Formolo, D, Bosse, T and van der Wal, N (2018) Studying the Impact of Trained Staff on Evacuation Scenarios by Agent-Based Simulation. In: Staab, S, Koltsova, O and Ignatov, DI, (eds.) Lecture Notes in Computer Science, vol 11186. SocInfo 2018: 10th International Conference on Social Informatics, 25-28 Sep 2018, St.Petersburg, Russia. Springer Verlag , pp. 85-96. ISBN 978-3-030-01158-1
Abstract
Human evacuation experiments can trigger distress, be unethical and present high costs. As a solution, computer simulations can predict the effectiveness of new emergency management procedures. This paper applies multi-agent simulation to measure the influence of staff members with diverse training levels on evacuation time. A previously developed and validated model was extended with explicit mechanisms to simulate staff members helping people to egress. The majority of parameter settings have been based on empirical data acquired in earlier studies. Therefore, simulation results are expected to be realistic. Results show that staff are more effective in complex environments, especially when trained. Not only specialised security professionals but, especially, regular workers of shopping facilities and offices play a significant role in evacuation processes when adequately trained. These results can inform policy makers and crowd managers on new emergency management procedures.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018, Springer Nature Switzerland AG. This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-01159-8_8. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Crowd management; Evacuation; Agent-based model; Staff |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Management Division Organizational Behaviour (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Feb 2019 14:44 |
Last Modified: | 04 Mar 2019 12:07 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/978-3-030-01159-8_8 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:143068 |