Assessment of models for pedestrian dynamics with functional principal component analysis

Chraibi, Mohcine; Ensslen, Tim; Gottschalk, Hanno; Seyfried, Armin; Saadi, Mohamed

doi:10.1016/j.physa.2016.01.058

Journal Article

FZJ-2016-01785

Assessment of models for pedestrian dynamics with functional principal component analysis

Chraibi, M. (Corresponding author)FZJ* ; Ensslen, T. ; Gottschalk, H. ; Saadi, M. ; Seyfried, A.FZJ*

2016
North Holland Publ. Co. Amsterdam

Physica / A 451, 475–489 (2016) [10.1016/j.physa.2016.01.058]

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Please use a persistent id in citations: doi:10.1016/j.physa.2016.01.058

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.

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