An Online Survey of Pedestrian Evacuation Model Usage and Users

Research output: Contribution to journalArticle


Pedestrian evacuation models are often used to assess life safety in the performance-based design process within fire safety engineering. Within this paper, a summary of data collected via an international online survey regarding the models and users’ experiences and needs is presented. This survey consisted of 22 questions focusing on: the assessment of the pedestrian evacuation model user community; their stated importance of model features to select a model; usage/awareness of models; knowledge of model validation and verification; training; and usage of multiple models. As such, the survey allowed the collection of information useful for instructing future pedestrian evacuation model development. The survey represents an expanded version of a previous survey conducted by the authors in 2011. Results with the previous survey were compared to identify any changes in preference and usage by pedestrian evacuation model users. The survey was completed by 234 respondents from 41 countries. The respondents had a wide range of education and occupational backgrounds and use models for a variety of different purposes. The results identified a total of 72 pedestrian evacuation models currently in use and indicated the most known models. In addition, the most used models were identified, and the results highlighted that the three key factors used to select a pedestrian evacuation model are overall consistent with the results of the 2011 survey: verification and validation, documentation, and data output of the model.


External organisations
  • Massey University Albany
  • Arup Shanghai
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Building Technologies
  • Other Computer and Information Science


  • Egress, Evacuation models, Modelling, Online survey, Simulation
Original languageEnglish
JournalFire Technology
Publication statusE-pub ahead of print - 2019 Nov 5
Publication categoryResearch