Modeling Stochastic Data Using Copulas for Applications in the Validation of Autonomous Driving

Lotto, Katrin; Nagler, Thomas und Radic, Mladjan (2022): Modeling Stochastic Data Using Copulas for Applications in the Validation of Autonomous Driving. In: Electronics, Bd. 11, Nr. 24, 4154

Abstract

The verification and validation processes of fully automated vehicles are 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. The resulting applications and possible extensions are discussed and explored.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Mathematik, Informatik und Statistik > Statistik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• Sprache: Englisch