The Computational Paradigm of Cellular Automata in Crowd Evacuation

Abstract

During last decades, Cellular Automata (CAs) as bio-inspired parallel computational tools have been proven rather efficient and robust on modeling and simulating many different physical processes and systems and solving scientific problems, in which global behavior arises from the collective effect of simple components that interact locally. Among others of most renowned and well established CA applications, crowd evacuation and pedestrian dynamics are considered ones of the most timely and lively topics. Numerous models and computational paradigms of CAs either as standalone models or coupled with other theoretical and practical modeling approaches have been introduced in literature. All these crowd models are taking advantage of the fact that CA 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 aspect, several CA models for crowd evacuation focusing on different modeling principles, like potential fields techniques, obstacle avoidance, follow the leader principles, grouping and queuing theory, long memory effects, etc. are presented in this paper. Moreover, having in mind the inherent parallelism of CA and their straightforward implementation in hardware, some anticipative crowd management systems based on CAs are also shown when operating on medium density crowd evacuation for indoor and outdoor environments. Real world cases and different environments were examined proving the efficiency of the proposed CA based anticipative systems. The proposed hardware implementation of the CAs-based crowd simulation models is advantageous in terms of low-cost, high-speed, compactness and portability features. Finally, robot guided evacuation with the help of CAs is also presented. The proposed framework relies on the well established CAs simulation models, while it employs a real-world evacuation implementation assisted by a mobile robotic guide, which in turn guides people towards a less congestive exit at a time.