Between races, Hildebrand is helping students at Stanford University develop a self-driving Audi TTS race car -- and it's learning quickly.
"The Audi is already within 1 percent of my lap time," Hildebrand said.
However, he added, the car still isn't capable of learning on the fly as well as humans, a skill some engineers are trying to develop by pushing the technology to the limits in a controlled environment.
In April, Schachter, who also competes in amateur human-driven race leagues with his Spec Miata, hosted the second annual Self Racing Cars at Thunderhill Raceway Park in northern California. Companies such as Comma.ai and AutonomouStuff, and student teams, including one from online classroom Udacity, participated.
The event wasn't a race in the traditional sense. Each team's car did fast laps on the track by itself. Out of the eight teams, just four cars were able to complete a lap. The fastest lap was just under 3 minutes 38 seconds -- a human-driven lap at Thunderhill is typically around 1 minute 45 seconds, according to Schachter.
"It's very casual," Schachter said. "Teams are building and testing interesting things."
Teams have been using the competition as a way to test specific features of their technology and learn from other groups trying different strategies, he said. Like traditional racing, which fostered the development of now common features such as rearview mirrors, innovation is born from the desire to compete.