Dynamic process (DP) models of route choice provide a sensible representation of the day-to-day evolution of network flows, but their application to the combined modeling of traffic assignment and signal control is not well documented in the literature. In this study, two alternative deterministic, discrete-time DP models of the interaction between signal control and route choice are proposed and compared with the conventional iterative optimization and assignment (IOA) method for network traffic signal setting. Convergence and equilibrium properties of the two DP models and of IOA are assessed on the basis of extensive numerical tests conducted on a small but realistic network. The frequency of signal resetting is shown to affect significantly the duration of the dynamic process needed to achieve a network flow-control equilibrium. Our findings also suggest that the realism of IOA may be questioned because of its lack of consideration for important behavioral features such as driver memory and habit. Finally, the possible emergence of instabilities in the DP models is demonstrated through the analysis of bifurcation examples. Copyright © 2012 John Wiley & Sons, Ltd.

Dynamic process models of combined traffic assignment and control with different signal updating strategies

MENEGUZZER, CLAUDIO
2012

Abstract

Dynamic process (DP) models of route choice provide a sensible representation of the day-to-day evolution of network flows, but their application to the combined modeling of traffic assignment and signal control is not well documented in the literature. In this study, two alternative deterministic, discrete-time DP models of the interaction between signal control and route choice are proposed and compared with the conventional iterative optimization and assignment (IOA) method for network traffic signal setting. Convergence and equilibrium properties of the two DP models and of IOA are assessed on the basis of extensive numerical tests conducted on a small but realistic network. The frequency of signal resetting is shown to affect significantly the duration of the dynamic process needed to achieve a network flow-control equilibrium. Our findings also suggest that the realism of IOA may be questioned because of its lack of consideration for important behavioral features such as driver memory and habit. Finally, the possible emergence of instabilities in the DP models is demonstrated through the analysis of bifurcation examples. Copyright © 2012 John Wiley & Sons, Ltd.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2502256
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