The gritty reality of racing without drivers teaches us a lot about the future of autonomous cars. 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 about the safety and reliability of the new technology. Motorsport racing was organized to 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. I am a computer science professor who , and I lead the team at the University of
Virginia. The team competes in the , a global contest where universities pit fully autonomous Indy race cars against each other. Since its 2021 inception, the event has drawn top international teams to prestigious circuits like the Indianapolis Motor Speedway. The field, marked by both rivalry and teamwork, shows that collective problem-solving drives advances in autonomous vehicle safety. At the Indy Autonomous Challenge passing competition held at the 2024 Consumer Electronics Show in
Las Vegas in January 2024, our Cavalier team clinched second place and hit speeds of 143 mph (230 kilometers per hour) while autonomously overtaking another race car, affirming its status as a leading
American team. TUM Autonomous Motorsport from the Technical University of Munich . The field of autonomous racing didn’t begin with race cars on professional race tracks but with miniature cars at robotics conferences. In 2015, my colleagues and I engineered a 1/10 scale autonomous race car. We transformed a remote-controlled car into a small but powerful research and educational tool, which I named , playing on the name of the traditional
Formula One, or F1, race car. The F1tenth platform is now used by over 70 institutions worldwide to construct their miniaturized autonomous racers. The is now a marquee event at robotics conferences where teams from across the planet gather, each wielding vehicles that are identical in hardware and sensors, to engage in what is essentially an intense “battle of algorithms.” Victory on the track is claimed not by raw power but by the advanced AI algorithms’ control of the cars. 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 and , which explains the process of how to build, drive, and autonomously race these vehicles. Today, the scope of our research has expanded significantly, advancing from small-scale models to that compete at speeds of upward of 150 mph (241 kph), executing complex overtaking maneuvers 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. are used in professional racing and are slightly smaller versions of the Indy cars made famous by the . The gritty reality of 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 maneuvers at 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 . In addition, autonomous racing researchers create algorithms that use data from cameras, radar, and , which is like radar but with lasers instead of radio waves, to the high-speed and unpredictable racing environment. My team has shared the world’s first for autonomous racing, inviting researchers everywhere to join in refining the algorithms that could help define the future of autonomous vehicles. More than just a technological showcase, autonomous racing is a critical research frontier. When autonomous systems can reliably function in these extreme conditions, they inherently possess a buffer when operating in the ordinary conditions of street traffic. Autonomous racing is a testbed where competition spurs innovation, collaboration fosters growth, and AI-controlled cars racing to the finish line chart a course toward safer autonomous vehicles.