道路信息提取方法综述  

Summary of road information extraction methods

作　　者：李小龙[1] 张昀 LI Xiaolong;ZHANG Yun(Faculty of Geomatics,East China University of Technology,Nanchang 330013,China)

机构地区：[1]东华理工大学测绘工程学院,江西南昌330013

出　　处：《测绘通报》2020年第6期22-27,共6页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(41501437)。

摘　　要：道路信息提取旨在使用相关数据和方法提取一条道路上的信息,如车道数量、中心线和边界线等。道路信息提取在交通规划和车辆导航等方面具有重要的应用价值。随着各种传感器设备的广泛应用,交通数据爆炸式增长,道路信息提取的方法也日新月异。本文结合近年来道路信息提取的研究进展,将道路信息提取方法按照数据来源分为基于影像视频数据、基于高密度点云数据和基于浮动车轨迹数据3类,并分别深入论述了这3类方法的主要实现算法,对这些算法模型进行了对比分析,最后探讨了现有道路信息提取方法在未来的研究趋势和面临的挑战。Road information extraction aims to extract information on a road by using relevant data and methods,such as the number of lanes,centerlines and boundary lines.Road information extraction has important application value in transportation planning and vehicle navigation.With the wide application of various sensor devices,the explosion of traffic data and the method of road information extraction are changing rapidly.This paper reviews the research progress of road information extraction recently.The road information extraction method is divided into three categories based on video and data,high-density point cloud data and floating vehicle trajectory data according to the data source,and these three categories are discussed in depth.The main implementation algorithms of the method,and the comparative analysis of these algorithm models,finally explored the future research trends and challenges of the existing road information extraction methods.

关 键 词：道路信息提取 数据挖掘 时空轨迹 影像数据 浮动车数据 高密度点云数据 

分 类 号：P237[天文地球—摄影测量与遥感]