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首页> 外文期刊>Accident Analysis & Prevention >Bivariate ordered-response probit model of driver's and passenger's injury severities in collisions with fixed objects.
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Bivariate ordered-response probit model of driver's and passenger's injury severities in collisions with fixed objects.

机译：与固定物体碰撞时驾驶员和乘客的伤害严重程度的双变量有序响应概率模型。

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A bivariate ordered-response probit model of driver's and most severely injured passenger's severity (IS) in collisions with fixed objects is developed in this study. Exact passenger's IS is not necessarily observed, especially when only most severe injury of the accident and driver's injury are recorded in the police reports. To accommodate passenger IS as well, we explicitly develop a partial observability model of passenger IS in multi-occupant vehicle (HOV). The model has consistent coefficients for the driver IS between single-occupant vehicle (SOV) and multiple-occupant vehicle accidents, and provides more efficient coefficient estimates by taking into account the common unobserved factors between driver and passenger IS. The results of the empirical analysis using 4-year statewide accident data in Washington State reveal the effects of driver's characteristics, vehicle attributes, types of objects, and environmental conditions on both driver and passenger IS, and that their IS have different elasticities to some of the risk factors.
机译：在这项研究中，开发了驾驶员和受重伤最严重的乘客的严重程度（IS）的双变量有序响应概率模型。不必严格遵守乘客的IS，尤其是在警察报告中仅记录了事故中最严重的伤害和驾驶员的伤害时。为了也适应乘客IS，我们显式地开发了多人车辆（HOV）中乘客IS的局部可观察性模型。该模型对单人车辆（SOV）和多人车辆事故之间的驾驶员IS具有一致的系数，并且通过考虑驾驶员与乘客IS之间的常见未观察因素，提供了更有效的系数估计。使用华盛顿州4年全州事故数据进行的实证分析结果表明，驾驶员的特性，车辆属性，物体类型和环境条件对驾驶员和乘客IS的影响，并且他们的IS对某些IS具有不同的弹性危险因素。

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