Calibration of microscopic traffic simulation models: Methods and application

Transportation Research Record

Volumn , Issue 1999, 2007, Pages 198-207

  Balakrishna, Ramachandran ^a   Antoniou, Constantinos ^b   Ben Akiva, Moshe ^c   Koutsopoulos, Haris N ^d   Wen, Yang ^c  

^a CALIPER CORPORATION   (United States)

^b NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^d NORTHEASTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; COMPUTER SIMULATION; DECISION THEORY; MATHEMATICAL MODELS; PARAMETER ESTIMATION; TIME VARYING SYSTEMS;

MATHEMATICAL FRAMEWORKS; MICROSCOPIC TRAFFIC SIMULATION; TRAFFIC MEASUREMENTS;

STREET TRAFFIC CONTROL;

EID: 38849140294     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/1999-21     Document Type: Article

References (39)

1. Toledo, T., H. N. Koutsopoulos, A. Davol, M. E. Ben-Akiva, W. Burghout, I. Andreasson, T. Johansson, and C. Lundin. Calibration and Validation of Microscopic Traffic Simulation Tools: Stockholm Case Study. In Transportation Research Record: Journal of the Transportation Research Board, No. 1831, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 65-75.
2. Ozbay, K., B. O. Bartin, and S. Mudigonda. Microscopic Simulation and Calibration of an Integrated Freeway and Toll Plaza Model. Presented at 85th Annual Meeting of the Transportation Research Board, Washington, D.C., 2006.
3. Liu, H. X., P. Chootinan, A. Chen, J. X. Ban, and L. Ding. Streamlined Network Calibration Procedure for California SR-41 Corridor Traffic Simulation Study. Presented at 85th Annual Meeting of the Transportation Research Board, Washington, D.C., 2006.
4. Smith, M. C., and A. W. Sadek. Challenges Calibrating a Large-Scale Microscopic Simulation Model of a Diverse Urban, Suburban, and Rural Network: A Practical Guide. Presented at 85th Annual Meeting of the Transportation Research Board, Washington, D.C., 2006.
5. Darda, D. Joint Calibration of a Microscopic Traffic Simulator and Estimation of Origin-Destination Flows. Master's thesis. Massachusetts Institute of Technology, 2002.
6. Mahanti, B. Aggregate Calibration of Microscopic Traffic Simulation Models. Master's thesis. Massachusetts Institute of Technology, Cambridge, 2004.
7. Zhang, M. H., J. Ma, and H. Dong. Calibration of Departure Time and Route Choice Parameters in Microsimulation with Macro Measurements and Genetic Algorithm. Presented at 85th Annual Meeting of the Transportation Research Board, Washington, D.C., 2006.
8. Abdulhai, B., J. B. Sheu, and W. Recker. Simulation of ITS on the Irvine FOT Area Using the 'PARAMICS 1.5' Scalable Microscopic Traffic Simulator. Phase I: Model Calibration and Validation. PATH Research Report UCB-ITS-PRR-99-12. University of California, Berkeley, 1999.
9. Kurian, M. Calibration of a Microscopic Traffic Simulator. Master's thesis. Massachusetts Institute of Technology, Cambridge, 2000.
10. Lee, D.-H., X. Yang, and P. Chandrasekr. Parameter Calibration for PARAMICS Using Genetic Algorithm. Presented at 80th Annual Meeting of the Transportation Research Board, Washington, D.C., 2001.
11. Kim, K.-O., and L. R. Rilett. Genetic-Algorithm-Based Approach to Traffic Microsimulation Calibration Using ITS Data. Presented at 83rd Annual Meeting of the Transportation Research Board, Washington, D.C., 2004.
12. Brockfeld, E., R. D. Kuhne, and P. Wagner. Calibration and Validation of Microscopic Traffic Flow Models. In Transportation Research Record: Journal of the Transportation Research Board, No. 1876, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 62-70.
13. Ma, J., H. Dong and H. M. Zhang. Calibration of Microsimulation with Heuristic Optimization Methods. In Transportation Research Record: Journal of the Transportation Research Board, No. 1999, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 208-217.
14. Balakrishna, R. Off-line Calibration of Dynamic Traffic Assignment Models. PhD thesis. Massachusetts Institute of Technology, 2006.
15. Balakrishna, R., M. Ben-Akiva, and H. N. Koutsopoulos. Time-Dependent Origin-Destination Estimation Without Assignment Matrices. Presented at Second International Symposium on Transport Simulation, Lausanne, Switzerland, 2006.
16. Balakrishna, R., M. Ben-Akiva, and H. N. Koutsopoulos. Offline Calibration of Dynamic Traffic Assignment: Simultaneous Demand-and-Supply Estimation. In Transportation Research Record: Journal of the Transportation Research Board, No. 2003, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 50-58.
17. Balakrishna, R., H. N. Koutsopoulos, and M. Ben-Akiva. Simultaneous Offline Demand and Supply Calibration of Dynamic Traffic Assignment Systems. Presented at 85th Annual Meeting of the Transportation Research Board, Washington, D.C., 2006.
18. Cascetta, E., and S. Nguyen. A Unified Framework for Estimating or Updating Origin/Destination Matrices from Traffic Counts. Transportation Research, Vol. 22B, No. 6, 1988, pp. 437-455.
19. Cascetta, E., D. Inaudi, and G. Marquis. Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts. Transportation Science, Vol. 27, No. 4, 1993, pp. 363-373.
20. Ashok, K. Estimation and Prediction of Time-Dependent Origin-Destination Flows. PhD thesis. Massachusetts Institute of Technology, Cambridge, 1996.
21. Cascetta, E., and M. N. Postorino. Fixed Point Approaches to the Estimation of O/D Matrices from Traffic Counts on Congested Networks. Transportation Science, Vol. 35, No. 2, 2001, pp. 134-147.
22. Box, M. J. A New Method of Constrained Optimization and a Comparison with Other Methods. The Computer Journal, Vol. 8, No. 1, 1965, pp. 42-52.
23. Huyer, W., and A. Neumaier. SNOBFIT-Stable Noisy Optimization by Branch and Fit. ACM Transactions on Mathematical Software (submitted 2004).
24. Spall, J. C. Implementation of the Simultaneous Perturbation Algorithm for Stochastic Approximation. IEEE Transactions on Aerospace and Electronic Systems, Vol. 34, No. 3, 1998.
25. Spall, J. C. Stochastic Optimization, Stochastic Approximation and Simulated Annealing. In Wiley Encyclopedia of Electrical and Electronics Engineering (J. G. Webster, ed.), Wiley-Interscience, New York, 1999.
26. Yang, Q., and H. N. Koutsopoulos. A Microscopic Traffic Simulator for Evaluation of Dynamic Traffic Management Systems. Transportation Research, Vol. 4C, 1996, pp. 113-129.
27. Yang, Q., H. N. Koutsopoulos, and M. E. Ben-Akiva. Simulation Laboratory for Evaluating Dynamic Traffic Management Systems. In Transportation Research Record: Journal of the Transportation Research Board, No. 1710, TRB, National Research Council, Washington, D.C., 2000, pp. 122-130.
28. Akhil, C. Development and Evaluation of Diversion Strategies Under Incident Response Using Dynamic Traffic Assignment System. Master's thesis. Massachusetts Institute of Technology, Cambridge, 2003.
29. Savitzky, A., and M. J. E. Golay. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Analytical Chemistry, Vol. 36, 1964, pp. 1627-1639.
30. Toledo, T. Integrated Driving Behavior Modeling. PhD thesis. Massachusetts Institute of Technology, Cambridge, 2003.
31. Toledo, T., and H. N. Koutsopoulos. Statistical Validation of Traffic Simulation Models. In Transportation Research Record: Journal of the Transportation Research Board, No. 1876, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 142-150.
32. Ashok, K., and M. Ben-Akiva. Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin-Destination Flows. Transportation Science, Vol. 34, No. 1, 2000, pp. 21-36.
33. Ashok, K., and M. Ben-Akiva. Estimation and Prediction of Time-Dependent Origin-Destination Flows with a Stochastic Mapping to Path Flows and Link Flows. Transportation Science, No. 36, No. 2, 2002, pp. 184-198.
34. Pindyck, R. S., and D. L. Rubinfeld. Econometric Models and Economic Forecasts, 4th ed. McGraw-Hill, New York, 1997.
35. Theil, H. Economic Forecasts and Policy. North-Holland, Amsterdam, Netherlands, 1961.
36. Traffic Analysis Toolbox, Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software. Publication FHWA-HRT-04-040. FHWA, U.S. Department of Transportation, 2004. http://ops.fhwa.dot.gov/ trafficanalysistools/tat_vol3/index.htm. Accessed Nov. 15, 2006.
37. Antoniou, C., M. Ben-Akiva, and H. N. Koutsopoulos. Incorporating Automated Vehicle Identification Data into Origin-Destination Estimation. In Transportation Research Record: Journal of the Transportation Research Board, No. 1882, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 37-44.
38. Antoniou, C., M. Ben-Akiva, and H. N. Koutsopoulos. Dynamic Traffic Demand Prediction Using Conventional and Emerging Data Sources. IEE Proceedings Intelligent Transport Systems, Vol. 153, No. 1, 2006, pp. 97-104.
39. Antoniou, C., B. Nowotny, A. Rechbauer, and M. Linauer. Calibration of DTA Models Using Floating Car Data: An Application of DynaMIT in Vienna. Presented at Second International Symposium in Transportation Simulation, Lausanne, Switzerland, 2006.