Comparing first order microscopic and macroscopic crowd models for an increasing number of massive agents

TL;DR

This paper compares microscopic and macroscopic crowd models with massive agents, showing they converge as the number of pedestrians increases when interaction parameters are properly scaled, reflecting adaptive behavior.

Contribution

It introduces a novel comparison of microscopic and macroscopic models considering massive agents with increasing total mass, extending previous models to more realistic scenarios.

Findings

Models approach each other as N increases with proper scaling.

Massive agents' total mass grows with N, affecting dynamics.

Pedestrians adapt interaction strength based on congestion.

Abstract

In this paper a comparison between first order microscopic and macroscopic differential models of crowd dynamics is established for an increasing number $N$ of pedestrians. The novelty is the fact of considering massive agents, namely particles whose individual mass does not become infinitesimal when $N$ grows. This implies that the total mass of the system is not constant but grows with $N$. The main result is that the two types of models approach one another in the limit $N\to\infty$, provided the strength and/or the domain of pedestrian interactions are properly modulated by $N$ at either scale. This is consistent with the idea that pedestrians may adapt their interpersonal attitudes according to the overall level of congestion.