Volume 22 Issue 3
Jun.  2022
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SHANGGUAN Wei, LI Xin, CHAI Lin-guo, CAO Yue, CHEN Jing-jing, PANG Hao-jie, RUI Tao. Research review on simulation and test of mixed traffic swarm in vehicle-infrastructure cooperative environment[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 19-40. doi: 10.19818/j.cnki.1671-1637.2022.03.002
Citation: SHANGGUAN Wei, LI Xin, CHAI Lin-guo, CAO Yue, CHEN Jing-jing, PANG Hao-jie, RUI Tao. Research review on simulation and test of mixed traffic swarm in vehicle-infrastructure cooperative environment[J]. Journal of Traffic and Transportation Engineering, 2022, 22(3): 19-40. doi: 10.19818/j.cnki.1671-1637.2022.03.002

Research review on simulation and test of mixed traffic swarm in vehicle-infrastructure cooperative environment

doi: 10.19818/j.cnki.1671-1637.2022.03.002
Funds:

National Key Research and Development Program of China 2018YFB1600600

More Information
  • Author Bio:

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

  • Received Date: 2021-12-27
  • Publish Date: 2022-06-25
  • The developments of vehicle-infrastructure cooperation and corresponding simulation and test technologies were summarized, and the simulation requirements, classical methods, and technical bottlenecks in the rudiment, infancy, and developing stages were discussed with a focus on the typical simulation results. A new three-layer virtual-real interactive simulation and test framework was proposed based on the traffic subject modeling, swarm behavior simulation, and test result analysis. According to the simulation requirements of mixed traffic subjects, a model for the heterogeneous traffic subjects was constructed, and the operation mechanism of mixed traffic was analyzed to serve as the underlying model support for the simulation system. With the designed virtual-real interactive simulation and test framework, breakthroughs were accomplished in the scenario generation technology for the mixed traffic swarm intelligence, and a simulation method for the mixed traffic swarm intelligence was put forward. Then, simulation tests of decision-making and control methods for different swarm intelligences were carried out in the selected typical traffic scenarios, such as intersections and road sections, to verify the effectiveness of the proposed method. Finally, the future development directions of vehicle-infrastructure cooperation and corresponding suggestions were summarized. Research results show that show that compared with the traditional simulation and test method, the proposed virtual-real interactive simulation and test method reduces the system's simulation granularity from 500 ms to less than 100 ms, the simulation scale increases from 9 nodes and 500 traffic subjects to 150 nodes and 2 000 traffic subjects, and the number of simulated scenarios enhances from 36 to 98. The dynamic adjustment within a range of 0-100% penetration rate of heterogeneous traffic subjects is achieved, and the efficiency, scale, and coverage of the vehicle-infrastructure cooperative simulation and test of mixed traffic are effectively improved. The requirements of vehicle-infrastructure cooperative simulation and test in the new mixed traffic environment are rapidly evolving towards the larger swarm, higher intelligence, and larger scale. Carrying out research on the method and technology for the simulation and test on the vehicle-infrastructure cooperative swarm intelligence based on the virtual-real interaction and operating environment data simulation will effectively promote the development of the next generation of the intelligent traffic system.

     

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