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Real-time Stochastic Evacuation Models for Decision Support in Actual Emergencies

Cuesta A., Alvear, D., Abreu O. and Silió D., 2014. Real-time Stochastic Evacuation Models for Decision Support in Actual Emergencies. Fire Safety Science 11: 1063-1076. 10.3801/IAFSS.FSS.11-1063


This paper introduces and proposes the use of evacuation models for decision support during actual emergencies. Two examples are presented: EvacTrain 2.0 and EvacTunnel. The proposed models are essentially stochastic, quick and easy to use and can generate and process results of several simulations within a few seconds. The main output parameter is the percentile (0.90, 0.95 or 0.99 th) of total evacuation times. They also provide other statistical characteristics and additional outputs. Both models have been compared with other validated evacuation models. Results suggest that the proposed models provide consistent and reliable results. The general findings described in this paper suggest that it is possible to develop efficient evacuation models for supporting emergency decisions in real-time.


human behaviour, fire safety management, Monte Carlo methods, real-time, modelling

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