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This feature examines the real-world friction between growing robotaxi fleets and emergency response efforts, stressing that current static regulations are struggling to keep pace with "discovery in motion."

On March 3, students from Del Valle High School stepped onto the campus of The University of Texas at Austin for a day that traded routine classroom lessons for discovery in motion. Hosted by the Oden Institute for Computational Engineering and Sciences, the visit immersed them in the world of robotics and computational science through hands-on demonstrations that turned abstract concepts into something they could see, touch, and test.

The Center for Autonomy, led by Ufuk Topcu, a core faculty member of the Oden Institute and a professor of aerospace engineering and engineering mechanics at UT's Cockrell School of Engineering, is entering a new era of growth and national leadership and expanding its research footprint while strengthening national collaborations.

Dr. Neel Bhatt, a postdoctoral researcher with the Center for Autonomy, was featured as an expert in recent coverage on autonomous vehicles in Texas. The segment draws on his expertise to underscore Texas’ growing role as a deployment hub for self-driving systems, with activity spanning both urban mobility and freight operations.

University of Texas researchers from the Center for Autonomy have proposed a new way to regulate autonomous-vehicle (AV) safety, pushing for adaptive, continuously updated standards. The project builds on Topcu’s 2023 research on “dynamic certifications,” or the ability for a system to learn while certifying.

University of Texas researchers from the Center for Autonomy have proposed a new way to regulate autonomous-vehicle (AV) safety, pushing for adaptive, continuously updated standards. The project builds on Topcu’s 2023 research on “dynamic certifications,” or the ability for a system to learn while certifying.

Postdoctoral Researcher, Dr. Neel Bhatt from The Center for Autonomy was recently featured on CBS Austin News for the Tech This Out segment, highlighting the Center's work on creating AI systems that can be reliably verified. Researchers are developing methods to ensure autonomous systems behave predictably, embedding constraints and testing frameworks so decisions can be explained and certified.

Autonomous systems deployed in real-world environments must operate safely despite uncertainty, adaptation, and changing conditions. Researchers in the Center for Autonomy at UT 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.