山区双车道公路机动车碰撞事故严重度致因比较分析与预测

以云南山区双车道公路1740起碰撞事故数据为基础,将事故数据分为机动车与机动车、机动车与摩托车、机动车与非机动车3种类型,事故严重度划分为仅财产损失、轻伤、重伤或死亡事故3个等级,分别用部分优势比模型和有序Logit模型建立3类机动车碰撞事故严重度分析模型,对比分析不同等级事故的显著影响因素和模型的预测准确率,分析部分...

Comparative Analysis and Prediction of Motor Vehicle Crash Severity on Mountainous Two-lane Highways

This paper developed the motor vehicle crash severity prediction models on mountainous two-lane highways using the partial proportional odds model and the ordered Logit model. Based on 1740 cases of motor vehicle crashes in Yunnan province, the crash data was classified as motor vehicle and motor vehicle crash, motor vehicle and motorcycle crash, motor and non- motorized vehicle crash. The accident severity was classified as property damage only, minor injuries, and serious injuries or fatal. The comparative analysis of the significant factors and the model prediction accuracy relevant to each severity grade was carried out. The marginal effect analysis was also performed to investigate significant variables of the partial proportional odds model. The results show that the impact factors for different accident severity are significantly different for different vehicle types. Compared to the ordered Logit model, the partial proportional odds model could be used to find the hidden variables that are not following the proportional odds assumption. The average prediction accuracy using the partial proportional odds model are respectively 78.29%, 73.63% and 72.04% for motor vehicle and motor vehicle crash, motor vehicle and motorcycle crash, and motor and non-motorized vehicle crash. The accuracy is respectively improved by 14.54%, 5.65% and 3.32% compared to the ordered Logit model. The study provides references for highway safety administrations to proactively prevent accidents and reduce risks.