DOI QR코드

DOI QR Code

Comparison Study of O/D Estimation Methods for Building a Large-Sized Microscopic Traffic Simulation Network: Cases of Gravity Model and QUEEENSOD Method

대규모 미시교통시뮬레이션모형 구축을 위한 O/D 추정 방법 성능 비교 - 중력모형과 QUEENSOD 방법을 중심으로 -

  • 윤정은 (한국건설기술연구원 도로연구소) ;
  • 이철기 (아주대학교 교통시스템공학과) ;
  • 이환필 (한국도로공사 도로교통연구원) ;
  • 김경현 (아주대학교 건설교통공학과) ;
  • 박원일 (운수산업연구원) ;
  • 윤일수 (아주대학교 교통시스템공학과)
  • Received : 2015.02.16
  • Accepted : 2016.03.17
  • Published : 2016.04.14

Abstract

PURPOSES : The aim of this study was to compare the performance of the QUEENSOD method and the gravity model in estimating Origin-Destination (O/D) tables for a large-sized microscopic traffic simulation network. METHODS : In this study, an expressway network was simulated using the microscopic traffic simulation model, VISSIM. The gravity model and QUEENSOD method were used to estimate the O/D pairs between internal and between external zones. RESULTS: After obtaining estimations of the O/D table by using both the gravity model and the QUEENSOD method, the value of the root mean square error (RMSE) for O/D pairs between internal zones were compared. For the gravity model and the QUEENSOD method, the RMSE obtained were 386.0 and 241.2, respectively. The O/D tables estimated using both methods were then entered into the VISSIM networks and calibrated with measured travel time. The resulting estimated travel times were then compared. For the gravity model and the QUEENSOD method, the estimated travel times showed 1.16% and 0.45% deviation from the surveyed travel time, respectively. CONCLUSIONS : In building a large-sized microscopic traffic simulation network, an O/D matrix is essential in order to produce reliable analysis results. When link counts from diverse ITS facilities are available, the QUEENSOD method outperforms the gravity model.

Keywords

References

  1. Kim, J., "Dynamic Travel Demand Estimation Using Real-time Traffic Data", University of Seoul, 2005.
  2. Lee, D., Yang, X., and Chandrasekar, P.," Parameter Calibration for PARAMICS Using Genetic Algorithm", Transportation Research board 01-2399, 2001.
  3. Lim, Y., Kim, H. and Baek, S., "Development and application of GLS OD matrix estimation with genetic algorithm for Seoul inner-ringroad", Korean Society of Transportation, Vol.18, No.4, pp.117-126, 2000.
  4. Park, B., Won, J., and Yun, I., "Application of Microscopic Simulation Model Calibration and Validation Procedure: A Case Study of Coordinated Actuated Signal System," Transportation Research Record (TRR) 1978, TRB, Washington D.C., 2006.
  5. PTV Vision", VISSIM 5.30-04 User Manual", PTV, 2011.
  6. Rakha, H., QUEENSOD Rel. 2.10 - Use's Guide: Estimating Origin - Destination Traffic Demands from Link Flow Counts, Van Aerde & Associates, 2010.
  7. Rho, J"., Transportation Planning", Nanam, 1999.
  8. Rho, J., Kim, T. and Kim, T., "A Suitability Analysis of Trip Distribution Models for Vehicular Movements on the Express Highway in Korea", The Korea Spatial Planning Review, vol.45, pp.93-104, 2005.
  9. Van Aerde, M., Hellinga, B., Mackinnon, G., "QUEENSOD: A Method for Estimating Time Varying Origin Destination Demands for Freeway Corridors/Networks", Annual Transportation Research Board Meeting, 1993.
  10. Yoon, J., "O/D Estimation and Calibration Method for Building Large-Sized Microscopic Traffic Simulation Model", Ajou University, 2013.
  11. Youn, Y.", Understanding Forecasting Theory", Freeaca, 1995.
  12. Zhao, F., "Refinement of FSUTMS trip distribution methodology, Calibration of an Intervening Opportunity Model for Plam Beach County", Technical Memorandum, No.3, Florida International University, 2001.