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Autonomous systems deployed in real-world environments must operate safely despite uncertainty, adaptation, and changing conditions. Researchers in the Center for Autonomy at The University of Texas at Austin are developing dynamic certification frameworks that continuously evaluate system behavior instead of relying solely on static pre-deployment testing. The goal is to provide more robust safety assurance for autonomous vehicles and other robotic systems as they are increasingly deployed outside controlled settings.

Ensuring the safety of autonomous systems requires certification methods that can keep pace with systems that learn, update, and operate in changing environments. Researchers at The University of Texas at Austin and collaborating institutions are developing new frameworks that move beyond traditional static certification approaches. The multi-university effort integrates expertise in controls, formal methods, machine learning, human factors, robotics, and systems engineering to study scalable methods for assuring safety in real-world autonomous systems.

John‑Paul Clarke, a professor of aerospace engineering at The University of Texas at Austin, was elected to the National Academy of Engineering. Clarke is recognized for pioneering aircraft arrival procedures that allow planes to glide during descent, reducing fuel use, emissions, and noise, and now used at major airports worldwide. His work in aircraft trajectory optimization and air traffic operations has helped improve the efficiency and environmental performance of modern aviation systems.