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A method for the analysis of behavioural uncertainty in evacuation modelling

Published

Author(s)

Enrico Ronchi, Paul A. Reneke, Richard D. Peacock

Abstract

Evacuation models generally include the use of distributions or probabilistic variables to simulate the variability of possible human behaviours. A single model setup of the same evacuation scenario may therefore produce a distribution of different occupant- evacuation time curves. This creates an additional component of uncertainty caused by the impact of the number of simulated runs of the same scenario on evacuation model predictions, here named behavioural uncertainty. To date there is no universally accepted quantitative method to evaluate behavioural uncertainty and the selection of the number of runs is left to a qualitative judgement of the model user. A simple quantitative method using convergence criteria based on functional analysis is presented to address this issue. The method permits 1) the analysis of the variability of model predictions in relation to the number of runs of the same evacuation scenario, i.e. the study of behavioural uncertainty 2) the identification of the optimal number of runs of the same scenario in relation to pre-defined acceptance criteria.
Citation
Fire Technology

Keywords

Evacuation modelling, Behavioural uncertainty, Human Behaviour in Fire, Functional Analysis, Convergence Criteria

Citation

Ronchi, E. , Reneke, P. and Peacock, R. (2013), A method for the analysis of behavioural uncertainty in evacuation modelling, Fire Technology, [online], https://doi.org/10.1007/s10694-013-0352-7 (Accessed February 29, 2024)
Created July 9, 2013, Updated November 10, 2018