About the author Preface 1 Introduction 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 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 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 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 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 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 References Index
鄂公網(wǎng)安備 42010302001612號 