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The Distribution of Congestion on a Class of Stochastic Kinematic Wave Models

Author

Listed:
  • Jorge A. Laval

    (School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Bhargava R. Chilukuri

    (School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

This paper shows that a wide range of stochastic extensions of the kinematic wave model tend to the same parameter-free expression for the probability of congestion at a given time-space point. This is shown for white noise initial density with deterministic and stochastic fundamental diagram in the case of Riemann problems and the bottleneck problem. It is also found that the stochastic solution (i) preserves the structure of the deterministic solution and (ii) tends to the deterministic solution with time at a given location.

Suggested Citation

  • Jorge A. Laval & Bhargava R. Chilukuri, 2014. "The Distribution of Congestion on a Class of Stochastic Kinematic Wave Models," Transportation Science, INFORMS, vol. 48(2), pages 217-224, May.
  • Handle: RePEc:inm:ortrsc:v:48:y:2014:i:2:p:217-224
    DOI: 10.1287/trsc.2013.0462
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    References listed on IDEAS

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    1. Kim, T. & Zhang, H.M., 2008. "A stochastic wave propagation model," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 619-634, August.
    2. Castillo, Jose M. del, 2001. "Propagation of perturbations in dense traffic flow: a model and its implications," Transportation Research Part B: Methodological, Elsevier, vol. 35(4), pages 367-389, May.
    3. Sopasakis, Alexandros, 2004. "Stochastic noise approach to traffic flow modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 741-754.
    4. Daganzo, Carlos F., 1994. "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transportation Research Part B: Methodological, Elsevier, vol. 28(4), pages 269-287, August.
    5. Newell, G. F., 2002. "A simplified car-following theory: a lower order model," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 195-205, March.
    6. Helbing, Dirk & Hennecke, Ansgar & Shvetsov, Vladimir & Treiber, Martin, 2001. "MASTER: macroscopic traffic simulation based on a gas-kinetic, non-local traffic model," Transportation Research Part B: Methodological, Elsevier, vol. 35(2), pages 183-211, February.
    7. Sumalee, A. & Zhong, R.X. & Pan, T.L. & Szeto, W.Y., 2011. "Stochastic cell transmission model (SCTM): A stochastic dynamic traffic model for traffic state surveillance and assignment," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 507-533, March.
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    Cited by:

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