Acta Geodaetica et Cartographica Sinica ›› 2024, Vol. 53 ›› Issue (1): 101-117.doi: 10.11947/j.AGCS.2024.20220626

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Vehicle high-precision positioning considering communication delay for intelligent vehicle-infrastructure cooperation system

ZHANG Hongjuan1,2, QIAN Chuang3, ZHAO Qianying1, LI Wenzhuo1, LI Bijun1,2   

  1. 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application, Ministry of Education of China, Wuhan University, Wuhan 430079, China;
    3. Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China
  • Received:2022-11-04 Revised:2023-06-07 Published:2024-02-06
  • Supported by:
    The National Key Research and Development Program of China (No. 2021YFB2501100); Independent Innovation Research Fund of Wuhan University of Technology (No. 223144001)

Abstract: 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 information of the roadside unit through the communication device for self-vehicle positioning. This paper aims to solve the problem 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 measurement unit (IMU) at the current moment with the lagging roadside target location results. Based on the incremental smoothing 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 traditional 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.

Key words: intelligent vehicle-infrastructure cooperation systems, wireless communication delay, high-precision positioning, factor graph, roadside perception, target recognition and localization

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