Sensitivity analysis of the LWR model for traffic forecast on large networks using Wasserstein distance

Abstract
In this paper we investigate the sensitivity of the LWR model on network to its parameters and to the network itself. The quantification of sensitivity is obtained by measuring the Wasserstein distance between two LWR solutions corresponding to different inputs. To this end, we propose a numerical method to approximate the Wasserstein distance between two density distributions defined on a network. We found a large sensitivity to the traffic distribution at junctions, the network size, and the network topology.
Anno
2018
Tipo pubblicazione
Altri Autori
Maya Briani, Emiliano Cristiani, Elisa Iacomini
Editore
International Press,
Rivista
Communications in mathematical sciences