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

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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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    Cited by:

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    2. Bouadi, Marouane & Jia, Bin & Jiang, Rui & Li, Xingang & Gao, Zi-You, 2022. "Stochastic factors and string stability of traffic flow: Analytical investigation and numerical study based on car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 96-122.
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    4. Jing Lu & Carolina Osorio, 2018. "A Probabilistic Traffic-Theoretic Network Loading Model Suitable for Large-Scale Network Analysis," Service Science, INFORMS, vol. 52(6), pages 1509-1530, December.

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