Towards a flexible and scalable fleet management service

IWCTS 2013 - 6th ACM SIGSPATIAL International Workshop on Computational Transportation Science

Volumn , Issue , 2013, Pages 79-84

  Efentakis, Alexandros ^a   Brakatsoulas, Sotiris ^a   Grivas, Nikos ^a   Lamprianidis, Giorgos ^a   Patroumpas, Kostas ^b   Pfoser, Dieter ^a,c  

^a Research Center Athena   (Greece)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^c GEORGE MASON UNIVERSITY   (United States)

Author keywords

FCD; Fleet Management; Isochrones; Map matching; Shortest Path

Indexed keywords

RESEARCH;

FCD; FLEET MANAGEMENT; ISOCHRONES; MAP MATCHING; SHORTEST-PATH;

FLEET OPERATIONS;

EID: 84892501453     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2533828.2533835     Document Type: Conference Paper

References (17)

1. V. Bauer, J. Gamper, R. Loperfido, S. Profanter, S. Putzer, and I. Timko. Computing isochrones in multi-modal, schedule-based transport networks. In Proc. 16th ACM SIGSPATIAL GIS conf., GIS '08, pages 78:1-78:2, New York, NY, USA, 2008. ACM.
2. S. Brakatsoulas, D. Pfoser, R. Salas, and C. Wenk. On map-matching vehicle tracking data. In Proc. 31st VLDB Conference, pages 853-864, 2005.
3. D. Delling and D. Wagner. Landmark-based routing in dynamic graphs. In Proc. 6th Experimental algorithms conf., WEA'07, pages 52-65, Berlin, Heidelberg, 2007. Springer-Verlag.
4. A. Efentakis, N. Grivas, G. Lamprianidis, G. Magenschab, and D. Pfoser. Isochrones, Traffic and DEMOgraphics. In Proc. 21st ACM SIGSPATIAL GIS conf., 2013. To appear.
5. A. Efentakis and D. Pfoser. Optimizing Landmark-Based Routing and Preprocessing. In Proc. 6th ACM SIGSPATIAL Computational Transportation Science Workshop, 2013. To appear.
6. A. Efentakis, D. Pfoser, and A. Voisard. Efficient data management in support of shortest-path computation. In Proc. 4th ACM SIGSPATIAL Computational Transportation Science Workshop, CTS '11, pages 28-33. ACM, 2011.
7. A. Efentakis, D. Theodorakis, and D. Pfoser. Crowdsourcing computing resources for shortest-path computation. In Proceedings of the 20th International Conference on Advances in Geographic Information Systems, SIGSPATIAL '12, pages 434-437, New York, NY, USA, 2012. ACM.
8. R. Geisberger, P. Sanders, D. Schultes, and D. Delling. Contraction hierarchies: faster and simpler hierarchical routing in road networks. In Proc. 7th Experimental Algorithms conf., WEA'08, pages 319-333, Berlin, Heidelberg, 2008. Springer-Verlag.
9. A. V. Goldberg and C. Harrelson. Computing the shortest path: A* search meets graph theory. In 16th ACM-SIAM Symposium on Discrete Algorithms, pages 156-165, 2004.
10. Google. Encoded Polyline Algorithm Format [Online]. https://developers. google.com/maps/documentation/utilities/polylinealgorithm, 2013.
11. L. Kabrt. Travel Time Analysis. http://code.google.com/p/ traveltimeanalysis/source/browse, 2010.
12. Y. Lou, C. Zhang, Y. Zheng, X. Xie, W. Wang, and Y. Huang. Map-matching for low-sampling-rate gps trajectories. In Proc. 17th ACM SIGSPATIAL GIS conf., GIS '09, pages 352-361, New York, NY, USA, 2009. ACM.
13. D. Luxen and C. Vetter. Real-time routing with openstreetmap data. In Proc. 19th ACM SIGSPATIAL GIS conf., GIS '11, pages 513-516, New York, NY, USA, 2011. ACM.
14. S. Marciuska and J. Gamper. Determining objects within isochrones in spatial network databases. In Proc. 14th ADBIS conf., ADBIS'10, pages 392-405, Berlin, Heidelberg, 2010. Springer-Verlag.
15. Okeanos. õkeanos IaaS [Online]. https://okeanos.grnet.gr/home/, 2013.
16. SimpleFleet. Democratizing fleet management [online]. http://www.simplefleet.eu, 2013.
17. C. Wenk, R. Salas, and D. Pfoser. Addressing the need for map-matching speed: Localizing global curve-matching algorithms. In Proc. 18th SSDBM conf., pages 379-388, 2006.