A Modification of the Social Force Model by Foresight

TL;DR

This paper enhances the social force model for pedestrian dynamics by incorporating foresight, allowing for anticipatory reactions that improve the realism of simulated crowd movements.

Contribution

It introduces a modification to the social force model by including foresight, addressing oscillations and unrealistic trajectories in pedestrian simulations.

Findings

Foresight reduces oscillations in pedestrian trajectories.

Combining relevant interactions improves model accuracy.

Anticipatory behavior leads to more realistic crowd simulations.

Abstract

The motion of pedestrian crowds (e.g. for simulation of an evacuation situation) can be modeled as a multi-body system of self driven particles with repulsive interaction. We use a few simple situations to determine the simplest allowed functional form of the force function. More complexity may be necessary to model more complex situations. There are many unknown parameters to such models, which have to be adjusted correctly. The parameters can be related to quantities that can be measured independently, like step length and frequency. The microscopic behavior is, however, only poorly reproduced in many situations, a person approaching a standing or slow obstacle will e.g. show oscillations in position, and the trajectories of two persons meeting in a corridor in opposite direction will be far from realistic and somewhat erratic. This is inpart due to the assumption of instantaneous reaction on the momentary situation. Obviously, persons react with a small time lag, while on the other hand they will anticipate changing situations for at least a short time. Thus basing the repulsive interaction on a (linear) extrapolation over a short time (e.g. 1 s) eliminates the oscillations at slowing down and smoothes the patterns of giving way to others to a more realistic behavior. A second problem is the additive combination of binary interactions. It is shown that combining only a few relevant interactions gives better model performance.