Volume 22 Issue 3
Jun.  2022
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QIU Wei-zhi, SHANGGUAN Wei, CHAI Lin-guo, CHU Duan-feng. Multi-scale filtering synchronization method for vehicle-infrastructure cooperative twin-simulation testing[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 199-209. doi: 10.19818/j.cnki.1671-1637.2022.03.016
Citation: QIU Wei-zhi, SHANGGUAN Wei, CHAI Lin-guo, CHU Duan-feng. Multi-scale filtering synchronization method for vehicle-infrastructure cooperative twin-simulation testing[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 199-209. doi: 10.19818/j.cnki.1671-1637.2022.03.016

Multi-scale filtering synchronization method for vehicle-infrastructure cooperative twin-simulation testing

doi: 10.19818/j.cnki.1671-1637.2022.03.016
Funds:

National Key Research and Development Program of China 2018YFB1600600

Beijing Natural Science Foundation-Fengtai Rail Transit Frontier Research Joint Fund L191013

More Information
  • Author Bio:

    QIU Wei-zhi(1995-), male, doctoral student, weizhi_qiu@bjtu.edu.cn

    SHANGGUAN Wei(1979-), male, professor, PhD, wshg@bjtu.edu.cn

  • Received Date: 2021-12-12
  • Publish Date: 2022-06-25
  • To enhance the synchronization performance of the vehicle-infrastructure cooperative twin-simulation testing system, the operation mechanism of twin objects was clarified. Then the interference factors affecting the synchronization performance of the system were analyzed to establish the synchronous mapping model for the twin state. In view of the asynchronous clock problem in twin state sampling, a clock error estimation strategy was designed to correct the measurement time deviation of the twin-simulation testing system. On this basis, a multi-scale filtering updating mechanism was introduced by combining the principle of the Kalman filtering. Furthermore, a measurement noise model considering the synchronization sampling errors was established, and the multi-scale filtering synchronization optimization method was proposed. Finally, the vehicle trajectories from the NGSIM dataset were selected to carry out experiments in a constructed prototype system of twin-simulation testing. Research results show that the synchronization performance can be well maintained by the proposed multi-scale filtering synchronization optimization method under different vehicle speeds. In terms of synchronizing the lateral coordinate, the mean absolute error (MAE) is less than 1 mm, and 99.5% of absolute error (AE) can be controlled to within 8 mm. In terms of synchronizing the longitudinal coordinate, the MAE is less than 9 mm, and 99.5% of AE can be controlled to within 38 mm. In terms of synchronizing the speed, the MAE is less than 2.8 cm·s-1, and 99.5% of AE can be controlled to within 24 cm·s-1. In terms of synchronizing the yaw angle, the MAE is less than 1.1×10-3 rad, and 99.5% of AE can be controlled to within 1.1×10-2 rad. Compared with the dead reckoning method, the proposed method can improve the synchronization accuracy by an average of 30.0% in terms of lateral coordinate, longitudinal coordinate, speed, and yaw angle, solve the asynchronous state problem for twin objects effectively, and guarantee the real-time synchronization and accurate operation of the vehicle-infrastructure cooperative twin-simulation testing system. 3 tabs, 10 figs, 31 refs.

     

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