Based on the empirical path set generated from the track data of dangerous goods vehicles, we present a new method for the risk analysis and path optimization of dangerous goods transportation. First of all, by exploring the travel rules of dangerous goods transport vehicles hidden in the track data, combined with the path set generation algorithm, the method of determining the empirical path set of dangerous goods transport is studied. Secondly, based on the empirical path set, mainly considering the travel rules of vehicles and people on the road, as well as the distribution of population and environment-sensitive areas along the road, a dual objective path selection model is proposed to comprehensively measure the risk and cost of road transportation under time-varying conditions. On this basis, given the principle of avoiding high-risk transportation paths, a comprehensive method of integrating multiple algorithms is proposed to solve the model. Finally, taking a road network as an example, the practicability and effectiveness of the proposed method are verified. The method proposed takes both practicability and safety into account. Based on the experience path set, considering the time-varying characteristics, the decision-maker could choose the appropriate transportation path of dangerous goods according to different preferences, so as to better solve the problem of path selection for dangerous goods transportation.

中文翻译：

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基于经验路径集的危险品运输风险分析与路径优化

基于危险品车辆跟踪数据生成的经验路径集，提出了危险品运输风险分析和路径优化的新方法。首先，通过探索隐藏在轨道数据中的危险品运输车辆的行驶规则，结合路径集生成算法，研究确定危险品运输经验路径集的方法。其次，基于经验路径集，主要考虑道路上车辆和人员的出行规则，以及道路上人口和环境敏感区域的分布，提出了一种双目标路径选择模型来综合测量时变条件下道路运输的风险和成本。在此基础上，根据避免高风险运输路径的原则，提出了一种综合多种算法的综合方法来求解该模型。最后以路网为例，验证了该方法的实用性和有效性。所提出的方法同时考虑了实用性和安全性。基于经验路径集，决策者可以考虑时变特征，根据不同的偏好选择合适的危险品运输路径，从而更好地解决危险品运输的路径选择问题。所提出的方法同时考虑了实用性和安全性。基于经验路径集，决策者可以考虑时变特征，根据不同的偏好选择合适的危险品运输路径，从而更好地解决危险品运输的路径选择问题。所提出的方法同时考虑了实用性和安全性。基于经验路径集，决策者可以考虑时变特征，根据不同的偏好选择合适的危险品运输路径，从而更好地解决危险品运输的路径选择问题。