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Analyzing the Crowd Evacuation Pattern of a Large Densely Populated Building

  • Yasser M. Alginahi
  • Mohammed Mudassar
  • Muhammad Nomani Kabir
  • Omar Tayan
Research Article - Computer Engineering and Computer Science
  • 6 Downloads

Abstract

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.

Keywords

Crowd evacuation Simulation Legion Evac Crowd evacuation behavior Cross-correlation analysis Evacuation patterns 

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Notes

Acknowledgements

The authors would like to thank the Deanship of Scientific Research at Taibah University for their support to conduct this research work under research grant no. 434/4317.

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Copyright information

© King Fahd University of Petroleum & Minerals 2018

Authors and Affiliations

  1. 1.Department of Computer Science, Deanship of Academic ServicesTaibah UniversityMedinaSaudi Arabia
  2. 2.Department of Computer Science, College of Computer Science and EngineeringTaibah UniversityMedinaSaudi Arabia
  3. 3.Faculty of Computer Systems and Software EngineeringUniversiti Malaysia PahangGambang, KuantanMalaysia
  4. 4.Department of Computer Engineering, College of Computer Science and EngineeringTaibah UniversityMedinaSaudi Arabia
  5. 5.IT Research Center for the Holy Quran and Its Sciences (NOOR)Taibah UniversityMedinaSaudi Arabia

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