Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment /

This book, authored by Zhijun Chen, delves into the construction of autonomous driving maps within an intelligent and connected environment. It explores the integration of modern high technology with the automotive and information industries, focusing on key technologies that enhance the stability a...

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主要作者: Chen, Zhijun
格式: 電子 電子書
語言:英语
出版: Amsterdam, Netherlands ; Oxford, United Kingdom ; Cambridge MA : Elsevier, [2024]
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040 |a EBLCP  |b eng  |e rda  |c EBLCP  |d YDX  |d OCLCQ  |d OPELS  |d OCLCO  |d YDX  |d UKAHL  |d UKKRT  |d OCLCA  |d OCLCL  |d SFB  |d OCLCF  |d OCLCO 
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020 |a 9780443273179  |q electronic book 
020 |a 0443273170  |q electronic book 
020 |z 9780443273162 
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035 |a (OCoLC)1429724187  |z (OCoLC)1428953555  |z (OCoLC)1433695997 
050 4 |a TE228.3  |b .C54 2024 
082 0 4 |a 625.7/94  |2 23/eng/20240514  |1 https://id.oclc.org/worldcat/ddc/E3vx76pqX3HpRb6vbHCTJ3tCgx 
100 1 |a Chen, Zhijun. 
245 1 0 |a Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment /  |c Zhijun Chen. 
264 1 |a Amsterdam, Netherlands ;  |a Oxford, United Kingdom ;  |a Cambridge MA :  |b Elsevier,  |c [2024] 
300 |a 1 online resource (197 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
505 0 |a Front Cover -- Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment -- Copyright Page -- Contents -- About the author -- Preface -- 1 Introduction -- 1.1 Intelligent networked environment and intelligent networked vehicles -- 1.1.1 History of intelligent connected environment -- 1.1.2 Composition and characteristics of intelligent network environment -- 1.1.3 Connotation of intelligent networked vehicles -- 1.1.4 Development status of intelligent connected vehicles -- 1.1.5 Development status of intelligent transportation system 
505 8 |a 1.1.6 Smart ethical norm challenges -- 1.2 Overview of target sensing technology based on road sensors -- 1.2.1 Perception technology based on in-vehicle perception devices -- 1.2.2 Perception technology based on roadside sensing devices -- 1.2.3 Development status and trend of collaborative sensing technology -- 1.2.3.1 Collaborative perception information sharing -- 1.2.3.2 Collaborative perception information fusion -- 1.3 Development of vehicle motion behavior recognition methods and prediction technology -- 1.3.1 Connotation and significance of vehicle motion behavior recognition 
505 8 |a 1.3.2 Development status of vehicle motion behavior recognition methods -- 1.3.3 Development status of vehicle motion behavior prediction methods -- 1.4 Overview of autonomous driving map -- 1.4.1 Concept and connotation of autonomous driving map -- 1.4.2 Composition and application of autonomous driving maps -- 1.4.2.1 Environment perception level -- 1.4.2.2 Decision planning level -- 1.4.2.3 Control execution level -- 1.4.3 Status and trends of autonomous driving map development -- 1.4.3.1 Enhancement of high-precision maps -- 1.4.3.2 Real-time update and dynamic maps 
505 8 |a 1.4.3.3 Multisource data fusion -- 1.4.3.4 Semantic understanding and contextual awareness -- 1.4.3.5 Cloud map service -- 1.4.3.6 Global standardization -- 1.4.4 Bottleneck problems and solutions -- 1.4.4.1 Lack of unified top-level standards and specifications -- 1.4.4.2 Lack of mature theory and technical support -- 1.4.5 Implementation path for the above problems -- 1.4.5.1 Building standards, specifications, and system frameworks related to intelligent connected environment and intellig... -- 1.4.6 Carrying out technical research on bottleneck problems 
505 8 |a 1.4.6.1 Strengthening multidisciplinary and cross-industry cooperation and giving full play to the advantages of industry, ... -- 1.4.6.2 Cross-industry and multiindustry collaborative research -- 2 Fusion target perception method based on vehicle vision and radar -- 2.1 Fusion theory of vehicle multisource perception information -- 2.1.1 Basis of vehicle multisource perception information fusion -- 2.1.2 Fusion method and application of vehicle multisource perception information -- 2.1.2.1 Fusion strategy based on distinguishable units -- 2.1.2.2 Fusion strategy based on complementary features 
500 |a 2.1.2.2.1 Target parameter extraction 
588 |a Description based on online resource; title from digital title page (viewed on September 27, 2024). 
520 |a This book, authored by Zhijun Chen, delves into the construction of autonomous driving maps within an intelligent and connected environment. It explores the integration of modern high technology with the automotive and information industries, focusing on key technologies that enhance the stability and development of autonomous vehicles. The book covers topics such as vehicle-road perception, vehicle motion recognition, and trajectory prediction using advanced neural networks. It aims to optimize traffic systems and promote the application of autonomous driving technology on a large scale. Intended for researchers, students, and professionals in traffic engineering and management, it provides a comprehensive knowledge system for constructing autonomous driving maps, contributing to safer and more efficient travel services.  |7 Generated by AI 
650 0 |a Intelligent transportation systems. 
650 0 |a Automated vehicles. 
650 6 |a Systèmes de transport intelligents.  |0 (CaQQLa)201-0252717 
650 6 |a Véhicules autonomes.  |0 (CaQQLa)000292338 
650 7 |a Automated vehicles  |2 fast  |0 (OCoLC)fst01909261 
650 7 |a Intelligent transportation systems  |2 fast  |0 (OCoLC)fst01723430 
776 0 8 |i Print version:  |a Chen, Zhijun  |t Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment  |d San Diego : Elsevier,c2024  |z 9780443273162 
856 4 0 |3 ScienceDirect  |u https://www.sciencedirect.com/science/book/9780443273162