Volume 24 Issue 2
Apr.  2024
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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2024  >  24(2): 243-253
LI Yan, SHI Xuan, NAN Si-rui, ZHU Cai-hua. Optimization of arterial traffic signal coordinated control with tandem pre-signal[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 243-253. doi: 10.19818/j.cnki.1671-1637.2024.02.017
Citation: LI Yan, SHI Xuan, NAN Si-rui, ZHU Cai-hua. Optimization of arterial traffic signal coordinated control with tandem pre-signal[J]. Journal of Traffic and Transportation Engineering, 2024, 24(2): 243-253. doi: 10.19818/j.cnki.1671-1637.2024.02.017
shu

Optimization of arterial traffic signal coordinated control with tandem pre-signal

doi: 10.19818/j.cnki.1671-1637.2024.02.017
  • 1.

    School of Transportation Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

  • 2.

    School of Transportation, Southeast University, Nanjing 211189, Jiangsu, China

  • 3.

    College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, Henan, China

Funds:

National Natural Science Foundation of China 72371035

Natural Science Basic Research Project of Shaanxi Province 2020JM-237

More Information
  • Author Bio:

    LI Yan(1983-), male, professor, PhD, lyan@chd.edu.cn

  • Received Date: 2023-11-27
    Available Online: 2024-05-16
  • Publish Date: 2024-04-30
    Abstract
  • To improve the overall traffic flow efficiency, a bi-level model was established for optimizing the timing plans of arterial traffic signal coordinated control system with tandem pre-signals, and its solving algorithm was proposed. The upper-level model of the bi-level model was an optimization model of the offset between main signals, and the traversal search algorithm was employed to solve it between intersections. The lower-level model was a multi-objective optimization model, which selected the throughput vehicles and the average delay time as the optimization objectives. The flower pollination algorithm(FPA) was established to solve the proposed multi-objective optimization model. The traffic parameters in the bi-level model were connected by using the shockwave model. The optimal solutions of the parameters were obtained through the iterations between the upper-level and lower-level models. Three consecutive intersections after setting up tandem pre-signals were chosen to test. The proposed method was applied to optimize the traffic signal coordination timing plan on arterial roads under both high and low traffic demands. The effectiveness of the selected scheme was tested by software SUMO. Research results indicate that the bi-level model can optimize the arterial traffic signal coordination timing plan with tandem pre-signals. Compared with the traditional arterial signal coordinated control plan, the timing plans obtained from the proposed methods can increase the throughput vehicles through the system by 16%-35% and 8%-17%, respectively. Under high and low traffic demands, and the delays reduce by 7%-17% and 2%-16%, respectively. Compared to the particle swarm optimization (PSO) algorithm and non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ), the FPA requires 13 and 24 fewer iterations to achieve the specified accuracy requirements, respectively. The simulation results indicate that the proposed model can further improve the operational efficiency of road under high demand conditions.

     

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