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제한된 GPS정보를 활용한 통행 시간 추정 알고리즘에 관한 연구

A Study on Algorithm for Travel Time Estimation using Restricted GPS Data

  • 유남현 (경남대학교 조선해양IT공학과)
  • 투고 : 2014.10.15
  • 심사 : 2014.12.15
  • 발행 : 2014.12.31

초록

교통정보서비스에서 정확한 통행량과 통행속도를 산출하기 위해서는 기본적으로 제공되는 GPS 데이터의 품질이 보장되어야 한다. 그렇지만, 통신비용의 문제로 인하여 GPS 데이터를 제공하는 Probe 차량으로부터 제한된 GPS 데이터가 제공이 된다면 정확한 정보를 제공하기 어렵다. 본 논문에서는 제한된 GPS 데이터로 인하여 손실되는 링크들을 위상정보와 결합시켜 복원시킨 후, 통행 속도를 산출하는 알고리즘을 개발하였다. 이를 적용한 S시의 T 교통정보서비스는 이전보다 더 정확한 통행량 및 통행 속도를 시민들에게 제공할 수 있게 되었다.

In order to calculate accurate traffic and traffic speed, qualified and sufficient GPS data should be provided. However, it is difficult to provide accurate traffic information using restricted GPS data from probe vehicles because of communication costs. This paper developed a algorithm that recovers links omitted by restricted GPS data with topology information, and calculate traffic speed with original links and recovered links. T traffic information service of city with a new algorithm can provide more accurate traffic and traffic speed than the original system.

키워드

참고문헌

  1. D. Choi, "Active ITS infrastructure management strategy for enhanced ITS service," J. Korea Contents, vol. 4, no. 9, Sept. 2014, pp. 45-53. https://doi.org/10.5392/JKCA.2014.14.09.045
  2. 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, Sept. 2003, pp. 157-167. https://doi.org/10.1007/s10291-003-0069-z
  3. W. Y. Ochieng, M. A. Quddus, and R. B. Noland, "Map-matching in complex urban road networks," J. of Cartography, vol. 55, no. 2, 2003, pp. 1-14.
  4. K.-B. Kim and Y.-W. Woo, "An enhanced maxmin neural network using a fuzzy control method," J. of the Korea Institute of Electronic Communication Sciences, vol. 8, no. 8, Aug. 2013, pp. 1195-1200. https://doi.org/10.13067/JKIECS.2013.8.8.1195
  5. 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, Oct. 2010, pp. 471-476.
  6. K. Choi, W.-P. Hong, and Y.-H. Choi, "A travel time estimation algorithm using transit GPS probe data," J. of Civil Engineering, vol. 26, no. 5, Sept. 2006, pp. 739-746.
  7. G.-Y. Hwang, Y.-K. Jeong, H.-J Choi, and X. Hui, "A study on a traffic signal operation system using complex sensor," J. of the Korea Institute of Electronic Communication Sciences, vol. 8, no. 10, Oct. 2013, pp. 1573-1580. https://doi.org/10.13067/JKIECS.2013.8.10.1573
  8. 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.
  9. E. J. Krakiwsky, C. B. Harris, and R. V. C. Wong, "A KALMAN filter for intergrating dead reckoning, map matching and GPS positioning," In Proc. IEEE Int. Symp. on Position Location and Navigation, Orlando, FL, Dec. 1988, pp. 39-46.
  10. A. Leonhardi, C. Nicu, and K. Rothermel, "A map-based dead reckoning protocol for updating location information," In Proc. IEEE Int. Symp. on Parallel and Distributed Processing, Ft. Lauderdale, FL, Apr. 2001.

피인용 문헌

  1. A Traffic congestion judgement Algorithm development for signal control using taxi gps data vol.15, pp.3, 2016, https://doi.org/10.12815/kits.2016.15.3.052