A Method for the Analysis of Behavioural Uncertainty in Evacuation Modelling

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

Research output: Contribution to journalArticlepeer-review

69 Citations (SciVal)

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.
Original languageEnglish
Pages (from-to)1545-1571
JournalFire Technology
Volume50
Issue number6
DOIs
Publication statusPublished - 2014

Subject classification (UKÄ)

  • Building Technologies
  • Other Civil Engineering

Keywords

  • Behavioural uncertainty
  • Convergence criteria
  • Evacuation modelling
  • Functional analysis
  • Human behaviour in fire

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