Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation

We investigate the propagation of uncertainties in the Aw-Rascle-Zhang model, which belongs to a class of second order traffic flow models described by a system of nonlinear hyperbolic equations. The stochastic quantities are expanded in terms of wavelet-based series expansions. Then, they are proje...

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Main Authors: Stephan Gerster, Michael Herty, Elisa Iacomini
Format: Article
Language:English
Published: AIMS Press 2021-05-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2021220?viewType=HTML
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author Stephan Gerster
Michael Herty
Elisa Iacomini
author_facet Stephan Gerster
Michael Herty
Elisa Iacomini
author_sort Stephan Gerster
collection DOAJ
description We investigate the propagation of uncertainties in the Aw-Rascle-Zhang model, which belongs to a class of second order traffic flow models described by a system of nonlinear hyperbolic equations. The stochastic quantities are expanded in terms of wavelet-based series expansions. Then, they are projected to obtain a deterministic system for the coefficients in the truncated series. Stochastic Galerkin formulations are presented in conservative form and for smooth solutions also in the corresponding non-conservative form. This allows to obtain stabilization results, when the system is relaxed to a first-order model. Computational tests illustrate the theoretical results.
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spelling doaj.art-f5799cc1fc1c4d8db90210e6944297942022-12-21T19:23:41ZengAIMS PressMathematical Biosciences and Engineering1551-00182021-05-011844372438910.3934/mbe.2021220Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxationStephan Gerster 0Michael Herty1Elisa Iacomini2RWTH Aachen University, Institute for Geometry and Applied Mathematics, Aachen, GermanyRWTH Aachen University, Institute for Geometry and Applied Mathematics, Aachen, GermanyRWTH Aachen University, Institute for Geometry and Applied Mathematics, Aachen, GermanyWe investigate the propagation of uncertainties in the Aw-Rascle-Zhang model, which belongs to a class of second order traffic flow models described by a system of nonlinear hyperbolic equations. The stochastic quantities are expanded in terms of wavelet-based series expansions. Then, they are projected to obtain a deterministic system for the coefficients in the truncated series. Stochastic Galerkin formulations are presented in conservative form and for smooth solutions also in the corresponding non-conservative form. This allows to obtain stabilization results, when the system is relaxed to a first-order model. Computational tests illustrate the theoretical results.https://www.aimspress.com/article/doi/10.3934/mbe.2021220?viewType=HTMLtraffic flowuncertainty quantificationstability analysisaw-rascle-zhang modelstochastic galerkinchapman-enskog expansion
spellingShingle Stephan Gerster
Michael Herty
Elisa Iacomini
Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation
Mathematical Biosciences and Engineering
traffic flow
uncertainty quantification
stability analysis
aw-rascle-zhang model
stochastic galerkin
chapman-enskog expansion
title Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation
title_full Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation
title_fullStr Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation
title_full_unstemmed Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation
title_short Stability analysis of a hyperbolic stochastic Galerkin formulation for the Aw-Rascle-Zhang model with relaxation
title_sort stability analysis of a hyperbolic stochastic galerkin formulation for the aw rascle zhang model with relaxation
topic traffic flow
uncertainty quantification
stability analysis
aw-rascle-zhang model
stochastic galerkin
chapman-enskog expansion
url https://www.aimspress.com/article/doi/10.3934/mbe.2021220?viewType=HTML
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