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

Author:

Xing Ruru1ORCID,Li Zimu1,Cai Xiaoyu2,Rong Xiaonan1,Yang Tao3,Peng Bo2

Affiliation:

1. College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China

2. College of Smart City, Chongqing Jiaotong University, Chongqing 400074, China

3. Chongqing Linggu Transportation Technology Co., Ltd., Chongqing 400064, 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.

Funder

Science and Technology Research Program of Chongqing Municipal Education Commission

Young Scientists Fund of the National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference23 articles.

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3. Yang, L., Wang, C., and Li, Z. (2022). Tunnel Traffic Evolution during Capacity Drop Based on High-Resolution Vehicle Trajectory Data. Algorithms, 15.

4. Use of public information for road-capacity reductions: A study of mediating strategies during tunnel rehabilitations in Oslo;Anders;Transportation,2020

5. Improving the existing roadway tunnels capacity by adding new tunnels—A structural approach;Mostafa;Arab. J. Geosci.,2018

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