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Real-life, out-of-laboratory, measurements of pedestrian movements allowextensive and fully-resolved statistical analyses. However, data acquisition inreal-life is subjected to the wide heterogeneity that characterizes crowd flowsover time. Disparate flow conditions, such as co-flows and counter-flows at lowand at high pedestrian densities, typically follow randomly one another. Whenanalysing the data in order to study the dynamics and behaviour of pedestriansit is crucial to be able disentangle and to properly select (query) data fromstatistically homogeneous flow conditions in order to avoid spurious statisticsand to enable qualitative comparisons. In this paper we extend our previousanalysis on the asymmetric pedestrian dynamics on a staircase landing, where wecollected a large statistical database of measurements from ad hoc continuousrecordings. This contribution has a two-fold aim: first, method-wise, wediscuss two possible approaches to query experimental datasets for homogeneousflow conditions. For given flow conditions, we can either agglomeratemeasurements on a time-frame basis (Eulerian queries) or on a trajectory basis(Lagrangian queries). Second, we employ these two different perspectives tofurther explore asymmetries in the pedestrian dynamics in our measurement site.We report cross-comparisons of statistics of pedestrian positions, velocitiesand accelerations vs. flow conditions as well as vs. Eulerian or Lagrangianapproach.

Eulerian vs. Lagrangian analyses of pedestrian dynamics asymmetries in a staircase landing