Modeling Rerouting Phenomena Through Dynamic Traffic Assignment in Rolling Horizon. Gentile, G., Kucharski, R., & Meschini, L. In Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013, pages 513-522, 2013.
Website abstract bibtex 2 downloads This article addresses the problem of simulating en-route path choices on transport networks. In particular, by rerouting, we mean changing the currently chosen path, after receiving some information about a traffic event. Indeed, when the forecasted performance pattern of travel times and costs, known or only perceived, changes significantly, drivers may react by shifting their current route to a better one. The representation of such situations is particularly challenging if the information reaches a driver who is already travelling toward the destination. At the state-of-the-practice, most traffic assignment models are not capable of reproducing these phenomena. We will model rerouting in the framework of within-day Dynamic Traffic Assignment (DTA). Two different solutions are presented here, both exploiting the rolling horizon technique. The first solution can be summarized as an alternate sequence of two fixed point problems for each traffic event: a Dynamic User Equilibrium (DUE) with warm start through saved flows, and a Dynamic Network Loading (DNL) for given route choices; this model is called DTA with Rolling Horizon Events (DTA-RHE) and allows setting the information time of each event before or after the event itself. The second one is a simplified version of the first one, under the assumption that all the events are communicated not later than their start time; this model is called DUE with Rolling Horizon Events (DUE-RHE), and is a sequence of Dynamic User Equilibria with warm start. Numerical examples show the results of the proposed models where rerouting phenomenon can be observed.
@inProceedings{
title = {Modeling Rerouting Phenomena Through Dynamic Traffic Assignment in Rolling Horizon},
type = {inProceedings},
year = {2013},
keywords = {choice,dynamic network loading,dynamic traffic assignment in,dynamic user equilibrium,en - route path,link transmission model,modeling rerouting phenomena through,rolling horizon,traffic events and information},
pages = {513-522},
websites = {https://www.researchgate.net/publication/259182668_Modelling_Rerouting_Phenomena_through_Dynamic_Traffic_Assignment_in_Rolling_Horizon},
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abstract = {This article addresses the problem of simulating en-route path choices on transport networks. In particular, by rerouting, we mean changing the currently chosen path, after receiving some information about a traffic event. Indeed, when the forecasted performance pattern of travel times and costs, known or only perceived, changes significantly, drivers may react by shifting their current route to a better one. The representation of such situations is particularly challenging if the information reaches a driver who is already travelling toward the destination. At the state-of-the-practice, most traffic assignment models are not capable of reproducing these phenomena. We will model rerouting in the framework of within-day Dynamic Traffic Assignment (DTA). Two different solutions are presented here, both exploiting the rolling horizon technique. The first solution can be summarized as an alternate sequence of two fixed point problems for each traffic event: a Dynamic User Equilibrium (DUE) with warm start through saved flows, and a Dynamic Network Loading (DNL) for given route choices; this model is called DTA with Rolling Horizon Events (DTA-RHE) and allows setting the information time of each event before or after the event itself. The second one is a simplified version of the first one, under the assumption that all the events are communicated not later than their start time; this model is called DUE with Rolling Horizon Events (DUE-RHE), and is a sequence of Dynamic User Equilibria with warm start. Numerical examples show the results of the proposed models where rerouting phenomenon can be observed.},
bibtype = {inProceedings},
author = {Gentile, Guido and Kucharski, Rafał and Meschini, Lorenzo},
booktitle = {Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013}
}
Downloads: 2
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