What drives autonomous race cars to peak performance when there’s no one behind the wheel? Which technologies make it possible to set new records on legendary racetracks? The answers lie with the Indy Autonomous Challenge (IAC): In this competition, international university teams race driverless cars against each other, supported by dSPACE with software and hardware solutions.
At the IAC, artificial intelligence (AI) and autonomous driving take center stage. Ten teams from universities around the globe compete against each other with their fully automated AV-24 race cars, controlled by AI drivers. To simulate the races in advance and process the large volumes of data generated during the competitions, solutions from dSPACE are used.
Which dSPACE products are used in the IAC?
- SIMPHERA: a simulation environment that enables the realistic testing and further development of AI driver software. It includes simulation models, test automation, and test analysis. SIMPHERA seamlessly integrates software-in-the-loop (SIL) and hardware-in-the-loop (HIL) platforms. The Cloud Racing Services, developed specifically for the IAC, offer a virtual test environment hosted in the AWS cloud, allowing flexible resource allocation and parallel execution of test scenarios.
- AUTERA AutoBox: a robust in-vehicle platform that serves as the central computer in all IAC race cars. It reads and processes data from lidar and radar sensors, cameras, and buses and networks in the vehicle. The unique combination of high computing power, ruggedization, and high-speed logging capabilities in a compact form makes the AUTERA AutoBox especially valuable for the IAC.
Record Hunting in Monza
As part of the Milano Monza Motor Show MIMO 2025, held from June 27 to 29, the IAC took place at the Autodromo Nazionale di Monza in Italy. Two university teams participated with their race cars.
The track is famous for its long straights, which allow drivers to reach high speeds. It features both right and left turns, giving teams the chance to test their technologies under real racing conditions. In the “Temple of Speed”, the Unimore Racing and TUM Autonomous Motorsport teams completed over 643 kilometers of autonomous testing in just six hours of track time.
With a lap time of 1:54.442 minutes, UNIMORE Racing improved the previous MIMO 2023 record by eleven seconds. In the same lap, the team also achieved 275 km/h, the highest speed ever reached by an IAC team on the Monza racetrack.
Virtual Preparation, Real Successes
On July 24, 2025, the world’s fastest autonomous race cars competed on the legendary WeatherTech Raceway Laguna Seca in the USA. The race kicked off the renowned Java House Grand Prix of Monterey and was held as a timed event. Eight IAC teams from North America, Europe, and Asia took part in this competition.
The racetrack is especially famous for its elevation changes and the challenging Corkscrew curve. On some sections, such as tunnels or under dense treetops, the vehicles can lose their GPS signal and must rely entirely on lidar and camera systems. Using SIMPHERA, our simulation and validation solution, the teams were able to virtually recreate these challenges and precisely adapt their algorithms to the specific conditions of the circuit.
After an exciting race day, Team PoliMOVE-MSU emerged as the top performer of the IAC with an impressive lap time of 1:29.792 minutes, an average speed of 144.5 km/h, and a top speed of 236.5 km/h. The teams Purdue AI Racing (2nd place) and KAIST (3rd place) also demonstrated their technical skills in an impressive manner.
The simulator is absolutely vital for safely testing our software on new tracks, giving us immediate feedback on how the car behaves in unfamiliar layouts. Moreover, when developing new planning algorithms, having a simulator that is able to replicate both vehicle dynamics and interaction with race control has proven fundamentally important.
Caltech Racer uses the dSPACE simulation solution to run virtual races as part of our verification and validation pipelines. In particular, we use dSPACE products to almost completely eliminate the track-specific integration while on-site, significantly improving our test slot utilization as we know our race lines and configurations will work before we even get to the track.
The dSPACE simulation environment has been pivotal for our team. It allows us to rigorously test and validate algorithms before hitting the track, which significantly bridges the sim-to-real gap and saves us invaluable time. The responsive support from the dSPACE team has also been instrumental in accelerating our development.
The dSPACE simulation environment is an extremely useful tool for developing and validating our autonomous driving software. For teams like ours based in Asia, where access to the track is limited, it allows us to thoroughly test and refine our systems ahead of rare on-track opportunities. The realistic simulation of both the environment and the vehicle model also gives us great confidence in the results.
What's next?
The IAC never stands still: Single time trials evolved into action-packed multicar races on oval tracks. The teams have already put their skills to the test on challenging road circuits with left- and right-hand turns. In the future, head-to-head duels on such tracks are planned. These advances are driving the development of autonomous vehicle technologies and are setting new standards in motorsport.
To further support this progress, dSPACE continually expands its support for the IAC. With AURELION, our sensor-realistic simulation software, teams can now realistically test perception algorithms on virtual racetracks. Simulated sensor data from cameras, radar, and lidar are transmitted in real time, so that data processing takes place just as it would in a real racing car. This brings simulation tests even closer to reality – an important step forward for autonomous racing progress.
