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Arterial Coordination Control Optimization Based on AM–BAND–PBAND Model

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  • Min Li

    (School of Mechanical and Automobile Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Qingdao 266520, China)

  • Dijia Luo

    (School of Mechanical and Automobile Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Qingdao 266520, China)

  • Bilong Liu

    (School of Mechanical and Automobile Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Qingdao 266520, China)

  • Xilong Zhang

    (School of Mechanical and Automobile Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Qingdao 266520, China)

  • Zhen Liu

    (Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle, Hubei University of Arts and Science, Xiangyang 441053, China)

  • Mengshan Li

    (School of Mechanical and Automobile Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Qingdao 266520, China)

Abstract

The green wave coordinated control model has evolved from the basic bandwidth maximization model to the multiweight approach to an asymmetrical multiband model and a general signal progression model with phase optimization to improve the operational efficiency of urban arterial roads and reduce driving delays and the amount of exhaust gas generated by vehicles queuing at intersections. However, most of the existing green wave models of arterial roads are based on a single phase pattern and little consider the optimization of the combination of multiple phase patterns. Initial queue clearing time is also considered at the green wave progression line in the time–space diagram, which leads to a waste of green light time. This study proposes a coordination control optimization method based on an asymmetrical multiband model with phase optimization to address the abovementioned problem. This model optimizes four aspects in the time–distance diagram: phase pattern selection, phase sequence, offset, and queue clearing time. Numerical experiments were conducted using the VISSIM micro traffic simulation tool for intersections along Kunlunshan South Road in Qingdao, and the effect of green wave coordination was evaluated using hierarchical analysis and compared with the signal-timing schemes generated by the four models: the multiweight approach, the improved multiweight approach, an asymmetrical multiband model, and a general signal progression model with phase optimization. The results show that an asymmetrical multiband model with phase optimization obtains a total bandwidth of 314 s in both directions. In the outbound direction, average number of stops, average travel speed, average travel time, and average delay time improve by 16%, 7.9%, 17.9%, and 15.6%, respectively. In the inbound direction, they improve by 43.7%, 16.1%, 40.7%, and 36%, respectively. Polluting gas emissions and fuel consumption improve by 17.9%. The applicability of the optimization method under different traffic flow conditions is analyzed, and results indicate a clear control effect when the traffic volume is moderate and the turning vehicles on the feeder roads are few. This work can provide a reference for the optimization of subsequent arterial signal coordination and also has indirect significance for environmental protection to a certain extent.

Suggested Citation

  • Min Li & Dijia Luo & Bilong Liu & Xilong Zhang & Zhen Liu & Mengshan Li, 2022. "Arterial Coordination Control Optimization Based on AM–BAND–PBAND Model," Sustainability, MDPI, vol. 14(16), pages 1-24, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10065-:d:888124
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    References listed on IDEAS

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    1. John T. Morgan & John D. C. Little, 1964. "Synchronizing Traffic Signals for Maximal Bandwidth," Operations Research, INFORMS, vol. 12(6), pages 896-912, December.
    2. John A. Hillier & Richard Rothery, 1967. "The Synchronization of Traffic Signals for Minimum Delay," Transportation Science, INFORMS, vol. 1(2), pages 81-94, May.
    3. Shenzhen Ding & Xumei Chen & Lei Yu & Xu Wang, 2019. "Arterial Offset Optimization Considering the Delay and Emission of Platoon: A Case Study in Beijing," Sustainability, MDPI, vol. 11(14), pages 1-19, July.
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    Cited by:

    1. Maksymilian Mądziel, 2023. "Vehicle Emission Models and Traffic Simulators: A Review," Energies, MDPI, vol. 16(9), pages 1-31, May.
    2. Minjung Kim & Max Schrader & Hwan-Sik Yoon & Joshua A. Bittle, 2023. "Optimal Traffic Signal Control Using Priority Metric Based on Real-Time Measured Traffic Information," Sustainability, MDPI, vol. 15(9), pages 1-18, May.
    3. Suhaib Alshayeb & Aleksandar Stevanovic & Nikola Mitrovic & Elio Espino, 2022. "Traffic Signal Optimization to Improve Sustainability: A Literature Review," Energies, MDPI, vol. 15(22), pages 1-24, November.

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