School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China.
College of Transportation Engineering, Tongji University, Shanghai 200082, China.
Int J Environ Res Public Health. 2020 Feb 15;17(4):1259. doi: 10.3390/ijerph17041259.
Understanding the influence factors and related causation of hazardous materials can improve hazardous materials drivers' safety awareness and help traffic professionals to develop effective countermeasures. This study investigates the statistical distribution characteristics, such as types of hazardous materials transportation accidents, driver properties, vehicle properties, environmental properties, road properties. In total, 343 data regarding hazardous materials accidents were collected from the chemical accident information network of China. An ordered logit regression (OLR) model is proposed to account for the unobserved heterogeneity across observations. Four independent variables, such as hazardous materials drivers' properties, vehicle properties, environmental properties, and road properties are employed based on the OLR model, an ordered multinomial logistic regression (MLR) is estimated the OLR model parameters. Both parameter estimates and odds ratio (OR) are employed to interpret the impact of influence factors on the severity of hazardous materials accidents. The model estimation results show that 10 factors such as violations, unsafe driving behaviors, vehicle faults, and so on are closely related to accidents severity of hazardous materials transportation. Furthermore, three enforcement countermeasures are proposed to prevent accidents when transporting hazardous materials.
了解危险物品的影响因素及其相关因果关系,可以提高危险物品驾驶员的安全意识,并帮助交通专业人员制定有效的对策。本研究调查了危险物品运输事故的统计分布特征,如事故类型、驾驶员特性、车辆特性、环境特性和道路特性。本研究共从中国化学品事故信息网收集了 343 起危险物品事故数据。提出了有序逻辑回归(OLR)模型来解释观测值之间的未观察到的异质性。基于 OLR 模型,选取了危险物品驾驶员特性、车辆特性、环境特性和道路特性等四个自变量,对 OLR 模型参数进行了有序多项逻辑回归(MLR)估计。使用参数估计和优势比(OR)来解释影响因素对危险物品事故严重程度的影响。模型估计结果表明,违反规定、不安全驾驶行为、车辆故障等 10 个因素与危险物品运输事故的严重程度密切相关。此外,提出了三项执法对策,以防止危险物品运输过程中的事故。