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The role of striking and struck vehicles in side crashes between vehicles: Bayesian bivariate probit analysis in China

机译:撞击和撞击车辆在车辆侧面碰撞中的作用:中国的贝叶斯双变量概率分析

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Objective: Side crashes between vehicles which usually lead to high casualties and property loss, rank first among total crashes in China. This paper aims to identify the factors associated with injury severity of side crashes at intersections and to provide suggestions for developing countermeasures to mitigate the levels of injuries.Method: In order to investigate the role of striking and struck vehicles in side crashes simultaneously, bivariate probit model was proposed and Bayesian approach was employed to evaluate the model, compared to the corresponding univariate probit model.Data: Crash data from Beijing, China for the period 2009-2012 were used to carry out the statistical analysis. Based on the investigation with vehicles and data analysis on events, 130 intersection side crash cases were selected to form a specific dataset. Then, the influence of human, vehicles, roadway and environmental variables on crash severity was examined by means of bivariate probit regression within Bayesian framework.Results: The effects of the factors on striking vehicle drivers and struck vehicle drivers were considered separately and simultaneously to find more targeted conclusions. The statistical analysis revealed vehicle type, lane number, no non-motorized lane and speeding have the corresponding influence on the injury severity of striking vehicles, while time of day and vehicle type of struck vehicles increased the likelihood of being injured.Conclusions: From the results it can be concluded that there indeed exists correlation between striking and struck vehicles in side crashes, although the correlation is not so strong. Importantly, Bayesian bivariate probit model can address the role of striking and struck vehicles in side crashes simultaneously and can accommodate the correlation clearly, which extends the range of univariate probit analysis. The general and empirical countermeasures are presented to improve the safety at intersections.
机译:目标:车辆之间的侧撞通常会导致高人员伤亡和财产损失,在中国全部撞车事故中排名第一。本文旨在找出与交叉路口侧撞事故严重程度相关的因素,并为制定减轻事故伤害水平的对策提供建议。方法:为了研究撞车和撞车在侧撞事故中的作用,双变量概率与相应的单变量概率模型相比,该模型被提出并采用贝叶斯方法进行了评估。数据:使用2009-2012年中国北京的碰撞数据进行统计分析。基于车辆调查和事件数据分析,选择了130个路口侧撞事故案例以形成特定的数据集。然后,通过贝叶斯框架内的双变量概率回归,研究了人,车辆,道路和环境变量对碰撞严重性的影响。结果:分别考虑了因素对撞击车辆驾驶员和撞击车辆驾驶员的影响,以找出有针对性的结论。统计分析表明,车辆类型,车道号,无机动车道和超速对撞车的伤害严重程度有相应的影响,而一天中的时间和被撞车的车型增加了受伤的可能性。结果可以得出结论,尽管侧面碰撞中的碰撞车辆与碰撞车辆之间确实存在相关性,但相关性并不强。重要的是,贝叶斯双变量概率模型可以同时解决碰撞和撞车在侧面碰撞中的作用,并且可以清楚地容纳相关性,从而扩展了单变量概率分析的范围。提出了一般和经验对策,以提高十字路口的安全性。

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