Wang Xuesong, Abdel-Aty Mohamed
Department of Civil & Environmental Engineering, University of Central Florida, Orlando, FL 32816-2450, United States.
Accid Anal Prev. 2008 Sep;40(5):1674-82. doi: 10.1016/j.aap.2008.06.001. Epub 2008 Jun 25.
The purpose of this study is to examine left-turn crash injury severity. Left-turning traffic colliding with opposing through traffic and with near-side through traffic are the two most frequently occurring conflicting patterns among left-turn crashes (Patterns 5 and 8 in the paper, respectively), and they are prone to be severe. Ordered probability models with either logit or probit function is commonly applied in crash injury severity analyses; however, its critical assumption that the slope coefficients do not vary over different alternatives except the cut-off points is usually too restrictive. Partial proportional odds models are generalizations of ordered probability models, for which some of the beta coefficients can differ across alternatives, were applied to investigate Patterns 5 and 8, and the total left-turn crash injuries. The results show that partial proportional odds models consistently perform better than ordered probability models. By focusing on specific conflicting patterns, locating crashes to the exact crash sites and relating approach variables to crash injury in the analysis, researchers are able to investigate how these variables affect left-turn crash injuries. For example, opposing through traffic and near-side crossing through traffic in the hour of collision were identified significant for Patterns 5 and 8 crash injuries, respectively. Protected left-turn phasing is significantly correlated with Pattern 5 crash injury. Many other variables in driver attributes, vehicular characteristics, roadway geometry design, environmental factors, and crash characteristics were identified. Specifically, the use of the partial proportional formulation allows a much better identification of the increasing effect of alcohol and/or drug use on crash injury severity, which previously was masked using the conventional ordered probability models.
本研究的目的是检验左转碰撞事故的伤害严重程度。左转车辆与对向直行车以及与左侧直行车相撞，是左转碰撞事故中最常出现的两种冲突模式（分别为本论文中的模式5和模式8），而且它们往往较为严重。在碰撞事故伤害严重程度分析中，通常会应用带有逻辑函数或概率单位函数的有序概率模型；然而，其关键假设，即除了分界点之外，斜率系数在不同备选方案中不会变化，通常过于严格。部分比例优势模型是有序概率模型的推广，其中一些β系数在不同备选方案中可能不同，该模型被用于研究模式5和模式8以及总的左转碰撞事故伤害情况。结果表明，部分比例优势模型的表现始终优于有序概率模型。通过在分析中关注特定的冲突模式、将碰撞事故定位到确切的碰撞地点，并将接近碰撞时的变量与碰撞伤害联系起来，研究人员能够探究这些变量如何影响左转碰撞事故的伤害情况。例如，对于模式5和模式8的碰撞伤害，分别确定了碰撞时的对向直行车流量和左侧交叉直行车流量具有显著影响。受保护的左转相位与模式5的碰撞伤害显著相关。还确定了驾驶员属性、车辆特征、道路几何设计、环境因素和碰撞特征等许多其他变量。具体而言，使用部分比例公式能够更好地识别酒精和/或药物使用对碰撞伤害严重程度的加剧影响，而这在以前使用传统的有序概率模型时被掩盖了。
