Pedestrian flows in bounded domains with obstacles

TL;DR

This paper introduces a discrete-time measure-based model for pedestrian flows in complex environments, capturing target-driven movement and crowd avoidance, and demonstrating its effectiveness through comparison with experimental data.

Contribution

It develops a novel Eulerian measure-based model for pedestrian dynamics that simplifies analysis and computation in complex, obstacle-filled domains.

Findings

Model reproduces experimental pedestrian flow patterns

Easier to analyze and simulate than hyperbolic conservation law models

Applicable to complex two-dimensional environments with obstacles

Abstract

In this paper we systematically apply the mathematical structures by time-evolving measures developed in a previous work to the macroscopic modeling of pedestrian flows. We propose a discrete-time Eulerian model, in which the space occupancy by pedestrians is described via a sequence of Radon positive measures generated by a push-forward recursive relation. We assume that two fundamental aspects of pedestrian behavior rule the dynamics of the system: On the one hand, the will to reach specific targets, which determines the main direction of motion of the walkers; on the other hand, the tendency to avoid crowding, which introduces interactions among the individuals. The resulting model is able to reproduce several experimental evidences of pedestrian flows pointed out in the specialized literature, being at the same time much easier to handle, from both the analytical and the numerical point of view, than other models relying on nonlinear hyperbolic conservation laws. This makes it suitable to address two-dimensional applications of practical interest, chiefly the motion of pedestrians in complex domains scattered with obstacles.