Computational Modeling of Human Behavior for Emergency Egress Analysis: A Multi-Agent Based Simulation Approach

This writing addresses the problem of bringing the perspectives of psychology and sociology about human behavior in emergencies into computational models for egress analysis. Efficacious analysis of emergency egress is facilitated by incorporation of diverse human behavior into a Multi-Agent Simulation System for Egress analysis (MASSEgress). MASSEgress adopts a multi-agent based simulation paradigm to model evacuees as individual agents equipped with sensors, brains and actuators. Individual behavior is simulated through modeling of sensing, decision-making, behavior selection and motor control. Social behavior is simulated through modeling of individual behavior and interactions among individuals. Competitive, queuing, herding, and leader-following behaviors are modeled. MASSEgress is a computational framework; its modular design allows easy extensions to include additional behavior types.

Dr. Pan is trained professionally in Architecture, Computer Science and Civil Engineering. He had dual Master¿s degrees in Architecture and Computer Science, and received a PhD degree in Civil Engineering from Stanford University. Currently he works for CDM Tech., Inc., San Luis Obispo, California, USA, researching AI and agent-based technologies.