Philip Koopman

Associate Professor Carnegie Mellon University

  • Pittsburgh PA

Philip Koopman is actively involved with AV policy and standards as well as more general embedded system design and software quality.

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Carnegie Mellon University

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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 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. He originated the UL 4600 standard for autonomous system safety issued in 2020. In 2022 he was named to the National Safety Council's Mobility Safety Advisory Group. In 2023 he was named the International System Safety Society's Educator of the Year. He is the author of the books: Understanding Checksums & Cyclic Redundancy Codes (2024), How Safe is Safe Enough: measuring and predicting autonomous vehicle safety (2022), The UL 4600 Guidebook (2022) and Better Embedded System Software (2010).

Areas of Expertise

Software Engineering
Autonomous Vehicle Safety
Embedded Systems
Safety-Critical Computer Systems
Automotive Computing

Media Appearances

Driverless Semi Trucks Are Here, With Little Regulation and Big Promises

The New York Times  online

2025-05-27

“This technology is really good at things it’s practiced, and really bad at things it has never seen before. From a safety point of view, nobody knows how it’s going to turn out,” said Philip Koopman (College of Engineering) about Aurora Innovation's driverless semi trucks in Texas.

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Elon Musk’s Tesla moves to launch free self-driving taxi service in California

The Washington Post  online

2025-03-27

esla is preparing to launch a taxi service in California that could eventually shuttle passengers in autonomous vehicles around the state, if a recent permit request is approved. “Getting the permits in place is a due diligence thing,” said Philip Koopman (College of Engineering). “The real question is, are these things going to be safe on the road?”

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Uber's CEO says he wants to find a way to work with Tesla because 'no one wants to compete against Tesla or Elon, if you can help it'

MSN  online

2025-02-14

Uber CEO Dara Khosrowshahi said he’d rather collaborate with Elon Musk than compete after Tesla announced its paid robotaxi service launching this summer. Phil Koopman (College of Engineering) noted that Tesla may face challenges securing federal approval for its steering wheel-free Cybercab and would also need state-level approvals to expand its robotaxi network.

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Industry Expertise

Automotive
Computer Software
Education/Learning
Research

Education

Rensselaer Polytechnic Institute

B.S.

Electrical, Computer, and System Engineering

1982

Rensselaer Polytechnic Institute

M.S.

Electrical, Computer, and System Engineering

1982

Carnegie Mellon University

Ph.D.

Electrical and Computer Engineering

1989

Articles

Challenges in Autonomous Vehicle Testing and Validation

SAE International Journal of Transportation Safety

2016

Software testing is all too often simply a bug hunt rather than a well-considered exercise in ensuring quality. A more methodical approach than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. The ISO 26262 development V process sets up a framework that ties each type of testing to a corresponding design or requirement document, but presents challenges when adapted to deal with the sorts of novel testing problems that face autonomous vehicles.

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Autonomous Vehicle Safety: An Interdisciplinary Challenge

IEEE Intelligent Transportation Systems Magazine

2017

Ensuring the safety of fully autonomous vehicles requires a multi-disciplinary approach across all the levels of functional hierarchy, from hardware fault tolerance, to resilient machine learning, to cooperating with humans driving conventional vehicles, to validating systems for operation in highly unstructured environments, to appropriate regulatory approaches. Significant open technical challenges include validating inductive learning in the face of novel environmental inputs and achieving the very high levels of dependability required for full-scale fleet deployment.

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UL 4600: What to Include in an Autonomous Vehicle Safety Case

Computer

2023

Autonomous vehicles (AVs) will not see widespread use until we can be sure that they are acceptably safe. That remains a big challenge, but robust support from safety standards can help. To illustrate what is involved in ensuring AV safety, this article provides an overview of the approach taken by the ANSI/UL 4600 AV safety standard.1

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