Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

TL;DR

This paper models pedestrian evacuation using a bionics-inspired cellular automaton, exploring how different behaviors affect evacuation times and identifying optimal herding and knowledge use for efficiency.

Contribution

Introduces a novel cellular automaton model based on chemotaxis principles to simulate pedestrian evacuation dynamics.

Findings

Evacuation times vary non-monotonically with model parameters.

Optimal evacuation occurs at intermediate levels of herding behavior.

Model captures a range of behaviors from regular to panic.

Abstract

We present simulations of evacuation processes using a recently introduced cellular automaton model for pedestrian dynamics. This model applies a bionics approach to describe the interaction between the pedestrians using ideas from chemotaxis. Here we study a rather simple situation, namely the evacuation from a large room with one or two doors. It is shown that the variation of the model parameters allows to describe different types of behaviour, from regular to panic. We find a non-monotonic dependence of the evacuation times on the coupling constants. These times depend on the strength of the herding behaviour, with minimal evacuation times for some intermediate values of the couplings, i.e. a proper combination of herding and use of knowledge about the shortest way to the exit.