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In the event of a disaster, saving human lives is of utmost importance. Fordeveloping proper evacuation procedures and guidance systems, behavioural dataon how people respond during panic and stress is crucial. In the absence ofreal human data on building evacuation, there is a need for a crowd simulatorto model egress and decision-making under uncertainty. In this paper, wepropose an agent-based simulation tool, which is grounded in human cognitionand decision-making, for evaluating and improving the effectiveness of buildingevacuation procedures and guidance systems during a disaster. Specifically, wepropose a predictive agent-wayfinding framework based on information theorythat is applied at intersections with variable route choices where it fuses Ndynamic information sources. The proposed framework can be used to visualizetrajectories and prediction results (i.e., total evacuation time, number ofpeople evacuated) for different combinations of reinforcing or contradictinginformation sources (i.e., signage, crowd flow, familiarity, and spatiallayout). This tool can enable designers to recreate various disaster scenariosand generate simulation data for improving the evacuation procedures andexisting guidance systems.

Cognitive Agent Based Simulation Model For Improving Disaster Response Procedures