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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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    1. Arnott, R. & de Palma, A. & Lindsey, R., 1990. "Departure time and route choice for the morning commute," Transportation Research Part B: Methodological, Elsevier, vol. 24(3), pages 209-228, June.
    2. Newell, G. F., 1989. "Comments on traffic dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 23(5), pages 386-389, October.
    3. Terry L. Friesz & David Bernstein & Tony E. Smith & Roger L. Tobin & B. W. Wie, 1993. "A Variational Inequality Formulation of the Dynamic Network User Equilibrium Problem," Operations Research, INFORMS, vol. 41(1), pages 179-191, February.
    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., 1993. "A simplified theory of kinematic waves in highway traffic, part III: Multi-destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 305-313, August.
    6. Ran, Bin & Rouphail, Nagui M. & Tarko, Andrzej & Boyce, David E., 1997. "Toward a class of link travel time functions for dynamic assignment models on signalized networks," Transportation Research Part B: Methodological, Elsevier, vol. 31(4), pages 277-290, August.
    7. Tong, C. O. & Wong, S. C., 2000. "A predictive dynamic traffic assignment model in congested capacity-constrained road networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(8), pages 625-644, November.
    8. Daganzo, Carlos F., 1995. "The cell transmission model, part II: Network traffic," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 79-93, April.
    9. N/A, 1989. "Comments," ILR Review, Cornell University, ILR School, vol. 43(1), pages 89-102, October.
    10. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 281-287, August.
    11. Daganzo, Carlos F., 1995. "Properties of link travel time functions under dynamic loads," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 95-98, April.
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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. 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.
    3. 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.
    4. 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.
    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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