A Cloud Based and Real Time Kinematic Sensing Solution for Automated Parking Function
Automated Valet Parking is foreseen as a highly automated function to be implemented on large scale in mass production in the near future.For such function,the authors have developed an innovative system concept using both real time kinematic sensing system and infrastructure IoT(Internet of things)camera to perform AVP function.As the driver activates the AVP function,the infrastructure identifies available parking spots by processing in real time camera frames and as the path is computed,the vehicle executes automated parking maneuvers.This paper introduces the system scheme and system engineering approach as well as key technology bricks to realize AVP function and proves the effectiveness and accuracy of the system through extensive vehicle testing.From system definition to final prototype validation,through Motion control algorithm description or deep learning algorithm tuning method,this paper covers a large spectrum of the engineering domains required to implement such function.The development approach is focused on a user perspective by emphasizing simplicity of usage,frugality of the solution and robustness of the system.
Autonomous Driving Vehicle Dynamic Deep learning Motion Control Real Time Kinematic Infrastructure Connectivity Internet of Things
David BARBé Xin YANG Zeng-hong CHEN Hao YE Ting CHEN Si-yuan FAN Xiao-yuan CAI Ya-ting GUO Tao YANG
Department of Electrification,Transmission and Vehicle,AVL Technical Center(Shanghai)Co.,Ltd,China
国际会议
武汉
英文
88-96
2020-01-12（万方平台首次上网日期，不代表论文的发表时间）