  In fluid mechanics, dimensionless numbers like the Reynolds number help
classify flows. We argue that such a classification is also relevant for crowd
flows by putting forward the dimensionless Intrusion and Avoidance
numbers.Using an extensive dataset, we show that these delineate regimes that
are characterized by distinct structural signatures, best probed in terms of
distances at low Avoidance number and times-to-collision at low Intrusion
number.These findings prompt a perturbative expansion of the agent-based
dynamics; the generic models thus obtained perform well in (and only in) the
regime in which they were derived.
