The excitement of auto racing comes from split-second decisions and daring passes by fearless drivers. Imagine that scene, but without the driver — the car alone, guided by the invisible hand of artificial intelligence. Can the rush of racing unfold without a driver steering the course? It turns out that it can.
Enter autonomous racing, a field that’s not just about high-speed competition but also pushing the boundaries of what autonomous vehicles can achieve and improving their safety.
Over a century ago, at the dawn of automobiles, as society shifted from horse-drawn to motor-powered vehicles, there was public doubt about the safety and reliability of the new technology. Motorsport racing was organised to showcase the technological performance and safety of these horseless carriages. Similarly, autonomous racing is the modern arena to prove the reliability of autonomous vehicle technology as driverless cars begin to hit the streets.
Autonomous racing’s high-speed trials mirror the real-world challenges that autonomous vehicles face on streets: adjusting to unexpected changes and reacting in fractions of a second. Mastering these challenges on the track, where speeds are higher and reaction times shorter, leads to safer autonomous vehicles on the road.
F1tenth has also emerged as an engaging and accessible gateway for students to delve into robotics research. Over the years, I’ve reached thousands of students via my courses and online lecture series, which explains the process of how to build, drive and autonomously race these vehicles.
Getting real
Today, the scope of our research has expanded significantly, advancing from small-scale models to actual autonomous Indy cars that compete at speeds of upward of 150 mph (241 kph), executing complex overtaking manoeuvres with other autonomous vehicles on the racetrack. The cars are built on a modified version of the Indy NXT chassis and are outfitted with sensors and controllers to allow autonomous driving. Indy NXT race cars are used in professional racing and are slightly smaller versions of the Indy cars made famous by the Indianapolis 500.
Cavalier Autonomous Racing, University of Virginia, CC BY-ND
The gritty reality of racing these advanced machines on real racetracks pushes the boundaries of what autonomous vehicles can do. Autonomous racing takes the challenges of robotics and AI to new levels, requiring researchers to refine our understanding of how machines perceive their environment, make safe decisions and control complex manoeuvres at a high speed where traditional methods begin to falter.
Precision is critical, and the margin for error in steering and acceleration is razor-thin, requiring a sophisticated grasp and exact mathematical description of the car’s movement, aerodynamics and drivetrain system. In addition, autonomous racing researchers create algorithms that use data from cameras, radar and lidar, which is like radar but with lasers instead of radio waves, to steer around competitors and safely navigate the high-speed and unpredictable racing environment.
My team has shared the world’s first open dataset for autonomous racing, inviting researchers everywhere to join in refining the algorithms that could help define the future of autonomous vehicles.