World First: Autonomous Racing Leaps Forward in Abu Dhabi as A2RL Season 2 Showcases Record Speed, Bold Overtakes and Real-Time AI Decision-Making
TUM Retains Crown as A2RL Delivers World’s First Six-Car Autonomous Grand Final Eleven international teams competed for $2.25 million prize pool Human vs AI: Former F1 star Daniil Kvyat stayed just ahead of the autonomous challenger’s time; for now, human drivers still hold a slight edge Watch the race here: https://youtu.be/d9LLZ5mb5cA?si=RgJnvjWhdasZdXZS
The Abu Dhabi Autonomous Racing League, A2RL, delivered a defining moment for autonomous technology as six fully driverless racecars pushed the limits of AI performance in a world-first Grand Final at Yas Marina Circuit. In a night marked by record speed, bold overtakes, and split-second AI decision-making, Germany’s TUMcemented its dominance by retaining the championship title, followed by TII Racing (UAE) in second place, and PoliMOVE (Italy) in third. With eleven international teams battling for a $2.25 million prize pool and a Human vs AI showdown featuring former F1 star Daniil Kvyat, the event showcased just how dramatically the race - and the technology behind it - has advanced since Season 1.
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World First: Autonomous Racing Leaps Forward in Abu Dhabi as A2RL Season 2 Showcases Record Speed, Bold Overtakes and Real-Time AI Decision-Making (Photo: AETOSWire)
From the moment the race began, polesitters TUM were under pressure from Unimore (Italy), who showcased their own record-setting pace to catch and overtake them for the lead in Turn 6 before the end of the second lap. Over the course of the next ten laps, the duo continued to battle at speeds ofover 250 km/h, with less than a second between them throughout. At the half-way stage of the 20-lap race, the pair were within half a second of one another as they met the back of the pack. Going for the overtake on sixth place Constructor (Germany), Unimore collided with the rear of the car mid corner, sending both cars off track and handing the lead back to TUM who then carried through to victory. Unimore claimed the Fastest Lap Award through the duration of the competition.
Trophies and medals were presented to the winners of the A2RL Grand Final by His Highness Sheikh Zayed bin Mohamed bin Zayed Al Nahyan, His Highness Sheikh Mohammed bin Sultan bin Khalifa Al Nahyan, Vice-Chairman of the Abu Dhabi International Marine Sports Club and Chairman of the UAE Marine Sports Federation, and His Excellency Faisal Al Bannai, Adviser to the UAE President and Secretary General of the Advanced Technology Research Council.
H.E. Faisal Al Bannai, who envisioned A2RL, said: “A2RL shows what happens when bold ambition meets scientific discipline. It is more than a race - it is a testbed accelerating the future of autonomous systems while building public trust in the technologies that will soon move through our cities, skies and industries. What unfolded on track reflects the power of global talent, rigorous research, and the UAE’s conviction that breakthroughs happen faster when you invite the world to innovate with you.”
Prof. Markus Lienkamp, Team Principal at TUM, said: “We expected a tight battle with Unimore behind us from the beginning. They have been getting faster and faster in every test session, especially on cold tyres. We expected they’d overtake us on lap two and then we would get closer as our tyres warmed up. Of course, we hoped to see action with Unimore all the way to the end, but regardless what we have shown tonight is the rapid improvement and professional capability of the teams in this championship, to be able to have such a close battle in front of the crowd tonight.”
Marko Bertogna, Team Principal, Unimore Racing, said: “I was very, very happy with the performance that we showed, our speed, the overtake, all showed the professional level that we have reached. Even a human racing driver would not have been able to avoid the collision we had, so this is just the nature of high-performance racing. I’m incredibly happy about the technological result, but of course less happy about the final result.”
In only its second season, A2RL and participating teams have demonstrated significant progress at the crossroads of motorsport, mobility, and AI. Often referred to as “science in the public domain”, A2RL is accelerating the development of high-performance autonomous racing technology by putting it under extreme competitive pressure.
Intensive qualifying in recent weeks saw AI-driven cars not only closing the gap with human benchmark lap times but surpassing them - moving from minutes behind to mere fractions of a second ahead. The Grand Final set a record as the largest autonomous race in the world, featuring six teams: TUM, Unimore, Kinetiz (UAE), TII Racing, PoliMOVE and Constructor (in order of the starting pole positions).
Man vs Machine: Daniil Kvyat takes on Champion’s AI driver
Former Formula 1 racer Daniil Kvyat was stunned by the progress teams had made since he last went head-to-head with an AI driver during a 2024 A2RL exhibition in Japan. This time, he was on track with reigning champion TUM’s autonomous car HAILEY. Beginning from a rolling start with a 10 second gap, Kvyat was given just ten laps to hunt down his AI competitor. Kvyat marked his best lap at 57.57 seconds, while HAILEY recorded its best lap at 59.15 seconds – leaving just 1.58 seconds between them, a dramatic shift from the 10-second gulf just 18 months ago and a clear sign that AI is catching up fast. The showcase ended with the duo roaring across the line in close succession, much to the delight of fans in the grandstand.
Daniil Kvyat, commented: “Looking back to when A2RL development first began a couple of years ago, with perhaps minutes between a human driver and the AI car, down to 10 seconds in our first showcase last year, and now we are seeing performance within fractions of a second – the technology progress is staggering. As a technology enthusiast and a racer, it’s fantastic to be a part of this development since the beginning. Being on track with an AI driver is unlike anything else and it was fun to bring an exciting battle to the fans this evening.”
Stephane Timpano, CEO of ASPIRE, the ATRC entity driving A2RL commented: “Congratulations to TUM on a remarkable win. This Grand Final proved exactly why A2RL exists: to push the boundaries of autonomous technology through real competition. In just 18 months, teams have gone from standing still to delivering human-beating lap times and mastering complex overtakes - progress that can take years. By combining virtual SIM Sprints with extensive real-world testing, they’ve unlocked capabilities that will influence far more than racing. My thanks to all eleven teams for showing what true innovation under pressure looks like.”
A2RL also hosted a STEM Competition in parallel to the main competition. Over 140 students from across all seven Emirates in the UAE participated in an educational program that culminated in racing DeepRacer 1/18th-scale autonomous cars, a mirror of the A2RL competition. It aims to inspire and enable the next generation of autonomy and AI specialists, equipping them with new skills and experience. This year, the winner of the University League was ‘UAE University’, while ‘SABIS - Ras Al Khaimah’ claimed the High Schools title.
This year’s A2RL Grand Final was the capstone to the first-ever Abu Dhabi Autonomous Week (ADAW), a six-day event bringing together researchers and industry experts across a series of high-profile summits, exhibitions, and events. ADAW includes the Abu Dhabi Autonomous Summit, DRIFTx Exhibition, and RoboCup Asia-Pacific.
A2RL Season 2 was attended by over 8,000 spectators, filling capacity at the North Grandstand. It is supported by SteerAI, alongside leading partners du infra and AD Ports Group, official partners AWS and Abu Dhabi Mobility; official supporters WIO Bank PHSC, Exxon Mobil and Castore; technical partners PACETEQ, Live in Five, Meccanica 42, and Vislink; as well as event partners Abu Dhabi Gaming, Miral - Yas Island, and the UAE Cybersecurity Council.
Watch the race here: https://youtu.be/d9LLZ5mb5cA?si=RgJnvjWhdasZdXZS
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