A method of floating car data correction based on OSM

doi:10.13474/j.cnki.11-2246.2020.0337

Abstract

Abstract: Floating car track data has great significance for the production and update of road map because of the wide coverage area, low cost and the short update cycle. However, compared to other data sources, the accuracy of it is low. This article adopts the OSM as reference data to correct the floating car track data. Firstly, the floating cat track data is matched with the OSM through a hierarchical space-time map matching algorithm. Then, an attraction model is used to correct the data. Finally, the taxs track data of Wuhan is used to verify the effectiveness of the algorithm. The result shows that the method in this paper could improve precision of floating car truck data.

Key words: open street map, map matching, floating car data, attraction model, data correction

CLC Number:

P208

HU Xiangyong, GUO Yuan. A method of floating car data correction based on OSM[J]. Bulletin of Surveying and Mapping, 2020, 0(10): 139-142,163.

References

[1] 杨伟, 艾廷华. 基于众源轨迹数据的道路中心线提取[J].地理与地理信息科学,2016,32(3):1-7.
[2] LI B J, GUO Y, ZHOU J, et al. A data correction algorithm for low-frequency floating car data[J].Sensors,2018,18(11):3639.
[3] BIAGIONI J,ERIKSSON J. Map inference in the face of noise and disparity[C]//The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York:[s.n.],2012.
[4] LIU X, BIAGIONI J, ERIKSSON J, et al. Mining large-scale, sparse GPS traces for map inference:comparison of approaches[C]//Proceedings of the 18th ACM SIGKDD International Conference on Knowledge discovery and data mining. New York:[s.n.],2012.
[5] 曹鹏, 马婕, 施展华.针对浮动车异常数据的增强型在线异常点检测算法[J]. 交通运输工程与信息学报, 2019, 17(2):23-35.
[6] LEE W C, KRUMM J. Trajectory preprocessing[M]. New York:Springer Computing with Spatial Trajectories, 2011.
[7] FOX D. Adapting the sample size in particle filters through KLD-sampling[J].The International Journal of Robotics Research, 2003, 22(12):985-1003.
[8] 赵东保, 刘雪梅, 张弘弢. 基于大规模浮动车轨迹点数据的道路网变化检测与更新方法研究[J]. 地理与地理信息科学, 2016, 32(2):1-5.
[9] LOU Y, ZHANG C, ZHENG Y, et al. Map-matching for low-sampling-rate GPS trajectories[C]//The 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle:ACM,2009.
[10] 张健钦,李明轩,段颖超,等.一种改进的快速浮动车地图匹配方法[J].测绘通报,2017(1):87-92.
[11] 李清泉, 黄练. 基于GPS轨迹数据的地图匹配算法[J]. 测绘学报, 2010,39(2):207-212.
[12] BARRON C, NEIS P, ZIPF A. A comprehensive framework for intrinsic openstreetmap quality analysis[J]. Transactions in GIS, 2014,18(6):877-895.
[13] WANG M, LI Q, HU Q, et al. Quality analysis of openstreetmap data[J]. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013, XL-2/W1: 155-158.
[14] WANG J, RUI X, SONG X, 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.
[15] CAO L L, KRUMM J. From GPS traces to a routable road map[C]//Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle: ACM, 2009.