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. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Affectivity and Proxemic Distances: an experimental agent-based modeling approach

Many manifestations of interactive human behavior (social and with the environment) are conditioned by emotions, influencing reasoning and other rational decision making activities. The study of the interplay of emotional and non-emotional behaviors (spatial motion) is here faced through the modeling of affective agents where affective states are explicitly measured and represented thanks to the collection of data in a dedicated experiment with humans. During this experiment, we observed that subjects of different ages (focusing on elderly) react differently to particular spatial stimuli (proxemics distance calculation), manifesting a strict relation between distancing and emotional states. The agent-based modeling and simulation of this behavior here presented is a contribution to the comprehension of complex interplays between spatial distances and affective states, amplified by the recent experience of pandemic, where aware distancing become a mandatory and affecting factor of the life, especially for fragile and aged people. The presented modeling approach relies on data collected with an online experiment performed to understand what kind of personal, psychological and situational factors influenced people’s behavior while distancing from others, in particular during the COVID-19 pandemic. The focus of the experiment was in the comparison of different age reactions, involving 80 participants aged between 16 and 92 years. © 2020 Copyright for this paper by its authors.