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Chapitre D'ouvrage Année : 2019

Multi-Attribute, Multi-Class, Trip-Based, Multi-Modal Traffic Network Equilibrium Model: Application to Large-Scale Network

Résumé

Transportation systems are dynamically driven not only by non-linear interactions between the different components but also by significant feedbacks between network state and user decision. In this work, we consider a trip-based multi-modal approach to network equilibrium. We assume that mode and path choice is carried out at the same level; therefore, travel time depends on the travel path and the mode attributes of travelers. First, we analyze the existing approaches in the literature to model users’ heterogeneity. Second, we present a formulation for static traffic network equilibrium and propose a hybrid formulation of the cost function for trip-based traffic assignment. Third, we consider dynamic traffic assignment (DTA) and propose a variational inequality formulation of the trip-based fixed demand function for the multi-class dynamic traffic equilibrium problem. Finally, we analyze the equilibrium in a large-scale DTA test case (Lyon 6e + Villeurbanne) by a simulation-based approach. Moreover, we propose a novel trip-based algorithm to solve the discrete DTA problem and compare it with the gap function-based method.
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Dates et versions

hal-04493602 , version 1 (13-03-2024)

Identifiants

Citer

Mostafa Ameli, Jean-Patrick Lebacque, Ludovic Leclercq. Multi-Attribute, Multi-Class, Trip-Based, Multi-Modal Traffic Network Equilibrium Model: Application to Large-Scale Network. Traffic and Granular Flow '17, Springer International Publishing, pp.487-495, 2019, 978-3-030-11439-8. ⟨10.1007/978-3-030-11440-4_53⟩. ⟨hal-04493602⟩
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