Acta Geodaetica et Cartographica Sinica >

2016 , Vol. 45 >Issue 12: 1455 - 1463

DOI: https://doi.org/10.11947/j.AGCS.2016.20160117

An Adaptive Filtering Method Based on Crowdsourced Big Trace Data

  • TANG Luliang ,
  • YANG Xue ,
  • NIU Le ,
  • CHANG Le ,
  • LI Qingquan
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  • 1. State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China

Received date: 2016-03-30

  Revised date: 2016-10-27

  Online published: 2017-01-02

Supported by

The National Natural Science Foundation of China (Nos.41671442,41571430,41271442)

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Abstract

Vehicles' GPS traces collected by crowds have being as a new kind of big data and are widely applied to mine urban geographic information with low-cost, quick-update and rich-informative. However, the growing volume of vehicles' GPS traces has caused difficulties in data processing and their low quality adds uncertainty when information mining. Thus, it is a hot topic to extract high-quality GPS data from the crowdsourced traces based on the expected accuracy. In this paper, we propose an efficient partition-and-filter model to filter trajectories with expected accuracy according to the spatial feature of high-precision GPS data and the error rule of GPS data. First, the proposed partition-and-filter model to partition a trajectory into sub-trajectories based on the constrained distance and angle, which are chosen as the basic unit for the next processing step. Secondly, the proposed method collects high-quality GPS data from each sub-trajectory according to the similarity between GPS tracking points and the reference baselines constructed using random sample consensus algorithm. Experimental results demonstrate that the proposed method can effectively pick up high quality GPS data from crowdsourced trace data sets with the expected accuracy.

Key words： crowdsourced trace; trajectories partition; similarity model; data filtering; big data

Cite this article

TANG Luliang , YANG Xue , NIU Le , CHANG Le , LI Qingquan . An Adaptive Filtering Method Based on Crowdsourced Big Trace Data[J]. Acta Geodaetica et Cartographica Sinica, 2016 , 45(12) : 1455 -1463 . DOI: 10.11947/j.AGCS.2016.20160117

References

[1] 刘瑜, 肖昱, 高松, 等. 基于位置感知设备的人类移动研究综述[J]. 地理与地理信息科学, 2011, 27(4):8-13, 31. LIU Yu, XIAO Yu, GAO Song, et al. A Review of Human Mobility Research Based on Location Aware Devices[J]. Geography and Geo-Information Science, 2011, 27(4):8-13, 31.
[2] 牟乃夏, 张恒才, 陈洁, 等. 轨迹数据挖掘城市应用研究综述[J]. 地球信息科学, 2015, 17(10):1136-1142. MOU Naixia, ZHANG Hengcai, CHEN Jie, et al. A Review on the Application Research of Trajectory Data Mining in Urban Cities[J]. Journal of Geo-information Science, 2015, 17(10):1136-1142.
[3] 李德仁. 多学科交叉中的大测绘科学[J]. 测绘学报, 2007, 36(4):363-365. DOI:10.3321/j.issn:1001-1595.2007.04.001. LI Deren. On Geomatics in Multi-discipline Integration[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(4):363-365. DOI:10.3321/j.issn:1001-1595.2007.04.001.
[4] 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. LI Qingquan, HUANG Lian. A Map Matching Algorithm for GPS Tracking Data[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(2):207-212.
[5] 唐炉亮, 常晓猛, 李清泉, 等. 基于蚁群优化算法与出租车GPS数据的公众出行路径优化[J]. 中国公路学报, 2011, 24(2):89-95, 126. TANG Luliang, CHANG Xiaomeng, LI Qingquan, et al. Public Travel Route Optimization Based on Ant Colony Optimization Algorithm and Taxi GPS Data[J]. China Journal of Highway and Transport, 2011, 24(2):89-95, 126.
[6] 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. DOI:10.11947/j.AGCS.2015.20140591. 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. DOI:10.11947/j.AGCS.2015.20140591.
[7] CHEN Yihua, KRUMM J. Probabilistic Modeling of Traffic Lanes from GPS Traces[C]//Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY:ACM, 2010:81-88.
[8] TANG Luliang, YANG Xue, KAN Zihan, et al. Lane-level Road Information Mining from Vehicle GPS Trajectories Based on Naïve Bayesian Classification[J]. ISPRS International Journal of Geo-Information, 2015, 4(4):2660-2680.
[9] 唐炉亮, 杨雪, 阚子涵, 等. 一种基于朴素贝叶斯分类的车道数量探测[J]. 中国公路学报, 2016, 29(3):116-123. TANG Luliang, YANG Xue, KAN Zihan, et al. Traffic Lane Numbers Detection Based on the Naïve Bayesian Classification[J]. China Journal of Highway and Transport, 2016, 29(3):116-123.
[10] LEE W C, KRUMM J. Trajectory Preprocessing[M]//ZHENG Yu, ZHOU Xiaofang. Computing with Spatial Trajectories. New York:Springer, 2011:3-33.
[11] 杨元喜, 何海波, 徐天河. 论动态自适应滤波[J]. 测绘学报, 2001, 30(4):293-298. DOI:10.3321/j.issn:1001-1595.2001.04.004. YANG Yuanxi, HE Haibo, XU Tianhe. Adaptive Robust Filtering for Kinematic GPS Positioningg[J]. Acta Geodaetica et Cartographica Sinica, 2001, 30(4):293-298. DOI:10.3321/j.issn:1001-1595.2001.04.004.
[12] 杨元喜, 唐颖哲, 李庆田, 等. 用于GIS道路信息修测的动态GPS自适应滤波试验[J]. 测绘科学, 2003, 28(4):9-11. YANG Yuanxi, TANG Yingzhe, LI Qingtian, et al. Experiments of Adaptive Filters for Kinemetic GPS Positioning Applied in Road Information Updating in GIS[J]. Science of Surveying and Mapping, 2003, 28(4):9-11.
[13] YANG Yuanxi, HE H, XU Guochang. Adaptively Robust Filtering for Kinematic Geodetic Positioning[J]. Journal of Geodesy, 2001, 75(2-3):109-116.
[14] YANG Yuanxi, GAO Weiguang. An Optimal Adaptive Kalman Filter[J]. Journal of Geodesy, 2006, 80(4):177-183.
[15] WANG Jing, RUI Xiaoping, SONG Xianfeng, 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.
[16] TANG Luliang, YANG Xue, DONG Zhen, et al. CLRIC:Collecting Lane-based Road Information via Crowdsourcing[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(9):2552-2562.
[17] YANIV Z. Random Sample Consensus (RANSAC) Algorithm:A Generic Implementation[Z]. Washington, DC:Georgetown University Medical Center, 2010.
[18] 高为广, 杨元喜, 崔先强, 等. IMU/GPS组合导航系统自适应Kalman滤波算法[J]. 武汉大学学报(信息科学版), 2006, 31(5):466-469. GAO Weiguang, YANG Yuanxi, GUI Xianqiang, et al. Application of Adaptive Kalman Filtering Algorithm in IMU/GPS Integrated Navigation System[J]. Geomatics and Information Science of Wuhan University, 2006, 31(5):466-469.
[19] 周乐韬, 黄丁发, 袁林果, 等. 网络RTK参考站间模糊度动态解算的卡尔曼滤波算法研究[J]. 测绘学报, 2007, 36(1):37-42. DOI:10.3321/j.issn:1001-1595.2007.01.007. ZHOU Letao, HUANG Dingfa, YUAN Linguo, et al. A Kalman Filtering Algorithm for Online Integer Ambiguity Resolution in Reference Station Network[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(1):37-42. DOI:10.3321/j.issn:1001-1595.2007.01.007.
[20] 丁仁杰, 闵勇, 冯亚东, 等. 基于GPS的全网同步时钟的建立和误差校正[J]. 清华大学学报(自然科学版), 1997, 37(7):74-77, 81. DING Renjie, MIN Yong, FENG Yadong, et al. Development of Power System Dynamic Monitoring Unit Based on GPS[J]. Journal of Tsinghua University (Science & Technology), 1997, 37(7):74-77, 81.
[21] LEE J G, HAN Jiawei, WHANG K Y. Trajectory Clustering:A Partition-and-group Framework[C]//Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data. New York, NY:ACM, 2007:593-604.
[22] 张治华. 基于GPS轨迹的出行信息提取研究[D]. 上海:华东师范大学, 2010. ZHANG Zhihua. Deriving Trip Information from GPS Trajectories[D]. Shanghai:East China Normal University, 2010.
[23] 欧阳鸿, 刘建勋, 刘毅志, 等. 基于步行GPS轨迹的路网提取方法[J]. 计算机与现代化, 2014(2):124-128. OUYANG Hong, LIU Jianxun, LIU Yizhi, et al. An Extraction Method of Road Network Based on Walking GPS Trajectories[J]. Computer and Modernization, 2014(2):124-128.
[24] 赵东保, 盛业华. 全局寻优的矢量道路网自动匹配方法研究[J]. 测绘学报, 2010, 39(4):416-421. ZHAO Dongbao, SHENG Yehua. Research on Automatic Matching of Vector Road Networks Based on Global Optimization[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(4):416-421.
[25] 唐炉亮, 李清泉, 杨必胜. 空间数据网络多分辨率传输的几何图形相似性度量[J]. 测绘学报, 2009, 38(4):336-340. DOI:10.3321/j.issn:1001-1595.2009.04.009. TANG Luliang, LI Qingquan, YANG Bisheng. Shape Similarity Measuring for Multi-resolution Transmission of Spatial Datasets over the Internet[J]. Acta Geodaetica et Cartographica Sinica, 2009, 38(4):336-340. DOI:10.3321/j.issn:1001-1595.2009.04.009.
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