Journal of Korean Society of Transportation (대한교통학회지)

Korean Society of Transportation (대한교통학회)
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Development of Auto-calibration System for Micro-Simulation Model using Aggregated Data (Case Study of Urban Express)

집계자료를 이용한 미시적 시뮬레이션 모형의 자동정산체계 개발 (도시고속도로사례)

  • Received : 2010.10.01
  • Accepted : 2011.01.29
  • Published : 2011.02.28
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Abstract

The application of micro-simulation model has been extended farther with improvement of computer performance and development of complicated model. To make a micro-simulation model accurately replicate field traffic conditions, model calibration is very crucial. Studies on calibration of micro-simulation model have not been enough while lots of studies on calibration of macro-simulation model have been continued in our country. This paper presents an auto-calibration of parameter values in micro-simulation model(VISSIM) using genetic algorithm. RMSE(Root Mean Square Error) of collected volume on the urban expressway versus simulated volume is set as MOP(measure of performance) and objective function of optimization is set as to minimize the RMSE. Applying to urban expressway(Nae-bu circular) as a case study, it shows that RMSE of optimized parameter values decrease 60.4%($19.3{\longrightarrow}7.6$) compared to default parameter values and the proposed auto-calibration system is very effective.

미시적 시뮬레이션 모형은 컴퓨터 성능이 향상되고 정교한 모형이 개발되면서 광역적인 범위까지 적용분야가 점차 확대되고 있다. 현장 교통상황을 정확하게 묘사하기 위해서는 시뮬레이션 모형의 정확한 정산이 매우 중요하다. 국내에서는 거시적 모형에 대한 정산연구는 많이 진행된 반면에 미시적 모형에 대한 정산연구는 매우 부족한 실정이다. 본 연구에서는 유전자알고리즘 이용하여 미시적 시뮬레이션 모형의 파라미터를 자동으로 최적화하는 자동정산 체계를 제시하였다. 내부순환로 지점검지기에서 수집되는 관측교통량과 미시적 시뮬레이션모형(VISSIM)의 교통량 간의 제곱오차(RMSE)를 성능지표로 하고, 최적화 목적함수는 제곱오차를 최소화 하는 것으로 설정하였다. 내부순환로에 적용한 결과, 기본 파라미터에 비해 자동정산체계의 RMSE가 60.4%($19.3{\longrightarrow}7.6$)나 감소하여 매우 효과적인 것으로 나타났다.

Keywords

References

  1. Sadek, A. W. et al(2006), "Challenges Calibrating Large-Scale Microscopic Simulation Model of Diverse Urban, Suburban, and Rural Network: Practical Guide", Transportation Research Board 85th Annual Meeting, TRB, p.19.
  2. Balmer, M. et al(2004), "Large-Scale Multi-Agent Simulations for Transportation Applications", Journal of Intelligent Transportation Systems, vol. 8, Taylor & Francis Inc., pp.205-221. https://doi.org/10.1080/15472450490523892
  3. Benehohal R. F. et al(1991), "Procedure for Validation of Microscopic Traffic Flow Simulation Models", Transportation Research Record 1320, TRB, pp.190-202.
  4. H. Rakha, B. et al(1996), "Systematic Verification, Validation and Calibration of Traffic Simulation Models", Transportation Research Board 75th Annual Meetng. TRB, pp.1-14.
  5. G. Daigle, M. et al(1998), "Field applications of corsim: I-40 freeway design evaluation, oklahoma city", 1998 Winter Simulation Conference, vol.2, WSC, pp.1161-1167.
  6. ISAC, L.(1999), "Experiences with Paramics at ISAC in Winter 98-99". Information Sharing and Analysis Center.
  7. Cheu, R. L. et al(1998), "Calibration of FRESIM for Singapore Expressway Using Genetic Algorithm", Journal of Transportation Engineering, ASCE, Vol. 124, No. 6, pp.526-535. https://doi.org/10.1061/(ASCE)0733-947X(1998)124:6(526)
  8. Lee, D. H. et al(2001), "Parameter Calibration for Paramics Using Genetic Algorithm", Transportation Research Board 80th Annual Meeting, TRB. pp.6-15.
  9. Gomes, G. et al(2004), "Congested Freeway Microsimulation Model Using VISSIM", Journal of the Transportation Research Board, No. 1876, Transportation Research Board of the National Academies, pp.71-81.
  10. Gardes, Y. et al(1993), "Simulation of IVHS on the Santa Monica Freeway Corridor Using the Integration Model. Phase 2: Preliminary ATIS and ATMS Experiments", California PATH Research Report, University of California.
  11. Lee, E. B. et al(2005), "Validation Study of Microscopic Traffic Simulations for Urban Freeway Reconstruction with High-Traffic Volume", 12th ITS World Congress, ITS World Congress.
  12. R. Balakrishna(2002). "Calibration of the demand simulator in a dynamic traffic assignment system", Masters thesis, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering.
  13. K. Kim. et al(2003), "Simplex based calibration of traffic microsimulation models using its data", Transportation Research Board 82nd Annual Meeting, TRB, pp.1-24
  14. M. Kurian(2000). "Calibration of a microscopic traffic simulator". Masters thesis, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering.
  15. D. Darda(2002). "Joint calibration of microscopic traffic simulator and estimation of origin- destination flows", Masters thesis, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering.
  16. Toledo, T. et al(2003), "Calibration and Validation of Microscopic Traffic Simulation Tools: Stockholm Case Study". Journal of the Transportation Research Board, No. 1831, Transportation Research Board of the National Academies, pp.65-75.
  17. B. Abdulhai. et al(1999), "Simulation of its on the irvine fot area using paramics 1.5 scalable microscopic traffic simulator: Phase 1: Model calibration and validation. Tec hni cal r epor t " , Cal i f orni a PATH Research Report, University of California.
  18. 김현미(2008), "미시적 교통류 시뮬레이션 파라미터 정산 방법 개발", 한국항공대학교 대학원 석사논문, 한국항공대학교.
  19. Zhang, H. M. et al(2006), "Development of a Calibration Procedure and Assistance Tools for Microsimulation", California PATH Research Report, University of California.
  20. Chu, L. et al(2004), "Calibration Procedure for Microscopic Traffic Simulation", Transportation Research Board 83rd Annual Meeting, TRB, pp.1-25.
  21. Byungkyu (Brian) Park et al(2006), "Application of Microscopic simulation Model Calibration and Validation Procedure - A Case Study of Coordinated Actuated Signal System", Journal of the Transportation Research Board, No. 1978, Transportation Research Board of the National Academies, pp.113-122.