Autonomous driving algorithms and Its IC Design
Autor Jianfeng Ren, Dong Xiaen Limba Engleză Paperback – 11 aug 2024
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Specificații
ISBN-13: 9789819928996
ISBN-10: 9819928990
Pagini: 316
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.48 kg
Editura: Springer
ISBN-10: 9819928990
Pagini: 316
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.48 kg
Editura: Springer
Cuprins
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.
Notă biografică
Dr. Jianfeng Ren serves as a Software Manager for Google’s Pixel Camera team and holds a Ph.D. in Electrical Engineering. With deep expertise in computer vision, machine learning, and computational photography, he has built an impressive career, including notable contributions during his tenure at Qualcomm and Huawei USA. Dr. Ren is the author of several acclaimed books, such as Autonomous Driving Algorithms and Chip Design, and is a participant in MIT’s prestigious CTO program. Blending academic rigor with industry leadership, he spearheads ground breaking AI solutions in autonomous driving and smart technologies, driven by a passion for innovation and excellence in technology and management. Andric Li is a graduate of the University of California, San Diego, with a strong foundation in computer science and a focus on Human-Computer Interaction. His expertise spans software engineering, computer graphics, machine learning, artificial intelligence, and extended reality (XR) technologies. Andric has worked on immersive projects combining virtual and augmented reality with web-based applications, contributing to innovative solutions in digital interaction and intelligent systems. Passionate about merging creativity with advanced technology, Andric aims to leverage his skills to create impactful and efficient systems that bridge the gap between physical and digital environments. Link - All python code is available here: https://github.com/JeffRen1977/python_interview
Textul de pe ultima copertă
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 2–6 focus on algorithm design for perception and planning control. Chapters 7–10 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.
The content is divided into thirteen chapters, the first chapter mainly introduces readers to the current challenges and research directions in autonomous driving. Chapters 2–6 focus on algorithm design for perception and planning control. Chapters 7–10 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.
Caracteristici
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