考虑天气影响的高速公路交织区交通运行状态识别

Identification of Traffic Operation Status in Freeway Weaving Segments Considering Weather Effects

为精准识别不利天气下高速公路交织区的交通运行状态,在传统交通流指标上引入天气因素,建立改进的k-prototypes交通运行状态划分方法。本方法通过分析在不同等级的降雨、能见度、风速下交通流特性的变化特征,确定天气对交通流状态的影响;利用随机森林模型选择交织区各车道交通流运行状态的影响变量;为提高模型精度,引入信息熵衡量k-prototype算法的相异性,并提出聚类效果评价指标衡量状态的有效性。结果表明:考虑天气及交通流特征的高速公路交织区各车道运行状态划分为7类最佳,分别对应《道路通行能力手册》中的各级服务水平。在恶劣天气影响下,交织区各车道服务水平均下降明显,车道1、3平均下降4个等级,车道2、4平均下降3个等级;在中度天气影响下,各车道下降2~3个服务水平。在同一服务等级下车道1、3车流运行最小速度下降范围在11.2~17.4 km·h^(-1),而车道2、4在21.2~27.4 km·h^(-1)。研究成果可为恶劣天气影响下更精细化的交通管理以及提高高速公路交织区服务水平提供理论基础。

This paper proposes a revised k-prototype method to improve the accuracy of the classification of traffic operational status at freeway weaving segments under adverse weather conditions by introducing the weather factors to traditional traffic flow indicators.The study determines the impact of weather on traffic flow status by analyzing the variation of traffic flow indicators under various levels of rainfall,visibility,and wind speed.The random forest model is used to select the influential variables of traffic flow operating status for each lane of the weaving sections.The information entropy is then introduced to measure the dissimilarity of the k-prototype algorithm and a clustering effectiveness evaluation indicator is used to measure the effectiveness of the status.The results show that the operation status in the lane level of the freeway weaving segments can be divided into seven categories.Corresponding to the Level of Service(LOS)at all levels in the Highway Capacity Manual,the LOS under adverse weather conditions would decrease significantly.The LOSs for lanes 1 and 3 decrease with an average of 4 levels,and the LOSs for lanes 2 and 4 decrease with an average of 3 levels.Under moderate weather conditions,each lane experiences a decrease of LOS by 2 to 3 levels.Under the same LOS,the minimum speed in lanes 1 and 3 would experience a decrease ranging from 11.2 to 17.4 km·h^(-1),and the minimum speed decreases in lanes 2 and 4 range from 21.2 to 27.4 km·h^(-1).The findings provide a theoretical basis for refined traffic management under adverse weather conditions,which helps to improve the traffic LOS at freeway weaving segments.