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@ARTICLE{Chraibi:283362,
author = {Chraibi, Mohcine and Ensslen, Tim and Gottschalk, Hanno and
Saadi, Mohamed and Seyfried, Armin},
title = {{A}ssessment of models for pedestrian dynamics with
functional principal component analysis},
journal = {Physica / A},
volume = {451},
issn = {0378-4371},
address = {Amsterdam},
publisher = {North Holland Publ. Co.},
reportid = {FZJ-2016-01785},
pages = {475–489},
year = {2016},
abstract = {Many agent based simulation approaches have been proposed
for pedestrian flow. As such models are applied e.g. in
evacuation studies, the quality and reliability of such
models is of vital interest. Pedestrian trajectories are
functional data and thus functional principal component
analysis is a natural tool to assess the quality of
pedestrian flow models beyond average properties. In this
article we conduct functional Principal Component Analysis
(PCA) for the trajectories of pedestrians passing through a
bottleneck. In this way it is possible to assess the quality
of the models not only on basis of average values but also
by considering its fluctuations. We benchmark two agent
based models of pedestrian flow against the experimental
data using PCA average and stochastic features. Functional
PCA proves to be an efficient tool to detect deviation
between simulation and experiment and to assess quality of
pedestrian models.},
cin = {JSC},
ddc = {500},
cid = {I:(DE-Juel1)JSC-20090406},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511)},
pid = {G:(DE-HGF)POF3-511},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000373420800044},
doi = {10.1016/j.physa.2016.01.058},
url = {https://juser.fz-juelich.de/record/283362},
}