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Understanding the topology of the road network and identifying key bayonet nodes to avoid traffic congestion

Author

Listed:
  • Lechen Guan

    (School of Mathematics, China University of Mining and Technology, No. 1, Daxue Road, Xuzhou, Jiangsu Province, P. R. China)

  • Dongle Wang

    (��Lianyungang JARI Electronics Co., Ltd., No. 18, Shenghu Road, Lianyungang, Jiangsu Province, P. R. China)

  • Hu Shao

    (School of Mathematics, China University of Mining and Technology, No. 1, Daxue Road, Xuzhou, Jiangsu Province, P. R. China)

  • Hao Fu

    (��Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Yuk Choi Road, Hung Hom, Kowloon, Hong Kong, P. R. China)

  • Jincheng Zhou

    (School of Mathematics, China University of Mining and Technology, No. 1, Daxue Road, Xuzhou, Jiangsu Province, P. R. China)

Abstract

Network topology is the basic for the development of traffic management and control. In a road network, bayonets with installation of surveillance facilities are key components to recognize traffic congestion from time to time. Therefore, identifying the essential bayonets in a road network becomes one of the most efficient ways to alleviate traffic congestion for traffic engineers and transport department. To do so, this paper aims to propose a novel sorting algorithm based on similarity measurements and traffic flow information to efficiently identify key bayonets in road networks. Our research results show that by analyzing the bayonet data in a fixed period of time in a medium-sized city of China, we have successfully identified the location of key bayonet points. Most of these key bayonet points are closed to residential areas and important traffic stations. The rank of these bayonet points can help the city managers better understand the topological characteristics of the road network as well as the propagation of congestion so as to make the traffic policies or control strategies for traffic congestion alleviation.

Suggested Citation

  • Lechen Guan & Dongle Wang & Hu Shao & Hao Fu & Jincheng Zhou, 2023. "Understanding the topology of the road network and identifying key bayonet nodes to avoid traffic congestion," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-22, March.
    • Handle: RePEc:wsi:ijmpcx:v:34:y:2023:i:03:n:s0129183123500316
    DOI: 10.1142/S0129183123500316
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    Cited by:

    1. Wang, Longjian & Zhang, Shuichao & Szűcs, Gábor & Wang, Yonggang, 2024. "Identifying the critical nodes in multi-modal transportation network with a traffic demand-based computational method," Reliability Engineering and System Safety, Elsevier, vol. 244(C).

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