Morgan & Claypool series of books on autonomous vehicles.

Morgan & Claypool has published multiple books on autonomous
vehicles from leading researchers around the world. 
They provide both theoretical background and science which is directly applicable to anyone working in autonomous vehicle engineering
including hardware and software. Here’s our most recently published
books.
Path Planning and Tracking for Vehicle Collision Avoidance inLateral and Longitudinal Motion Directions

Jie Ji, Southwest University, ChinaHong Wang, Tsinghua University, ChinaYue Ren, Southwest University, China

Print ISBN: 9781681739397 |
PDF ISBN: 9781681739403
This book provides a comprehensive overview of the current collision avoidance strategies for traditional vehicles and CAVs. It introduces some emergency path planning methods that can be applied in global route design and local path generation situations which are the most common scenarios in driving. In addition, this book designs and applies robust control to solve the path-tracking problem and verify its tracking effect in different scenarios. Finally, this book introduces the basic principles and test methods of AEB system for collision avoidance of a single vehicle.
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Decision Making, Planning, and Control Strategies for Intelligent Vehicles

Haotian Cao, Hunan UniversityMingjun Li, Hunan UniversitySong
Zhao, University of WaterlooXiaolin Song, Hunan University

Print ISBN: 9781681738826 | PDF ISBN: 9781681738833This short book covers various strategies of designing the decision making, trajectory planning, and tracking control, as well as share driving, of the human-automation to adapt to different levels of the automated driving system.
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Cyber-Physical Vehicle Systems: Methodology and Applications

Chen Lv, Nanyang Technological UniversityYang Xing, Nanyang Technological UniversityJunzhi Zhang, Tsinghua UniversityDongpu Cao, University of Waterloo

Print ISBN: 9781681737317 | PDF ISBN: 9781681737324
This book studies the design optimization, state estimation, and advanced control methods for cyber-physical vehicle systems (CPVS) and their applications in real-world automotive systems.
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Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles

Teng Liu, University of Waterloo
Print ISBN: 9781681736181 | PDF ISBN: 9781681736198
In this book, a series hybrid electric vehicle was considered as the
powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system.
The proposed system can not only integrate predictive road information but also achieve online learning and updating.
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Deep Learning for Autonomous Vehicle Control: Algorithms,State-of-the-Art, and Future Prospects

Sampo Kuutti, University of Surrey, UKSaber Fallah, University of Surrey, UKRichard Bowden, University of Surrey, UKPhil Barber, Jaguar Land Rover
Print ISBN: 9781681736075 | PDF ISBN: 9781681736082
In this book, we introduce relevant deep learning techniques, discuss recent algorithms applied to autonomous vehicle control, identify strengths and limitations of available methods, discuss research challenges in the field, and provide insights into the future trends in this rapidly evolving field.
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Creating Autonomous Vehicle Systems, Second Edition

Shaoshan Liu, PerceptInLiyun Li, Xpeng MotorsJie Tang, South China University of TechnologyShuang Wu, YiTuJean-Luc Gaudiot, University of California, Irvine
Print ISBN: 9781681739359 | PDF ISBN: 9781681739366

This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled “Teaching and Learning from this Book” was added to help instructors better utilize this book in their classes.
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