Philip Koopman
Associate Professor, Electrical and Computer Engineering
Associate Professor, Electrical and Computer Engineering
Philip Koopman is an associate professor in Electrical and Computer Engineering with additional affiliations with the Institute for Software Research and the Robotics Institute. He leads research on safe and secure embedded systems and teaches cost-effective embedded system design techniques. He has over 20 years of experience with autonomous vehicle safety, dating back to the Carnegie Mellon Navlab team and the Automated Highway Systems (AHS) program.
Koopman's most recent projects include using stress testing and run time monitoring to ensure safety for a variety of vehicle and robotic applications for research, industry, and defense applications. He has additional experience with automotive and industrial functional safety, including testifying as an expert in vehicle safety class action litigation and consulting to NHTSA. He is a co-founder of Edge Case Research, which provides tools and services for autonomous vehicle testing and safety validation.
His pre-university career includes experience as a US Navy submarine officer, an embedded CPU designer at Harris Semiconductor, and an embedded system architect at United Technologies. He is a senior member of IEEE and
1989 Ph.D., Computer Engineering, Carnegie Mellon University
1982 Master of Engineering, Computer and Systems Engineering, Rensselaer Polytechnic Institute
1982 BS, Computer and Systems Engineering, Rensselaer Polytechnic Institute
EE Times
ECE’s Phil Koopman comments in EE Times on the challenges of testing self-driving cars.
Semiconductor Engineering
On-chip networks play a big role in artificial intelligence and machine learning. They are often used in self-driving cars to complete complex, system-level operations, such as recognizing pedestrians and traffic lights. ECE’s Phil Koopman is working on the UL 4600 spec, a standard meant to ensure the reliability of these on-chip networks and the safety of autonomous cars.
Bloomberg
ECE’s Philip Koopman was interviewed by Bloomberg in an article about car crashes caused by Tesla vehicles. The article explains that sensors struggle when the vehicle in front changes lanes, known as the cut-out scenario. “The cut-out is one of the hardest scenarios,” Koopman said. “There’s no question about that.”
Communications of the ACM
ECE’s Philip Koopman was quoted by Communications of the ACM about the multiple challenges for self-driving cars. Many problems arise when these vehicles encounter unanticipated circumstances and try to transfer control to humans.
Pittsburgh Post-Gazette
ECE’s Phil Koopman is skeptical of Tesla’s bold claims of fully driverless cars in the near future: “The rabbit hole goes pretty deep if you want to make that [full self-driving] argument.”
WIRED
ECE’s Philip Koopman is helping to create the first set of safety standards for autonomous vehicles.
The Atlantic
In The Atlantic’s article about the future of self-driving cars, ECE’s Phil Koopman commented on how safety might impact the technology’s future.
Axios
ECE’s Philip Koopman was recently quoted in Axios’ autonomous vehicle newsletter praising Waymo’s decision to err on the side of caution in comparison to many of its AV competitors.
The Verge
Apple’s first ever self-driving car crash occurred in Sunnyvale, CA, when a human-driven car rear-ended the self-driving car, just one of several accidents involving a human driver rear-ending a stationary or slow-moving self-driving car. ECE’s Philip Koopman explained that a possible reason was that the cars and humans drive in different ways.
Axios
ECE’s Philip Koopman recently authored a piece on regulators’ focus on human operators as the key to ensuring safe testing of autonomous vehicles.
Pittsburgh Tribune-Review
ECE’s Raj Rajkumar and Philip Koopman were both quoted in a recent article in the Pittsburgh Tribune-Review on PennDOT’s new autonomous vehicle guidelines.
TechRadar
ECE’s Philip Koopman commented for TechRadar on the challenges that will need to be overcome in order to achieve safe, widespread deployment of self-driving vehicles.