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驾驶疲劳对危险化学品道路运输事故风险的影响规律

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近年来,随着危险化学品使用量的急剧攀升,危险化学品道路运输事故率也呈现上升的趋势,且此类事故的发生往往会导致严重后果.为研究危险化学品道路运输事故动态风险变化规律,在修正贝叶斯网络模型基础上,利用2017-2021年历史数据进行机器学习,根据驾驶疲劳程度计算得到"驾驶人行为"动态节点的状态转移概率矩阵,建立基于动态贝叶斯网络(Dynamic Bayesian Network,DBN)的危险化学品道路运输动态风险预测模型并进行推理分析.研究显示:在驾驶3 h内,驾驶人"疲劳驾驶"发生概率随时间推移而增加,但增幅有所下降;在最常见情境下,随驾驶人"疲劳驾驶"概率增加,"侧翻"和"碰撞"事故类型的发生概率明显增加,进而导致"泄漏"事故后果的发生概率有所增加;驾驶人"疲劳驾驶"概率增加会导致"有伤亡事故"发生概率增加,即加重事故的严重程度;在驾驶3 h内,"侧翻""碰撞""泄漏"和"有伤亡事故"发生概率的变化趋势与驾驶人"疲劳驾驶"发生概率的变化趋势一致.
Influence of driving fatigue on the risk of road transport accidents of hazardous chemicals
In recent years,with the rapid increase in the use of hazardous chemicals,the accident rate of hazardous chemicals in road transportation also shows an upward trend and such accidents often leads to serious accident consequences.To study the dynamic risk change law of road transport accidents of hazardous chemicals,A Bayesian network model was modified and verified and the historical data from 2017 to 2021 was used to conduct machine learning.According to the data of driving fatigue probability changes over time and using the Markov state transition probability matrix calculation method the state transition probability matrix of dynamic node"driver behavior"was obtained,for the dynamic risk prediction model of road transportation of hazardous-chemicals based on Dynamic Bayesian Network(DBN)was established and induced.The study shows that the accuracy of the improved model for the prediction results of the accident consequence nodes is higher or equal to eighty percent,indicating that the model is acceptable.Within three hours of driving,the probability of the driver's"fatigue driving"increases over time,but the rate of increase decreases.In the most common situation,with the nonlinear increase of the driver's probability of"fatigue driving"over time,the probability of"vehicle-rollover"and"crash"accidents increases significantly,which leads to a certain increase of the occurrence probability of the consequences of"leakage"accident.The increase in the probability of"fatigue driving"will lead to an increase in the probability of"casualty"accidents,that is,the increase in fatigue degree aggravates the severity of the accident.In addition,the changing trend of the occurrence probability of"vehicle-rollover","crash","leakage"and"casualty"accidents within the first three hours of driving are consistent with the changing trend of the occurrence probability of"fatigued driving".

safety livelihood scienceDynamic Bayesian NetworkExpectation Maximization(EM)algorithmhazardous chemicalsroad transportdynamic risk

陈文瑛、邵海莉、张沚芊

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首都经济贸易大学管理工程学院,北京 100070

城市群系统演化与发展的决策模拟研究北京市重点实验室,北京 100071

安全人体学 动态贝叶斯网络 最大期望(EM)算法 危险化学品 道路运输 动态风险

2024

安全与环境学报
北京理工大学 中国环境科学学会 中国职业安全健康协会

安全与环境学报

CSTPCD北大核心
影响因子:0.943
ISSN:1009-6094
年,卷(期):2024.24(2)
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