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Railway Signaling Safety Factors Quantitative Analysis Using an Improved 5M Model

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  • Haixiang Lin

    (Key Laboratory of Railway Industry of BIM Engineering and Intelligent for Electric Power, Traction Power Supply, Communication and Signaling, Lanzhou Jiaotong University, Lanzhou 730070, China
    School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Tengfei Yuan

    (SHU-UTS SILC Business School, Shanghai University, Shanghai 201800, China
    Shanghai pleEngineering Research Center of Urban Infrastructure Renewal, Shanghai 200032, China)

  • Wansheng Bai

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Zhengxiang Zhao

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Ran Lu

    (School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Xinqin Li

    (Institute of Computing Technology, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China)

  • Qi Lin

    (School of Materials Science and Engineering, Beihang University, Beijng 100191, China)

Abstract

In order to improve the sustainability of modern cities, the safe operation of rail transportation is critical. Meanwhile, rail signaling safety is also fundamental for rail transportation, and quantitative analysis of railway signaling safety factors can guarantee this basis. To achieve this, this research proposes an improved rail signaling 5M (Management-Machine-Man-Media-Mission) accident cause hierarchical model, which can make up for the previous lack of objectivity and statistics. According to the demands of rail signaling accident analysis, this research collects and classifies the rail signaling accident data from 2000 to 2017. Then, the hierarchical association rule method is used to calculate the relationships between the 5M factors, and the factor analysis method is applied to measure the weights of the 5M subfactors. Therefore, the safety evaluation index system for railway signaling system is established. The results show that the Management element is the most important factor in rail signaling accidents, while the Mission element is dispensable. Moreover, the subfactors, such as the equipment material, safety management, external humans affected, and hidden danger should also not be ignored. Eventually, the rail signaling accidents analysis is conducted between the 5M model and the improved 5M model; the comparison shows that the improved 5M can not only improve the safety factors influence rate by more than 84.64%, but it can also improve the railway signaling safety, which can provide strong support for the safe operation of rail transportation and sustainable development of a modern city.

Suggested Citation

  • Haixiang Lin & Tengfei Yuan & Wansheng Bai & Zhengxiang Zhao & Ran Lu & Xinqin Li & Qi Lin, 2022. "Railway Signaling Safety Factors Quantitative Analysis Using an Improved 5M Model," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6247-:d:820146
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    References listed on IDEAS

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    1. Hsu, Yueh-Ling & Liu, Te-Chang, 2012. "Structuring risk factors related to airline cabin safety," Journal of Air Transport Management, Elsevier, vol. 20(C), pages 54-56.
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    Cited by:

    1. Liu, Yanyan & Li, Keping & Yan, Dongyang, 2024. "Quantification analysis of potential risk in railway accidents: A new random walk based approach," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Silvestar Grabušić & Danijela Barić, 2023. "A Systematic Review of Railway Trespassing: Problems and Prevention Measures," Sustainability, MDPI, vol. 15(18), pages 1-23, September.

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