中文摘要：

根据道路在车载激光点云数据中的表达特征,提出一种基于轨迹线辅助下的K均值聚类算法,开展针对道路边界线的自动精细提取研究,算法描述为：先进行数据预处理,将复杂轨迹简化成单一轨迹;再利用轨迹辅助,通过插入截面,将点云投影在截面上获得“断面线”;然后以断面线为基础,采用K均值聚类算法提取出道路边界;最后对提取的道路边界进行检核、优化,获取精细道路边界信息.实验表明,该方法实现了道路边界高效准确地全自动提取.

英文摘要：

According to the characteristics of the road in vehicle-borne LiDAR point cloud data,analgorithmofk-means clustering was proposed based on the trajectory,aiming to research the automatic extraction method on road boundary.Thealgorithm is described as followings.firstly,simplify the complex trajectory into one single trackfordata preprocessing; then,insert sections using the trajectory,getting section lines through projection in cross section of the point cloud ; thirdly,use K-means clustering algorithm to extract the road boundary based on the section line ; lastly,check and optimize the result for accurate road boundaryinformation.The test resultshows that the algorithmcan automatically extract road boundary efficiently and accurately.