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The assessment of traffic accident risk based on grey relational analysis and fuzzy comprehensive evaluation method

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Abstract

The traffic accident risk includes three aspects, traffic accident probability, traffic accident severity, and traffic accident trend respectively. In this paper, nine indicators are selected to evaluate the traffic accident risk. The grey relational analysis method was used to determine the weights, and the fuzzy comprehensive evaluation method was used to calculate the risk. These methods were applied to assess the comprehensive risk of traffic accident in 31 provinces in China. The results show that the average value of traffic accident risk is 55.17. Nine provinces which are located in the northwest area and southeast area belong to the high-risk level. The medium-risk areas are widely distributed in the central, northeast, and southwest regions. The low-risk areas are Jilin, Neimenggu, Guizhou, and Beijing. The results have great significance for the measurement and management of regional traffic accident risk.

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Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (NSFC) (Nos. 41301580, 41401600), Youth Foundation of Taiyuan University of Technology (2015QN086), the Qualified Personnel Foundation of Taiyuan University of Technology (No. TYUT-RC201110A). We gratefully acknowledge the thoughtful comments of the editor and reviewers.

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Authors and Affiliations

  1. College of Economics and Management, Taiyuan University of Technology, Jinzhong, 030600, China

    Yaolong Liu & Xiaoli Huang

  2. Institute of Politics and Law, Taiyuan University of Technology, Jinzhong, 030600, China

    Jin Duan

  3. Meteorological Disaster Prevention Technology Center of Shanxi Province, Taiyuan, 030002, China

    Huaming Zhang

Authors
  1. Yaolong Liu
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  2. Xiaoli Huang
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  3. Jin Duan
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  4. Huaming Zhang
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Correspondence to Yaolong Liu.

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Liu, Y., Huang, X., Duan, J. et al. The assessment of traffic accident risk based on grey relational analysis and fuzzy comprehensive evaluation method. Nat Hazards 88, 1409–1422 (2017). https://doi.org/10.1007/s11069-017-2923-2

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  • DOI: https://doi.org/10.1007/s11069-017-2923-2

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