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Research on Calculating Traffic Capacity in Extra-Long Subsea Tunnels—A Case Study of the Qingdao Jiaozhou Bay Subsea Tunnel

Author

Listed:
  • Ruru Xing

    (College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

  • Zimu Li

    (College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

  • Xiaoyu Cai

    (College of Smart City, Chongqing Jiaotong University, Chongqing 400074, China)

  • Xiaonan Rong

    (College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China)

  • Tao Yang

    (Chongqing Linggu Transportation Technology Co., Ltd., Chongqing 400064, China)

  • Bo Peng

    (College of Smart City, Chongqing Jiaotong University, Chongqing 400074, China)

Abstract

Analyzing the traffic capacity of extra-long tunnels is crucial in assessing their sustainable capacity. However, previous studies on tunnel capacity mainly considered the influence of a single factor, ignoring the interaction between multiple factors, which cannot reflect the actual tunnel capacity. Therefore, considering the influence of multiple factors, this paper constructs an actual capacity calculation model for extra-long tunnels. Firstly, by combining hierarchical analysis and the entropy method, we determined the key factors that influence the capacity of extra-long tunnels. Secondly, based on the constructed traffic simulation model, we constructed an actual capacity model of extra-long tunnels by using multiple non-linear regression equations and tested the goodness of fit with the help of the misfit term. Finally, we determined the key correction coefficients of the model using the difference proportion method. Taking Qingdao Jiaozhou Bay undersea Tunnel as an example, the research results show that the method proposed in this paper can accurately determine the tunnel capacity with an error of less than 4%, providing a theoretical basis and practical guidance for the management and control of the tunnel’s sustainable carrying capacity after traffic congestion.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7543-:d:1139403
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    References listed on IDEAS

    as
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    2. 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.
    3. Ghiasi, Amir & Hussain, Omar & Qian, Zhen (Sean) & Li, Xiaopeng, 2017. "A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 266-292.
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    5. Edward S. Olcott, 1955. "The Influence of Vehicular Speed and Spacing on Tunnel Capacity," Operations Research, INFORMS, vol. 3(2), pages 147-167, May.
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