In the field, queue spillback contributes substantially to urban congestion. Therefore, most dynamic network loading models either explicitly include spillback, or frame a failure to model spillback as an unfortunate consequence of mathematical or computational tractability that should be relaxed in future work. Although models with spillback are undeniably more realistic, they are also less robust to errors in input demand. We show that when there is high uncertainty in input demand, excluding spillback can actually reduce error by reducing sensitivity to demand errors. Our demonstrations include a small network that can be solved analytically, and dynamic user equilibrium on two real-world networks representing Austin, TX, and San Antonio, TX. We conclude that model realism must be carefully balanced against the accuracy of the input parameters, and the sensitivity of the model to any such errors in these inputs.


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    Titel :

    Queue Spillback and Demand Uncertainty in Dynamic Network Loading


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:


    Erscheinungsdatum :

    2019-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch