Abstract:In this work, we propose a compositional data-driven approach for the formal estimation of collision risks for autonomous vehicles (AVs) with black-box dynamics acting in a stochastic multi-agent framework. The proposed approach is based on the construction of sub-barrier certificates for each stochastic agent via a set of data collected from its trajectories while providing a-priori guaranteed confidence on the datadriven estimation. In our proposed setting, we first cast the original collision risk problem f… Show more
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