In recent years,with the development of intelligent transportation and communication technology,intelligent vehicle-infrastructure cooperation systems have attracted widespread attention.The location features of vehicles are the basic elements in intelligent transportation.In the vehicle-infrastructure collaborative environment,the vehicle can receive the positioning in-formation of the roadside unit through the communication device for self-vehicle positioning.This paper aims to solve the prob-lem of positioning errors caused by unstable communication delays in the vehicle-infrastructure collaborative environment and proposes a high-precision vehicle positioning model based on factor graphs that considers communication delays.In the absence of global navigation satellite system(GNSS)information,the target vehicle is identified and located based on the roadside light detection and ranging(LiDAR)point cloud clustering method.The target positioning result is sent to the vehicle through the 4G communication network.The factor graph is used to directly fuse the measurement information of the vehicle inertial meas-urement unit(IMU)at the current moment with the lagging roadside target location results.Based on the incremental smoot-hing inference method,the optimal estimation of the vehicle position,speed and attitude is realized.Finally,combined with the measured and simulated data,the method proposed in this paper is verified by real vehicle experiments.Compared with the tra-ditional extrapolation method of processing time delay,the results show that our method can improve the accuracy of vehicle positioning and speed measurement and eliminate the influence of highly unstable communication delay on positioning.
关键词
车路协同/通信延迟/高精度定位/因子图/路侧感知/目标识别与定位
Key words
intelligent vehicle-infrastructure cooperation systems/wireless communication delay/high-precision positioning/factor graph/roadside perception/target recognition and localization
维普
万方数据