Creating Autonomous Vehicle Systems
Π½ΠΎΡΠ±. 2022β―Π³. Β· Springer Nature
ΠΠ»Π΅ΠΊΡΡΠΎΠ½Π½Π°Ρ ΠΊΠ½ΠΈΠ³Π°
186
ΠΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΡΡΡΠ°Π½ΠΈΡ
reportΠΡΠ΅Π½ΠΊΠΈ ΠΈ ΠΎΡΠ·ΡΠ²Ρ Π½Π΅ ΠΏΡΠΎΠ²Π΅ΡΠ΅Π½Ρ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅β¦
ΠΠ± ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠΉ ΠΊΠ½ΠΈΠ³Π΅
This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD mapβplus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technologystack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.
ΠΠ± Π°Π²ΡΠΎΡΠ΅
Y.C. Tay received his BSc from the University of Singapore and PhD from Harvard University. He is a professor in the Department of Mathematics and Department of Computer Science at the National University of Singapore. He has spent sabbaticals at Princeton, MIT, Cambridge, UCLA, Microsoft, Intel and VMware. He has served on program committees for SIGMET-RICS, SIGMOD, PERFORMANCE, VLDB, ICDE, MASCOTS, IWQoS and ICS. His main research interest is performance modeling (database transactions, wireless protocols, trafficequilibrium, cache misses). Other interests include database systems and distributed protocols. He has won several teaching awards.
ΠΡΠ΅Π½ΠΈΡΠ΅ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΡΡ ΠΊΠ½ΠΈΠ³Ρ
ΠΠΎΠ΄Π΅Π»ΠΈΡΠ΅ΡΡ Ρ Π½Π°ΠΌΠΈ ΡΠ²ΠΎΠΈΠΌ ΠΌΠ½Π΅Π½ΠΈΠ΅ΠΌ.
ΠΠ΄Π΅ ΡΠΈΡΠ°ΡΡ ΠΊΠ½ΠΈΠ³ΠΈ
Π‘ΠΌΠ°ΡΡΡΠΎΠ½Ρ ΠΈ ΠΏΠ»Π°Π½ΡΠ΅ΡΡ
Π£ΡΡΠ°Π½ΠΎΠ²ΠΈΡΠ΅ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ Google Play ΠΠ½ΠΈΠ³ΠΈ Π΄Π»Ρ Android ΠΈΠ»ΠΈ iPad/iPhone. ΠΠ½ΠΎ ΡΠΈΠ½Ρ
ΡΠΎΠ½ΠΈΠ·ΠΈΡΡΠ΅ΡΡΡ Ρ Π²Π°ΡΠΈΠΌ Π°ΠΊΠΊΠ°ΡΠ½ΡΠΎΠΌ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈ, ΠΈ Π²Ρ ΡΠΌΠΎΠΆΠ΅ΡΠ΅ ΡΠΈΡΠ°ΡΡ Π»ΡΠ±ΠΈΠΌΡΠ΅ ΠΊΠ½ΠΈΠ³ΠΈ ΠΎΠ½Π»Π°ΠΉΠ½ ΠΈ ΠΎΡΠ»Π°ΠΉΠ½ Π³Π΄Π΅ ΡΠ³ΠΎΠ΄Π½ΠΎ.
ΠΠΎΡΡΠ±ΡΠΊΠΈ ΠΈ Π½Π°ΡΡΠΎΠ»ΡΠ½ΡΠ΅ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΡ
Π‘Π»ΡΡΠ°ΠΉΡΠ΅ Π°ΡΠ΄ΠΈΠΎΠΊΠ½ΠΈΠ³ΠΈ ΠΈΠ· Google Play Π² Π²Π΅Π±-Π±ΡΠ°ΡΠ·Π΅ΡΠ΅ Π½Π° ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ΅.
Π£ΡΡΡΠΎΠΉΡΡΠ²Π° Π΄Π»Ρ ΡΡΠ΅Π½ΠΈΡ ΠΊΠ½ΠΈΠ³
Π§ΡΠΎΠ±Ρ ΠΎΡΠΊΡΡΡΡ ΠΊΠ½ΠΈΠ³Ρ Π½Π° ΡΠ°ΠΊΠΎΠΌ ΡΡΡΡΠΎΠΉΡΡΠ²Π΅ Π΄Π»Ρ ΡΡΠ΅Π½ΠΈΡ, ΠΊΠ°ΠΊ Kobo, ΡΠΊΠ°ΡΠ°ΠΉΡΠ΅ ΡΠ°ΠΉΠ» ΠΈ Π΄ΠΎΠ±Π°Π²ΡΡΠ΅ Π΅Π³ΠΎ Π½Π° ΡΡΡΡΠΎΠΉΡΡΠ²ΠΎ. ΠΠΎΠ΄ΡΠΎΠ±Π½ΡΠ΅ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΌΠΎΠΆΠ½ΠΎ Π½Π°ΠΉΡΠΈ Π² Π‘ΠΏΡΠ°Π²ΠΎΡΠ½ΠΎΠΌ ΡΠ΅Π½ΡΡΠ΅.
