利用浮动车数据提取停车场位置  

Parking Lot Extraction Method Based on Floating Car Data

作　　者：李军[1] 秦其明[1] 游林[2] 解超[1] 

机构地区：[1]北京大学遥感与地理信息系统研究所,北京市海淀区颐和园路5号100871 [2]宁波市规划与地理信息中心

出　　处：《武汉大学学报（信息科学版）》2013年第5期599-603,共5页Geomatics and Information Science of Wuhan University

基　　金：国家863计划资助项目(2012AA121305)

摘　　要：针对当前停车场信息采集手段周期长、成本高的问题,提出了利用浮动车数据自动提取停车场位置的方法。通过分析在停车场内采集的浮动车数据具有的典型特点后,使用DBSCAN算法检测出位于停车场内的点簇进而提取停车场的位置;同时针对DBSCAN算法具有高时间复杂度的缺点,结合定位点簇的空间尺寸限制条件构建了特定的空间索引,提高了聚类算法的效率。试验结果验证了该方法的有效性。The phenomena that parking is difficult in large and medium-sized cities makes people＇s desire for parking lot information become stronger and stronger, and the level of detail and accuracy of parking lot information in electronic maps directly impact the service quality of maps. In view of the problems of current surveying methods of parking lots, this paper proposes an approach to automatically extract the locations of parking lots from floating car data. In this paper, the DBSCAN algorithm is used to detect point clusters located within parking areas, and a special spatial grid index is established to decrease the time complexity of the clustering algorithm. Experiment results validate the proposed method.

关 键 词：POI更新 停车场提取 浮动车数据 DBSCAN算法 

分 类 号：P208[天文地球—地图制图学与地理信息工程]