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Advances in Multimedia
Volume 2015 (2015), Article ID 420689, 7 pages
http://dx.doi.org/10.1155/2015/420689
Research Article

Discovering Congested Routes Using Vehicle Trajectories in Road Networks

1School of Information and Communication Engineering, Chungbuk National University, 52 Naesudong-ro, Chungbuk, Seowon-Gu, Cheongju 362-763, Republic of Korea
2School of Software, Xidian University, No. 2 South Taibai Road, Xi’an City, Shaanxi 710071, China

Received 28 August 2014; Accepted 23 October 2014

Academic Editor: Seungmin Rho

Copyright © 2015 Kyoung Soo Bok et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Z. Chen, H. T. Shen, and X. Zhou, “Discovering popular routes from trajectories,” in Proceedings of the IEEE 27th International Conference on Data Engineering (ICDE '11), pp. 900–911, Hanover, Germany, April 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. P. Cudre-Mauroux, E. Wu, and S. Madden, “TrajStore: an adaptive storage system for very large trajectory data sets,” in Proceedings of the 26th IEEE International Conference on Data Engineering (ICDE '10), pp. 109–120, Long Beach, Calif, USA, March 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. E. Kanoulas, Y. Du, T. Xia, and D. Zhang, “Finding fastest paths on a road network with speed patterns,” in Proceedings of the 22nd International Conference on Data Engineering, p. 10, April 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. G. Gidófalvi, C. Borgelt, M. Kaul, and T. B. Pedersen, “Frequent route based continuous moving object location- and density prediction on road networks,” in Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS '11), pp. 381–384, November 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. J.-W. Chang, M.-S. Song, and J.-H. Um, “TMN-tree: new trajectory index structure for moving objects in spatial networks,” in Proceedings of the IEEE 10th International Conference on Computer and Information Technology (CIT '10), pp. 1633–1638, Bradford, UK, June-July 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. M. Huang, P. Hu, and L. Xia, “A grid based trajectory indexing method for moving objects on fixed network,” in Proceedings of the 18th International Conference on Geoinformatics, June 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. J.-I. Won, S.-W. Kim, J.-H. Baek, and J. Lee, “Trajectory clustering in road network environment,” in Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining (CIDM '09), pp. 299–305, April 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. G.-P. Roh, J.-W. Roh, S.-W. Hwang, and B.-K. Yi, “Supporting pattern-matching queries over trajectories on road networks,” IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 11, pp. 1753–1758, 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. N. Pelekis, I. Kopanakis, E. E. Kotsifakos, E. Frentzos, and Y. Theodoridis, “Clustering trajectories of moving objects in an uncertain world,” in Proceedings of the IEEE International Conference on Data Mining (ICDM '09), pp. 417–427, December 2009. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Kimura, S. Inoue, Y. Kakuda, and T. Dohi, “A route discovery method for alleviating traffic congestion based on VANETs in urban transportations considering a relation between vehicle density and average velocity,” in Proceedings of International Symposium on 10th International Symposium on Autonomous Decentralized Systems (ISADS '11), pp. 299–302, March 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. L.-Y. Wei, W.-C. Peng, and W.-C. Lee, “Exploring pattern-aware travel routes for trajectory search,” ACM Transactions on Intelligent Systems and Technology, vol. 4, no. 3, article 48, 2013. View at Publisher · View at Google Scholar · View at Scopus
  12. Y. Xu and J. Wang, “Optimal path solution of urban traffic road,” in Proceedings of the 7th International Conference on Natural Computation (ICNC '11), pp. 799–802, July 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. A. Kharrat, K. Zeitouni, I. Sandu-Popa, and S. Faiz, “Characterizing traffic density and its evolution through moving object trajectories,” in Proceedings of the 5th International Conference on Signal Image Technology and Internet Based Systems (SITIS '09), pp. 257–263, December 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. K. W. Min, J. W. Kim, and J. H. Park, “Optimal route determination technology based on trajectory querying moving object database,” in Proceedings of International Conference on Database and Expert Systems Applications, pp. 666–675, 2006.
  15. V. Tyagi, S. Kalyanaraman, and R. Krishnapuram, “Vehicular traffic density state estimation based on cumulative road acoustics,” IEEE Transactions on Intelligent Transportation Systems, vol. 13, no. 3, pp. 1156–1166, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. X. Li, J. Han, J. Lee, and H. Gonzalez, “Traffic density-based discovery of hot routes in road networks,” in Proceedings of SIAM International Conference on Data Mining, pp. 441–459, 2007.
  17. H. M. O. Mokhtar, O. Ossama, and M. E. Sharkawi, “A time parameterized technique for clustering moving object trajectories,” Journal of Data Mining and Knowledge Management Process, vol. 1, no. 1, pp. 14–30, 2011. View at Google Scholar
  18. I. Abraham, D. Delling, A. V. Goldberg, and R. F. Werneck, “Alternative routes in road networks,” Journal of Experimental Algorithmics, vol. 18, article 1.3, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. A. Selamat, M. Zolfpour-Arokhlo, S. Z. Hashim, and M. H. Selamat, “A fast path planning algorithm for route guidance system,” in Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC '11), pp. 2773–2778, Anchorage, Alaska, USA, October 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. H. Gonzalez, J. Han, X. Li, M. Myslinska, and J. P. Sondag, “Adaptive fastest path computation on a road network: a traffic mining approach,” in Proceedings of International Conference on Very Large Data Bases, pp. 794–805, 2007.
  21. T. Brinkhoff, “A framework for generating network-based moving objects,” GeoInformatica, vol. 6, no. 2, pp. 153–180, 2002. View at Publisher · View at Google Scholar · View at Scopus