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
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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.Abstract: 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.