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Autonomous race cars are starting to show up on some very famous tracks. On Sept. 3, the Indy Autonomous Challenge brought its driverless race cars to WeatherTech Raceway Laguna Seca in California. Purdue AI Racing set a new autonomous track record and finished second in a head-to-head passing competition. Italy’s Unimore Racing took the win.
Two days later, autonomous racing took another step forward in Europe. Five teams brought fully autonomous race cars to Italy’s Imola Circuit for the Abu Dhabi Autonomous Racing League’s first race outside Abu Dhabi. Team Kinetiz came from fourth on the grid to win the 12-lap event.
Now autonomous racing has reached major circuits in the U.S., Europe and Abu Dhabi. The technology clearly travels. The bigger question is whether the fans will follow.
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University teams and their autonomous race cars gather at WeatherTech Raceway Laguna Seca after the Indy Autonomous Challenge’s Sept. 3, 2026 competition. (Indy Autonomous Challenge)
Driverless racing is becoming a global competition
The races at Laguna Seca and Imola came from two different autonomous racing programs. The Indy Autonomous Challenge brings together university teams that develop AI drivers for identical race cars. At Laguna Seca, nine university teams from North America, Europe and Asia were scheduled to compete.
The Sept. 3 event pushed the competition further by adapting the Indy Autonomous Challenge’s passing format to a road course for the first time. Instead of several cars racing as a pack, two autonomous cars take turns in attacking and defending roles. The software has to manage spacing and decide when it can safely make a move.
Purdue became the only American team to qualify for that portion of the competition. Its car also set a 1:27.731 autonomous lap record before finishing runner-up to Unimore. Then came Imola. A2RL brought autonomous racing from its home at Yas Marina Circuit in Abu Dhabi to Europe for the first time. The league says Imola represents another step toward its goal of creating an international championship for fully autonomous race cars.
Five autonomous race cars headed to the grid at Imola
Imola raised the difficulty again. Kinetiz, Constructor Racing, PoliMOVE, Unimore Racing and two-time A2RL champion TUM entered the event. Each team competed with identical EAV-25 race car hardware based on the Dallara Super Formula SF23 platform. That means much of the competitive advantage came from the software each team developed.
The AI had to figure out where the car was, understand what was happening around it and decide what to do next. Then it had to turn those decisions into braking and steering inputs at racing speed.
TUM ran into a technical problem on the formation lap and returned to the pits before the rolling start. That left the remaining cars to fight for position. Unimore had started from pole and led the race. Then things went wrong.
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Team Kinetiz celebrates with its autonomous race car after winning Europe’s first multi-car autonomous race at Italy’s Imola Circuit on Sept. 5, 2026. (A2RL)
A crash showed how hard autonomous racing can be
Unimore set the fastest lap of the race before suffering a technical problem that caused the car to slow dramatically. PoliMOVE was close behind and hit the slowing Unimore car from the rear. The collision ended both teams’ runs. That opened the door for Kinetiz.
The Singapore-UAE team had started fourth but moved into the lead and won by 10.963 seconds over Germany’s Constructor Racing. PoliMOVE was classified third. The crash may also be one of the most revealing parts of the race.
Driving fast on an empty track is one challenge. Reacting when the car directly in front of you suddenly loses speed creates a much harder problem. That is exactly the type of unpredictability autonomous systems have to learn to handle.
These AI race cars are getting seriously fast
These cars are moving a lot faster than you might expect. At Imola, PoliMOVE hit about 157 mph with nobody behind the wheel. During testing, the fastest autonomous lap came within 0.85 seconds of a benchmark lap set by Super Formula driver Juju Noda. That is surprisingly close.
In Abu Dhabi last year, former Formula 1 driver Daniil Kvyat still set a faster lap than the autonomous challenger, but the gap had narrowed to just 1.58 seconds. So the question has changed. We already know these cars can get around a race track at serious speeds. Now we are seeing what happens when they have to race another car and make those decisions in real time.
But who are fans supposed to root for?
Here’s where autonomous racing faces a challenge that has nothing to do with speed. Part of the fun of racing is having someone to root for. Fans follow drivers, get to know their personalities and pick favorites. Take the driver out of the car and suddenly that connection looks very different.
With autonomous racing, you are rooting for the team behind the software. For some tech fans, that may be enough. Watching engineers figure out how to make an AI-powered race car faster and smarter could become part of the appeal. But will people come back race after race?
We are already starting to get a sense of that. The Indy Autonomous Challenge returned to Laguna Seca this year and moved from solo time trials in 2025 to head-to-head passing on the road course. Just two days later, five autonomous race cars competed together at Imola in Italy.
Now the harder part may be building the kind of connection that keeps people watching after the surprise of seeing an empty cockpit wears off.
Five fully autonomous race cars compete at Italy’s Imola Circuit during A2RL’s first international race on Sept. 5, 2026. (A2RL)
So what is the point of racing cars without drivers?
There is another reason these competitions are worth watching. Race tracks give autonomous driving researchers a place to push software extremely hard. At Laguna Seca, Purdue’s team spent weeks practicing and used simulation to find bugs in its software before race day. At Imola, the AI had to deal with high speeds and other autonomous cars making their own decisions.
That pressure can reveal weaknesses quickly. A passenger car on a public road faces a very different environment. It has to deal with pedestrians, intersections and countless situations that do not exist on a closed race track.
So winning an autonomous race does not mean the same software is ready to drive you around town. Still, the basic challenge overlaps. An autonomous vehicle has to understand what is happening around it and decide how to respond. Racing forces researchers to test those capabilities at the edge of what the vehicle can handle. That is where this becomes relevant even if you never watch a single autonomous race.
Kurt’s key takeaways
Here’s what gets me about autonomous racing. We have gone from asking whether AI can keep a race car on the track to watching these cars chase each other at more than 150 mph. That is pretty remarkable. But speed alone will not turn this into a sport people care about. Part of what makes racing so compelling is the person inside the car. You follow the driver, learn their personality and pick someone you want to win. When the cockpit is empty, that connection changes completely. Could fans eventually start rooting for the teams behind the technology instead? I can see Purdue students and engineers developing their own following as these competitions grow. But autonomous racing still has to prove that watching great software compete can be as exciting as watching a great driver push a car to the limit. The cars are clearly ready to race. Now we get to see whether the fans are ready to care.
Would you watch an entire race with nobody behind the wheel? Let us know by writing to us at Cyberguy.com
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