测绘学报 ›› 2018, Vol. 47 ›› Issue (12): 1650-1659.doi: 10.11947/j.AGCS.2018.20170182

• 地图学与地理信息 • 上一篇    下一篇

轨迹分割与图层融合的车辆轨迹线构建道路地图方法

杨伟, 艾廷华   

  1. 武汉大学资源与环境科学学院, 湖北 武汉 430079
  • 收稿日期:2017-04-11 修回日期:2018-07-26 出版日期:2018-12-20 发布日期:2018-12-24
  • 通讯作者: 艾廷华 E-mail:tinghua_ai@tom.com
  • 作者简介:杨伟(1987-),男,博士生,研究方向为时空轨迹数据挖掘与行为建模。E-mail:ywgismap@whu.edu.cn
  • 基金资助:
    国家自然科学基金重点项目(41531180);国家重点研发计划(2017YFB0503500)

A Method for Road Map Construction Based on Trajectory Segmentation and Layer Fusion Using Vehicle Track Line

YANG Wei, AI Tinghua   

  1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
  • Received:2017-04-11 Revised:2018-07-26 Online:2018-12-20 Published:2018-12-24
  • Supported by:
    The National Natural Science Foundation of China (No. 41531180);The National Key Research and Development Program of China (No. 2017YFB0503500)

摘要: 传统道路地图构建方法将轨迹点(线)同等对待提取道路数据,忽略车辆轨迹的空间差异性,制约其结果精度与应用范围。为此,本文根据轨迹速度将轨迹线集分割滤选为3个轨迹线子集,将轨迹方向与Delaunay三角网模型集成探测路网拓扑结构;顾及轨迹线子集的特征差异选取不同参数值和约束条件并分层提取道路几何、交通语义数据,分别构建3个道路图层;运用缓冲区方法并根据道路几何、语义特征将多个道路图层融合为单个完整道路地图。运用出租车轨迹数据进行试验分析,结果表明:该方法顾及轨迹分布差异性,能将道路几何、交通语义信息融合提取,更适于处理复杂道路结构下的轨迹线。

关键词: 众源轨迹, 轨迹分割, 数据融合, 道路地图, Delaunay三角网

Abstract: Traditional methods treat track points (lines) equally to extract road data, which ignores the spatial distribution disparity and restricts its application. Therefore, this paper proposes a new approach for map construction based on trajectory segmentation and layer fusion from vehicle tracks. First, track line subset is selected through the segmentation filtering method based on speed profile. Second, three road map layers are constructed by the Delaunay triangulation through adding different constraints according to the feature of track line subset. Third, buffer method is used to integrate multiple road layers into a single road map. An experiment using taxi GPS traces in Beijing is verified the novel method. The experimental results show that our method can extract road geometry and traffic semantic data considering the heterogeneity of trajectory, and the accuracy of result is improved compared with the two existing methods.

Key words: GPS trajectory, trajectory segmentation, data fusion, road map, Delaunay triangulation

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