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First published January 2000

Simulation Laboratory for Evaluating Dynamic Traffic Management Systems

Abstract

Advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS) are promising technologies for achieving efficiency in the operation of transportation systems. A simulation-based laboratory environment, MITSIMLab, is presented that is designed for testing and evaluation of dynamic traffic management systems. The core of MITSIMLab is a microscopic traffic simulator (MITSIM) and a traffic management simulator (TMS). MITSIM represents traffic flows in the network, and the TMS represents the traffic management system under evaluation. An important feature of MITSIMLab is its ability to model ATMS or ATIS that generate traffic controls and route guidance based on predicted traffic conditions. A graphical user interface allows visualization of the simulation, including animation of vehicle movements. An ATIS case study with a realistic network is also presented to demonstrate the functionality of MITSIMLab.

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References

1. Mahmassani H. S., Hu T. Y., Peeta S., and Ziliaskopoulos A. Development and Testing of Dynamic Traffic Assignment and Simulation Procedures for ATIS-ATMS Applications. Report DTFH61-90-R-00074-FG. FHWA, U.S. Department of Transportation, McLean, Va., 1994.
2. Ben-Akiva M. E., Bierlaire M., Bottom J., Koutsopoulos H., and Mishalani R. Development of a Route Guidance Generation System for Real-Time Application. Proc., 8th IFAC Symposium on Transportation Systems, Crete, Greece (Papageorgiou M. and Pouliezos A., eds.), June 1997.
3. Diakaki C., and Papageorgiou M. Design and Simulation Test of Coordinated Ramp Metering Control (METALINE) for A10-West in Amsterdam. ATT-Project Eurocor V2017. Department of Production Engineering and Management, Technical University of Crete, Chania, Greece, 1995.
4. Gartner N. H., and Stamatiadis C. Integration of Dynamic Traffic Assignment with Real-Time Traffic Adaptive Control System. In Transportation Research Record 1644, TRB, National Research Council, Washington, D.C., 1998, pp. 150–156.
5. Gartner N. H., Stamatiadis C., and Tarnoff P. J. Development of Advanced Traffic Signal Control Strategies for Intelligent Transportation Systems: Multilevel Design. In Transportation Research Record 1494, TRB, National Research Council, Washington, D.C., 1995, pp. 98–105.
6. Koutsopoulos H. N., and Yang Q. Modeling Requirements for Emerging Transportation System Operating Environments. Report DTRS-57-88-C-0078, TTD 29. Volpe National Transportation Systems Center, Cambridge, Mass., 1992.
7. The Review of Micro-Simulation Models. Technical Report. Institute for Transport Studies, University of Leeds, Leeds, U.K., 1997. http://www.its.leeds.ac.uk/smartest/.
8. Barcelo J., and Ferrer J. L. A Simulation Study for an Area of Dublin Using the AIMSUN2 Traffic Simulator. Technical Report. Department of Statistics and Operation Research, Universidad Politecnica de Catalunya, Spain, May 1995.
9. CORSIM User Guide. Technical Report Version 1.0. FHWA, U.S. Department of Transportation, 1996.
10. Kosonen I. HUTSIM: Simulation Tool for Traffic Signal Control Planning. Transportation Engineering Publication 89. Helsinki University of Technology, Helsinki, Finland, Oct. 1996.
11. dePalma A., Marchal F., and Nesterov Y. METROPOLIS: A Modular System for Dynamic Traffic Simulation, 1996. http://www.ceic.com/metro.
12. Ben-Akiva M. E., Bierlaire M., Koutsopoulos H. N., and Mishalani R. G. DynaMIT: Dynamic Network Assignment for the Management of Information to Travelers. Proc., 4th Meeting of the EURO Working Group on Transportation, Newcastle, England 1996.
13. van Aerde M., and Yagar S. Dynamic Integrated Freeway/Traffic Signal Networks: A Routing-Based Modeling Approach. Transportation Research A, Vol. 22, No. 6, 1988, pp. 445–453.
14. van Aerde M. INTEGRATION: A Dynamic Traffic Simulation/Assignment Model. Presented at the IVHS Dynamic Traffic Assignment and Simulation Workshop, FHWA, U.S. Department of Transportation, 1992.
15. Codelli D. K., Niedringhaus W. P., and Wang P. The Traffic and Highway Objects for REsearch, Analysis, and Understanding (THOREAU) IVHS Model, Vol. I. Technical Report MTR 92W208V1. MITRE, McLean, Va., Nov. 1992.
16. Lin F.-B. Need for Improved Evaluation Models for Signal Coordination in Adaptive Control. In Large Urban Systems—Proceedings of the Advanced Traffic Management Conference (Yagar S. and Santiago A., eds.), St. Petersburg, Fla., Oct. 1993.
17. Underwood S. E., and Gehring S. G. Framework for Evaluating Intelligent Vehicle-Highway Systems. In Transportation Research Record 1453, TRB, National Research Council, Washington, D.C., 1994, pp. 16–22.
18. Ben-Akiva M. E., Bierlaire M., Koutsopoulos H. N., and Mishalani R. G. Integrated Simulation Framework for Evaluating Dynamic Traffic Management Systems. Proc., First World Congress on Applications of Transport Telematics and Intelligent Transportation Systems, Paris, 1998.
19. Yang Q., and Koutsopoulos H. N. A Microscopic Traffic Simulator for Evaluation of Dynamic Traffic Management Systems. Transportation Research C, Vol. 4, No. 3, 1996, pp. 113–129.
20. Cascetta E., Nuzzolo A., Russo F., and Vitetta A. A Modified Logit Route Choice Model Overcoming Path Overlapping Problems: Specification and Some Calibration Results for Interurban Networks. Proc., 13th International Symposium on Transportation and Traffic Theory, Lyon, France, 1996.
21. Yang Q. A Simulation Laboratory for Dynamic Traffic Management Systems. Ph.D. thesis. Massachusetts Institute of Technology, Cambridge, 1997.
22. Herman R., Montroll E. W., Potts R., and Rothery R. W. Traffic Dynamics: Analysis of Stability in Car-Following. Operations Research, Vol. 1, No. 7, 1959, pp. 86–106.
23. Herman R., and Rothery R. W. Car-Following and Steady State Flow. In International Symposium on the Theory of Road Traffic Flow, Elsevier, New York, 1961.
24. Wicks D. A. INTRAS: A Microscopic Freeway Corridor Simulation Model. In Overview of Simulation in Highway Transportation, Vol. 1, 1977.
25. Ahmed K. Modeling Drivers’ Acceleration and Lane Changing Behavior. Ph.D. thesis. Massachusetts Institute of Technology, Cambridge, 1999.
26. Gipps P. G. A Model for the Structure of Lane Changing Decisions. Transportation Research, Vol. 20B, No. 5, 1986, pp. 403–414.
27. Ahmed K., Ben-Akiva M., Koutsopoulos H. N., and Mishalani R. G. Models for Freeway Lane Changing and Gap Acceptance Behavior. Proc., 13th International Symposium on Transportation and Traffic Theory, Lyon, France, 1996.
28. Kaysi I., Ben-Akiva M., and Koutsopoulos H. Integrated Approach to Vehicle Routing and Congestion Prediction for Real-Time Driver Guidance. In Transportation Research Record 1408, TRB, National Research Council, Washington, D.C., 1993, pp. 66–74.
29. Ran B., and Boyce D. Modeling Dynamic Transportation Networks: An Intelligent Transportation System Oriented Approach. Springer, Berlin, 1996.
30. Special Report 209: Highway Capacity Manual. TRB, National Research Council, Washington, D.C., 1985.
31. Ben-Akiva M., Bierlaire M., Bottom J., Koutsopoulos H. N., and Yang Q. Investigation of Route Guidance Generation Issues by Simulation with DynaMIT. Proc., 14th International Symposium on Transportation and Traffic Theory (ISTTT), Jerusalem, Israel, July 1999.
32. Papageorgiou M., Hadj-Salem H., and Blosseville J.-M. ALINEA: A Local Feedback Control Law for On-Ramp Metering. In Transportation Research Record 1320, TRB, National Research Council, Washington, D.C., 1991, pp. 58–64.
33. Chen O. J. A Dynamic Traffic Control Model for Real Time Freeway Operations. Master’s thesis. Massachusetts Institute of Technology, Cambridge, 1996.
34. Hasan M. Evaluation of Ramp Control Algorithms Using a Microscopic Traffic Simulation Laboratory - MITSIM. Master’s thesis. Massachusetts Institute of Technology, Cambridge, 1999.
35. Persaud B. N., and Hall F. L. Catastrophe Theory and Patterns in 30-Second Freeway Traffic Data—Implications for Incident Detection. Transportation Research, Vol. 23, No. 2, 1989, pp. 103–113.
36. Persaud B. N., Hall F. L., and Hall L. M. Congestion Identification Aspects of the McMaster Incident Detection Algorithm. In Transportation Research Record 1287, TRB, National Research Council, Washington, D.C., 1990, pp. 167–175.
37. Masters P. H., Lam J. K., and Kam W. Incident Detection Algorithms for Compass—An Advanced Traffic Management System. In Proceedings of Vehicle Navigation and Information Systems Conference, 1991.
38. Thirukkonda S. Design and Evaluation of Freeway Incident Detection Algorithm. Master’s thesis. Massachusetts Institute of Technology, Cambridge, 1999.
39. Cascetta E., Inaudi D., and Marquis G. Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts. Transportation Science, Vol. 27, No. 4, 1993, pp. 363–373.
40. Ashok K. Estimation and Prediction of Time-Dependent Origin-Destination Flows. Ph.D. thesis. Massachusetts Institute of Technology, Cambridge, 1996.

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Article first published: January 2000
Issue published: January 2000

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© 2000 National Academy of Sciences.
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Authors

Affiliations

Qi Yang
Caliper Corporation, 1172 Beacon Street, Newton, MA 02461
Haris N. Koutsopoulos
Volpe National Transportation Systems Center, Cambridge, MA 02142
Moshe E. Ben-Akiva
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139

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