  In this work we investigate the behaviour of a human crowd in a cross-flow.
We first analyse the results of a set of controlled experiments in which
subjects were divided into two groups, in such a way to explore different
density settings, and asked to walk through the crossing area. We study the
results of the experiment by analysing, along with traditional indicators such
as density and velocity, also walking and body orientation, studying how these
microscopic observables are influenced by density. Furthermore, we report a
preliminary but quantitative analysis on the emergence of self-organising
stripes in the crossing area.
  We also try to reproduce the empirical results using a hierarchy of models,
which differ in the details of the body shape (using a disk-shaped body vs a
more realistic elliptical shape) and in how collision avoiding is performed
(using only information regarding "centre of mass" distance and velocity, or
actually introducing body shape information). We verified that the most
detailed model (i.e., using body shape information and an elliptical body)
outperforms in a significant way the simplest one (using only centre of mass
distance and velocity, and disk-shaped bodies). Furthermore, we observed that
if elliptical bodies are introduced without using such information in collision
avoidance, the performance of the model is relatively poor. Nevertheless, the
difference between the different models is relevant only in describing the
"tails" of the observable distributions, suggesting that the more complex
models could be of practical use only for describing high density settings. We
also verified that "stripe formation" emerges in all models.
