Studies of past emergency events have revealed that occupants’ behaviors, local geometry, and environmental constraints affect crowd movement and evacuation. Design of egress systems should take into consideration the social characteristics of the occupants and the unique layout of the buildings. This paper describes an agent-based egress simulation tool, SAFEgress, which is designed to incorporate human and social behaviors during evacuations. The unique feature of SAFEgress is its flexibility to model different individual, group, and crowd behavior. Simulations are conducted to examine egress performance of a museum floor plan for three scenarios: (1) expected occupancy load during peak hours; (2) group behaviors among museum visitors; and (3) measures to reduce pre-evacuation delay. By assuming different occupants’ behaviors in the simulations, engineers, designers, and facility managers can study the important human and social factors on an egress situation and, thereby, improve the design of safe egress systems and procedures.
Emergency evacuation (egress) is considered one of the most important issues in the design of buildings and public facilities. Given the complexity and variability in an evacuation situation, computational simulation tool is often used to help assess the performance of an egress design. Studies have revealed that social behaviors can have significant influence on the evacuating crowd during an emergency. Among the challenges in designing safe egress thus include identifying the social behaviors and incorporating them in the design analysis. Even though many egress simulation tools now exist, realistic human and social behaviors commonly observed in emergency situations are not supported. This paper describes an egress simulation approach that incorporates research results from social science regarding human and social behaviors observed in emergency situations. By integrating the behavioral theories proposed by social scientists, the simulation tool can potentially produce more realistic predications than current tools which heavily rely on simplified and, in most cases, mathematical assumptions.
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