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Information use by humans during dynamic route choice in virtual crowd evacuations.
Bode, Nikolai W F; Kemloh Wagoum, Armel U; Codling, Edward A.
Afiliación
  • Bode NW; Department of Mathematical Sciences , University of Essex , Colchester CO4 3SQ, UK ; Department of Engineering Mathematics , University of Bristol , Bristol BS8 1UB, UK.
  • Kemloh Wagoum AU; Jülich Supercomputing Centre , Forschungszentrum Jülich GmbH , 52428 Jülich, Germany.
  • Codling EA; Department of Mathematical Sciences , University of Essex , Colchester CO4 3SQ, UK.
R Soc Open Sci ; 2(1): 140410, 2015 Jan.
Article en En | MEDLINE | ID: mdl-26064589
We conducted a computer-based experiment with over 450 human participants and used a Bayesian model selection approach to explore dynamic exit route choice mechanisms of individuals in simulated crowd evacuations. In contrast to previous work, we explicitly explore the use of time-dependent and time-independent information in decision-making. Our findings suggest that participants tended to base their exit choices on time-dependent information, such as differences in queue lengths and queue speeds at exits rather than on time-independent information, such as differences in exit widths or exit route length. We found weak support for similar decision-making mechanisms under a stress-inducing experimental treatment. However, under this treatment participants were less able or willing to adjust their original exit choice in the course of the evacuation. Our experiment is not a direct test of behaviour in real evacuations, but it does highlight the role different types of information and stress play in real human decision-making in a virtual environment. Our findings may be useful in identifying topics for future study on real human crowd movements or for developing more realistic agent-based simulations.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: R Soc Open Sci Año: 2015 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: R Soc Open Sci Año: 2015 Tipo del documento: Article