DOI QR코드

DOI QR Code

Study on Map Matching Using Characteristics of Vehicular Movements

차량 주행 특성을 이용한 지도 매칭에 대한 연구

  • 이세환 (웨이브엠 교통정보팀) ;
  • 이철기 (아주대학교 공과대학 교통시스템공학과) ;
  • 윤일수 (아주대학교 공과대학 교통시스템공학과) ;
  • 김남선 (국립경찰대학 치안정책연구소) ;
  • 강다미 (아주대학교 건설교통공학과)
  • Received : 2015.07.02
  • Accepted : 2015.10.02
  • Published : 2015.10.15

Abstract

PURPOSES : In link matching using vehicular trajectory in a car navigation system, it is technically difficult to match the location of the subject vehicle with a link on an electronic map in the vehicle on a grade separation highway segment consisting of an elevated highway and atgrade highway, because of the overlap of geometric lines of the two highways. This study was initiated to propose a link matching algorithm using the characteristics of vehicular movement of the subject vehicle. METHODS : The selected test site is the highway segment between Jeong-reung IC and Gil-eum IC where the Inner Circulation Road and Jeong-reung-ro run together. To evaluate the proposed algorithm, this study collected the raw packet data of vehicles that drove on the test site. In a simulation environment, link matching was performed using an existing algorithm as well as the proposed algorithm. RESULTS: It was clearly found that the characteristics of vehicular movements are different on the two highways. CONCLUSIONS: The proposed algorithm outperformed the existing algorithm.

Keywords

References

  1. D. Andersson and J. Fjellstorm, Vehicle positioning with map matching using integration of a dead reckoning system and GPS. Linkoping, Sweden : Linkopings universitet/Institutionen for systemteknik, 2004.
  2. D. Min, L. Zhilin, and C. Xiaoyang, "Extended Hausdorff Distance for Spatial Objects in GIS", International Journal of Geographical Information Science, Vol. 21, No. 4, pp. 459-475, 2007. https://doi.org/10.1080/13658810601073315
  3. J. H. Lee and J. W. Kim, "Recognition of a new car plate using color information and error back-propagation neural network algorithms", J. of the Korea Institute of Electronic Communication Sciences, vol. 5, no. 5, pp. 471-476, Oct. 2010.
  4. K. B. Kim and Y. W. Woo, "An enhanced max-min neural network using a fuzzy control method", J. of the Korea Institute of Electronic Communication Sciences, Vol. 8, No. 8, pp. 1195-1200, Aug. 2013. https://doi.org/10.13067/JKIECS.2013.8.8.1195
  5. M. A. Quddus, W. Y, Ochieng, L. Zhao, and R. B. Noland, "A general map matching algorithm for transport telematics applications", Springer-Verlag GPS Solutions, Vol. 7, No. 3, pp. 157-167, September, 2003. https://doi.org/10.1007/s10291-003-0069-z
  6. S. Jeong, The study of CNS(Car Navigation System) focusing on map matching method, Proceeding of the Korea Institute of Information Scientists and Engineers, 2003.
  7. S. H. Cheon, H. M. Kim, "Use of car navigation data for traffic section", KOTI, Monthly Traffic, Vol. 183, pp. 54-59, 2013.
  8. Y. Huh, W. M. Son, J. B. Lee, "Road network data matching using the network division technique", Journal of Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, vol. 31, no. 4, pp. 285-292, 2013. https://doi.org/10.7848/ksgpc.2013.31.4.285
  9. Y. Kim, "Map Matching Algorithm in BIS", Master Thesis, Chungang University, 2014.
  10. Y. Li, Q. Huang, M. Kerber, L. Zhang, L. Guibas, "Large-Scale Joint Map Matching of GPS Traces", Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 214-223, November, 2013.
  11. Y. S. Bang, J. B. Lee, Y. Huh, K. Y. Yu, "Node Matching of Road Network Data by Comparing link shape", Journal of Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, pp. 23-25, 2009.
  12. W. Y. Ochieng, M. A. Quddus, and R. B. Noland, "Map-matching in complex urban road networks", J. of Cartography, Vol. 55, No. 2, pp. 1-14, 2003.