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Empirical study of a unidirectional dense crowd during a real mass event

Author

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  • Zhang, X.L.
  • Weng, W.G.
  • Yuan, H.Y.
  • Chen, J.G.

Abstract

Many tragic crowd disasters have happened across the world in recent years, such as the Phnom Penh stampede in Cambodia, crowd disaster in Mina/Makkah, and the Love Parade disaster in Germany, showing that management of mass events is a tough task for organizers. The study of unidirectional flow, one of the most common forms of motion in mass activities, is essential for safe organization of such events. In this paper, the properties of unidirectional flow in a crowded street during a real mass event in China are quantitatively investigated with sophisticated active infrared counters and an image processing method. A complete dataset of flow rates during the whole celebration is recorded, and a time series analysis gives new insight into such activities. The spatial analysis shows that the velocity and density of the crowd are inhomogeneous due to the boundary effect, whereas the flux is uniform. The estimated capacity of the street indicates that the maximum flow rate under normal condition should be between 1.73 and 1.98 /m/s, which is in good agreement with several field studies available in the existing literature. In consideration of the significant deviation among different studies, fundamental diagrams of dense crowds are also re-verified, and the results here are consistent with those from other field studies of unidirectional flow, but different from the bidirectional and experimental results. It is suggested that the data from multidirectional flow and experiments cannot be directly applied to unidirectional dense flow in a real mass event. The results also imply that the density of a similar unidirectional marching crowd should be controlled to be under 5 /m2, which can produce optimal efficiency and have more possibility to ensure safety. The field study data given here provide a good example of a database for crowd studies.

Suggested Citation

  • Zhang, X.L. & Weng, W.G. & Yuan, H.Y. & Chen, J.G., 2013. "Empirical study of a unidirectional dense crowd during a real mass event," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(12), pages 2781-2791.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:12:p:2781-2791
    DOI: 10.1016/j.physa.2013.02.019
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    References listed on IDEAS

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    1. Armin Seyfried & Oliver Passon & Bernhard Steffen & Maik Boltes & Tobias Rupprecht & Wolfram Klingsch, 2009. "New Insights into Pedestrian Flow Through Bottlenecks," Transportation Science, INFORMS, vol. 43(3), pages 395-406, August.
    2. Dirk Helbing & Pratik Mukerji, "undated". "Crowd Disasters as Systemic Failures: Analysis of the Love Parade Disaster," Working Papers ETH-RC-12-010, ETH Zurich, Chair of Systems Design.
    3. Wenguo Weng & Hongyong Yuan & Weicheng Fan & Yuji Hasemi, 2007. "Experimental Validation Of Motor Schema-Based Cellular Automaton Model For Pedestrian Dynamics," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(06), pages 927-936.
    4. Steffen, B. & Seyfried, A., 2010. "Methods for measuring pedestrian density, flow, speed and direction with minimal scatter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1902-1910.
    5. Liu, Xuan & Song, Weiguo & Zhang, Jun, 2009. "Extraction and quantitative analysis of microscopic evacuation characteristics based on digital image processing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(13), pages 2717-2726.
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