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Full Description
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.
Contents
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
