Risk exists in the whole process of before, during and after the accident of hazardous materials (hazmat) transportation, which usually lead to serious consequences. Risk assessment is a significant way to identify hidden dangers and their interactions, which can curb accidents happen. The purpose of this study is to analyze the risk factors of hazmat road transportation accidents through entire process risk assessment and propose management strategies. Considering nodes dependency, i.e. accident type and rescue time, this study applies the concept of Tree Augmented Naive Bayes (TAN) and built a hazmat road transportation Bayesian network (HRT-BN). Mutual information and model validation are carried on to better facilitate convenient inference and diagnosis of risk nodes and their interactions. Results show that in causal inference with single factors, human risk factors are more significant, which are likely to lead to leakage accident with slight consequences and short rescue time (s2). Meanwhile, with coupling effect of multiple factors, accident types become more diverse with serious consequence. In diagnostic inference, the rescue time is linked to seasonal and regional factors, e.g., the rescue time in summer is longer. Based on these analysis, targeted recommendations have been proposed at the end. This study provides a whole angle of view to assess risks in hazmat transportation, which has significant practical feasibility for risk management and planning of hazmat road transportation.

中文翻译：

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使用贝叶斯网络对事故前、事故中和事故后危险品道路运输事故进行风险评估


危险品运输事故前、中、后全过程都存在风险，往往会导致严重后果。风险评估是识别隐患及其相互作用、遏制事故发生的重要手段。本研究的目的是通过全过程风险评估，分析危险品道路运输事故的风险因素，并提出管理策略。考虑节点依赖性，即事故类型和救援时间，本研究应用树增强朴素贝叶斯（TAN）的概念，构建了危险品道路运输贝叶斯网络（HRT-BN）。进行互信息和模型验证，更好地方便对风险节点及其相互作用进行推理和诊断。结果表明，在单因素因果推断中，人为危险因素更为显着，容易导致后果轻微、救援时间短的泄漏事故（s2）。同时，在多种因素的耦合作用下，事故类型更加多样化，后果也更加严重。在诊断推断中，救援时间与季节和地区因素有关，如夏季救援时间较长。基于这些分析，最后提出了有针对性的建议。本研究为危险品运输风险评估提供了一个整体视角，对于危险品道路运输风险管理和规划具有重要的现实可行性。