Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building

Understanding crowd evacuation behavior is of utmost importance for large buildings in order to achieve efficient crowd monitoring and management. This paper presents the simulation and analysis of crowd evacuation pattern for a large building called Al Masjid An Nabawi, widely known as ‘the Haram,’...

Full description

Saved in:
Bibliographic Details
Main Authors: Alginahi, Yasser M., Mudassar, Mohammed, Kabir, M. Nomani, Tayan, Omar
Format: Article
Language:English
Published: Springer 2018
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/23485/1/Analyzing%20the%20Crowd%20Evacuation%20Pattern%20of%20a%20Large%20Densely1.pdf
http://umpir.ump.edu.my/id/eprint/23485/
https://doi.org/10.1007/s13369-018-3411-z
https://doi.org/10.1007/s13369-018-3411-z
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ump.umpir.23485
record_format eprints
spelling my.ump.umpir.234852019-01-02T06:45:21Z http://umpir.ump.edu.my/id/eprint/23485/ Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building Alginahi, Yasser M. Mudassar, Mohammed Kabir, M. Nomani Tayan, Omar Q Science (General) Understanding crowd evacuation behavior is of utmost importance for large buildings in order to achieve efficient crowd monitoring and management. This paper presents the simulation and analysis of crowd evacuation pattern for a large building called Al Masjid An Nabawi, widely known as ‘the Haram,’ in Madinah, Saudi Arabia. Legion Evac software is employed to simulate the crowd evacuation. During simulation, Legion computes various metrics that holistically reflect the crowd evacuation pattern, which captures the crowd evacuation behavior. We analyze the magnitude and temporal variations with respect to the general evacuation patterns (GEP) of the building. The magnitude is analyzed using the t-test, which is a hypothesis testing method. However, the temporal variations are analyzed using cross-correlation analysis. The GEP captures the general crowd evacuation behavior (across all sections) of the building by aggregating the evacuation patterns of each section of the building. The crowd evacuation simulation resulted in an evacuation time of 21 min to evacuate a population of approximately 170,000. The analysis of evacuation patterns shows that the evacuation pattern of different sections of the building differs significantly in magnitude, but has significant temporal similarity with respect to GEP. Finally, insights are derived from the analysis results, which aid in efficient crowd monitoring and management. Springer 2018 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/23485/1/Analyzing%20the%20Crowd%20Evacuation%20Pattern%20of%20a%20Large%20Densely1.pdf Alginahi, Yasser M. and Mudassar, Mohammed and Kabir, M. Nomani and Tayan, Omar (2018) Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building. Arabian Journal for Science and Engineering. pp. 1-16. ISSN 1319-8025 (print); 2191-4281 (online) (In Press) https://doi.org/10.1007/s13369-018-3411-z https://doi.org/10.1007/s13369-018-3411-z
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Alginahi, Yasser M.
Mudassar, Mohammed
Kabir, M. Nomani
Tayan, Omar
Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building
description Understanding crowd evacuation behavior is of utmost importance for large buildings in order to achieve efficient crowd monitoring and management. This paper presents the simulation and analysis of crowd evacuation pattern for a large building called Al Masjid An Nabawi, widely known as ‘the Haram,’ in Madinah, Saudi Arabia. Legion Evac software is employed to simulate the crowd evacuation. During simulation, Legion computes various metrics that holistically reflect the crowd evacuation pattern, which captures the crowd evacuation behavior. We analyze the magnitude and temporal variations with respect to the general evacuation patterns (GEP) of the building. The magnitude is analyzed using the t-test, which is a hypothesis testing method. However, the temporal variations are analyzed using cross-correlation analysis. The GEP captures the general crowd evacuation behavior (across all sections) of the building by aggregating the evacuation patterns of each section of the building. The crowd evacuation simulation resulted in an evacuation time of 21 min to evacuate a population of approximately 170,000. The analysis of evacuation patterns shows that the evacuation pattern of different sections of the building differs significantly in magnitude, but has significant temporal similarity with respect to GEP. Finally, insights are derived from the analysis results, which aid in efficient crowd monitoring and management.
format Article
author Alginahi, Yasser M.
Mudassar, Mohammed
Kabir, M. Nomani
Tayan, Omar
author_facet Alginahi, Yasser M.
Mudassar, Mohammed
Kabir, M. Nomani
Tayan, Omar
author_sort Alginahi, Yasser M.
title Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building
title_short Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building
title_full Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building
title_fullStr Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building
title_full_unstemmed Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building
title_sort analyzing the crowd evacuation pattern of a large densely populated building
publisher Springer
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/23485/1/Analyzing%20the%20Crowd%20Evacuation%20Pattern%20of%20a%20Large%20Densely1.pdf
http://umpir.ump.edu.my/id/eprint/23485/
https://doi.org/10.1007/s13369-018-3411-z
https://doi.org/10.1007/s13369-018-3411-z
_version_ 1643669610768105472
score 13.160551