Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
Accid Anal Prev. 2024 Dec;208:107785. doi: 10.1016/j.aap.2024.107785. Epub 2024 Sep 14.
Crash type, a key contributory factor of crash injury severity level, is typically included in crash severity models as an explanatory variable. However, certain unobserved factors could influence both the crash type and crash injury severity simultaneously. As such, there could exist an endogenous effect of crash type on crash injury severity. The present paper investigates this hypothesis using data from highway ramp areas. These locations tend to be crash-prone because of the frequent lane changes and speed differentials associated with merging, diverging, and weaving of vehicles at those locations. Conventional approaches used in past ramp safety studies modeled crash type and crash injury severity separately, not addressing the endogenous effect of crash type on crash severity at these locations. In this study, a random parameter recursive bivariate probit model is proposed to model the crash type (hit-object and rollover) and crash injury severity at ramp areas simultaneously and to account for any endogenous effect of crash type. The study used highway crash data from ramp areas at highway located in North Carolina from 2016 to 2018. The results indicate that the proposed model can and does capture the endogenous effect of crash type. The likelihood of injury for a rollover crash would be underestimated if endogeneity were not considered. Other exogenous variables including aberrant driving behavior, safety belt, road surface condition, lighting condition, area type, crash location, and ramp type that affect the type and injury severity of crashes at highway ramp areas were identified. The exogenous variables that are significant only for the crash type, such as vehicle type, and speed limit, were detected to have indirect effects on the crash injury severity. Furthermore, the effects of individual heterogeneity of the explanatory variables are considered. Female drivers and old drivers are statistically significant in the means of random parameters. The findings shed light on the potential need and effectiveness of prospective traffic management and control measures to mitigate crash risk at highway ramp areas.
碰撞类型是碰撞严重程度的一个关键影响因素，通常作为解释变量包含在碰撞严重程度模型中。然而，某些未被观察到的因素可能同时影响碰撞类型和碰撞严重程度。因此，碰撞类型对碰撞严重程度可能存在内生效应。本文利用来自高速公路匝道区域的数据来检验这一假设。这些位置由于车辆在这些位置的合并、分流和交织时频繁的车道变换和速度差异，往往容易发生碰撞。过去的匝道安全研究中使用的传统方法分别对碰撞类型和碰撞严重程度进行建模，没有解决这些位置碰撞类型对碰撞严重程度的内生效应。在这项研究中，提出了一种随机参数递归二元概率模型，用于同时对匝道区域的碰撞类型（碰撞对象和翻车）和碰撞严重程度进行建模，并考虑到碰撞类型对碰撞严重程度的任何内生效应。该研究使用了 2016 年至 2018 年北卡罗来纳州高速公路匝道区域的公路碰撞数据。结果表明，所提出的模型可以并且确实捕捉到了碰撞类型的内生效应。如果不考虑内生性，翻车碰撞的受伤可能性将会被低估。其他影响高速公路匝道区域碰撞类型和伤害严重程度的外生变量，包括异常驾驶行为、安全带、路面状况、照明状况、区域类型、碰撞位置和匝道类型，也被识别出来。仅对碰撞类型有影响的外生变量，如车辆类型和限速，被检测到对碰撞伤害严重程度有间接影响。此外，还考虑了解释变量个体异质性的影响。女性驾驶员和老年驾驶员在随机参数的均值上具有统计学意义。研究结果表明，有必要和有效性采取前瞻性的交通管理和控制措施，以降低高速公路匝道区域的碰撞风险。
