Ronchi, E., Nieto Uriz, F., Criel, X. et al. (1 more author) (2016) Modelling large-scale evacuation of music festivals. Case Studies in Fire Safety, 5. pp. 11-19. ISSN 2214-398X
Abstract
This paper explores the use of multi-agent continuous evacuation modelling for representing large-scale evacuation scenarios at music festivals. A 65,000 people capacity music festival area was simulated using the model Pathfinder. Three evacuation scenarios were developed in order to explore the capabilities of evacuation modelling during such incidents, namely (1) a preventive evacuation of a section of the festival area containing approximately 15,000 people due to a fire breaking out on a ship, (2) an escalating scenario involving the total evacuation of the entire festival area (65,000 people) due to a bomb threat, and (3) a cascading scenario involving the total evacuation of the entire festival area (65,000 people) due to the threat of an explosion caused by a ship engine overheating. This study suggests that the analysis of the people-evacuation time curves produced by evacuation models, coupled with a visual analysis of the simulated evacuation scenarios, allows for the identification of the main factors affecting the evacuation process (e.g., delay times, overcrowding at exits in relation to exit widths, etc.) and potential measures that could improve safety.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 The Author(s). Article available under the terms of the Attribution-NonCommercial-NoDerivatives 4.0 International licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Emergency evacuation; Evacuation modelling; Crowd management; Music festival; Cascading effects |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Jan 2016 10:20 |
Last Modified: | 21 Jan 2016 10:20 |
Published Version: | http://dx.doi.org/10.1016/j.csfs.2015.12.002 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.csfs.2015.12.002 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:93886 |