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As the development of autonomous driving is in its infancy, more and more companies, engineers, scientists, and students are entering or planning to enter this field. As a practitioner who has been deeply involved in computer software, computer vision, and machine learning for decades and has entered the front line of research and development in this emerging technology field, we want to systematically introduce the cutting-edge technical theories of autonomous driving to the newcomers. Since autonomous driving contains too much content, with limited pages, the focus of this book is on the introduction of cutting-edge technologies, especially the tracking of some current hot spots in autonomous driving, such as sensor fusion for perception, maps and localization, driving behavior learning and prediction, end-to-end planning and control, BEV and occupancy perception, neural rendering and Gaussian splatting, large scale models and AI agent-based autonomous driving technology.
The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.
List of contents
Chapter 1 Overview of Autonomous Driving Systems.- Chapter 2 Basic Theory of Autonomous Driving.- Chapter 3 Hardware Platform for Autonomous Driving.- Chapter 4 The Software Platform for Autonomous Driving.- Chapter 5 Perception Module of Autonomous Driving.- Chapter 6 High-Definition Map for Autonomous Driving.- Chapter 7 Localization Module for Autonomous Driving.- Chapter 8 Planning Module for Autonomous Driving.- Chapter 9 Control Module for Autonomous Driving.- Chapter 10 Simulation Module for Autonomous Driving.- Chapter 11 Safety Model.- Chapter 12 System Integration, Validation and Verification (V&V).- Chapter 13 Automatic and Autonomous Parking.- Chapter 14 Vehicle Networking.- Chapter 15 Neural Rendering Technology.- Chapter 16 Diffusion Models.- Chapter 17 Large Scale Models in Autonomous Driving.- Chapter 18 Ethics and Legal Aspects.
About the author
Dr. Yu Huang is the Chief Executive Officer of Roboraction.AI, a startup focused on autonomous driving and embodied AI. Formerly he was Chief Scientist of Synkrotron Technology Inc, Chief Autonomous Driving Scientist at SAIC Zone Tech, Adjust professor of Shanghai University, VP of Autonomous Driving Research at Black Sesame Technology, Chairman of Singulato USA. Dr. Huang also worked in Baidu USA, Intel (San Jose), Samsung Electronics USA and Futurewei Technology Inc. In Aug. 2025, he was appointed as moderator of Industrial Innovation Forum “Embodied AI”, IEEE MIPR’25, San Jose, USA. In Aug. 2024, he was also invited to be Speaker and Panelist of Innovation Forum "The Age of Industrial AI Agents: Opportunities & Challenges", IEEE MIPR'24, San Jose, USA. In Jan. 2024, Dr. Huang was a keynote speaker at the first workshop on Large Language and Vision Models for Autonomous Driving (LLVM-AD), in conjunction with IEEE/CVF WACV’24, Hawaii, USA. In 2020, He was selected as Distinguished Industrial Leader by Asia-Pacific Signal and Information Processing Association (APSIPA). In Mar. 2019, Yu was Moderator of Innovation Forum "Towards Autonomous Driving", IEEE MIPR’19, San Jose, USA. Dr. Huang have more than 40 academic papers published in international conferences and journals, 19 patents issued in US and Europe and one book “System Development of Autonomous Driving” (in Chinese). He got BS degree, MS degree and Doctor degree at Xi'an Jiaotong University, Xidian University, Beijing Jiaotong University respectively. Dr. Huang also was an AvH (Alexander von Humboldt) research scholar (Germany) and postdoctoral associate of Beckman Inst., UIUC.
Dr. Zijiang James Yang is a professor and director of the Synthetic Data and Simulation Engineering Center at the University of Science and Technology of China (USTC). He completed his undergraduate studies at USTC, and earned his master's degree from Rice University and his Ph.D. from the University of Pennsylvania. He has served as a professor at Western Michigan University and a visiting professor at the University of Michigan. Currently Dr. Yang serves as co-chair of the IEEE Technical Committee on Electric and Autonomous Driving, vice-chair of the IEEE Standards Working Group on Autonomous Driving, co-chair of the IEEE International Symposium on Autonomous Driving Software. He has published over 100 papers and received SIGSOFT Outstanding Paper Award, ACM TODAES Best Paper Award, and Google Computer Science Engagement Award. Dr. Yang is a founder of Synkrotron, a company incubated by Turing award winner Dr. Andrew Yao. Synkrotron aims to accelerate the evolution of physical AI by providing synthetic data and tool chains for the development of self-driving cars and robots.
Summary
As the development of autonomous driving is in its infancy, more and more companies, engineers, scientists, and students are entering or planning to enter this field. As a practitioner who has been deeply involved in computer software, computer vision, and machine learning for decades and has entered the front line of research and development in this emerging technology field, we want to systematically introduce the cutting-edge technical theories of autonomous driving to the newcomers. Since autonomous driving contains too much content, with limited pages, the focus of this book is on the introduction of cutting-edge technologies, especially the tracking of some current hot spots in autonomous driving, such as sensor fusion for perception, maps and localization, driving behavior learning and prediction, end-to-end planning and control, BEV and occupancy perception, neural rendering and Gaussian splatting, large scale models and AI agent-based autonomous driving technology.
The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.
