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Trajectory Aggregation for a Routable Map

  • Conference paper
Web and Wireless Geographical Information Systems (W2GIS 2014)

Abstract

In this paper, we compare different approaches to merge trajectory data for later use in a map construction process. Merging trajectory data reduces storage space and can be of great help as far as data privacy is concerned. We consider different distance measures and different merge strategies, taking into account the cost of calculation, the connectivity of the results, and the storage space of the result. Finally, we give a hint on a possible information loss for each approach.

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References

  1. Canalys: Sony and HTC overtake RIM and Nokia in smart phones (2012), http://www.canalys.com/newsroom/sony-and-htc-overtake-rim-and-nokia-smart-phones

  2. Association for Computing Machinery: ACM digital library (2013), https://dl.acm.org/

  3. Yuan, J., Zheng, Y., Zhang, C., Xie, W., Xie, X., Sun, G., Huang, Y.: T-drive: driving directions based on taxi trajectories. In: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2010, pp. 99–108. ACM, New York (2010)

    Google Scholar 

  4. Evans, M.R., Oliver, D., Shekhar, S., Harvey, F.: Summarizing trajectories into k-primary corridors: a summary of results. In: Proceedings of the 20th International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2012, pp. 454–457. ACM, New York (2012)

    Google Scholar 

  5. Andrienko, G., Andrienko, N., Giannotti, F., Monreale, A., Pedreschi, D.: Movement data anonymity through generalization. In: Proceedings of the 2nd SIGSPATIAL ACM GIS 2009 International Workshop on Security and Privacy in GIS and LBS, SPRINGL 2009, pp. 27–31. ACM, New York (2009)

    Chapter  Google Scholar 

  6. Goel, P., Kulik, L., Kotagiri, R.: Privacy aware trajectory determination in road traffic networks. In: Proceedings of the 20th International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2012, pp. 406–409. ACM, New York (2012)

    Google Scholar 

  7. Alt, H., Godau, M.: Computing the Fréchet distance between two polygonal curves. Int. J. Comput. Geometry Appl. 5, 75–91 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  8. Buchin, K., Buchin, M., Wang, Y.: Exact algorithms for partial curve matching via the Fréchet distance. In: Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2009, pp. 645–654. Society for Industrial and Applied Mathematics, Philadelphia (2009)

    Chapter  Google Scholar 

  9. Rockafellar, R.: Variational analysis. Springer, Berlin (1998)

    Book  MATH  Google Scholar 

  10. Devogele, T.: A new merging process for data integration based on the discrete Fréchet distance. In: Richardson, D.E., Van Oosterom, P., van Oosterom, P.J.M. (eds.) Advances in Spatial Data Handling: 10th International Symposium on Spatial Data Handling, Ottawa, Canada, pp. 167–181 (2002)

    Google Scholar 

  11. Zhang, L., Sester, M.: Incremental data acquisition from GPS-traces. In: Geospatial Data and Geovisualization: Environment, Security, and Society; Special Joint Symposium of ISPRS Commission IV and AutoCarto 2010 in Conjunction with ASPRS/CaGIS 2010 Special Conference. ASPRS/CaGIS 2010 (2010)

    Google Scholar 

  12. Cao, L., Krumm, J.: From GPS traces to a routable road map. In: Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2009, pp. 3–12. ACM, New York (2009)

    Google Scholar 

  13. Buchin, K., Buchin, M., Gudmundsson, J., Löffler, M., Luo, J.: Detecting commuting patterns by clustering subtrajectories. In: Hong, S.-H., Nagamochi, H., Fukunaga, T. (eds.) ISAAC 2008. LNCS, vol. 5369, pp. 644–655. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  14. Lee, J.G., Han, J., Whang, K.Y.: Trajectory clustering: a partition-and-group framework. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, SIGMOD 2007, pp. 593–604. ACM, New York (2007)

    Chapter  Google Scholar 

  15. Zhu, H., Luo, J., Yin, H., Zhou, X., Huang, J.Z., Zhan, F.B.: Mining trajectory corridors using Fréchet distance and meshing grids. In: Zaki, M.J., Yu, J.X., Ravindran, B., Pudi, V. (eds.) PAKDD 2010, Part I. LNCS, vol. 6118, pp. 228–237. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. Gudmundsson, J., Valladares, N.: A GPU approach to subtrajectory clustering using the Fréchet distance. In: Proceedings of the 20th International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2012, pp. 259–268. ACM, New York (2012)

    Google Scholar 

  17. Dodge, S., Laube, P., Weibel, R.: Movement similarity assessment using symbolic representation of trajectories. Int. J. Geogr. Inf. Sci. 26(9), 1563–1588 (2012)

    Article  Google Scholar 

  18. van Kreveld, M., Wiratma, L.: Median trajectories using well-visited regions and shortest paths. In: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2011, pp. 241–250. ACM, New York (2011)

    Google Scholar 

  19. Scott, J.: JCoord (2013), http://www.jstott.me.uk/jcoord/

  20. Foster, D.: GPX: the GPS exchange format (2013), http://www.topografix.com/gpx.asp

  21. OpenStreetMap Community: OSM XML - OpenStreetMap wiki (2013), https://wiki.openstreetmap.org/wiki/OSM_XML

  22. Ramer, U.: An iterative procedure for the polygonal approximation of plane curves. Computer Graphics and Image Processing 1(3), 244–256 (1972)

    Article  Google Scholar 

  23. Douglas, D.H., Peucker, T.K.: Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartographica: The International Journal for Geographic Information and Geovisualization 10(2), 112–122 (1973)

    Article  Google Scholar 

  24. Mitlmeier, J.: Generierung von Straßengraphen aus aggregierten GPS-Spuren. Master thesis, Freie Universität Berlin (2012)

    Google Scholar 

  25. OpenStreetMap Community: Public GPS traces, http://www.openstreetmap.org/traces (2013)

  26. Fischer, J.: GPS track aggregation with use of Fréchet distance. Bachelor thesis, Freie Universität Berlin (2012)

    Google Scholar 

  27. Müller, S.: Agg2graph (2013), http://sebastian-fu.github.com/agg2graph/

  28. Hastie, T., Tibshirani, R., Friedman, J.H.: The elements of statistical learning: data mining, inference, and prediction: with 200 full-color illustrations. Springer, New York (2001)

    Google Scholar 

  29. Hastie, T.J., Tibshirani, R.J.: Generalized additive models. Chapman & Hall, London (1990)

    MATH  Google Scholar 

  30. Welch, G., Bishop, G.: An introduction to the Kalman filter. Technical report, Chapel Hill, NC, USA (1995)

    Google Scholar 

  31. Chazal, F., Chen, D., Guibas, L., Jiang, X., Sommer, C.: Data-driven trajectory smoothing. In: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2011, pp. 251–260. ACM, New York (2011)

    Google Scholar 

  32. Buchin, M., Driemel, A., van Kreveld, M., Sacristán, V.: An algorithmic framework for segmenting trajectories based on spatio-temporal criteria. In: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2010, pp. 202–211. ACM, New York (2010)

    Google Scholar 

  33. Xie, K., Deng, K., Zhou, X.: From trajectories to activities: a spatio-temporal join approach. In: Proceedings of the 2009 International Workshop on Location Based Social Networks, LBSN 2009, pp. 25–32. ACM, New York (2009)

    Chapter  Google Scholar 

  34. Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 10(5), 557–570 (2002)

    Article  MATH  MathSciNet  Google Scholar 

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Müller, S., Mehta, P., Voisard, A. (2014). Trajectory Aggregation for a Routable Map. In: Pfoser, D., Li, KJ. (eds) Web and Wireless Geographical Information Systems. W2GIS 2014. Lecture Notes in Computer Science, vol 8470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55334-9_3

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  • DOI: https://doi.org/10.1007/978-3-642-55334-9_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-55333-2

  • Online ISBN: 978-3-642-55334-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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