Stanford’s self-driving Audi TTS, Shelley, hit 120 mph on a recent track test. Combined with new research on professional drivers’ brain activity, the car’s performance could get even better.

Shelley is the product of collaboration between Stanford’s Dynamic Design Lab, led by mechanical engineering Associate Professor Chris Gerdes, and the Volkswagen Electronics Research Lab.

There’s very little difference between the path a professional driver takes around the course and the route charted by Shelley’s algorithms. And yet, the very best human drivers are still faster around the track, if just by a few seconds.

“Human drivers are OK with the car operating in a comfortable range of states,” Gerdes said. “We’re trying to capture some of that spirit.”

Gerdes and his students will have the opportunity to do just that Aug. 17-19 at the Rolex Monterey Motorsports Reunion races at the Laguna Seca Raceway. The group has enlisted two professional drivers to wear a suite of biological sensors as they race around the track; among other things, the sensors will record the drivers’ body temperature and heart rate. And in an effort to determine which driving maneuvers require the most concentration and brainpower, scalp electrodes will register drivers’ brain activity as they race against other humans.

The biological data will be paired with mechanical performance data from the car – a 1966 Ford GT40, the only American-built automobile to finish first overall at the 24 Hours of Le Mans race – which Stanford has kitted out with feedback sensors similar to those on Shelley.

“We need to know what the best drivers do that makes them so successful,” Gerdes says. “If we can pair that with the vehicle dynamics data, we can better use the car’s capabilities.”