Cellular Automata for Crowd Dynamics

Abstract

Cellular Automata (CA) as bio-inspired parallel computational models of self-reproducing organisms can capture the essential features of systems where global behavior arises from the collective effect of simple components which interact locally. In this aspect, CAs have been considered as a fine candidate to model pedestrian behavior and crowd dynamics in a fine manner. In specific, for crowd modeling, the CA models show evidence of a macroscopic nature with microscopic extensions, i.e. they provide adequate details in the description of human behavior and interaction, whilst they retain the computational cost at low levels. In this paper several CA models for crowd evacuation taking into consideration different modeling principles, like potential fields techniques, obstacle avoidance, follow-the-leader principles, grouping theory, etc. will be presented in an attempt to accomplish efficient crowd evacuation simulation. Moreover, an integrated system based on CAs that operates as an anticipative crowd management tool in cases of medium density crowd evacuation for indoor and outdoor environments is also shown, and its results different real world cases and different environments prove its efficiency. Finally, robot guided evacuation with the help of CAs is also presented. Quite recently, an evacuation system was proposed, based on an accurate CA model capable of assessing the human behavior during emergency situations takes advantage of the simulation output to provide sufficient information to a mobile robotic guide, which in turn guides people towards a less congestive exit at a time.