低频轨迹数据的多时相增量式道路提取方法A method of multi-temporal incremental extraction of road network based on low-frequency trajectory data
张云菲,佘婷婷,邓敏,周访滨
摘要(Abstract)：
针对目前利用低频时空轨迹数据进行道路提取与更新,难以同时满足提取精度和算法效率要求的问题,该文提出一种基于低频轨迹数据的多时相增量式道路提取方法。首先,将原始轨迹数据分割为多个时相轨迹序列,并利用栅格化法得到多个时相的初始道路中心线;接着,采用吸引力模型纠正初始道路中心线的位置偏差,再通过k-segment主曲线算法拟合得到最终道路中心线,构建道路骨架地图;最后,统计与道路中心线关联的轨迹位置与方向信息,进一步挖掘道路宽度与单双向通行规则等交通语义信息,丰富道路骨架地图。实验结果表明,基于多时相轨迹分别提取与增量融合的方式,可有效发现道路网的时空变化规律,获得较高的道路检测概率与信息提取准确率,同时避免对全时段轨迹直接处理的复杂运算量。
关键词(KeyWords)： 道路提取;GPS轨迹;多时相分割;增量融合
基金项目(Foundation): 国家自然科学基金项目(41601495,41971421,41730105,41771492,41671446);; 湖南省自然科学基金项目(2018JJ3525);; 湖南省教育厅科学研究项目(18C0228);; 测绘遥感信息工程国家重点实验开放基金项目(17s01);; 长沙理工大学公路地质灾变预警空间信息技术湖南省工程实验室开放基金项目(kfj170605)
作者(Author): 张云菲,佘婷婷,邓敏,周访滨
DOI: 10.16251/j.cnki.1009-2307.2020.04.027
参考文献(References)：
- [1] 唐炉亮,刘章,杨雪,等.符合认知规律的时空轨迹融合与路网生成方法[J].测绘学报,2015,44(11):1271-1276.(TANG Luliang,LIU Zhang,YANG Xue,et al.A method of spatio-temporal trajectory fusion and road network generation based on cognitive law[J].Acta Geodaetica et Cartographica Sinica,2015 44(11):1271-1276.)
- [2] KUNTZSCH C,SESTER M,BRENNER C.Generative models for road network reconstruction[J].International Journal of Geographical Information Science,2016,30(5):1-28.
- [3] AHMED M,KARAGIORGOU S,PFOSER D,et al.A comparison and evaluation of map construction algorithms using vehicle tracking data[J].Geoinformatica,2015,19(3):601-632.
- [4] 蒋益娟,李响,李小杰,等.利用车辆轨迹数据提取道路网络的几何特征与精度分析 [J].地球信息科学学报,2012,14(2):165-170.(JIANG Yijuan,LI Xiang,LI Xiaojie,et al.Geometrical characteristics extraction and accuracy analysis of road network based on vehicle trajectory data[J].Journal of Geo-information Science,2012,14(2):165-170.)
- [5] SHI W H,SHEN S H,LIU Y C.Automatic generation of road network map from massive GPS vehicle trajectories [C]//Proceedings of 12th International IEEE Conference on Intelligent Transportation Systems.[S.l.]:IEEE,2009:1-6.
- [6] BRUNTRUP R,EDELKAMP S,JABBAR S,et al.Incremental map generation with GPS traces[C]//Proceedings of Intelligent Transportation Systems.[S.l.]:IEEE,2005:574-579.
- [7] LI J,QIN Q M,XIE C,ZHAO Y,et al.Integrated use of spatial and semantic relationships for extracting road networks from floating car data[J].International Journal of Applied Earth Observation and Geoinformation,2012,19(1):238-247.
- [8] SCHROEDL S,WAGSTAFF K,ROGERS S,et al.Mining GPS traces for map refinement [J].Data Mining & Knowledge Discovery,2004,9(1):59-87.
- [9] WU T,XIANG L G,GONG J Y.Updating road networks by local renewal from GPS trajectories[J].ISPRS International Journal of Geo-Information,2016,5(9):163-181.
- [10] ZHANG L J,THIEMANN F,SESTER M.Integration of GPS traces with road map[C]//Proceedings of International Workshop on Computational Transportation Science.New York:ACM,2010:17-22.
- [11] 杨伟,艾廷华.运用约束Delaunay三角网从众源轨迹线提取道路边界[J].测绘学报,2017,46(2):237-245.(YANG Wei,AI Tinghua.The extraction of road boundary from crowdsourcing trajectory using constrained delaunay triangulation[J].Acta Geodaetica et Cartographica Sinica,2017 46(2):237-245.)
- [12] WANG J,RUI X P,SONG X F,et al.A novel approach for generating routable road maps from vehicle GPS traces[J].International Journal of Geographical Information Science,2015,29(1):69-91.
- [13] VERBEEK J J,VLASSIS N,KR?SE B.A k-segments algorithm for finding principal curves[J].Pattern Recognition Letters,2002,23(8):1009-1017.
- [14] AHMED M,WENK C.Constructing street networks from GPS trajectories[C]//Proceedings of European Symposium on Algorithms.Berlin:Springer-Verlag,2012:60-71.