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A Quasi-Poisson Approach on Modeling Accident Hazard Index for Urban Road Segments

机译:城市道路路段事故危险指数建模的拟泊松方法

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In light of the recently emphasized studies on risk evaluation of crashes, accident counts under specific transportation facilities are adopted to reflect the chance of crash occurrence. The current study introduces more comprehensive measure with the supplement information of accidental harmfulness into the expression of accident risks which are also named Accident Hazard Index (AHI) in the following context. Before the statistical analysis, datasets from various sources are integrated under a GIS platform and the corresponding procedures are presented as an illustrated example for similar analysis. Then, a quasi-Poisson regression model is suggested for analyses and the results show that the model is appropriate for dealing with overdispersed count data and several key explanatory variables were found to have significant impact on the estimation of AHI. In addition, the effect of weight on different severity levels of accidents is examined and the selection of the weight is also discussed.
机译:根据最近关于碰撞事故风险评估的研究,采用特定运输设施下的事故计数来反映碰撞事故发生的可能性。当前的研究将更全面的措施与事故危害的补充信息一起引入事故风险的表达中,在以下情况下也称为事故危害指数(AHI)。在进行统计分析之前,将来自各种来源的数据集集成在GIS平台下,并给出了相应的步骤,作为进行类似分析的示例。然后,提出了拟泊松回归模型进行分析,结果表明该模型适用于处理过度分散的计数数据,并且发现几个关键的解释变量对AHI的估计有重大影响。此外,还研究了重量对不同严重程度事故的影响,并讨论了重量的选择。

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