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Assessing Casualty Risk of Railroad-Grade Crossing Crashes Using Zero-Inflated Poisson Models

机译:使用零膨胀泊松模型评估铁路平交道口事故的人员伤亡风险

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摘要

A railroad grade crossing (RGC) is a spatial location where rail and highway users share the right-of-way. A significant number of traffic crashes and severe consequences at RGCs have signaled the need for appropriate models to investigate the key factors associated with the casualty risk level at an RGC in terms of the number of fatalities or injuries caused by one or more crashes in a specific time period. This study used a zero-inflated Poisson regression model to describe the relationship between the extra-zero count fatality or injury data and explanatory variables collected at 592 RGCs in Taiwan. The annual averaged daily traffic and the presence of Guidance Sign 31 were significantly associated with the probability of no fatality or injury encountered at an RGC; if an RGC was at risk of a fatality or injury, the number of daily trains, crossing angle, and Guidance Sign 31 significantly influenced the expected total number of fatalities or injuries caused by traffic crashes. The empirical results indicated that traffic exposure and traffic signage have significant effects on the risk levels of casualties at an RGC.
机译:铁路平交道口(RGC)是一个空间位置,铁路和公路使用者共享路权。大量的交通事故和对RGC的严重后果表明,有必要采用适当的模型来研究与RGC造成人员伤亡风险水平相关的关键因素,具体原因是特定地点一次或多次事故造成的死亡或伤害数量时间段。这项研究使用零膨胀的Poisson回归模型来描述零计数死亡或伤害数据与台湾592个RGC收集的解释变量之间的关系。每年的平均每日交通量和是否有指导标志31与RGC处没有死亡或受伤的可能性显着相关;如果RGC有死亡或受伤的危险,则每日火车的数量,交叉口角和指引标志31会严重影响交通事故造成的死亡或伤害的预期总数。实证结果表明,交通风险和交通标志对RGC的人员伤亡风险水平有重大影响。

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