From Crowd Dynamics to Crowd Safety: a Video-Based Analysis

By Anders Johansson, Dirk Helbing, Habib Z. Al-Abideen, Salim Al-Bosta. Advances in Complex Systems, 2008

354 citations recorded by the source corpus.

The study of crowd dynamics is interesting because of the various self-organization phenomena resulting from the interactions of many pedestrians, which may improve or obstruct their flow. Besides formation of lanes of uniform walking direction and oscillations at bottlenecks at moderate densities, it was recently discovered that stop-and-go waves [D. Helbing et al., Phys. Rev. Lett. 97 (2006) 168001] and a phenomenon called "crowd turbulence" can occur at high pedestrian densities [D. Helbing et al., Phys. Rev. E 75 (2007) 046109]. Although the behavior of pedestrian crowds under extreme conditions is decisive for the safety of crowds during the access to or egress from mass events as well as for situations of emergency evacuation, there is still a lack of empirical studies of extreme crowding. Therefore, this paper discusses how one may study high-density conditions based on suitable video data. This is illustrated at the example of pilgrim flows entering the previous Jamarat Bridge in Mina, 5 kilometers from the Holy Mosque in Makkah, Saudi-Arabia. Our results reveal previously unexpected pattern formation phenomena and show that the average individual speed does not go to zero even at local densities of 10 persons per square meter. Since the maximum density and flow are different from measurements in other countries, this has implications for the capacity assessment and dimensioning of facilities for mass events. When conditions become congested, the flow drops significantly, which can cause stop-and-go waves and a further increase of the density until critical crowd conditions are reached. Then, "crowd turbulence" sets in, which may trigger crowd disasters. For this reason, it is important to operate pedestrian facilities sufficiently below their maximum capacity and to take measures to improve crowd safety, some of which are discussed in the end.

Subfields: Building and Construction, Control and Systems Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/aa875264314115d24af5d235cb79b310b1d00ae6

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Citations in the corpus

Crowded Scene Analysis: A Survey (2015, methodology): “In this paper, combined with previous studies, we will elaborate the key aspects of crowded scene analysis in automated video surveillance.”
Predictability of population displacement after the 2010 Haiti earthquake (2012, background): “Despite a number of studies on human mobility patterns during small-scale, short-term emergencies such as crowd panics (7, 8) and fires (9, 10), research on the dynamics of population mobility during large-scale disasters such as earthquakes, tsunamis, floods, and hurricanes has been limited (11).”
Methods for measuring pedestrian density, flow, speed and direction with minimal scatter (2009, background): “(a): Total run; (b): ‘Quasi’ stationary state t = [20, 32] s; (c):Ds , 〈Ds〉space and 〈Ds〉time; (d): Ds , DV and 〈Ds〉time .”
Crowd disasters as systemic failures: analysis of the Love Parade disaster (2012, background): “As a consequence, an uncontrollable kind of collective dynamics occurs in the crowd, which is called ‘crowd turbulence’ or ‘crowd quake’ [16,172].”
Human mobility: Models and applications (2017, methodology): “high density regimes, such as those occurring in videos taken of the disaster of the Jamarat Bridge in the Hajj pilgrimage of 2006, the trajectories of single pedestrians become turbulent [227, 232] (Fig.”
The spatial variability of vehicle densities as determinant of urban network capacity (2010, background): “…& Gärling 1992; Biham et al. 1992; Nagel & Schreckenberg 1992; Schadschneider & Schrenkenberg 1993; Daganzo 1994; Herrmann 1996; Klar & Wegener 1998; Charypar & Nagel 2005; Herty et al. 2006; Bretti et al. 2007; Lämmer et al. 2007; Ma & Lebacque 2007; De Martino et al. 2009; Padberg et al. 2009).”