Model Development for Risk Assessment of Driving on Freeway under Rainy Weather Conditions
Model Development for Risk Assessment of Driving on Freeway under Rainy Weather Conditions
复制标题
雨天高速公路行驶风险评估模型开发
作者：
Xiaonan Cai;Chen Wang;Shengdi Chen;Jian Lu
下雨的天气条件可能会对在高速公路上驾驶造成严重的负面影响。然而，由于缺乏足够的历史数据和监测设施，许多地区无法建立可靠的风险评估模型来识别此类影响。针对这种情况，本文提出了一种基于驾驶员主观问卷的风险评估方法，并通过实际碰撞数据验证了该方法的有效性。首先，基于中国G15高速公路的问卷调查数据，建立了一个有序的Logit模型来估计驾驶员感知风险与车辆类型、雨强、交通量、位置等因素之间的关系。然后，通过该模型得到不同情况下的加权驾驶风险，并利用秩序聚类分析将其进一步划分为四个预警级别(以颜色表示)。在此之后，建立了一个风险矩阵，以确定在特定情况下应该向司机传播哪种警告颜色。最后，将G15高速公路的实际碰撞数据与基于风险矩阵的安全预测结果进行了比较，验证了该方法的有效性。结果表明，在雨天条件下，所得到的风险矩阵能够预测出与实际安全含义相一致的驾驶风险。
Rainy weather conditions could result in significantly negative impacts on driving on freeways. However, due to lack of enough historical data and monitoring facilities, many regions are not able to establish reliable risk assessment models to identify such impacts. Given the situation, this paper provides an alternative solution where the procedure of risk assessment is developed based on drivers’ subjective questionnaire and its performance is validated by using actual crash data. First, an ordered logit model was developed, based on questionnaire data collected from Freeway G15 in China, to estimate the relationship between drivers’ perceived risk and factors, including vehicle type, rain intensity, traffic volume, and location. Then, weighted driving risk for different conditions was obtained by the model, and further divided into four levels of early warning (specified by colors) using a rank order cluster analysis. After that, a risk matrix was established to determine which warning color should be disseminated to drivers, given a specific condition. Finally, to validate the proposed procedure, actual crash data from Freeway G15 were compared with the safety prediction based on the risk matrix. The results show that the risk matrix obtained in the study is able to predict driving risk consistent with actual safety implications, under rainy weather conditions.