Problem
Research questions and friction points this paper is trying to address.
Operational Design Domain
resilient autonomous systems
out-of-ODD scenarios
system reliability
Formally Guaranteed Control Adaptation for ODD-Resilient Autonomous Systems
🤖 AI Summary
This work addresses the limited reliability of autonomous driving systems operating beyond their designated Operational Design Domain (ODD) by proposing an adaptive control framework that integrates probabilistic modeling, dynamic model adaptation, and formal verification. The approach uniquely enables concurrent behavioral adjustment and quantifiable safety guarantees during control adaptation, substantially enhancing system resilience in previously unseen environments. Experimental results demonstrate that the proposed method effectively improves operational reliability in ODD-exceeding scenarios while preserving rigorous formal safety assurances.
📝 Abstract
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. Preliminary results demonstrate that our approach effectively increases system reliability by adapting its behaviour and providing formal guarantees even under unforeseen out-of-ODD situations.
Innovation
Methods, ideas, or system contributions that make the work stand out.
ODD-resilient
formal guarantees
control adaptation
probabilistic models
autonomous systems
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