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@ARTICLE{Kpper:1005495,
author = {Küpper, Mira and Seyfried, Armin},
title = {{I}dentification of social groups and waiting pedestrians
at railway platforms using trajectory data},
journal = {PLOS ONE},
volume = {18},
number = {3},
issn = {1932-6203},
address = {San Francisco, California, US},
publisher = {PLOS},
reportid = {FZJ-2023-01501},
pages = {e0282526 -},
year = {2023},
abstract = {To investigate the impact of social groups on waiting
behaviour of passengers at railway platforms a method to
identify social groups through the monitoring of distances
between pedestrians and the stability of those distances
over time is introduced. The method allows the recognition
of groups using trajectories only and thus opens up the
possibility of studying crowds in public places without
constrains caused by privacy protection issues. Trajectories
from a railway platform in Switzerland were used to analyse
the waiting behaviour of passengers in dependence of waiting
time as well as the size of social groups. The analysis of
the trajectories shows that the portion of passengers
travelling in groups reaches up to $10\%$ during the week
and increases to $20\%$ on the weekends. $60\%$ of the
groups were pairs, larger groups were less frequent. With
increasing group size, the mean speed of the members
decreases. Individuals and pairs often choose waiting spots
at the sides of the stairs and in vicinity of obstacles,
while larger groups wait close to the platform entries. The
results indicate that passengers choose waiting places
according to the following criteria and ranking: shortest
ways, direction of the next intended action, undisturbed
places and ensured communication. While individual
passengers often wait in places where they are undisturbed
and do not hinder others, the dominating comfort criterion
for groups is to ensure communication. The results regarding
space requirements of waiting passengers could be used for
different applications. E.g. to enhance the level of service
concept assessing the comfort of different types of users,
to avoid temporary bottlenecks to improve the boarding and
alighting process or to increase the robustness of the
performance of railway platforms during peak loads by
optimising the pedestrian distribution.},
cin = {IAS-7},
ddc = {610},
cid = {I:(DE-Juel1)IAS-7-20180321},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511) / Verbundprojekt:
Crowd-Management in Verkehrsinfrastrukturen (CroMa) -
Teilvorhaben: Experimentelle Untersuchungen zum Fußverkehr
und Crowd-Management (13N14533)},
pid = {G:(DE-HGF)POF4-5111 / G:(BMBF)13N14533},
typ = {PUB:(DE-HGF)16},
pubmed = {36920891},
UT = {WOS:000954452200058},
doi = {10.1371/journal.pone.0282526},
url = {https://juser.fz-juelich.de/record/1005495},
}