基于判别分析的高速公路交通安全实时评价指标

为了实时评价交通流变化对高速公路交通事故风险的影响,利用高精度交通流数据建立了高速公路交通安全实时评价指标.提取了美国加州I-880 N高速公路上采集间隔为30 s的实时交通流数据和事故数据,采用Fisher判别分析方法建立交通流参数的线性组合,以判别危险交通流状态.该线性组合被定义为高速公路交通安全实时评价指标,当该指标小于0时,代表危险交通流状态,有发生交通事故的风险；当该指标大于0时,代表正常交通流状态,没有发生交通事故的风险.采用条件logistic回归模型进一步研究了该指标与交通事故风险之间的定量关系.研究结果表明,该指标预测事故的精度为65.7％.另外,该指标每减小1个单位,交通事故风险将提高1.8倍.

Discriminant analysis based method to develop real-time crash indicator for evaluating freeway safety

To evaluate the impacts of changing traffic flow conditions on the risks of crash on freeways,a quantitative indicator based on real-time traffic flow data is developed to predict the occurrences of crash on freeways.Crash data and real-time traffic data with an interval of 30s are extracted from a segment of the I-880 N freeway in the state of California,United States.A linear combination of traffic flow parameters which is defined as real-time crash indicator is developed by Fisher discriminant analysis to identify dangerous traffic conditions.Negative real-time crash indicators represent dangerous traffic conditions potentially leading to crash occurrences while positive crash indicators represent normal traffic conditions which theoretically will not lead to crash occurrences.The conditional logistic regression model is applied to quantify the impacts of real-time crash indicator on the crash risk.The results show that the accuracy of using real-time crash indicator to predict crash occurrences on freeways is 65.7%.Moreover,one unit decrease in real-time crash indicator may increase the crash risk by 1.8 times.