Abstract:

In the application of vehicle-road cooperative technology for dynamic display of the roadside twin maps， due to the delay problem of the communication between networked devices and the existence of the roadside perception error， the fusion perception accuracy of the roadside edge computing unit will be seriously affected， which will lead to the jitter and delay of the vehicle display track in the twin map. Hence， in this paper a vehicle-road cooperative sensing and localization method that fuses high definition map under high communication delay is proposed. The method first analyzes and models the communication delay between the vehicle end of the connected vehicle and the roadside edge processing unit in the vehicle-road cooperative system， divides the delay model into sensor synchronization delay and communication transmission delay， and proposes a synchronization optimization method for the delay. After the synchronization optimization， a collaborative multidimensional particle filter algorithm for swarm vehicles is proposed， where the states of the particles represent the pose of different connected vehicles and non-connected vehicles in the swarm vehicles. In the proposed multidimensional particle filter algorithm， the state of the particles is firstly updated using the observation of the state of the particles by utilizing the roadside RSU observation data and the curvature information of the lanes in the high-definition map. Then the self-localization information of the received delayed synchronized smart connected cars combined with the left and right lane line lateral constraint information and the lane line equations of the lanes in the high definition map are used to update the observation of the state portion of the particle that represents the smart connected cars. The experimental results show that the perceptual and localization accuracy of the edge server is improved by 59.4% in the low delay scenario with less communication interference， and its accuracy is improved by 38.6% in the high delay scenario with severe communication interference. Therefore， the proposed vehicle-road cooperative sensing method incorporating high definition map under high communication delay can effectively deal with the communication delay problem and improve the multi-vehicle perception accuracy of the edge computing unit， thus improving the accuracy， stability and continuity of the twin map dynamic data.

Key words: time-delay synchronization, vehicle-road coordination, HD map, particle filter