In the days leading up to this year's IndyCar Java House Grand Prix of Monterey, eight race cars sped around one of the most famous road courses in the United States: the WeatherTech Raceway Laguna Seca. But there were no celebrity drivers in the cockpits. These were self-driving, autonomous vehicles programmed by university teams and aided by AI, whipping around curves and flying down Laguna Seca's straightaways, sometimes at speeds approaching 150 mph. The newest team of the bunch, the Caltech Racer, laid down what commentators described as an aggressively fast performance.
The July 24 event was part of the Indy Autonomous Challenge (IAC), an ongoing multiyear effort kicked off in 2019 by Indianapolis-based nonprofit Energy Systems Network "to challenge university students around the world to imagine, invent and prove a new generation of automated vehicle software to run fully autonomous racecars and inspire the next generation of STEM talent," according to the IAC website.
There are now 10 active teams in the challenge, representing universities and public-private partnerships from around the world. The IAC supplies each team with a "drive-by-wire" IAC AV-24 car complete with a suite of sensors. The big difference from team to team lies within their computing stacks-the advanced control and autonomy algorithms and intelligence systems run by computers that give the race cars the ability to perceive the novel environment and make decisions about things like acceleration, braking, and navigation as they tear around a track.
