Autonomous driving algorithms and Its IC Design

With the rapid development of artificial intelligence and the emergence of various new sensors, autonomous driving has grown in popularity in recent years. The implementation of autonomous driving requires new sources of sensory data, such as cameras, radars, and lidars, and the algorithm processing requires a high degree of parallel computing. In this regard, traditional CPUs have insufficient computing power, while DSPs are good at image processing but lack sufficient performance for deep learning. Although GPUs are good at training, they are too power-hungry, which can affect vehicle performance. Therefore, this book looks to the future, arguing that custom ASICs are bound to become mainstream. With the goal of ICs design for autonomous driving, this book discusses the theory and engineering practice of designing future-oriented autonomous driving SoC chips.

The content is divided into thirteen chapters, the first chapter mainly introduces readers to the current challenges and research directions in autonomous driving. Chapters 26 focus on algorithm design for perception and planning control. Chapters 710 address the optimization of deep learning models and the design of deep learning chips, while Chapters 11-12 cover automatic driving software architecture design. Chapter 13 discusses the 5G application on autonomous drving.

This book is suitable for all undergraduates, graduate students, and engineering technicians who are interested in autonomous driving.

Systematically introduces readers to all aspects of autonomous driving algorithm, software and chip design Highlights potential autonomous driving products and services and potential business opportunities Written by experts with more than 10 years of experience in the field

Autorentext
Dr. Jianfeng Ren, currently working at Google Inc., received his PhD in Electrical Engineering from the University of Texas at Dallas in 2009. Previously, he worked for Qualcomm and Huawei HiSilicon for many years, and has published more than 40 papers and more than 30 US patents. His current research focus is on computational photograph/computer vision algorithms.

Dr. Dong xia, received the PhD degree in Communication and Information System in the National University of Defense Technology. He has long been engaged in research work in the field of artificial intelligence, chip algorithm design and automatic target recognition, and published more than 60 patents.

Inhalt

Chapter 1 Autonomous Driving: The Challenges.- Chapter 2 3D Object Detection.- Chapter 3 Lane Detection.- Chapter 4 Motion Planning and Control.- Chapter 5 Positioning and Mapping.- Chapter 6 Autonomous Driving Simulator.- Chapter 7 Autonomous Driving Chip.- Chapter 8 Deep Learning Model Optimization.- Chapter 9 Deep Learning Chip Design.- Chapter 10 Autonomous Driving SoC Chip Design.- Chapter 11 Autonomous Driving Operating System.- Chapter 12 Autonomous Driving Software Architecture.- Chapter 13 V2X.