In recent years, the construction of underground roads emerged in Megacities, which was regarded as an effective method to alleviate the imbalance between urban traffic supply and demand. A complicated underground road tunnel network, including tunnels, loop roads, and ramp, is semi-closed, resulting in weak navigation signals, which brings new challenges for urban traffic management. A multiscale simulation application framework from macro to micro has been proposed. It is used to evaluate the impact of different traffic management measures on the operation of urban underground traffic, providing a scientific basis for urban traffic planning and optimization. In macroscopic simulation, the Four-Step Method was used to predict the total vehicle volume, and the vehicle volume between each traffic zone was allocated based on the vehicle travel time. In microscopic simulation, VISSIM was used to simulate the underground space road tunnel network and identify congested road sections. Then, a road tunnel network under construction in a large underground space in Guangzhou, China, was selected as a research case. In this case, some schemes, such as variable information regarding traffic guidance signage systems and backup signal lights, were simulated and evaluated to evacuate congested vehicles. The simulation result indicates that these schemes can effectively reduce the average delay and increase the average speed.


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    Title :

    Research on Vehicle Evacuation in Large Underground Road Tunnel Network Based on Multiscale Traffic Simulation


    Contributors:
    Yang, Wenjie (author) / Hu, Mingwei (author) / Zhang, Yani (author) / Xie, Xiaofeng (author) / Wang, Daochu (author) / Chen, Yongsheng (author)

    Conference:

    24th COTA International Conference of Transportation Professionals ; 2024 ; Shenzhen, China


    Published in:

    CICTP 2024 ; 1882-1892


    Publication date :

    2024-12-11




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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