Non-local first-order modelling of crowd dynamics: a multidimensional framework with applications

TL;DR

This paper introduces a versatile physical modeling framework for crowd dynamics that captures non-local, anisotropic pedestrian behavior and applies it to real-world scenarios like footbridge interaction and underground station flow.

Contribution

It presents a novel multidimensional framework and two first-order models tailored for specific crowd applications, demonstrating its adaptability and importance of perception in crowd behavior.

Findings

Models successfully simulate crowd-structure interactions.

Perception significantly influences crowd movement patterns.

Framework proves versatile across different engineering problems.

Abstract

In this work a physical modelling framework is presented, describing the intelligent, non-local, and anisotropic behaviour of pedestrians. Its phenomenological basics and constitutive elements are detailed, and a qualitative analysis is provided. Within this common framework, two first-order mathematical models, along with related numerical solution techniques, are derived. The models are oriented to specific real world applications: a one-dimensional model of crowd-structure interaction in footbridges and a two-dimensional model of pedestrian flow in an underground station with several obstacles and exits. The noticeable heterogeneity of the applications demonstrates the significance of the physical framework and its versatility in addressing different engineering problems. The results of the simulations point out the key role played by the physiological and psychological features of human perception on the overall crowd dynamics.