Formally Guaranteed Control Adaptation for ODD-Resilient Autonomous Systems

Ensuring reliable performance in situations outside the Operational Design Domain (ODD) remains a primary challenge in devising resilient autonomous systems. We explore this challenge by introducing an approach for adapting probabilistic system models to handle out-of-ODD scenarios while, in parallel, providing quantitative guarantees. Our approach dynamically extends the coverage of existing system situation capabilities, supporting the verification and adaptation of the system's behaviour under unanticipated situations at runtime. Preliminary results demonstrate that our approach effectively increases system reliability by adapting its behaviour and providing formal quantitative guarantees even under unforeseen out-of-ODD situations.