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First published online January 1, 2008

From Existing Accident-Free Car-Following Models to Colliding Vehicles: Exploration and Assessment

Abstract

The study explores the specifications of microscopic traffic models that could capture congestion dynamics and model accident-prone behaviors on a highway section in greater realism than existing models currently used in practice (commercial software). A comparative assessment of several major acceleration models is conducted, especially for congestion formation and incident modeling. On the basis of this assessment, alternative specifications for car-following and lane-changing models are developed and implemented in a microscopic simulation framework. The models are calibrated and compared for resulting vehicle trajectories and macroscopic flow-density relationships. Experiments are conducted with the models under different degrees of relaxation of the safety constraints typically applied in conjunction with simulation codes used in practice. The ability of the proposed specifications to capture traffic behavior in extreme situations is examined. The results suggest that these specifications offer an improved basis for microscopic traffic simulation for situations that do not require an accident-free environment. As such, the same basic behavior model structure could accommodate both extreme situations (evacuation scenarios, oversaturated networks) as well as normal daily traffic conditions.

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References

1. Rothery R. W. Traffic Flow Theory: A State-of-the-Art Report: Revised Monograph on Traffic Flow Theory. Transportation Research Board, National Research Council, Washington, D.C., 1999.
2. Boer E. R. Car Following from the Driver's Perspective. Transportation Research F, Vol. 2, No. 4, 1999, pp. 201–206.
3. Treiber M. Hennecke K. and Helbing D. Congested Traffic States in Empirical Observations and Microscopic Simulations. Physical Review E, Vol. 2, No. 2 2000, pp. 1805–1824.
4. Gazis D. C. Herman R. and Potts R. Car-Following Theory of Steady State Traffic Flow. Operations Research, Vol. 7, 1959, pp. 499–505.
5. Gipps P. G. A Behavioral Car-Following Model for Computer Simulation. Transportation Research B, Vol. 15, 1981, pp. 101–115.
6. Nagel K. and Shreckenberg M. A Cellular Automaton Model for Freeway Traffic. Journal of Physics I, Vol. 2, 1992, pp. 2221–2229.
7. Krawss S. and Wagner P. Metastable States in a Microscopic Model of Traffic Flow. Physical Review E, Vol. 55, No. 5 1997, pp. 5597–5602.
8. Treiber M. and Helbing D. Memory Effect of Microscopic Traffic Models and Wide Scattering in Flow-Density Data. Physical Review E, Vol. 68, 2003, PDF 046119.
9. Wiedemann R. and Reiter U. Microscopic Traffic Simulation, the Simulation System Mission. PhD dissertation. University of Karlsruhe, Germany, 1991.
10. Gazis D. Herman R. and Rothery R. Nonlinear Follow-the-Leader Models of Traffic Flow. Operations Research, Vol. 9, 1961, pp. 545–567.
11. Newell G. F. Nonlinear Effects in the Dynamics of Car Following. Operations Research, Vol. 9, No. 2 1961, pp. 209–229.
12. Bando M. Hasebe K. Nakayama A. Shibata A. and Sugiyama Y. Dynamical Model of Traffic Congestion and Numerical Simulation. Physical Review E, Vol. 51, 1995, pp. 1035–1042.
13. Tilch B. and Helbing D. Generalized Force Model of Traffic Dynamics. Physical Review E, Vol. 58, No. 133, 1998.
14. Cambridge Systematics. NGSIM Task E.1-1: Core Algorithms Assessment. FHWA, U.S. Department of Transportation, 2004.
15. Brockfeld E. Kuhne R. D. and Wagner P. 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., 2004, pp. 62–70.
16. Brockfeld E. Kuhne R. D. and Wagner P. Calibration and Validation of Microscopic Models of Traffic Flow. In Transportation Research Record: Journal of the Transportation Research Board, No.1934, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 179–187.
17. Krauss S. Wagner P. and Gawron C. Continuous Limit of Nagel-Shreckenberg Model. Physical Review E, Vol. 54, No. 4 1996, pp. 3707–3712.
18. Todosiev E. P. The Action-Point Model of the Driver-Vehicle-System. Ohio State University, Columbus, 1963.
19. Querejeta-Iraola A. and Reiter U. Calibration, Validation and Testing of Multi-Lane Simulation Model. EC DRIVE Project ICARUS (V-1052), Brussels, Belgium, 1991.
20. Daganzo C. F. A Behavioral Theory of Multi-Lane Traffic Flow, Part I: Long Homogeneous Freeway Sections. Institute of Transportation Studies, University of California, Berkeley, 1999.
21. Gipps P. G. A Model for the Structure of Lane Changing Decisions. Transportation Research B, Vol. 20, 1986, pp. 403–414.
22. Lane Changing on Multi-Lane Highways. FHWA, U.S. Department of Transportation, 1969.

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Article first published online: January 1, 2008
Issue published: January 2008

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© 2008 National Academy of Sciences.
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Authors

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Samer H. Hamdar
Department of Civil and Environmental Engineering, Northwestern University, Transportation Center, Chambers Hall, 600 Foster Street, Evanston, IL 60208.
Hani S. Mahmassani
Department of Civil and Environmental Engineering, Northwestern University, Transportation Center, Chambers Hall, 600 Foster Street, Evanston, IL 60208.

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