Limited Offer
Save 50% on book bundles
Immediately download your ebook while waiting for your print delivery. No promo code needed.
Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment
- 1st Edition - April 4, 2024
- Author: Zhijun Chen
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 7 3 1 6 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 7 3 1 7 - 9
Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment not only supports the development of Intelligent & Connected Transportation, but also… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteConstruction Methods for an Autonomous Driving Map in an Intelligent Network Environment not only supports the development of Intelligent & Connected Transportation, but also promotes the landing application of autonomous driving. Areas covered include the fusion target perception method based on vehicle vision and millimeter wave radar, cross-field of view object perception method, vehicle motion recognition method based on vehicle road fusion information, vehicle trajectory prediction method based on improved hybrid neural network and driving map construction driven by road perception fusion are introduced in this book.
Benefiting from the development of computer technique, the advanced machine learning and artificial intelligence theories are used by this book to show readers the construction process of the Autonomous Driving Map.
Researchers involved in autonomous driving, traffic planning, traffic engineering, traffic control and traffic management
- Cover image
- Title page
- Table of Contents
- Copyright
- About the author
- Preface
- 1. Introduction
- Abstarct
- 1.1 Intelligent networked environment and intelligent networked vehicles
- 1.2 Overview of target sensing technology based on road sensors
- 1.3 Development of vehicle motion behavior recognition methods and prediction technology
- 1.4 Overview of autonomous driving map
- 2. Fusion target perception method based on vehicle vision and radar
- Abstract
- 2.1 Fusion theory of vehicle multisource perception information
- 2.2 Overview of object perception methods based on vehicle perception equipment
- 2.3 Target perception technology integrating vehicle vision and millimeter-wave radar information
- 2.4 Chapter summary
- 3. Crossfield of view object perception method
- Abstract
- 3.1 Basics of crossfield target perception
- 3.2 Vehicle target association matching method based on road perception information
- 3.3 Crossfield of view target re-identification method
- 4. Vehicle motion recognition method based on vehicle road fusion information
- Abstract
- 4.1 Theory and method of vehicle road information fusion
- 4.2 Representation and analysis of vehicle motion state
- 4.3 Vehicle movement behavior recognition method
- 4.4 Chapter summary
- 5. Vehicle trajectory prediction method based on improved hybrid neural network
- Abstract
- 5.1 Basic theory and characterization methods of vehicle trajectory prediction
- 5.2 Analysis of spatiotemporal relationship of vehicle trajectory
- 5.3 Vehicle trajectory prediction model based on improved hybrid neural network
- 5.4 Chapter summary
- 6. Driving map construction based on road perception fusion
- Abstract
- 6.1 Introduction to the theory and method of vehicle road target perception
- 6.2 Concept and connotation of driving map
- 6.3 Intelligent vehicle driving map construction based on vehicle-road perception information
- 6.4 Chapter summary
- 7. Conclusion
- Abstract
- Index
- No. of pages: 206
- Language: English
- Edition: 1
- Published: April 4, 2024
- Imprint: Elsevier
- Paperback ISBN: 9780443273162
- eBook ISBN: 9780443273179
ZC
Zhijun Chen
Dr Chen is the Deputy Director of the Institute of Traffic Information and Intelligent Systems, Intelligent Transportation Systems Research Center, Wuhan University of Technology. His expertise areas include artificial intelligence, image processing, big data mining, vehicle-road collaboration and connected automated driving, intelligent driving, autonomous driving
Affiliations and expertise
Deputy Director, Institute of Traffic Information and Intelligent Systems, Intelligent Transportation Systems Research Center, Wuhan University of Technology, ChinaRead Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment on ScienceDirect