利用车载LiDAR点云数据提取城市道路规则多边形

随着自动驾驶高精地图的发展，准确高效地提取道路规则多边形成为必要。本文以苏州市某城市快速路为研究对象，通过使用徕卡车载激光移动测量系统获得城市道路点云数据，观察了解车载点云数据各类属性信息，根据观察结果组合利用点云数据高差、点云灰度差值、点云强度差值，在此基础上再利用网格密度法实现道路规则多边形的提取，然后通过对目标的矢量化得到三维矢量规则多边形。最后对提取的矢量化结果进行精度评定。试验结果表明：该方法在提取道路规则多边形方面能得到较好的结果且能满足高精地图需求。

Method for extracting urban road regular polygon by using vehicle-mounted LiDAR point cloud data

With the development of self-driving high-precision map, it is necessary to extract the road rules accurately and efficiently. This paper takes a city expressway in suzhou city as the research object, obtains the city road point cloud data by using the leica vehicle-borne laser mobile measurement system, observes and understands all kinds of attribute information of the vehicle-borne point cloud data. According to the observation results, the point cloud data height difference, the point cloud gray level difference and the point cloud intensity difference are combined. Finally, the accuracy of the extracted vectorization results is evaluated. The experimental results show that: This method can get good results in extracting regular polygons and can meet the demand of high precision maps.