  Verification and validation of fully automated vehicles is linked to an
almost intractable challenge of reflecting the real world with all its
interactions in a virtual environment. Influential stochastic parameters need
to be extracted from real-world measurements and real-time data, capturing all
interdependencies, for an accurate simulation of reality. A copula is a
probability model that represents a multivariate distribution, examining the
dependence between the underlying variables. This model is used on drone
measurement data from a roundabout containing dependent stochastic parameters.
With the help of the copula model, samples are generated that reflect the
real-time data. Resulting applications and possible extensions are discussed
and explored.
