An interdisciplinary research team from the University of Waterloo is building systems that mimic the human brain to improve the power efficiency and performance of artificial neural networks like those used in autonomous vehicle (AV) technology.
Dr. Chris Eliasmith, a professor jointly appointed to the Departments of Systems Design Engineering and Philosophy, leads Waterloo’s Computational Neuroscience Research Group (CNRG), which focuses on replicating human brain function to create more efficient and powerful artificial systems.
In a collaboration with Mercedes-Benz, CNRG will apply their neuromorphic computing expertise — designing and developing software and hardware development designed to mimic how the brain works — to making autonomous vehicle technology more efficient and safer.
“The brain is by far the best autonomous system we know,” said Eliasmith. “It operates with unmatched power efficiency, using only about 20 watts. Computers are smart and AI language models like ChatGPT are very human-like, but they use at least 1000 times more power, which makes them impractical for extensive mobile use.
"If we can take what the brain does naturally and apply it to AVs, we can build autonomous cars that not only think faster and better but also conserve battery power, allowing for better overall performance," Eliasmith added.
Self-driving cars must navigate, make decisions and react in real time to changing environments. AV systems struggle with complex tasks like “scene understanding”, for example, the use of body language and eye contact to interpret whether a pedestrian is about to cross the road. To improve how an AV performs complex tasks such as its response to a critical situation, requires supplying its AI system with a lot of computing power. This increased drain on the vehicle’s battery could also have an impact on its driving range.
“Our research using neuromorphic computers has already demonstrated a 10 to 100 times reduction in the amount of power required to do control and perception tasks without any loss of accuracy, and often with improvements,” Eliasmith said.
Go to Using our brains to advance the power and performance of AVs for the full story.