Numerical study of macroscopic pedestrian flow models

We analyze numerically macroscopic models of crowd dynamics: classical Hughes model and the second order model being an extension to pedestrian motion of the Payne-Whitham vehicular traffic model. The desired direction of motion is determined by solving an eikonal equation with density dependent running cost function standing for minimization of the travel time and avoidance of congested areas. We apply a mixed finite volume-element method to solve the problems and present error analysis in case of the eikonal solver, gradient computation and the second order model yielding a first order convergence. We show that Hughes' model is incapable of reproducing complex crowd dynamics such as stop-and-go waves and clogging at bottlenecks. Finally, using the second order model, we study numerically the evacuation of pedestrians from a room through a narrow exit. In particular, we analyze the effect on the total evacuation time of the level of compression, the desired speed and the presence of obstacles.

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Source https://inria.hal.science/hal-00849587
Author Twarogowska, Monika, Goatin, Paola, Duvigneau, Régis
Maintainer CCSD
Last Updated May 10, 2026, 04:23 (UTC)
Created May 10, 2026, 04:23 (UTC)
Identifier Report N°: RR-8340
Language en
Rights https://about.hal.science/hal-authorisation-v1/
contributor Optimization and control, numerical algorithms and integration of complex multidiscipline systems governed by PDE (OPALE) ; Centre Inria d'Université Côte d'Azur ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Alexandre Dieudonné (LJAD) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UniCA)
creator Twarogowska, Monika
date 2013-07-31T00:00:00
harvest_object_id b11017be-12c6-461a-9bca-46bcccb5d5d8
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2025-08-26T00:00:00
set_spec type:REPORT