Integrating the Implications of Distance-Based Affective States in Cellular Automata Pedestrian Simulation

Cellular Automata have successfully been applied to the modeling and simulation of pedestrian dynamics. These simulations have often been focused on the evaluation of situations of medium-high density, in which the motivation of pedestrians overcomes natural proxemic tendencies. The COVID-19 outbreak has shown that in certain situations it is instead crucial to focus on situations in which proxemic is amplified by the particular affective state of the individuals involved in the studied scenario. We present the first steps in a research effort aimed at integrating results of quantitative analyses concerning effects of affective states on the perception of mutual distances by pedestrians of different type and the modeling of movement choices in a cellular automata framework.