【作者】 陈宁；

【Author】 CHEN Ning Zhejiang University of Science and Technology,Hang Zhou 310023,P.R.China

【机构】 浙江科技学院机械与汽车工程学院；

【摘要】 路段平均行程时间是城市交通管理部门、交通行业部门制定调度方案及管控预案的重要信息依据。为了能够有效利用低频采样GPS数据,实现路段平均行程时间的精确估计,本文提出一种基于模糊C均值聚类的路段平均行程时间估计方法:首先利用改进地图匹配算法,对低频采样浮动车数据进行预处理,将路段的上下游交叉口详细分析,准确估计车辆经过路段交叉口的时刻,通过两交叉口的时差计算单车路段行程时间;然后基于模糊C均值聚类(FCM)方法,将某时段的单车路段行程时间分成快、中、慢速三类,利用各类的聚类中心和分类后数据,按一定的权值,估计平均路段行程时间。计算结果表明:平均行程时间估计值与实测值比较接近,能够满足城市城市交通管理部门、交通行业部门的需求。更多还原

【Abstract】 In order to availably utilize taxi GPS data with low frequency and precisely estimate the average link travel time(ALTT),an estimation approach of ALTT and Improved Map-matching algorithm was proposed.After analyzing upstream and downstream intersections of link particularly,more accurate estimates the moment of a vehicle through the intersection.Using the time difference of upstream and downstream intersections as single vehicle link travel time(SLTT).We generate patterns for the high,middle and low speed level by calculating the SLTT using FCM.ALTT calculated by means of a certain weight using the center value of each cluster after confirming of cluster membership of SLTT data.Computation result shows that the relative tolerance is less between the measure value and computation value of ALTT.更多还原