Human-Like Decision Making and Control for Autonomous Driving

1. Auflage 2022
ISBN: 978-1-032-26208-6
Verlag: CRC Press

Buch, Englisch, 200 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 463 g

This book details cutting-edge research into human-like driving technology, utilising game theory to better suit a human and machine hybrid driving environment. Covering feature identification and modelling of human driving behaviours, the book explains how to design an algorithm for decision making and control of autonomous vehicles in complex scenarios.

Beginning with a review of current research in the field, the book uses this as a springboard from which to present a new theory of human-like driving framework for autonomous vehicles. Chapters cover system models of decision making and control, driving safety, riding comfort and travel efficiency. Throughout the book, game theory is applied to human-like decision making, enabling the autonomous vehicle and the human driver interaction to be modelled using noncooperative game theory approach. It also uses game theory to model collaborative decision making between connected autonomous vehicles. This framework enables human-like decision making and control of autonomous vehicles, which leads to safer and more efficient driving in complicated traffic scenarios.

The book will be of interest to students and professionals alike, in the field of automotive engineering, computer engineering and control engineering.

Autoren/Hrsg.

Hang, Peng

Lv, Chen

Chen, Xinbo

Fachgebiete

• Mathematik | Informatik Mathematik Algebra Zahlentheorie
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik

Inhaltsverzeichnis

1. Introduction
2. Human-Like Driving Feature Identification and Representation
3. System Modelling for Decision Making and Control of Autonomous Vehicles
4. Path Planning and Tracking Control of Autonomous Vehicles
5. Human-Like Decision Making for Autonomous Vehicles with Noncooperative Game Theoretic Method
6. Decision Making for Connected Autonomous Vehicles with Cooperative Game Theoretic Method
7. Conclusion, Discussion and Prospects

Über Autor(innen)

Dr. Peng Hang is at Nanyang Technological University, Singapore. His research interests include decision making, motion planning and control for connected autonomous vehicles. He received a Ph.D. degree in the School of Automotive Studies, Tongji University, and was a Visiting Researcher at the National University of Singapore, and a Software Engineer at SAIC Motor, China. He has written over 50 academic papers in the field of autonomous driving, as well as applying for more than 20 patents. He serves as an Associate Editor of SAE International Journal of Vehicle Dynamics, Stability, and NVH, and Guest Editors of Actuators, IET Intelligent Transport Systems, and Journal of Advanced Transportation.

Dr. Chen Lv is Professor at Nanyang Technology University, Singapore. He received his Ph.D. at the Department of Automotive Engineering, Tsinghua University, China, and researched at EECS Dept., University of California, Berkeley. His research interests are in advanced vehicle control and intelligence, where he has written over 100 papers and obtained 12 granted patents. He is also Academic Editor for IEEE Transactions on Intelligent Transportation Systems, SAE International Journal of Electrified Vehicles, etc, and Guest Editor for IEEE/ASME Transactions on Mechatronics and IEEE Intelligent Transportation Systems Magazine.

Professor Xinbo Chen studied at Zhejiang University, Tongji University and Tohoku University. He is now Professor in the school of Automotive Studies, Tongji University. He is the author of more than 200 articles and more than 70 patents. His research interests include dynamic control of electric vehicles, design and control of active/semi-active suspension system.