Furthering an agent-based modeling approach introducing affective states based on real data

Modeling new agent-based simulation systems focused on pedestrian and crowd management that include information regarding affective states, in order to involve agents replicating human behaviour more closely, is to this day an open challenge in pedestrian simulation. Taking into consideration how human perception and decision-making processes work, being them heavily influenced not only by a person’s environment but also by his/her personal psychological and physiological aspects, is of vital importance in the perspective of trying and introduce agents with more realistic behaviour inside simulations. In this regard, following up on a recent work, this paper presents further steps operated in a research effort aimed at utilizing quantitative data recorded through an online experiment to proceed with the modeling of affective agents. The presented approach leads then to some preliminary simulations, showing the impact and effect of the newly introduced information on pedestrian’s proxemic distances and movement choices when moving in different situations among other people influencing them with their behaviour as well.