Modelo baseado em autômatos celulares para simulação de dinâmica coletiva de pedestres em ambientes internos

Abstract

Understanding human behavior and predicting it in normal and emergency situations is a challenging task that attracts the attention of many researchers. In this context, simulations of collective pedestrian dynamics (SCPD) are essential in society as they are used in various scenarios, such as urban planning and public safety. Cellular automata stand out as simple computational tools capable of identifying and reproducing the complexity of various patterns, such as pedestrian movement, especially in cases of emergency evacuation. These models take into account several parameters, such as the strategy for choosing the floor, the interaction between pedestrians, social phenomena, such as panic and the tendency to follow crowds, among others. This work proposes a model based on cellular automata for modeling SCPD, strongly based on the Varas's model, which combines three modifications to make the simulation closer to reality. They are: changing the dynamics of movement, representing the separation between surmountable and insurmountable obstacles, and changing the permission to pass between objects along the diagonal.