煤炭工程 ›› 2017, Vol. 49 ›› Issue (4): 94-97.doi: 10.11799/ce201704028

• 研究探讨 • 上一篇    下一篇

基于卡车的海量GPS轨迹数据的矿区路网自动更新技术

李强1,陈宜金2   

  1. 1. 中国矿业大学(北京) 地球科学与测绘工程学院
    2. 中国矿业大学(北京)
  • 收稿日期:2016-06-14 修回日期:2016-07-17 出版日期:2017-04-09 发布日期:2017-05-16
  • 通讯作者: 李强 E-mail:li_cumtb@163.com

Road Network Updating in Mining Area Based on Massive GPS Trajectory Data of Truck

  • Received:2016-06-14 Revised:2016-07-17 Online:2017-04-09 Published:2017-05-16

摘要: 针对露天矿区道路网随环境的不断变化,运用矿用卡车的海量移动轨迹数据,实现矿区路网的自动更新技术。通过对轨迹数据的精度进行分析评价,筛选出可靠数据,并对数据应用改进后的DBSCAN密度聚类算法来获取聚类点簇,然后对聚类点簇执行B样条曲线拟合,建立拓扑关系,形成矿区路网图。结果表明该算法可以适用于绝大部分的矿区道路环境。

关键词: 矿用卡车, GPS, 轨迹数据, 密度聚类, 矿区路网

Abstract: The timely updating of the transportation road network in open-pit mine, is a reliable guarantee for normal transportation in open-pit mine. Aiming at the constant changing of mine road network with the environment, this paper realized the automatic updating technology of mine road network by using massive trajectory data of mine truck.Through analysis and evaluation of the accuracy of the trajectory data to screen out the reliable data, and the improved DBSCAN density clustering algorithm was applied to the data to obtain the clustering points, then the clustering points was performed quasi uniform B-spline curve fitting, establishing topological relations and forming a road map of mining area. The result showed that the algorithm can adapt to the vast majority of mining area road environment

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