Numerical computation of generalized Wasserstein distances with applications to traffic model analysis

Generalized Wasserstein distances allow us to quantitatively compare two continuous or atomic mass distributions with equal or different total masses. In this paper, we propose four numerical methods for the approximation of three different generalized Wasserstein distances introduced in the past few years, giving some insights into their physical meaning. After that, we explore their usage in the context of a sensitivity analysis of differential models for traffic flow. The quantification of the models' sensitivity is obtained by computing the generalized Wasserstein distances between two (numerical) solutions corresponding to different inputs, including different boundary conditions.

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Publication Details

Journal
Networks and Heterogeneous Media
Published
2025-01-01
DOI
https://doi.org/10.3934/nhm.2025048
Primary Topic
Geometric Analysis and Curvature Flows
Type
article
Field-Weighted Citation Impact
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article

Numerical computation of generalized Wasserstein distances with applications to traffic model analysis

Emiliano Cristiani, Maya Briani, Giovanni Franzina, Francesca L. Ignoto
Networks and Heterogeneous Media
Geometric Analysis and Curvature Flows
article

Numerical computation of generalized Wasserstein distances with applications to traffic model analysis

Emiliano Cristiani, Maya Briani, Giovanni Franzina, Francesca L. Ignoto
article en

Abstract

Generalized Wasserstein distances allow us to quantitatively compare two continuous or atomic mass distributions with equal or different total masses. In this paper, we propose four numerical methods for the approximation of three different generalized Wasserstein distances introduced in the past few years, giving some insights into their physical meaning. After that, we explore their usage in the context of a sensitivity analysis of differential models for traffic flow. The quantification of the models' sensitivity is obtained by computing the generalized Wasserstein distances between two (numerical) solutions corresponding to different inputs, including different boundary conditions.

Networks and Heterogeneous MediaVol. 20(4)
Istituto per le Applicazioni del Calcolo Mauro Picone (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 57%
Geometric Analysis and Curvature Flows
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Numerical computation of generalized Wasserstein distances with applications to traffic model analysis — Emiliano Cristiani, Maya Briani, et al. · Networks and Heterogeneous Media (2025) | TGRS Research Map | TGRS