While Max Verstappen won the Formula 1 race on the circuit in Austin, Texas, a racing car from the Technical University of Munich won the car race in Indianapolis at the weekend. However, neither Lewis Hamilton nor Max Verstappen sat at the wheel of the racing car – the car was purely autonomous.
The TUM Autonomous Motorsport racing team from the Technical University of Munich has won the Indy Autonomous Challenge, the first competition for autonomous racing cars at the Indianapolis Motor Speedway. The Technical University of Munich prevailed in a field of nine teams from 21 universities and won a prize of one million US dollars with its victory. The legendary Indianapolis circuit has seen spectacular car races over the past few decades, but an event like the weekend doesn’t happen every day in the motorsport-mad capital of the US state of Indiana. Indiana Governor Eric J. Holcomb officially opened the race with the appeal: “Ladies and gentlemen start your software and crank your engines”.
The racing cars were not controlled by humans, but by computers. Universities from all over the world were called upon to develop systems based on artificial intelligence in order to let the racing cars drive autonomously on the racetrack at top speed. The main objective of the race: to advance technology development for autonomous driving and advanced driver assistance systems. Of the numerous applicants, nine teams were admitted, with the TUM Autonomous Motorsport racing team being the only university in Germany that was allowed to start in the high-speed funnel of Indianapolis with its own racing car. Other tams came from other US states, Poland, Austria, Colombia or Switzerland. Ultimately, a spectacular average speed of 218 km / h was enough for victory. “We are super happy with this result,” says team manager Alexander Wischnewski, “our goal was to reach over 200 km / h and we achieved that. The demands placed on a vehicle at the Indy Autonomous Challenge are enormous. At speeds of up to 300 kilometers per hour, the software has to react extremely quickly to changes. “
The on-board computer in the racing car records and analyzes all information provided by cameras, LIDAR sensors, GPS receivers and radar sensors in a fraction of a second. With the help of the data, forecasts are made about where the other vehicles are moving in order to make decisions that are given as driving commands to the steering or braking. For around 18 months, around 60 doctoral candidates and students from the Chair for Vehicle Technology and the Chair for Control Engineering at TUM worked on a software architecture with which these tasks can be solved quickly and safely. It was helpful that the students were able to draw on experience from previous projects, because the TUM Autonomous Motorsport Team had already participated in the Roborace demonstrations at the Formula E event in Berlin in 2018 and on the racetrack in Monteblanco, Spain, in 2019.
“We put a lot of time and energy into simulating the racing car and the racetrack,” remembers Alexander Wischnewski, “through the virtual races we were able to identify and correct many errors. And so we also had the advantage that the Software on the real car wasn’t a big problem for us. ” A major challenge remained to digitally reproduce the sensors such as optical cameras and lasers. The researchers and students also managed to simulate races with up to eight autonomous racing vehicles. The rules of the competition were for each team to compete for the fastest lap that included an obstacle avoidance component. Alex Wischnewski, team leader at TUM Autonomous Motorsport: “Our next goal is to win a fast, autonomous head-to-head race.” Organized by Energy Systems Network and Indianapolis Motor Speedway, the primary goal of the IAC is to advance technologies that accelerate the commercialization of fully autonomous vehicles and the use of advanced driver assistance systems. In the long term, the technology of the racing cars should also be installed in series vehicles.
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