Chengshi guidao jiaotong yanjiu (Sep 2024)

Application Research on Vehicle-ground Integrated Sensing System of Suzhou High-tech Zone Tram

  • ZHANG Chuanxi,
  • YU Zhe,
  • FENG Junyi

DOI
https://doi.org/10.16037/j.1007-869x.2024.09.061
Journal volume & issue
Vol. 27, no. 9
pp. 334 – 337

Abstract

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Objective In the semi-independent right-of-way operation scenario of the tram, there exists the potential risk of pedestrians or vehicles entering the track area, especially in the intersection area. The sensing system deployed on the tram and the ground can monitor the track area and the area around the tram to identify potential risks. In order to ensure the operation safety of the tram and improve the operation efficiency of the line, it is necessary to conduct in-depth research on the application of the tram vehicle-ground integrated sensing system. Method Based on Suzhou Hi-tech Zone tram project, the application scenarios of the tram sensing system and V2X communication technology in the field of urban rail transit are analyzed, including vehicle control, environment sensing, over-the-horizon sensing, vehicle-to-vehicle and vehicle-to-ground communication, etc. The application of the vehicle-ground integrated sensing system in Suzhou Hi-tech Zone tram is introduced, and the performance of the system is tested and evaluated by the actual operation data. Result & Conclusion The test results show that the tram can detect the common social vehicles and pedestrians in road traffic at a distance of 250m after the on-board camera and LiDAR data are processed based on the deep learning method. And with the V2X communication technology, the tram can obtain the ground sensing information of the intersection 600 meters away, realizing the over-the-horizon sensing of the intersection. With on-board V2X equipment, the current tram can implement real-time exchange of the operation information and surrounding environment data with other trams and ground control systems. The response time of the vehicle-ground integrated sensing system is less than 0.33s, and its missing detection rate is less than 0.1%.

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