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Macroscopic arc performance models with capacity constraints for within-day dynamic traffic assignment

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  • Gentile, Guido
  • Meschini, Lorenzo
  • Papola, Natale

Abstract

In this paper, we present a new nonstationary link-based macroscopic arc performance model with capacity constraints, derived from an approximate solution to the simplified kinematic wave theory which based on the assumption, often introduced in the algorithms solving Dynamic Traffic Assignment, that the arc inflows are piece-wise constant in time. Although the model does not require to introduce any spatial discretization, it is capable of taking implicitly into account the variability of the flow state along the arc accordingly to any concave fundamental diagram. To appreciate the effect of the approximation introduced, the model has been compared in terms of efficiency and effectiveness with three typical existing models, which have been to this end suitably modified and enhanced.

Suggested Citation

  • Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2005. "Macroscopic arc performance models with capacity constraints for within-day dynamic traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 39(4), pages 319-338, May.
    • Handle: RePEc:eee:transb:v:39:y:2005:i:4:p:319-338
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    Cited by:

    1. Gentile, Guido & Meschini, Lorenzo & Papola, Natale, 2007. "Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(10), pages 1114-1138, December.
    2. Zhong, R.X. & Sumalee, A. & Friesz, T.L. & Lam, William H.K., 2011. "Dynamic user equilibrium with side constraints for a traffic network: Theoretical development and numerical solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1035-1061, August.
    3. Gentile, Guido, 2016. "Solving a Dynamic User Equilibrium model based on splitting rates with Gradient Projection algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 120-147.
    4. Ngoduy, D. & Hoang, N.H. & Vu, H.L. & Watling, D., 2016. "Optimal queue placement in dynamic system optimum solutions for single origin-destination traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 92(PB), pages 148-169.
    5. Smith, Mike & Huang, Wei & Viti, Francesco & Tampère, Chris M.J. & Lo, Hong K., 2019. "Quasi-dynamic traffic assignment with spatial queueing, control and blocking back," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 140-166.

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