  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 asses the quality of pedestrian flow models beyond average properties.
In this article we conduct functional PCA for the trajectories of pedestrians
passing through a bottleneck. 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 asses quality of pedestrian models.
