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

by Zhijun Chen

Overview

This book provides an overview of constructing advanced Autonomous Driving Maps. It includes coverage of such methods as: fusion target perception (based on vehicle vision and millimeter wave radar), cross-field of view object perception, vehicle motion recognition (based on vehicle road fusion information), vehicle trajectory prediction (based on improved hybrid neural network) and the driving map construction method driven by road perception fusion. An Autonomous Driving Map is used for optimization of not only for a single vehicle, but also for the entire traffic system.

Product Details

ISBN-13:	9780443273179
Publisher:	Elsevier Science
Publication date:	04/04/2024
Sold by:	Barnes & Noble
Format:	eBook
Pages:	206
File size:	23 MB
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About the Author

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

Table of Contents

1. Introduction2. Fusion Target Perception Method Based on Vehicle Vision and Millimeter Wave Radar3. Cross-Field of View Object Perception Method4. Vehicle Motion Recognition Method Based on Vehicle Road Fusion Information5. Vehicle Trajectory Prediction Method Based on Improved Hybrid Neural Network6. Driving Map Construction Driven by Road Perception Fusion7. Summary and conclusions

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From the Publisher

Provides an overview of the construction and development of Autonomous Driving Maps as part of the move towards autonomous driving technology