运用约束Delaunay三角网从众源轨迹线提取道路边界  

The Extraction of Road Boundary from Crowdsourcing Trajectory Using Constrained Delaunay Triangulation

作　　者：杨伟[1] 艾廷华[1] 

机构地区：[1]武汉大学资源与环境科学学院,湖北武汉430079

出　　处：《测绘学报》2017年第2期237-245,共9页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金重点项目(41531180);国家863计划(2015AA1239012)~~

摘　　要：运用众源车辆轨迹数据提取道路信息需要解决轨迹点采样稀疏、高噪音、密度差异大等问题。为此,本文提出一种运用约束Delaunay三角网从车辆轨迹线集中提取道路边界的方法。首先,通过三角形边长度和Voronoi面积等几何特征表达轨迹点分布的聚集性差异,并将这两种不同几何维数的控制条件集成建立道路边界识别模型,运用"种子点"区域扩展方法实现道路边界的精确提取。最后,运用北京市出租车GPS轨迹进行试验,结果表明该方法适于车辆分布频率悬殊、时间跨度不同、道路网结构复杂的轨迹线数据处理。Extraction of road boundary accurately from crowdsourcing trajectory lines is still a hard work.Therefore,this study presented a new approach to use vehicle trajectory lines to extract road boundary.Firstly, constructing constrained Delaunay triangulation within interpolated track lines to calculate road boundary descriptors using triangle edge length and Voronoi cell.Road boundary recognition model was established by integrating the two boundary descriptors.Then,based on seed polygons,a regional growing method was proposed to extract road boundary. Finally, taxi GPS traces in Beijing were used to verify the validity of the novel method, and the results also showed that our method was suitable for GPS traces with disparity density,complex road structure and different time interval.

关 键 词：众源轨迹 道路更新 约束Delaunay三角网 空间聚类 

分 类 号：P208[天文地球—地图制图学与地理信息工程]