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

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.

An Autonomous Driving Map is used for optimization of not only for a single vehicle, but also for the entire traffic system.

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