An Agent-Based Simulation Model to Evaluate Contacts, Layout, and Policies in Entrance, Exit, and Seating in Indoor Activities Under a Pandemic Situation

The outbreak of the novel coronavirus SARS-CoV2 has dramatically changed the world and has been a severe health threat in 2020 and 2021. In this article, an agent-based simulation model of pedestrian dynamics is proposed for classroom-type indoor spaces (e.g., classroom, auditorium, food court, and meeting room), which will help organizations such as universities to evaluate alternative policies (namely entrance and exit policy, seating policy, and room layout) concerning the contact-caused risk associated with activities in such places during a pandemic situation. In particular, the proposed work focuses on solving the indoor seat allocation and traffic movement problem while practicing appropriate physical distancing measures. The proposed seating policy evaluates the distance of a seat from the doors and pathways facilitating the evaluation of contact-caused risk associated with the pathway and indoor area movement. Various statistics from two perspectives, risk, and logistics, are reported in the simulation results. The risk metrics used in evaluating different policies include average exposure duration and an average number of contacts with others. To develop a highly realistic crowd simulation considering physical distancing and human intervention nature, deadlock detection and resolution mechanisms are incorporated. From this study, it has been observed that the proposed social distancing (SD) seating policy and zonal exit policy can significantly reduce the contact number and exposure duration at a higher occupancy level. The proposed work helps the organizational policymakers to evaluate different policies and ensure the safe operation of the organizations under pandemic situations.