出租车轨迹数据的道路提取

doi:10.13474/j.cnki.11-2246.2018.0209

测绘通报 ›› 2018, Vol. 0 ›› Issue (7): 53-57.doi: 10.13474/j.cnki.11-2246.2018.0209

出租车轨迹数据的道路提取

胡瀚, 向隆刚, 王德浩

武汉大学测绘遥感信息工程国家重点实验室, 湖北武汉 430079

收稿日期:2017-09-20 出版日期:2018-07-25 发布日期:2018-08-02
通讯作者: 向隆刚。E-mail:geoxlg@whu.edu.cn E-mail:geoxlg@whu.edu.cn
作者简介:胡瀚(1993-),男,硕士,主要研究方向为轨迹数据处理分析。E-mail:hh0620@whu.edu.cn
基金资助:
国家自然科学基金（41471374）

Road Extraction Based on Taxi Trajectory Data

HU Han, XIANG Longgang, WANG Dehao

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Received:2017-09-20 Online:2018-07-25 Published:2018-08-02

摘要/Abstract

摘要： 相对高频GPS轨迹数据而言，低频GPS轨迹数据具有数据量大、容易获取、低成本等优点。对此，本文提出了一种基于大量低频轨迹数据的道路信息提取方法。该方法采用数学形态学滤波和细化方法对栅格化的道路图像进行道路中心线与交叉口的提取，然后采用道格拉斯-普克算法对交叉口间的路段进行简化与平滑，最终得到道路信息。其中在交叉口的提取上，采用多分辨率的图像融合的方法尽可能多地提取交叉口。试验表明，该方法在一定程度上克服了低频轨迹数据采样间隔不固定、定位精度低、噪声点多、数据分布不均等缺点，能够提取出较为准确的道路交叉口和中心线。

关键词: 轨迹数据, 数学形态学, 多分辨率融合, 道路交叉口, 道格拉斯-普克

Abstract: Relative to high frequency GPS trajectory data,low frequency GPS trajectory data has the advantages of large amount of data,easy access,low cost and so on.For this reason,a method of road information extraction based on a large number of low frequency trajectory data is proposed.The road image method with mathematical morphology and refinement method for rasterizing extraction line and cross road center port,then the Douglas-Peucker algorithm of intersection between the sections of simplification and smoothing,finally get the road information.Among them,the method of multi-resolution image fusion is used to extract the intersection as much as possible.Experiments show that this method in a certain extent overcome interval is not fixed,low positioning accuracy,noise and uneven distribution of defects of low frequency data sampling trajectory data,extract the road intersection and the center line more accurate.

Key words: trajectory data, mathematical morphology, multi-resolution image fusion, road intersection, Douglas-Peucker

中图分类号:

P208

胡瀚, 向隆刚, 王德浩. 出租车轨迹数据的道路提取[J]. 测绘通报, 2018, 0(7): 53-57.

HU Han, XIANG Longgang, WANG Dehao. Road Extraction Based on Taxi Trajectory Data[J]. 测绘通报, 2018, 0(7): 53-57.

参考文献

[1] SHI W,MIAO Z,DEBAVLE J.An Integrated Method for Urban Main-road Centerline Extraction from Optical Remotely Sensed Imagery[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(6):3359-3373.
[2] 傅罡.多源遥感数据的道路提取方法研究[D].北京:清华大学,2014.
[3] HU X,LI Y,SHAN J,et al.Road Centerline Extraction in Complex Urban Scenes from LiDAR Data Based on Multiple Features[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(11):7448-7456.
[4] 李卉.集成LiDAR和遥感影像城市道路提取与三维建模[J].测绘学报,2011,40(1):133-133.
[5] LIU X,BIAGIONI J,ERIKSSON J,et al.Mining Large-scale,Sparse GPS Traces for Map Inference:Comparison of Approaches[J].Proceedings of 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,2012,9(4):669-677.
[6] KARAGIORGOU S,PFOSER D,SKOUTAS D.Segmentation-based Road Network Construction[C]//Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.New York:ACM,2013:450-453.
[7] STEINER A,LEONHARDT A.Map-generation Algorithm Using Low-frequency Vehicle Position Data[C]//Compendium of Papers of the 90th Annual Meeting of Transportation Research Board.Washington D C:[s.n.],2011.
[8] JIANG Y,LI X,LI X,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.
[9] 王振华,胡翔云,单杰.众源GPS浮动车数据中城市道路中心线分级提取的栅格化方法[J].测绘通报,2015(8):22-24.
[10] FATHI A,KRUMM J.Detecting Road Intersections from GPS Traces[C]//Proceedings of the 6th International Conference on Geographic Information Science.Berlin:Springer-verlag,2010:56-69.
[11] 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.
[12] GONZALEZ R C,WOODS R E,EDDINS S L.数字图像处理[M].2版.阮秋琦译.北京:电子工业出版社,2007.
[13] DOUGLAS D,PEUCKER T K.Algorithms for the Deduction of the Number of Points Required to Represent a Digitized Line or Its Caricature[J].Cartographer,2011,10(2):112-122.

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出租车轨迹数据的道路提取

Road Extraction Based on Taxi Trajectory Data

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