Pedestrian Models based on Rational Behaviour

TL;DR

This paper introduces a rational, anticipation-based model for pedestrian dynamics that improves upon traditional force-based models by better capturing high-density crowd behaviors through a game-theoretic approach.

Contribution

It presents a novel pedestrian model incorporating anticipation and rational decision-making, addressing limitations of mechanistic models in high-density scenarios.

Findings

Model reproduces realistic high-density crowd dynamics

Anticipation improves accuracy over purely mechanical models

Validates approach across different congestion regimes

Abstract

Following the paradigm set by attraction-repulsion-alignment schemes, a myriad of individual based models have been proposed to calculate the evolution of abstract agents. While the emergent features of many agent systems have been described astonishingly well with force-based models, this is not the case for pedestrians. Many of the classical schemes have failed to capture the fine detail of crowd dynamics, and it is unlikely that a purely mechanical model will succeed. As a response to the mechanistic literature, we will consider a model for pedestrian dynamics that attempts to reproduce the rational behaviour of individual agents through the means of anticipation. Each pedestrian undergoes a two-step time evolution based on a perception stage and a decision stage. We will discuss the validity of this game theoretical based model in regimes with varying degrees of congestion, ultimately presenting a correction to the mechanistic model in order to achieve realistic high-density dynamics.