2D-LWR in large-scale network with space dependent fundamental diagram

Stéphane Mollier 1 Maria Laura Delle Monache 1 Carlos Canudas de Wit 1
1 NECS - Networked Controlled Systems
Inria Grenoble - Rhône-Alpes, GIPSA-DA - Département Automatique
Abstract : Traffic modeling of large-scale urban networks is a challenging task. In the literature, the network is mainly assumed to be homogeneous. However, in a large-scale scenario, it is unlikely that the traffic network characteristics–such as speed limit, number of lanes, or the network geometry–remain constant throughout the network. Therefore, we introduce a two dimensional macroscopic model for large-scale traffic networks where the fundamental diagram is space-dependent and varies with respect to the area considered. We simulate our model and compare the results with those obtained by microsimulation.
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Communication dans un congrès
ITSC 2018 - 21st IEEE International Conference on Intelligent Transportation Systems, Nov 2018, Maui, United States. IEEE, pp.1-8
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Soumis le : lundi 3 septembre 2018 - 17:30:25
Dernière modification le : vendredi 30 novembre 2018 - 09:37:07
Document(s) archivé(s) le : mardi 4 décembre 2018 - 19:08:28

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Stéphane Mollier, Maria Laura Delle Monache, Carlos Canudas de Wit. 2D-LWR in large-scale network with space dependent fundamental diagram. ITSC 2018 - 21st IEEE International Conference on Intelligent Transportation Systems, Nov 2018, Maui, United States. IEEE, pp.1-8. 〈hal-01866959〉

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