arrow
返回

A macroscopic pedestrian model with variable maximal density

delete2025-03-01
delete0
delete
OA
AI
L
Laura Bartoli
S
Simone Cacace
E
Emiliano Cristiani *
R
Roberto Ferretti
DOI:10.1016/j.amc.2025.129404delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
In this paper we propose a novel macroscopic (fluid dynamics) model for describing pedestrian flow in low and high density regimes. The model is characterized by the fact that the maximal density reachable by the crowd - usually a fixed model parameter - is instead a state variable. To do that, the model couples a conservation law, devised as usual for tracking the evolution of the crowd density, with a Burgers-like PDE with a nonlocal term describing the evolution of the maximal density. The variable maximal density is used here to describe the effects of the psychological/physical pushing forces which are observed in crowds during competitive or emergency situations. Specific attention is also dedicated to the fundamental diagram, i.e., the function which expresses the relationship between crowd density and flux. Although the model needs a well defined fundamental diagram as known input parameter, it is not evident a priori which relationship between density and flux will be actually observed, due to the time-varying maximal density. An a posteriori analysis shows that the observed fundamental diagram has an elongated tail in the congested region, thus resulting similar to the concave/concave fundamental diagram with double hump observed in real crowds. The main features of the model are investigated through 1D and 2D numerical simulations. The numerical code for the 1D simulation is freely available on this Gitlab repository.
Keyword:
SIMULATION
CROWDS
FORCE
FLOWS

期刊

Applied Mathematics and Computation 封面图
Applied Mathematics and Computation
IF:
3.4
论文数:
2.3W
被引数:
3.3W

机构

R
Roma Tre University
学者数:
5.1K
论文数: 4.9K
被引数: 5.4K
C
consiglio nazionale delle ricerche (cnr)
学者数:
6.2W
论文数: 5.7W
被引数: 48
S
sapienza university rome
学者数:
6.3W
论文数: 4.7W
被引数: 381
学者 查看更多机构
引用论文

引用论文

暂无论文信息