Trace Interpolation Algorithm Based on Intersection Vehicle Movement Modeling

DOI: 10.4236/wsn.2010.211099   PDF   HTML     6,361 Downloads   10,038 Views   Citations


Real vehicle tracking data play an important role in the research of routing in vehicle sensor networks. Most of the vehicle tracking data, however, were collected periodically and could not meet the requirements of real-time by many applications. Most of the existing trace interpolation algorithms use uniform interpolation methods and have low accuracy problem. From our observation, intersection vehicle status is critical to the vehicle movement. In this paper, we proposed a novel trace interpolation algorithm. Our algorithm used intersection vehicle movement modeling (IVMM) and velocity data mining (VDM) to assist the interpolation process. The algorithm is evaluated with real vehicle GPS data. Results show that our algorithm has much higher accuracy than traditional trace interpolation algorithms.

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J. Shen and G. Xue, "Trace Interpolation Algorithm Based on Intersection Vehicle Movement Modeling," Wireless Sensor Network, Vol. 2 No. 11, 2010, pp. 823-827. doi: 10.4236/wsn.2010.211099.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] X. W. Chen, F. Z. Zhang, M. Sun and Y. H. Luo, “System Architecture of LBS Based on Spatial Information Integration,” IEEE International conference on Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings, Anchorage, Alaska, Vol. 4, September 2004, pp. 2409-2411.
[2] Y. Q. Huang and X. M. Gu, “The Combination of GPS and GSM Mobile Location Technology,” Journal of Jiamusi University, Sicence, Vol. 23, October 2005, pp. 530-533.
[3] L. Perusco and K. Michael, “Humancentric Applications of Precise Location Based Services,” IEEE International Conference on e-Business Engineering, Beijing, 18-21 October 2005, pp. 409-418.
[4] M. Wallbaum and S. Diepolder, “Benchmarking Wireless Location Systems,” The Second International Workshop on Mobile Commerce and Services, IEEE, Germany, July 2005, pp. 42-51.
[5] D. Bernstein and A. Kornhauser, “An Introduction to Map Matching for Personal Navigation Assistants,” Technical report, New Jersey TIDE Center Technical Report, 1996.
[6] M. Quddus, W. Ochieng, L. Zhao and R. Noland, “A General Map Matching Algorithm for Transport Telematics Applications,” GPS Solutions Journal, Vol. 7, No. 3, 2003, pp. 157-167.
[7] H. Yin and O. Wolfson, “A Weight-Based Map Matching Method in Moving Objects Databases,” In Proceedings of 16th SSDBM conference, Santorini Island, Greece, 2004, pp. 437-438.
[8] H. H. Gao, K. B. Jia, X. H. Bao and J. He, “Research and Implementation of Road Match and Trace Replay Algorithm,” MultiMedia and Information Technology, Three Gorges, 30-31 December 2008, pp. 74-77.
[9] J. Zhao and G. Cao, “VADD: Vehicle-Assisted Data Delivery in Vehicular Ad Hoc Networks,” Proceedings of IEEE INFOCOM’06, Barcelona, April 2006, pp. 1-12.
[10] M. Jerbi, S. M. Senouci, R. Meraihi and Y. Ghamri- Doudane, “An Improved Vehicular Ad Hoc Routing Protocol for City Environments,” IEEE International Conference on Communications, Glasgow, 24-28 June 2007, pp. 3972-3979.
[11] J. Zhao, Y. Zhang and G. Cao, “Data Pouring and Buffering on the Road: A New Data Dissemination Paradigm for Vehicular Ad Hoc Networks,” IEEE Transactions on Vehicular Technology, Vol. 56, No. 6, November 2007, pp. 3266-3277.
[12] F. Dion, H. Rakha and Y. Kang, “Comparison of Delay Estimates at Undersaturated and Over-Saturated Pre- Timed Signalized Intersections,” Transportation Research, Part B: Methodological, Vol. 38, No. 2, Feburary 2004, pp. 99-122.

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