Follower-Leader Concept in Microscopic Analysis of Pedestrian Movement in a Crowd
DOI:
https://doi.org/10.17815/CD.2020.111Keywords:
pedestrian dynamics, egress experiment, correlation, individual density, follow-the-leaderAbstract
This paper presents a microscopic analysis of factors influencing pedestrian movement and interactions with their surroundings for two considered modes: independent movement influenced only by the surrounding conditions and synchronized movement based on following another pedestrian. This study analyses which of these effects prevail in different phases of the movement. The results show that the significant value of correlation between pedestrian velocity and corresponding individual density is observed mainly during approaching the crowd. Contrarily, in the segment of pedestrian trajectory which corresponds to movement inside the crowd, correlation between the velocity of a follower and a leader is more important. This confirms that the pedestrian behaviour in a crowd is a complex field.References
M. Bukáček and P. Hrabák and M. Krbálek, “Microscopic Travel Time Analysis of Bottleneck
Experiments,” Transportmetrica A: Transport Science, 2018.
M. Bukáček and J. Vacková, “Evaluation of pedestrian density distribution with respect to the velocity
response,” in Traffic and Granular Flow, 2017, submitted.
B. Steffen and A. Seyfried, “Methods for Measuring Pedestrian Density: Flow, Speed and Direction
with Minimal Scatter,” Physica A 389(9): 1902 -- 1910, Elsevier, 2010.
A. Schadschneider and D. Chowdhury and K. Nishinari, Stochastic Transport in Complex Systems.
Elsevier, 2010.
J. Poryzcki and J. Was and L. Hedayatifar and F. Hassanibesheli and K. Kulakowski, “Velocity
correlations and spatial dependencies between neighbors in a unidirectional flow of pedestrians,”
Physical review E, 2017.
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Copyright (c) 2020 Jana Vacková, Marek Bukáček
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