAS)

Edited by

Abdelaziz Bensrhair
Thierry Bapin
First published 2021 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
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The rights of Abdelaziz Bensrhair and Thierry Bapin to be identified as the authors of this work have
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Library of Congress Control Number: 2021938230

British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-78630-727-9
Contents
Foreword 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Thierry BAPIN
Foreword 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Dominique GRUYER
Foreword 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix
Alberto BROGGI
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxi
Abdelaziz BENSRHAIR
Chapter 1. Artificial Intelligence for Vehicles . . . . . . . . . . . . . . . . 1
Gérard YAHIAOUI
1.1. What is AI? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2. The main methods of AI . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1. Deep Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.2. Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.3. Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.4. Reinforcement learning . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.2.5. Case-based reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.2.6. Logical reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.2.7. Multi-agent systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.2.8. PAC learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.3. Modern AI challenges for the industry . . . . . . . . . . . . . . . . . . . . 9
1.3.1. Explainability: XAI (eXplainable Artificial Intelligence) . . . . . . 9
1.3.2. The design of so-called “hybrid” AI systems . . . . . . . . . . . . . 10
vi From AI to Autonomous and Connected Vehicles
1.4. What is an “intelligent” vehicle? . . . . . . . . . . . . . . . . . . . . . . . 10
1.4.1. ADAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.4.2. The autonomous vehicle . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.4.2. The construction of the intelligent vehicle’s basic building
blocks employing AI methods . . . . . . . . . . . . . . . . . . . . . . . . . . 18
1.5. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Chapter 2. Conventional Vision or Not: A Selection of
Low-level Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Fabien BONARDI, Samia BOUCHAFA, Hicham HADJ-ABDELKADER and
Désiré SIDIBÉ
2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.2. Vision sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.1. Conventional cameras . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.2.2. Emerging sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.3. Vision algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3.1. Choosing the type of information to be retrieved from the images . 34
2.3.2. Estimation of ego-movement and localization . . . . . . . . . . . . . 39
2.3.3. Detection of the navigable space by a dense approach . . . . . . . . 44
2.3.4. From the detection of 3D plans to visual odometry . . . . . . . . . . 58
2.3.5. Detection of obstacles through the compensation of ego-movement . . 62
2.3.6. Visual odometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
2.4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
2.5. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
Chapter 3. Automated Driving, a Question of
Trajectory Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Olivier ORFILA, Dominique GRUYER and Rémi SAINCT
3.1. Definition of planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
3.2. Trajectory planning: general characteristics . . . . . . . . . . . . . . . . . 81
3.2.1. Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.2.2. Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.2.3. Cost functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.2.4. Planning methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
3.2.5. Co-pilot respecting legal traffic rules . . . . . . . . . . . . . . . . . . 88
3.2.6. Trajectory prediction for “ghost” objects and vehicles . . . . . . . . 92
3.2.7. Trajectory evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
3.2.8. Results on real vehicles and on simulators . . . . . . . . . . . . . . . 101
3.3. Multi-objective trajectory planning . . . . . . . . . . . . . . . . . . . . . . 104
3.3.1. Linear scalarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
3.3.2. Nonlinear scalarization . . . . . . . . . . . . . . . . . . . . . . . . . . 114
3.3.3. Ideal methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
Contents vii
3.3.4. Summary of multi-objective planning methods . . . . . . . . . . . . 119
3.3.5. High level information . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
3.4. Conclusion on multi-agent planning for a fleet of vehicles:
the future of planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
3.5. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
Chapter 4. From Virtual to Real, How to Prototype, Test, Evaluate
and Validate ADAS for the Automated and Connected Vehicle? . . 125
Dominique GRUYER, Serge LAVERDURE, Jean-Sébastien BERTHY,
Philippe DESOUZA and Mokrane HADJ-BACHIR
4.1. Context and goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
4.2. Generic dynamic and distributed architecture . . . . . . . . . . . . . . . . 128
4.2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
4.2.2. An interoperable platform . . . . . . . . . . . . . . . . . . . . . . . . . 129
4.3. Environment and climatic conditions . . . . . . . . . . . . . . . . . . . . . 132
4.3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
4.3.2. Environmental modeling: lights, shadows, materials
and textures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
4.3.3. Degraded, adverse and climatic conditions . . . . . . . . . . . . . . . 136
4.3.4. Visibility layers and ground truths . . . . . . . . . . . . . . . . . . . . 140
4.4. Modeling of perception sensors . . . . . . . . . . . . . . . . . . . . . . . . 143
4.4.1. Typology of sensor technologies . . . . . . . . . . . . . . . . . . . . . 143
4.4.2. From a functional model to a physical model . . . . . . . . . . . . . 145
4.4.3. Optical sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
4.4.4. LIght Detection And Ranging (LIDAR) . . . . . . . . . . . . . . . . 149
4.4.5. RAdio Detection And Ranging (RADAR) . . . . . . . . . . . . . . . 151
4.4.6. Global Navigation Satellite System (GNSS) . . . . . . . . . . . . . . 153
4.5. Connectivity and means of communication . . . . . . . . . . . . . . . . . 157
4.5.1. State of the art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
4.5.2. Statistical model of the propagation channel . . . . . . . . . . . . . . 158
4.5.3. Multi-platform physico-realistic model . . . . . . . . . . . . . . . . . 159
4.6. Some relevant use cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
4.6.1. Graphic resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
4.6.2. Communication and overall risk . . . . . . . . . . . . . . . . . . . . . 161
4.6.3. Automated parking maneuver . . . . . . . . . . . . . . . . . . . . . . 166
4.6.4. Co-pilot and automated driving . . . . . . . . . . . . . . . . . . . . . 169
4.6.5. Eco-mobility and eco-responsible driving profile . . . . . . . . . . . 171
4.7. Conclusion and perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . 174
4.8. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
viii From AI to Autonomous and Connected Vehicles
Chapter 5. Standards for Cooperative Intelligent
Transport Systems (C-ITS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
Thierry ERNST
5.1. Context and goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
5.1.1. Intelligent transport systems (ITS) . . . . . . . . . . . . . . . . . . . . 182
5.1.2. The connected and cooperative vehicle . . . . . . . . . . . . . . . . . 184
5.1.3. Silos communication systems . . . . . . . . . . . . . . . . . . . . . . . 185
5.1.4. Cooperative Intelligent Transport Systems (C-ITS) . . . . . . . . . . 186
5.1.5. Diversity of Cooperative ITS services. . . . . . . . . . . . . . . . . . 186
5.1.6. Standardization bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
5.1.7. Genesis of the “Cooperative ITS” standards . . . . . . . . . . . . . . 190
5.2. “ITS station” architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
5.2.1. General description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
5.2.2. ITS station communication units . . . . . . . . . . . . . . . . . . . . . 195
5.2.3. Types of ITS stations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
5.3. Features of the ITS station architecture . . . . . . . . . . . . . . . . . . . 197
5.3.1. Combination of communication technologies . . . . . . . . . . . . . 197
5.3.2. Centralized communications . . . . . . . . . . . . . . . . . . . . . . . 198
5.3.3. Localized communications (V2X) . . . . . . . . . . . . . . . . . . . . 198
5.3.4. Hybrid communications . . . . . . . . . . . . . . . . . . . . . . . . . . 200
5.3.5. Extensive communications . . . . . . . . . . . . . . . . . . . . . . . . 202
5.3.6. Communications management . . . . . . . . . . . . . . . . . . . . . . 203
5.3.7. Messaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
5.3.8. Data organization and identification . . . . . . . . . . . . . . . . . . . 206
5.3.9. Secure communications and access to data . . . . . . . . . . . . . . . 207
5.3.10. Evolution of standards . . . . . . . . . . . . . . . . . . . . . . . . . . 208
5.4. Features of the ITS station architecture . . . . . . . . . . . . . . . . . . . 208
5.5. Deployment of Cooperative ITS services . . . . . . . . . . . . . . . . . . 209
5.6. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
Chapter 6. The Integration of Pedestrian Orientation for the
Benefit of ADAS: A Moroccan Case Study . . . . . . . . . . . . . . . . . 215
Aouatif AMINE, Abdelaziz BENSRHAIR, Safaa DAFRALLAH and
Stéphane MOUSSET
6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
6.2. Advanced Driver Assistance System (ADAS) . . . . . . . . . . . . . . . 218
6.3. Proposal for an applicable system to the Moroccan case . . . . . . . . . 219
6.4. General conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
6.5. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231