TY - JOUR
T1 - An Agent-Based Simulation Model to Evaluate Contacts, Layout, and Policies in Entrance, Exit, and Seating in Indoor Activities Under a Pandemic Situation
AU - Islam, Md Tariqul
AU - Jain, Saurabh
AU - Chen, Yijie
AU - Chowdhury, Bijoy Dripta Barua
AU - Son, Young Jun
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - 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. Note to Practitioners - This article was motivated to ensure safer and efficient operations within indoor facilities by evaluating contact-caused risks and entrance/exit policies during a pandemic situation like coronavirus disease (COVID-19). Most of the recent works related to COVID-19 disease propagation focus on the evaluation of disease transmission at an organization level, however, limited studies focus on the operational aspect of indoor facilities within the organization. To bridge this gap, this article utilizes an agent-based modeling approach to model and understand the pedestrian dynamics in the classroom-like facilities considering physical distancing, seat assignment, and entry/exit policies. Comprehensive simulation modeling and analysis allows the amalgamation of real data, including layout, class schedules, seating arrangement, and allowable capacity to perform various what-if analyses under different policies. This article proposes and evaluates seating assignment based on the associated number and duration of contacts during movements in the pathway and entrance/ exit area of a confined space. In addition, this work evaluates different indoor layouts (e.g., classroom, meeting room, and office) and exit policies (e.g., zonal and non-zonal) at different occupancy levels for appropriate decision support. The proposed approach will aid organizations (e.g., educational institutions, corporate offices, and recreational facilities) to evaluate necessary policies (namely entrance and exit policy, seating policy, and room layout) for safe indoor operations with respect to the minimum contact-caused risk associated with the activities. As a future direction, the outputs from the proposed work can be utilized to obtain the realistic input parameters needed for organization-wide disease propagation models, which will provide decision support at an organizational level.
AB - 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. Note to Practitioners - This article was motivated to ensure safer and efficient operations within indoor facilities by evaluating contact-caused risks and entrance/exit policies during a pandemic situation like coronavirus disease (COVID-19). Most of the recent works related to COVID-19 disease propagation focus on the evaluation of disease transmission at an organization level, however, limited studies focus on the operational aspect of indoor facilities within the organization. To bridge this gap, this article utilizes an agent-based modeling approach to model and understand the pedestrian dynamics in the classroom-like facilities considering physical distancing, seat assignment, and entry/exit policies. Comprehensive simulation modeling and analysis allows the amalgamation of real data, including layout, class schedules, seating arrangement, and allowable capacity to perform various what-if analyses under different policies. This article proposes and evaluates seating assignment based on the associated number and duration of contacts during movements in the pathway and entrance/ exit area of a confined space. In addition, this work evaluates different indoor layouts (e.g., classroom, meeting room, and office) and exit policies (e.g., zonal and non-zonal) at different occupancy levels for appropriate decision support. The proposed approach will aid organizations (e.g., educational institutions, corporate offices, and recreational facilities) to evaluate necessary policies (namely entrance and exit policy, seating policy, and room layout) for safe indoor operations with respect to the minimum contact-caused risk associated with the activities. As a future direction, the outputs from the proposed work can be utilized to obtain the realistic input parameters needed for organization-wide disease propagation models, which will provide decision support at an organizational level.
KW - Agent-based simulation
KW - contact-caused risks
KW - coronavirus disease (COVID-19)
KW - indoor activities
KW - policy evaluation
UR - http://www.scopus.com/inward/record.url?scp=85118252570&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118252570&partnerID=8YFLogxK
U2 - 10.1109/TASE.2021.3118008
DO - 10.1109/TASE.2021.3118008
M3 - Article
AN - SCOPUS:85118252570
SN - 1545-5955
VL - 19
SP - 603
EP - 619
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 2
ER -