Agent-Based Simulation to Predict Occupants' Physical-Distancing Behaviors in Educational Buildings

Abstract

With a long-term global pandemic impact, it is strongly recommended to secure the physical distance in daily lives. Physical-distancing is the most efficient strategy to defend individuals by lowering the risk of community spreading. Policies of securing physical distances are strongly considered for indoor spaces are essential (i.e., office, school, store). We develop an agent-based simulation model to test the physical-distancing policies (i.e., controlling the capacity of occupants, breaktime between classes, occupants' behavior tendency to secure the distances) based on multiple layers of occupancy behaviors that are possibly occurred in the educational building. The model measures and compares the possible risk that occupants experience from physical distance violation for each policy. The results show the impacts of capacity, break time duration, and internal intent to secure the physical distance on the risks of violating the physical distance. This study can contribute to designing the physical-distancing policies for the educational building.