
Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment
Zhijun Chen(Author)
Elsevier (Publisher)
Published on 9. April 2024
Book
Paperback/Softback
196 pages
978-0-443-27316-2 (ISBN)
Description
Construction 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.
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.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 229 mm
Width: 152 mm
Weight
340 gr
ISBN-13
978-0-443-27316-2 (9780443273162)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Zhijun Chen
Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment
E-Book
04/2024
Elsevier
€157.99
Available for download
Person
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
Author
Deputy Director, Institute of Traffic Information and Intelligent Systems, Intelligent Transportation Systems Research Center, Wuhan University of Technology, China
Content
1. Introduction
2. Fusion Target Perception Method Based on Vehicle Vision and Millimeter Wave Radar
3. Cross-Field of View Object Perception Method
4. Vehicle Motion Recognition Method Based on Vehicle Road Fusion Information
5. Vehicle Trajectory Prediction Method Based on Improved Hybrid Neural Network
6. Driving Map Construction Driven by Road Perception Fusion
7. Summary and conclusions
2. Fusion Target Perception Method Based on Vehicle Vision and Millimeter Wave Radar
3. Cross-Field of View Object Perception Method
4. Vehicle Motion Recognition Method Based on Vehicle Road Fusion Information
5. Vehicle Trajectory Prediction Method Based on Improved Hybrid Neural Network
6. Driving Map Construction Driven by Road Perception Fusion
7. Summary and conclusions