Summary
This paper explores specifications of microscopic traffic models that could capture congestion dynamics and model accident-prone behaviors on a highway section in greater realism than models currently used in practice. A comparative assessment of several major acceleration models is conducted, especially in regards to congestion formation and incident modeling. Based on this assessment, alternative specifications for a car-following/lane changing model are developed and implemented in a microscopic simulation framework. The models are calibrated and compared in terms of 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, over-saturated networks) as well as “normal” daily traffic conditions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
R. W. Rothery, 1999. Traffic Flow Theory: A State-of-the-Art Report-Revised Monograph on Traffic Flow Theory. Transportation Research Board, National Research Council, Washington, D. C.
E. R. Boer, 1999. Car Following from the Driver’s Perspective. Transportation Research, Part F, No. 4, pp. 201-206.
M. Treiber, K. Hennecke, and D. Helbing, 2000. Congested Traffic States in Empirical Observations and Microscopic Simulations. Physical Review E, Volume 2, No. 2, pp. 1805-1824.
D. C. Gaziz, R. Herman, and R. Potts, 1959. Car-Following Theory of Steady State Traffic Flow. Operations Research, Issue 7, pp. 499-505.
P. G. Gipps, 1981. A Behavioral Car-Following Model for Computer Simulation. Transportation Research 15B, pp. 101-115.
S. Krauss, P. Wagner, and C. Gawron, 1996. Continuous Limit of Nagel-Shreckenberg Model. Physical Review E, Vol. 54, No. 4, pp. 3707-3712.
M. Treiber and D. Helbing, 2003. Memory Effect of Microscopic Traffic Models and Wide Scattering in Flow-Density Data. Physical Review E68, 046119.
G. Newel, 1961. Nonlinear Effects in the Dynamics of Car-Following. Operations Research 9, pp. 209-229.
M. Bando, K. Hasebe, A. Nakayama, A. Shibata, and Y. Sugiyama, 1995. Dynamical Model of Traffic Congestion and Numerical Simulation. Physical Review E 51, pp. 1035-1042.
B. Tilch and D. Helbing, 1998. Generalized Force Model of Traffic Dynamics. Physical Review E, Vol. 58, Issue 133.
FHWA, 2004. NGSIM Task E. 1-1: Core Algorithms Assessment, Final Report. Cambridge Systematic, Inc., Massachusetts.
A. Querejeta-Iraola and U. Reiter, 1991. Calibration, Validation and Tesing of Multi-Lane Simulation Model. Deliverable of EC DRIVE Project ICARUS (V-1052), Brussels.
C. F. Daganzo, 1999. A Behavioral Theory of Multi-Lane Taffic Flow, Part I: Long Homogeneous Freeway Sections. Institute of Transportation Studies, University of California, Berkeley.
FHWA, 1969. Lane Changing on Multi-Lane Highways, Final Report. U. S. DOT, Department of Civil and Environmental Engineering, Northwestern University, Evanston, Illinois.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hamdar, S.H., Mahmassani, H.S. (2009). Colliding Particles: Beyond Accident-Free Car Following Models. In: Appert-Rolland, C., Chevoir, F., Gondret, P., Lassarre, S., Lebacque, JP., Schreckenberg, M. (eds) Traffic and Granular Flow ’07. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77074-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-77074-9_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77073-2
Online ISBN: 978-3-540-77074-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)