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"AI" and Autonomous Vehicle Safety (Invited Presenter / Phil Koopman)

Date and Time: Wednesday, July 12, 2023: 1:30 PM - 5:00 PM

Philip Koopman 

Associate Professor, Carnegie Mellon University
@PhilKoopman

Presentation Description

This talk gives a high level overview of AI and machine learning, including applications to image classification and generative AI. Advantages for using this technology include training based on examples, more scalable development, and impressive effectiveness compared to older techniques. Challenges include a lack of deep understanding, vulnerability to surprises, and fundamental challenges with testing-only approaches to safety assurance. The talk ends with four questions to ask manufacturers about their AV safety approach.

Speaker Biography

Prof. Philip Koopman is an internationally recognized expert on Autonomous Vehicle (AV) safety whose work in that area spans over 25 years. He is also actively involved with AV policy and standards as well as more general embedded system design and software quality. His pioneering research work includes software robustness testing and run time monitoring of autonomous systems to identify how they break and how to fix them. He has extensive experience in software safety and software quality across numerous transportation, industrial, and defense application domains including conventional automotive software and hardware systems. He was the principal technical contributor to the UL 4600 standard for autonomous system safety issued in 2020. He is a faculty member of the Carnegie Mellon University ECE department where he teaches software skills for mission-critical systems. In 2018 he was awarded the highly selective IEEE-SSIT Carl Barus Award for outstanding service in the public interest for his work in promoting automotive computer-based system safety. In 2022 he was named to the National Safety Council's Mobility Safety Advisory Group. He is the author of the books: Better Embedded System Software (2010), How Safe is Safe Enough: measuring and predicting autonomous vehicle safety (2022), and The UL 4600 Guidebook (2022).

Presentation File