Agent-based simulation of affordance-based human behaviors in emergency evacuation

Jaekoo Joo, Namhun Kim, Richard A. Wysk, Ling Rothrock, Young Jun Son, Yeong Gwang Oh, Seungho Lee

Research output: Contribution to journalArticlepeer-review

122 Scopus citations


Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory. In this paper, we explore simulating human behaviors using affordance-based finite state automata (FSA) modeling, based on the ecological concept of affordance theory. To this end, we introduce the conceptual and generic framework of affordance-based human behavior simulation developed through our previous work. Following the generic framework, formal simulation models of affordance-based human behaviors are developed, especially for emergency evacuation, to mimic perception-based dynamic human actions interacting with emergent environmental changes, such as fire. A "warehouse fire evacuation" case is used to demonstrate the applicability of the proposed framework. The human action planning algorithms in the simulation model are developed and implemented using the Adjusted Floor Field Indicators, which represent not only the evacuee's prior knowledge of the floor layout but the perceivable information about dynamic environmental changes. The results of our simulation study verify that the proposed framework accurately simulates human fire evacuation behavior. The proposed framework is expected to capture the natural manner in which humans behave in emergency evacuation and enhance the simulation fidelity of analyses and predictions of perceptual human behaviors/responses in the systems by incorporating cognitive intent into human behavior simulations.

Original languageEnglish (US)
Pages (from-to)99-115
Number of pages17
JournalSimulation Modelling Practice and Theory
StatePublished - 2013

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Hardware and Architecture


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