基于两阶段K-means聚类的道路运行状况评价方法

摘要

为有效评价道路运行状况,通过分析车辆在行驶过程中运行状态的变化,研究了一种基于两阶段K-means聚类(TSKC)的道路运行状况评价方法.针对K-means聚类数选取的任意性和聚类中心选取的随机性问题,提出基于遍历的K-means聚类方法,采用类吸引度确定聚类数和初始中心,并以此为初始条件进行第二阶段K-means聚类,得到交通模式.提出模式吸引度、路段评价指数、分布均衡度,并用这些指标来评价路段交通运行状况.以北京市朝阳区北辰东路为例进行验证,结果表明,该方法比传统道路评价方法更细致、全面、直观地描绘了车辆状态的演变过程和交通模式的分布情况,具有良好的实用性.%In order to effectively evaluate road operation condition,an evaluation method based on Two-Stage Kmeans clustering (TSKC) is developed by analyzing variation of vehicle operating state.First,aiming at the arbitrariness in the choice of K-means cluster number and the randomness of selection of cluster center,a K-means clustering method based on traversal is proposed.The cluster number and initial centers are determined by class attractiveness,and used as the initial condition of the second stage K-means clustering to explore the traffic pattern.The pattern attractiveness,the road evaluation indices,and the distribution equilibrium are proposed as indices to evaluate road operation condition.Beichen East Road of Chaoyang district in Beijing is taken as a case study.The results show that the proposed method is more detailed,comprehensive,and intuitive than the traditional evaluation method when describing the evolution of vehicle state and the distribution of traffic patterns.The results also indicate the great practicability of the method.