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This book comprehensively explores the fundamental aspects of game theory and its application in autonomous driving, with an additional focus on real-world implementations. It provides robust examples of game formulation, driving behavior modeling, estimation, and the realization of experimental platforms.
The book begins by introducing the basic concepts of game theory and discussing its necessity in the development of autonomous vehicles. It then covers both classical and modern game theory models. Fundamental concepts and the background of the autonomous vehicles' software stack are detailed, illustrating how game theory integrates into this framework. The book also demonstrates special modifications in game formulation that consider realistic driving behaviors and the characteristics of urban traffic. Finally, it presents the real-world implementation of a shuttle bus platform and the corresponding experimental results.
Intended for senior undergraduate and graduate students, vehicle R&D departments, and anyone interested in designing and implementing self-driving systems in highly interactive environments, the book adopts a step-by-step approach to simplify complex concepts. It is enriched with diagrams, graphs, and practical examples to aid understanding.
Sommario
Chapter 1 Introduction.- Chapter 2 Background of Game Theory.- Chapter 3 Implementing Game Theory in Autonomous Driving System.- Chapter 4 Realistic Game Theory Modelling for Autonomous Driving.- Chapter 5 Realistic Game Theory Modelling for Autonomous Driving.- Chapter 6 Challenges and Future Trends.
Info autore
Dr. Keqi Shu received his Ph.D. in Mechanical and Mechatronics Engineering from the University of Waterloo, Canada. He currently serves as a Postdoctoral Fellow/Research Associate in the Mechatronic Vehicle Systems Lab, focusing on game theory, strong-interactive decision-making, and planning for self-driving vehicles.
Dr. Shu has collaborated extensively with OEMs (Original Equipment Manufacturers), suppliers, and research institutes. He has developed multiple decision-making algorithms and a corresponding platform for urban-driving autonomous vehicles and is actively involved in developing a real-world connected vehicle system. His research has been successfully transferred to industry applications, leading to several patents and publications.
Dr. Yukun Lu joined the Department of Mechanical Engineering at the University of New Brunswick as an Assistant Professor in July 2025. She also serves as an Adjunct Assistant Professor at the University of Waterloo. She earned her Ph.D. in Mechanical and Mechatronics Engineering from the University of Waterloo in 2023, where she continued as a Postdoctoral Researcher at the Mechatronic Vehicle Systems Lab. She holds a B.Eng. in Vehicle Engineering with a minor in Business Administration, completed in 2018. Her background and future research interests include ground vehicle corner modules, intelligent robotic mobility, data-driven learning-based control strategies, vehicle dynamics and control, etc.
Dr. Amir Khajepour is a professor of Mechanical and Mechatronics Engineering and the Director of Waterloo Center for Automotive Research (WatCAR) and the Mechatronic Vehicle Systems (MVS) Lab. He held the Tier 1 Canada Research Chair in Mechatronic Vehicle Systems from 2008 to 2022 and the Senior NSERC/General Motors Industrial Research Chair in Holistic Vehicle Control from 2017 to 2022. His work has resulted in training of over 160 PhD and MASc students, 30 patents, 600 research papers, many books, numerous technology transfers, and several start-up companies. He has been recognized with the Engineering Medal from Professional Engineering Ontario and is a fellow of the Engineering Institute of Canada, the American Society of Mechanical Engineering, and the Canadian Society of Mechanical Engineering.
Riassunto
This book comprehensively explores the fundamental aspects of game theory and its application in autonomous driving, with an additional focus on real-world implementations. It provides robust examples of game formulation, driving behavior modeling, estimation, and the realization of experimental platforms.
The book begins by introducing the basic concepts of game theory and discussing its necessity in the development of autonomous vehicles. It then covers both classical and modern game theory models. Fundamental concepts and the background of the autonomous vehicles’ software stack are detailed, illustrating how game theory integrates into this framework. The book also demonstrates special modifications in game formulation that consider realistic driving behaviors and the characteristics of urban traffic. Finally, it presents the real-world implementation of a shuttle bus platform and the corresponding experimental results.
Intended for senior undergraduate and graduate students, vehicle R&D departments, and anyone interested in designing and implementing self-driving systems in highly interactive environments, the book adopts a step-by-step approach to simplify complex concepts. It is enriched with diagrams, graphs, and practical examples to aid understanding.
