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A Method for the Analysis of Behavioural Uncertainty in Evacuation Modelling

Ronchi, Enrico LU ; Reneke, Paul A. and Peacock, Richard D. (2014) In Fire Technology 50(6). p.1545-1571
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 in the case of the use of a random sampling method. 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... (More)
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 in the case of the use of a random sampling method. 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 and (2) the identification of the optimal number of runs of the same scenario in relation to pre-defined acceptance criteria. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Behavioural uncertainty, Convergence criteria, Evacuation modelling, Functional analysis, Human behaviour in fire
in
Fire Technology
volume
50
issue
6
pages
1545 - 1571
publisher
Kluwer
external identifiers
  • wos:000343721200013
  • scopus:84918546487
ISSN
0015-2684
DOI
10.1007/s10694-013-0352-7
language
English
LU publication?
yes
id
10b5c4aa-b30e-4028-8ccc-c614d629e744 (old id 4001463)
date added to LUP
2013-08-27 10:59:43
date last changed
2017-11-12 03:34:43
@article{10b5c4aa-b30e-4028-8ccc-c614d629e744,
  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 in the case of the use of a random sampling method. 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 and (2) the identification of the optimal number of runs of the same scenario in relation to pre-defined acceptance criteria.},
  author       = {Ronchi, Enrico and Reneke, Paul A. and Peacock, Richard D.},
  issn         = {0015-2684},
  keyword      = {Behavioural uncertainty,Convergence criteria,Evacuation modelling,Functional analysis,Human behaviour in fire},
  language     = {eng},
  number       = {6},
  pages        = {1545--1571},
  publisher    = {Kluwer},
  series       = {Fire Technology},
  title        = {A Method for the Analysis of Behavioural Uncertainty in Evacuation Modelling},
  url          = {http://dx.doi.org/10.1007/s10694-013-0352-7},
  volume       = {50},
  year         = {2014},
}