Vision-based macroscopic pedestrian models

TL;DR

This paper develops a hierarchy of kinetic and macroscopic models for large pedestrian systems, based on interaction rules involving bearing angle derivatives and time-to-interaction, and discusses their applicability for crowd simulation.

Contribution

It introduces a new hierarchy of pedestrian models derived from interaction rules and explores different closure assumptions and hydrodynamic limits.

Findings

Derived a mean-field kinetic model for pedestrian interactions.

Proposed three macroscopic models with different closure assumptions.

Discussed the practical relevance of each model for crowd simulation.

Abstract

We propose a hierarchy of kinetic and macroscopic models for a system consisting of a large number of interacting pedestrians. The basic interaction rules are derived from earlier work where the dangerousness level of an interaction with another pedestrian is measured in terms of the derivative of the bearing angle (angle between the walking direction and the line connecting the two subjects) and of the time-to-interaction (time before reaching the closest distance between the two subjects). A mean-field kinetic model is derived. Then, three different macroscopic continuum models are proposed. The first two ones rely on two different closure assumptions of the kinetic model, respectively based on a monokinetic and a von Mises-Fisher distribution. The third one is derived through a hydrodynamic limit. In each case, we discuss the relevance of the model for practical simulations of pedestrian crowds.