Efficient cost-based tracking of scheduled vehicle journeys

Proceedings - IEEE International Conference on Mobile Data Management

Volumn , Issue , 2008, Pages 9-16

  Tiešyte, Dalia ^a   Jensen, Christian S ^a  

^a AALBORG UNIVERSITY   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSPORTATION ROUTES;

GPS DATA; INTERNATIONAL CONFERENCES; MOBILE DATA MANAGEMENT;

VEHICLES;

EID: 51349110219     PISSN: 15516245     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MDM.2008.22     Document Type: Conference Paper

References (19)

1. Y. Bin, Y. Zhongzhen, and Y Baozhen. Bus arrival time prediction using support vector machines. Int. Transp. Syst., 10: 151-158.
2. F. Cathey and D. Dailey. A prescription for transit arrival/departure prediction using automatic vehicle location data. Transp. Res. Part C. pp. 241-264, 2003.
3. M. Chen, X. Liu, and J. XiaDOI Dynamic prediction method with schedule recovery impact for bus arrival time. Transp. Res. Rec, 1932(1): 208-217, 2005.
4. S. I.-J. Chien, Y. Ding, and C. Wei. Dynamic bus arrival time prediction with artificial neural networks. Transp. Engrg., 128: 429-438, 2002.
5. D. Crout. Accuracy and Precision of the Transit Tracker System. Transp. Res. Rec. 1992(-1): 93-100. 2007.
6. D. Dailey, S. Maclean, F. Cathey, and Z. Wall. Transit vehicle arrival prediction: an algorithm and a large scale implementation. Transp. Res. Rec., Transportation Network Modeling, pp. 46-51, 2001.
7. J. R. Hee and L. R. Rilett. Bus arrival time prediction using artificial neural network model. In IEEE ITSC, pp. 988-993. 2004.
8. Hovedstatens Udviklinksraad (HUR). http://www.hur.dk/.
9. R. H. Jeong. The prediction of bus arrival time using automatic vehicle location systems data. Doctoral dissertation, Texas A&M University, 2004.
10. R. Kalaputapu and M. J. Demetsky. Modeling schedule deviations of buses using automatic vehicle location data and artificial neural networks. Transp. Res. Rec., 1497: 44-52, 1995.
11. Nordjyllands Trafikselskab (NT). http://www.nordjyllandstrafikselskab. dk/.
12. T. Park, S. Lee, and Y.-J. Moon. Real time estimation of bus arrival time under mobile environment. In ICCSA. 3043: 1088-1096, 2004.
13. A. Shalaby and A. Farhan. Prediction model of bus arrival and departure times using avl and apc data. Journal of Pub. Transp., 7: 41-61, 2004.
14. D. Tiešytė and C. S. Jensen. Challenges in the tracking and prediction of scheduled-vehicle journeys. In IEEE PerCom Workshops, pp. 407-412. March 2007.
15. A. Čivilis, C. S. Jensen, and S. Pakalnis. Techniques for efficient road-network-based tracking of moving objects. In IEEE TKDE, 17(5): 698-712, 2005.
16. O. Wolfson, S. Chamberlain, S. Dao, L. Jiang, and G. Mendez. Cost and imprecision in modeling the position of moving objects. In ICDE, pp. 588-596, 1998.
17. O. Wolfson, A. P. Sistla, S. Chamberlain, and Y Yesha. Updating and querying databases that track mobile units. Distrib. and Par. Databases, 7: 257-387, 1999.
18. O. Wolfson and H. Yin. Accuracy and resource consumption in tracking moving objects. In SSTD, pp. 325-343, 2003.
19. J. Zhou, H. Leong, Q. Lu, and K. Lee. Generic adaptive moving object tracking algorithms. ICPP, pp. 93-100, 2006.