Abstract
In order to analyze the behavior of moving objects, a measure for determining the similarity of trajectories needs to be defined. Although research has been conducted that retrieved similar trajectories of moving objects in Euclidean space, very little research has been conducted on moving objects in the space defined by road networks. In terms of real applications, most moving objects are located in road network space rather than in Euclidean space. In this paper, we investigate the properties of similar trajectories in road network space. And we propose a method to retrieve similar trajectories based on this observation and similarity measure between trajectories on road network space. Experimental results show that this method provides not only a practical method for searching for similar trajectories but also a clustering method for trajectories.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pfoser, D., Jensen, C.S., Theodoridis, Y.: Novel Approaches in Query Processing for Moving Object Trajectories. In: Proceedings of the 26th International Conference on Very Large Data Bases, pp. 395–406 (2000)
Vlachos, M., Kollios, G., Gunopulos, D.: Discovering Similar Multidimensional Trajectories. In: Proceedings of the Eighteenth International Conference on Data Engineering, pp. 673–684. IEEE Computer Society Press, Los Alamitos (2002)
Yanagisawa, Y., ichi Akahani, J., Satoh, T.: Shape-Based Similarity Query for Trajectory of Mobile Objects. In: Chen, M.-S., Chrysanthis, P.K., Sloman, M., Zaslavsky, A. (eds.) MDM 2003. LNCS, vol. 2574, pp. 63–77. Springer, Heidelberg (2003)
Speicys, L., Jensen, C.S., Kligys, A.: Computational Data Modeling for Network-constrained Moving Objects. In: Proceedings of the Eleventh ACM International Symposium on Advances in Geographic Information Systems, pp. 118–125 (2003)
Vazirgiannis, M., Wolfson, O.: A Spatiotemporal Model and Language for Moving Objects on Road Networks. In: Proceedings of the Seventh International Symposium on Spatial and Temporal Databases, pp. 20–35. Springer, Heidelberg (2001)
Hariharan, R., Toyama, K.: Project Lachesis: Parsing and Modeling Location Histories. In: Egenhofer, M.J., Freksa, C., Miller, H.J. (eds.) GIScience 2004. LNCS, vol. 3234, pp. 106–124. Springer, Heidelberg (2004)
Hornsby, K., Egenhofer, M.: Modeling Moving Objects over Multiple Granularities. Annals of Mathematics and Artificial Intelligence 36, 177–194 (2002)
Jensen, C.S., Kolárvr, J., Pedersen, T.B., Timko, I.: Nearest Neighbor Queries in Road Networks. In: Proceedings of the Eleventh ACM International Symposium on Advances in Geographic Information Systems, pp. 1–8 (2003)
Van de Weghe, N., Cohn, A.G., Bogaert, P., De Maeyer, P.: Representation of Moving Objects along a Road Network. In: Proceedings of the twelfth International Conference on Geoinformatics
Vlachos, M., Gunopulos, D., Kollios, G.: Robust Similarity Measures for Mobile Object Trajectories. In: Proceedings of the Thirteenth International Workshop on Database and Expert Systems Applications, pp. 721–728. IEEE Computer Society Press, Los Alamitos (2002)
Shim, C.-B., Chang, J.-W.: Similar Sub-Trajectory Retrieval for Moving Objects in Spatio-temporal Databases. In: Proceedings of the Seventh East-European Conference on Advances in Databases and Informations Systems, pp. 308–322. Springer, Heidelberg (2003)
Zhang, T., Ramakrishnan, R., Livny, M.: BIRCH: An Efficient Data Clustering Method for Very Large Databases. In: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, pp. 103–114. ACM Press, New York (1996)
Wang, H., Wang, W., Yang, J., Yu, P.S.: Clustering by Pattern Similarity in Large Data Sets. In: Proceedings of the 2002 ACM SIGMOD international conference on Management of data, pp. 394–405. ACM Press, New York (2002)
Liao, S., Lopez, M.A., Leutenegger, S.T.: High Dimensional Similartity Search With Space Filling Curves. In: Proceedings of the seventeenth International Conference on Data Engineering, pp. 615–622. IEEE Computer Society Press, Los Alamitos (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hwang, JR., Kang, HY., Li, KJ. (2005). Spatio-temporal Similarity Analysis Between Trajectories on Road Networks. In: Akoka, J., et al. Perspectives in Conceptual Modeling. ER 2005. Lecture Notes in Computer Science, vol 3770. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11568346_30
Download citation
DOI: https://doi.org/10.1007/11568346_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29395-8
Online ISBN: 978-3-540-32239-9
eBook Packages: Computer ScienceComputer Science (R0)