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Study on the Design of Variable Lane Demarcation in Urban Tunnels

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  • Song Fang

    (College of Locomotive and Vehicle, Nanjing Vocational Institute of Railway Technology, Nanjing 210031, China
    College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Linghong Shen

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Jianxiao Ma

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Chubo Xu

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

Abstract

In order to alleviate the influence of low-speed vehicles on tunnel safety, this paper discusses the setting method of variable lane boundaries in urban tunnels. VISSIM simulation software is used to analyze the influence of low-speed vehicles on tunnel traffic flow when lane changes are allowed and when lane changes are prohibited. The results show that the influence of low-speed vehicles on the average speed of traffic flow in urban tunnels is the greatest, and the influence of low-speed vehicles on the average speed of traffic flow can be significantly alleviated when lane changes are allowed in the lane dividing line. When the speed of low-speed vehicles is 40 km/h and the variable lane is set, the average delay time is reduced by 30–50%. The existence of low-speed vehicles significantly increased the average delay time of the local lane, and the lower the vehicle speed and the greater the road traffic volume, the longer the average delay time. When the speed of low-speed vehicles is 40 km/h and the traffic volume is 1200 pcu/h, the traffic density of the right-hand lane decreases by 43.5% after the variable lane is set. While lane changing is prohibited, the presence of low-speed vehicles causes a backlog of vehicles in the rear of the lane, which leads to a significant increase in traffic density. Setting lane-changing permits can alleviate the impact of low-speed vehicles on traffic flow. The research results can provide a scientific basis for the operation and management of urban tunnels.

Suggested Citation

  • Song Fang & Linghong Shen & Jianxiao Ma & Chubo Xu, 2022. "Study on the Design of Variable Lane Demarcation in Urban Tunnels," Sustainability, MDPI, vol. 14(9), pages 1-12, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5682-:d:811020
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    References listed on IDEAS

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    1. Li, Xin-Gang & Jia, Bin & Gao, Zi-You & Jiang, Rui, 2006. "A realistic two-lane cellular automata traffic model considering aggressive lane-changing behavior of fast vehicle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 479-486.
    2. Ma, Yanli & Zhang, Peng & Hu, Baoyu, 2019. "Active lane-changing model of vehicle in B-type weaving region based on potential energy field theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    3. Jian Wang & Jian-Xun Ding & Qin Shi & Reinhart D. Kühne, 2016. "Lane-changing behavior and its effect on energy dissipation using full velocity difference model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(02), pages 1-14, February.
    4. Song Fang & Jianxiao Ma, 2021. "Influence Range and Traffic Risk Analysis of Moving Work Zones on Urban Roads," Sustainability, MDPI, vol. 13(8), pages 1-14, April.
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    Cited by:

    1. Chubo Xu & Jianxiao Ma & Xiang Tang, 2022. "A Simulation-Based Study of the Influence of Low-Speed Vehicles on Expressway Traffic Safety," Sustainability, MDPI, vol. 14(19), pages 1-19, September.
    2. Ruru Xing & Zimu Li & Xiaoyu Cai & Xiaonan Rong & Tao Yang & Bo Peng, 2023. "Research on Calculating Traffic Capacity in Extra-Long Subsea Tunnels—A Case Study of the Qingdao Jiaozhou Bay Subsea Tunnel," Sustainability, MDPI, vol. 15(9), pages 1-29, May.

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