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Risk coupling analysis of road transportation accidents of hazardous materials in complicated maritime environment

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  • Guo, Jian
  • Luo, Cheng
  • Ma, Kaijiang

Abstract

The complicated maritime environment and multiple risk coupling pose significant challenges to hazardous material transportation safety in coastal areas. This paper studies the risk coupling problems by analyzing 362 hazardous materials accidents. Firstly, the transportation risks are divided into 6 categories and 22 risk factors are identified. Then, the definition and types of risk coupling are determined. Finally, a novel risk coupling model is constructed by using analytic hierarchy process (AHP) and N-K model. AHP–N-K model is used to calculate the coupling degree of risk factors. Furthermore, the correlation mechanism between the risk values and the risk components in complicated maritime environment is analyzed. The results show that the risk of hazardous materials transportation has a gradually increasing trend with the increase of risk coupling factors. Owing to the risk coupling of driver factors and road environmental factors, the probability of accidents is high. The coupling risk of subjective and objective risk factors is more likely to cause accidents than subjective risk factors. The coupling effect of rainy days and curves with other risk factors is very strong.

Suggested Citation

  • Guo, Jian & Luo, Cheng & Ma, Kaijiang, 2023. "Risk coupling analysis of road transportation accidents of hazardous materials in complicated maritime environment," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:reensy:v:229:y:2023:i:c:s0951832022005087
    DOI: 10.1016/j.ress.2022.108891
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    6. Liwei Yuan & Di Chen & Sumin Li & Guolong Wang & Yanlin Li & Bin Li & Minghui Chen, 2024. "Coupled Analysis of Risk Factor for Tailing Pond Dam Failure Accident Based on N–K Model and SNA," Sustainability, MDPI, vol. 16(19), pages 1-20, October.
    7. Guo, Jian & Ma, Kaijiang, 2024. "Risk analysis for hazardous chemical vehicle-bridge transportation system: A dynamic Bayesian network model incorporating vehicle dynamics," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

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