A Framework for Simulating Human Cognitive Behavior and Movement When Predicting Impacts of Catastrophic Events

Abstract

Our nation has seen an increased need to train its civil authorities and emergency personnel under life-threatening scenarios where human life and critical infrastructure are assumed to be at risk. This training is typically obtained or re-enforced via (human) performance-based tests. At issue is the ability to accurately simulate the scenarios without exposing personnel or human test subjects to injury. In addition, these performance-based tests carry a large monetary cost, and certain scenarios are so complicated, catastrophic or rare that any performance-based test is unrealistic. Our paper outlines the research that must be conducted to develop a framework for modeling and analyzing risk-assessment and decision making when evacuating large populations. The research is aimed at extending an existing construct for simulating passenger and crew behavior during aircraft evacuations, to larger populations, and relies upon rare-event simulation methods, paralleland-distributed simulation and agent-based simulation.

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

“…First of all, there exists quite an extensive amount of literature in the field of behavioural sciences relating to humans' psychological response to, for example, (imminent) emergency conditions, and decision making under timepressure and safety concerns (for an overview see Court et al 2004;Dombroski et al 2006;Mawson 2005). This kind of research has found almost no reference in evacuation traffic modelling and simulation studies.…”

Technosocial Predictive Analytics in Support of Naturalistic Decision Making

“…• Social Movement Theory: Integrated understanding of the infrastructural, social and ideational context in which contentious social movements operate is an essential analytical step in framing the emergence of violent behavior (Wiktorowicz, 2004) • Disaster Recovery: Anticipating how the public will react to official rescue and recovery directives during a major catastrophe and how the public's reaction will interact with infrastructural and logistic factors is key to maximizing the effectiveness of emergency-response operations (Court, Pittman, Alexopoulos, Goldsman, Kim, Loper, Pritchett & Haddock, 2004) • Climate Change: Combined understanding of anthropogenic effects (e.g., chemical waste) and natural processes (e.g., solar variation) is needed to predict the impact of global warming (Gore, 2006) • Nuclear Risk Prevention: Most nuclear accidents can be anticipated by a predictable interaction of technology and human performance failures (NRC, 2005) • Fuel Efficiency Standards: EPA fuel-efficiency tests have overstated performance because human factors such as faster speeds and acceleration and air-conditioner use have been neglected in use-case forecasting (EPA, 2006) • Behavioral Economics: Insights on human cognitive and emotional biases improve our understanding of economic decisions and the effect of economic decisions on market prices, returns, and the allocation of resources (Mullainathan & Thalerb, 2001) • Human Health: Multilevel studies that consider a broad range of biological, family, community, socio-cultural, environmental, policy, and macro-level economic factors are necessary to prevent and mitigate the emergence of health threats such as childhood obesity (NIH RFA-HD-08-023, 2008) and drug addiction (NIDA, 2007).…”