基于线形与交通状态的山区高速公路追尾事故预测

Prediction of Rear-end Collision on Mountainous Expressway Based on Geometric Alignment and Traffic Conditions

为了进行山区高速公路追尾事故预测并识别追尾事故突出诱导因素,在对两车追尾事故进行类别划分并确定出典型两车追尾事故的基础上,分析了典型两车追尾事故的事故率与线形指标、车速差、大型车混入率、交通量等单一因素间的相关关系。鉴于单一因素与追尾事故率间的关系不能准确描述追尾事故发生规律的缺陷,建立了线形与交通状态组合条件下的追尾事故次数负二项分布预测模型,并给出了模型变量弹性系数计算方法,用以确定追尾事故的突出诱导因素。研究结果表明:基于线形与交通状态的追尾事故负二项分布预测模型能够对追尾事故进行准确预测,利用弹性系数计算方法确定出车速差、年平均日交通量(AADT)以及竖曲线半径为典型两车追尾事故的突出诱导因素。

In order to predict the rear-end collisio on mountainous expressway, typical two-vehicle the relationship between REC rate and the single vehicles, traffic composition and traffic volume between single element and REC rate could not binomial （NB） prediction model based on the developed, and the elasticity coefficient calcul induction factors was proposed. The r accurately. Speed difference, AADT factors for typical two-vehicle REC by n （REC） and identify its main induction factors REC was defined based on its classification, and geometric alignment indexes, speed difference of was analyzed respectively. As the relationship fully describe the occurrence of REC, negative geometric alignment and traffic condition was ation method esults show that the NB used to confirm the prominent prediction model can predict REC and vertical curve radius are confirmed to be prominent the elasticity coefficient calculation method.