基于低频浮动车数据的实时地图匹配算法  

Real-Time Map Matching Algorithm Based on Low-Sampling-Rate Probe Vehicle Data

作　　者：姚恩建[1] 左婷[1] 

机构地区：[1]北京交通大学交通运输学院,北京100044

出　　处：《北京工业大学学报》2013年第6期909-913,共5页Journal of Beijing University of Technology

基　　金：国家"973"计划资助项目(2012CB725403);北京交通大学科技基金资助项目(T09J00040)

摘　　要：在考虑GPS误差等影响因素的前提下,按照5 min时间间隔为单位,对该时间段的GPS点筛选候选匹配链路;然后利用最短路算法获得浮动车行驶的候选径路集,并通过模糊逻辑推理确定最终行驶径路,实现低频浮动车数据的地图匹配;最后,基于北京市采集的浮动车高频数据,利用不同频率下随机抽取低频数据对算法进行验证.By considering GPS errors, candidate links were selected for every GPS point which was partitioned into different time windows according to 5-minute time interval. Then, map-matching for low sampling-rate probe vehicle data was developed via fuzzy logic inference to search for a final path from candidate paths set obtained by the shortest path computation. Finally, the proposed algorithm was evaluated in terms of matching accuracy and calculating time with different sampling-rate probe vehicle data collected in Beijing.

关 键 词：浮动车 地图匹配 最短路算法 模糊逻辑推理 

分 类 号：U491[交通运输工程—交通运输规划与管理]