Long-range dependence and time-clustering behavior in pedestrian movement patterns in stampedes: The Love Parade case-study

Author:  Lian, L. P., Song, W. G., Richard, Y. K. K., Ma, J., Telesca, L.

Journal: Physica a-Statistical Mechanics and Its Applications

DOI: 10.1016/j.physa.2016.11.048

Keywords: Crowd dynamics, Detrended fluctuation analysis, Coefficient of variation, detrended fluctuation analysis, cortical-neurons, dynamics, series, crowd, model, Physics

Abstract:

Pedestrian stampede happened more and more often during these years, such as Love Parade disaster in Germany 2010, trampling in Shanghai bund 2014 and crowd stampede in pilgrimages. Love Parade disaster 2010 stands out for well recorded videos, which are HD quality and available for researchers. There were totally seven surveillance cameras capturing the whole festival progress and the video we study is just before the disaster happened. Pedestrian motion was special and a small disturbance would lead the group to an avalanche in this kind of critical situation. Here we focus on the individual movement pattern. The trajectories of each pedestrian involved were extracted by a mean-shift algorithm. We analyzed the space-time patterns of the pedestrians involved in the Love Parade stampede by using the detrended fluctuation analysis and the coefficient of variation. Our results reveal that the pedestrians' movement in crowd-quakes is persistent in space, globally time-clusterized but locally regular or quasi-periodic behavior. Pedestrian movement was treated as stop and go state by point process-based representation. When the threshold increases, this means that the go state is longer and pedestrians keep on walking in several consecutive time frames; this is difficult in crowded situations and lead to special time-clustering behavior of the sequence of go events. The study reveals pedestrian motion characteristics in critical situations, which will enhance the understanding of pedestrian behaviors and supply early warning features for not only Love Parade Disaster, but also other similar large events. (C) 2016 Published by Elsevier B.V.