Impacts of Anxiety in Building Fire and Smoke Evacuation: Modeling and Validation

Anxiety impairs evacuees' ability to select appropriate routes during building fire and smoke evacuations. Understanding anxiety is thus essential to provide proper guidance to evacuees. However, it is challenging to model how anxiety affects evacuees' decision-making process, and how to validate the resulting approach with very limited available data. In addition, mimicking anxiety in existing simulation packages is not easy because of the lack of appropriate features in simulators. This paper captures the impacts of anxiety on route choices and the interaction with other psychological features such as responses to guidance and herding. This is achieved by using an optimization framework where the number of planning steps and values of psychological parameters are affected by anxiety. To validate our approach, the levels of anxiety were manipulated by hazardous conditions and lengths of planning horizon are evaluated by comparing derived route choices against the data in virtual reality experiments. Impacts of anxiety on large crowds were also mimicked in Fire Dynamic Simulator + Evacuation with and without effective guidance. Testing results demonstrate that effective guidance help reduce negative impacts of anxiety on route choices.

[1]  R L Paulsen,et al.  Human behavior and fires: An introduction , 1984, Fire technology.

[2]  Daniel M. Madrzykowski,et al.  Report of the Technical Investigation of The Station Nightclub Fire (NIST NCSTAR 2) ***DRAFT for Public Comments*** | NIST , 2005 .

[3]  Peter B. Luh,et al.  Crowd Guidance in Building Emergencies: Using Virtual Reality Experiments to Confirm Macroscopic Mathematical Modeling of Psychological Variables , 2014 .

[4]  Federico Garriga Garzón,et al.  Optimal building evacuation time considering evacuation routes , 2009, Eur. J. Oper. Res..

[5]  P. Philippot,et al.  Attention training toward and away from threat in social phobia: effects on subjective, behavioral, and physiological measures of anxiety. , 2012, Behaviour research and therapy.

[6]  B. Aguirre,et al.  Contributions of social science to agent-based models of building evacuation , 2011 .

[7]  S. Folkman,et al.  Stress, appraisal, and coping , 1974 .

[8]  J. Berger Statistical Decision Theory and Bayesian Analysis , 1988 .

[9]  D. Derryberry,et al.  Anxiety and attentional focusing: trait, state and hemispheric influences , 1998 .

[10]  Daniel M. Madrzykowski,et al.  Report of the technical investigation of The Station nightclub fire :: appendices , 2005 .

[11]  Kincho H. Law,et al.  A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations , 2007, AI & SOCIETY.

[12]  Peter B. Luh,et al.  Modeling and Optimization of Building Emergency Evacuation Considering Blocking Effects on Crowd Movement , 2012, IEEE Transactions on Automation Science and Engineering.

[13]  Timo Korhonen,et al.  Fire Dynamics Simulator with Evacuation: FDS+Evac , 2010 .

[14]  Norman I. Badler,et al.  Modeling Crowd and Trained Leader Behavior during Building Evacuation , 2006, IEEE Computer Graphics and Applications.

[15]  Enrico Ronchi,et al.  Virtual reality for fire evacuation research , 2014, 2014 Federated Conference on Computer Science and Information Systems.

[16]  Guylène Proulx,et al.  A stress model for people facing a fire , 1993 .

[17]  T. Vicsek,et al.  Simulation of pedestrian crowds in normal and evacuation situations , 2002 .

[18]  Peter B. Luh,et al.  Guidance optimization of building evacuation considering psychological features in route choice , 2014, Proceeding of the 11th World Congress on Intelligent Control and Automation.