Philip Koopman
Associate Professor | Carnegie Mellon University
Pittsburgh, PA, UNITED STATES
Philip Koopman is actively involved with AV policy and standards as well as more general embedded system design and software quality.
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 (5)
Software Engineering
Autonomous Vehicle Safety
Embedded Systems
Safety-Critical Computer Systems
Automotive Computing
Media Appearances (9)
On roads teeming with robotaxis, crossing the street can be harrowing
Washington Post online
2024-12-30
Phil Koopman, a Carnegie Mellon University professor who conducts research on autonomous-vehicle safety, said the Waymo cars had no excuse not to stop. “A person making the decision not to yield to a pedestrian in a crosswalk is acting with the knowledge of potential penalties, ranging from a traffic ticket, to a civil tort lawsuit for injuries, to potential jail time,” Koopman said. “In California, a computer driver can’t even get a meaningful traffic ticket yet and is certainly not worried about going to jail.”
Waymo’s Robot Taxis Are Almost Mainstream. Can They Now Turn a Profit?
New York Times online
2024-09-04
“Waymo has not had the big crash yet,” said Phil Koopman, an engineering professor at Carnegie Mellon University who specializes in autonomous vehicles. “I don’t know if they will have a big, embarrassing, problematic crash, and based upon the data, they don’t know, either.”
Tesla was in 'full self-driving' mode when car hit, killed motorcyclist on SR 522 in April
MSN online
2024-07-30
Phil Koopman, a professor at Carnegie Mellon University who studies autonomous vehicle safety, said he doesn't see Tesla running robotaxis without human drivers on nearly all roads for another decade. The safety record Musk cites is based on having a human driver supervise the automated system, he said. “Unless you have data showing that the driver never has to supervise the automation, then there's no basis for claiming they're going to be acceptably safe,” he said.
GM's Cruise to start testing robotaxis in Phoenix area with human safety drivers on board
MSN online
2024-05-13
Phil Koopman, a professor at Carnegie Mellon University who studies autonomous vehicle safety, said Phoenix is a good choice for Cruise to restart its operations, in part because it has less stringent regulations than the company faced in San Francisco.
Tesla's bet on robotaxis is a long way from paying off
Reuters online
2024-04-06
"Everyone else has found out that what they thought was a two or three-year project turns out to be a 10 or 20-year project," said Philip Koopman, a Carnegie Mellon University professor working on autonomous vehicle safety. "Tesla's found that out too."
Despite fear of self-driving vehicles, this expert says their expansion is inevitable
KJZZ online
2024-03-20
ROY: Well, one of the biggest problems is that there are very few experts if any who aren't working at these companies. But among the people who've looked at the data are people like Professor Philip Koopman at CMU, who himself is quite a skeptic, has acknowledged that, you know, some of Waymo recent data indicates both progress and that they are even with human-driven ride-hail drivers, if not slightly better. So what's critical here is that there is progress and demonstrable improvement.
AV Safety Expert Proposes a New Classification for Autonomy Levels
autoevolution online
2022-02-07
In any discussion about autonomous cars, you may have already heard about Level 2, 3, 4, and 5. They refer to the classifications made by SAE J3016, a document that tried to establish what autonomous-driving cars are expected to do. Philip Koopman thinks these classifications are only helpful from an engineering point of view, not to regular drives. This is why the AV safety expert decided to propose a new classification system.
Will state-by-state regulation of self-driving vehicles work -- and keep people safe?
ABC News online
2022-01-31
Philip Koopman, a professor at Carnegie Mellon University, warned lawmakers in an op-ed in the Pittsburgh Post-Gazette that the bill's current language lacks specific guidance in several areas.
Gaming while driving: Tesla allows it, Mercedes does recall
The Detroit News online
2021-12-10
“MB is following the regulatory rules as they are supposed to – in sharp contrast to what we’ve been seeing from Tesla,” said Philip Koopman, a professor of electrical and computer engineering at Carnegie Mellon University. If NHTSA doesn’t take action against Tesla, the agency will have one standard for Tesla and another for Mercedes and other automakers, Koopman said.
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Industry Expertise (4)
Automotive
Computer Software
Education/Learning
Research
Education (3)
Carnegie Mellon University: Ph.D., Electrical and Computer Engineering 1989
Rensselaer Polytechnic Institute: M.S., Electrical, Computer, and System Engineering 1982
Rensselaer Polytechnic Institute: B.S., Electrical, Computer, and System Engineering 1982
Links (3)
Articles (5)
Redefining Safety for Autonomous Vehicles
Computer Safety, Reliability, and Security2024 Existing definitions and associated conceptual frameworks for computer-based system safety should be revisited in light of real-world experiences from deploying autonomous vehicles. Current terminology used by industry safety standards emphasizes mitigation of risk from specifically identified hazards, and carries assumptions based on human-supervised vehicle operation.
Breaking the Tyranny of Net Risk Metrics for Automated Vehicle Safety
Safety-Critical Systems eJournal2024 An inquiry into how safe might be “safe enough” for automated vehicle technology must go far beyond the superficial “safer than a human driver” metric to yield an answer that will be workable in practice. Issues include the complexities of creating a like-for-like human driver baseline for comparison, avoiding risk transfer despite net risk reduction, avoiding negligent computer driver behaviour, conforming to industry consensus safety standards as a basis to justify predictions of net safety improvement, avoiding regulatory problems with unreasonably dangerous specific features despite improved net safety, and avoiding problematic ethical and equity outcomes.
UL 4600: What to Include in an Autonomous Vehicle Safety Case
Computer2023 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
Autonomous Vehicle Safety: An Interdisciplinary Challenge
IEEE Intelligent Transportation Systems Magazine2017 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.
Challenges in Autonomous Vehicle Testing and Validation
SAE International Journal of Transportation Safety2016 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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