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Investigating the Effect of Network Traffic Signal Timing Strategy with Dynamic Variable Guidance Lanes

Author

Listed:
  • Fei Zhao

    (Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430062, China
    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430062, China
    Department of Civil & Environmental Engineering, Faculty of Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada)

  • Liping Fu

    (Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430062, China
    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430062, China)

  • Xiaofeng Pan

    (Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430062, China
    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430062, China)

  • Tae J. Kwon

    (Department of Civil & Environmental Engineering, Faculty of Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada)

  • Ming Zhong

    (Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430062, China
    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430062, China)

Abstract

This paper aims to investigate the effect of network signal timing strategy with dynamic variable guidance lanes based on a two-step approach, where the first step is an interactive traffic signal optimization model for each single interaction (e.g., lane allocation plans, cycle length) in the network, and the second refers to network signal control (e.g., split, off-sets). The optimization problem in the first step is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-ΙΙ), and the network signal control problem in the second step is solved through SYNCHRO. To verify the effect of dynamic variable guidance lanes and also the reliability and validity of the proposed approach, a numerical case study is carried out. The results show that the average vehicle delay in the entire road network was reduced by 25.06% after optimization using the proposed model. Moreover, the sensitivity of influencing factors of the proposed model is also analyzed. The results show that when the traffic flow is increased by 60% of the original traffic flow, the optimization effect of the model is more significant. However, when the lane capacity is more than 1300 pcu/h, the vehicle delay will increase slowly. To sum up, this method can improve the regional traffic efficiency of the traffic-stressed lanes and further promote the full utilization of space-time resources of the road network.

Suggested Citation

  • Fei Zhao & Liping Fu & Xiaofeng Pan & Tae J. Kwon & Ming Zhong, 2022. "Investigating the Effect of Network Traffic Signal Timing Strategy with Dynamic Variable Guidance Lanes," Sustainability, MDPI, vol. 14(15), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9394-:d:877470
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