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Safety analysis of traffic flow characteristics of highway tunnel based on artificial intelligence flow net algorithm

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Abstract

With the increasing development of traffic nowadays, traffic safety has become the focus of current research. Among them, highway tunnel is a special geographical obstacle on freeway, so it is very important to analyze its traffic flow security. Based on this, his paper studies the characteristics of highway tunnel traffic safety from the angle of artificial intelligence network algorithm; the improvements were made on the basis the classic FCM clustering algorithm in artificial intelligence net according to the unique complexity of highway tunnel; and an improved FCM clustering algorithm was proposed; then indexes, data and traffic flow clustering in freeway tunnel were studied in detail. Based on the actual traffic flow data, an example is given. According to the improved FCM clustering algorithm, the safety data of expressway tunnel was obtained, which was used to divide the safety area for highway tunnel. To sum up, the research in this paper can provide a strong theoretical basis for the safety characteristics of freeway tunnel traffic flow, and it is of great significance.

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Authors and Affiliations

  1. School of Safety Science and Engineering, Nanjing University of Technology, Nanjing, 21000, Jiangsu, China

    Lingling Tian

  2. Nanjing University of Technology, Nanjing, 21000, Jiangsu, China

    Juncheng Jiang

  3. York University, Toronto, M3J 1P3, Canada

    L. Tian

Authors
  1. Lingling Tian
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  2. Juncheng Jiang
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  3. L. Tian
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Correspondence to Juncheng Jiang.

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Tian, L., Jiang, J. & Tian, L. Safety analysis of traffic flow characteristics of highway tunnel based on artificial intelligence flow net algorithm. Cluster Comput 22 (Suppl 1), 573–582 (2019). https://doi.org/10.1007/s10586-017-1340-3

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  • DOI: https://doi.org/10.1007/s10586-017-1340-3

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