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

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.

Mots clés: Macroscopic model; space dependent flux function; large scale traffic modelling

Domaines: Equations aux dérivées partielles [math.AP]; Modélisation et simulation

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. pp.1-8. ⟨hal-01866959⟩