DOI QR코드

DOI QR Code

An Expressway Path Travel Time Estimation Using Hi-pass DSRC Off-Line Travel Data

하이패스 DSRC 자료를 활용한 고속도로 오프라인 경로통행시간 추정기법 개발

  • Shim, Sangwoo (Transportation Research Institute, Ajou University) ;
  • Choi, Keechoo (Department of Transportation Systems Engineering, Ajou University) ;
  • Lee, Sangsoo (Department of Transportation Systems Engineering, Ajou University) ;
  • NamKoong, Seong J. (Expressway and Transportation Research Institute, Korea Expressway Corporation)
  • 심상우 (아주대학교 교통연구센터) ;
  • 최기주 (아주대학교 교통시스템공학과) ;
  • 이상수 (아주대학교 교통시스템공학과) ;
  • 남궁성 (한국도로공사 도로교통연구원)
  • Received : 2013.01.16
  • Accepted : 2013.03.20
  • Published : 2013.06.30

Abstract

Korea Expressway Corporation has been utilizing vehicles equipped with dedicated short range communication (DSRC) based on-board equipment (OBE) for collecting path travel times. A path based method (PBM) estimates the path travel time using probe vehicles traveling whole links on the path, so it is not always possible to obtain sufficient samples for calculating path travel time in the DSRC system. Having this problem in utilizing DSRC for travel time information, this study attempted to estimate path travel time with the help of a link based method (LBM) and examined whether the LBM can be used for obtaining reliable path travel times. Some comparisons were made and identified that the MAPE difference between the LBM and the PBM estimates are less than 3%, signaling that LBM can be used as a proxy for PBM in case of sparse sample conditions. Some limitations and a future research agenda have also been proposed.

DSRC의 원래 목적은 통행료 수집이었으나, 최근 한국도로공사는 DSRC 기반의 하이패스시스템을 교통정보체계에 응용하여 노변기지국간의 링크통행시간과 기 종점의 경로통행시간을 수집하는데 활용하고 있다. 기 종점을 통과한 차량을 통해 경로통행시간을 추정하는 경로기반방식(PBM: Path-based Method)은 수집표본수가 적고, 통과차량이 없을 경우 경로통행시간을 산출할 수 없는 문제점이 있는바, 링크기반방식(LBM: Link-based Method)을 제시하였다. 이는 실제 차량 궤적과 상이할 수 있는 문제점이 있으나 본 연구에서는 하이패스 DSRC 자료의 특성을 고려한 고속도로 경로통행시간 추정 모형 개발을 목적으로 개발되었다. LBM과 PBM의 경로통행시간 비교를 시도하였고, 그 결과 MAPE가 3% 이내로 나타났다. 이러한 결과로 볼 때 LBM을 통해 신뢰성 있는 경로통행시간을 추정할 수 있는 것으로 판단된다. 약간의 한계와 장래연구항목에 대해서도 제시하였다.

Keywords

References

  1. Ban X. J., Li Y., Skabardonis A., Margulici J. D. (2010), Performance Evaluation of Travel-Time Estimation Methods for Real-Time Traffic Applications, J. Intell. Transp. Syst., Vol.14, Issue 2, Taylor and Francis, pp.54-67. https://doi.org/10.1080/15472451003719699
  2. Chen C., Skabardonis A., Varaiya P. (2004), A System for Displaying Travel Times on Changeable Message Signs, Proceedings of 83rd TRB Annual Meeting, Washington D.C.
  3. Chen M., Chein S. (2000), Determining the Number of Probe Vehicles for Freeway Travel Estimation Using Microscopic Simulation, Transp. Res. Rec., No.1719, pp.61-68.
  4. Chen M., Chein S. (2001), Dynamic Freeway Travel Time Prediction Using Probe Vehicle Data: Link-based vs. Path-based, Proceedings of TRB 80th Annual Meeting, Washington D.C.
  5. Choi K. C., Shin C. H. (1998), Link Travel Time Derivation Using GPS and GIS, J. Korean Soc. Transp., Vol.16, No.2, Korean Society of Transportation, pp.197-207.
  6. Jintanakul K., Chu L., Jayakrishnan R. (2008), A Bayesian Mixture Model for Estimating Freeway Travel Time Distributions Using Small Probe Samples from Multiple Days, Proceedings of TRB 89th Annual Meeting, Washington D.C.
  7. Kang J. K., Namkoong S. (2002), Development of The Freeway Operating Time Prediction Model Using Toll Collection System Data, J. Korean Soc. Transp., Vol.20, No.4, Korean Society of Transportation, pp.151-162.
  8. Kim J. J., Rho J. H., Park D. J. (2006), On-Line Departure time based link travel time estimation using Spatial Detection System, J. Korean Soc. Transp., Vol.24, No.2, Korean Society of Transportation, pp.157-168.
  9. Lee E. E., Kim J. H. (2002), Development of a Freeway Travel Time Forecasting Model for Long Distance Section with Due Regard to Time-lag, J. Korean Soc. Transp., Vol.20, No.4, Korean Society of Transportation, pp.51-61.
  10. Lee H. S., Jeon K. S. (2009), A Path Travel Time Estimation Study on Expressway using TCS Link Travel Time, J. Korean Soc. Transp., Vol.27, No.5, Korean Society of Transportation, pp.209-221.
  11. Lee Y. I., Lee J. H. (2002), A Study on Link Travel Time Estimating Methodology for Traffic Information Service, J. Korean Soc. Transp., Vol.20, No.3, Korean Society of Transportation, pp.55-67.
  12. Namkoong S. (2005), Progressive Iterative Forward and Backward (PIFAB) Search Method to Estimate Path-Travel Time on Freeways Using Toll Collection System Data, J. Korean Soc. Transp., Vol.23, No.5, Korean Society of Transportation, pp.147-155.
  13. Oliver D., Nour-Eddin E. (2006), Innovative Processing of Toll Collection Data, LICIT report, No.0604.
  14. Pu W., Lin J., Long L. (2008), Real-Time Estimation of Urban Street Segment Travel Time Using Buses as Speed Probes, Proceedings of 89th TRB Annual Meeting, Washington, D.C.
  15. Pu W., Lin J., Long L. (2009), Estimation of Urban Street Segment Travel Time Using Buses as Real-time Speed Probes, Proceedings of 90th TRB Annual Meeting, Washington, D.C.
  16. Quiroga C., Bullock D. (1998), Travel Time Studies with Global Positioning and Geographic Information Systems: An Integrated Methodology, Transp. Res. Part C, Vol.6C, Issue 1-2, ELSEVIER, pp.101-127.
  17. Rice J., Zwet E. (2004), A Simple and Effective Method for Predicting Travel Times on Freeways, IEEE Trans. Intell. Transp. Syst., Vol.5, Issue 3, IEEE Transactions, pp.200-207. https://doi.org/10.1109/TITS.2004.833765
  18. Shim S. W., Choi K. C. (2006), Link Travel Time Estimation Using Uncompleted Link-passing GPS Probe Data in Congested Traffic Condition, J. Korean Soc. Transp., Vol.24, No.5, Korean Society of Transportation, pp.7-18.
  19. Soriguera F. Thorson L., Robuste F. (2007), Travel Time Measurement Using Toll Infrastructure, Transp. Res. Rec., Issue 2027, Transportation Research Board, pp.99-107.
  20. Sun L., Yang J., Mahmassani H. (2008), Travel Time Estimation based on Piecewise Truncated Quadratic Speed Trajectory, Transp. Res. Part A, Vol.42, Issue 1, ELSEVIER, pp.173-186.
  21. Thomas R., Robert M. (2003), Using Archived Data to Estimate Predicted Travel Time in the Phoenix Area, Proceedings of 13th ITS America 2003 Annual Meeting, Minneapolis.
  22. Wei C., Lee Y. (2007), Development of Freeway Travel Time Forecasting Models by Integrating Different Sources of Traffic Data, IEEE Trans. Veh. Technol., Vol.56, Issue 6-2, IEEE Transactions, pp.3682-3694. https://doi.org/10.1109/TVT.2007.901965
  23. Xie C., Cheu R., Lee D. (2004), Improving Arterial Link Travel Time Estimation by Data Fusion, Proceedings of 84th TRB Annual Meeting, Washington D.C.
  24. Yoshikazu O., Hideki U., Masao K. (2000), Travel Time Prediction Method for Expressway Using Toll Collection System Data, Proceedings of 7th ITS World Congress, Torino.
  25. Yu J. H. (2008), Real-time Travel Time Estimation Model Using Point-based and Link-based Data, J. Korean Soc. Road Eng., Vol.10, No.1, Korean Society of Road Engineers, pp.155-164.
  26. Zhang X., Rice J. (2003), Short-term Travel Time Prediction, Transp. Res. Part C, Vol.11, Issue 3-4, ELSEVIER, pp.187-210. https://doi.org/10.1016/S0968-090X(03)00026-3

Cited by

  1. A Study on Spatial Aggregation Method for Path Travel Time Estimation using Hi-Pass DSRC System vol.16, pp.3, 2014, https://doi.org/10.7855/IJHE.2014.16.3.119
  2. A Study on Improving the Reliability of DSRC Traffic Information Considering Traffic and Road Characteristics - Focusing on Busan Urban Expressway - vol.34, pp.5, 2014, https://doi.org/10.12652/Ksce.2014.34.5.1535