On Map-Matching Vehicle Tracking Data

@inproceedings{Brakatsoulas2005OnMV,
  title={On Map-Matching Vehicle Tracking Data},
  author={Sotiris Brakatsoulas and Dieter Pfoser and Randall Salas and Carola Wenk},
  booktitle={VLDB},
  year={2005}
}
Vehicle tracking data is an essential “raw” material for a broad range of applications such as traffic management and control, routing, and navigation. An important issue with this data is its accuracy. The method of sampling vehicular movement using GPS is affected by two error sources and consequently produces inaccurate trajectory data. To become useful, the data has to be related to the underlying road network by means of map matching algorithms. We present three such algorithms that… CONTINUE READING
Highly Influential
This paper has highly influenced 29 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 507 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 295 extracted citations

507 Citations

020406080'08'11'14'17
Citations per Year
Semantic Scholar estimates that this publication has 507 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 19 references

New approaches for traffic management in metropolitan areas

  • R. Kuehne, R.-P. Schaefer, J. Mikat, K.-U. Thiessenhusen, U. Boettger, S. Lorkowski
  • In Proc. IFAC CTS Symposium,
  • 2003
1 Excerpt

Matching GPS observations to locations on a digital map

  • J. Greenfeld
  • In Proc. 81th Annual Meeting of the…
  • 2002
3 Excerpts

Efficient algorithms for normalized edit distance

  • A. Arslan, O. Egecioglu
  • J. of Discrete Algorithms,
  • 2000
1 Excerpt

Similar Papers

Loading similar papers…