AVL

Our research addresses urgent challenges in high confidence testing of automotive systems due to on-going and anticipated introduction of advanced, connected, and autonomous vehicle technologies. We pursue the development of tools for maneuver and data optimization to determine test trajectories and scenarios to facilitate vehicle testing. Our approaches exploit game theoretic traffic interaction modeling to inform in-traffic relevant trajectories, model-free optimization to identify trajectories falsifying time domain specifications, and the development of Smart Black Box

Abstract:

This project addresses urgent challenges in high confidence validation and verification of automotive vehicles due to on-going and anticipated introduction of advanced, connected and autonomous vehicles into mass production. Since such vehicles operate across both physical and cyber domains, faults can occur in traditional physical components, in cyber components (i.e., algorithms, processors, networks, etc.), or in both.