Ever since we first heard about this company called Roborace that builds driverless AI racing cars, we knew we had to see it in action at some point — change was in the air. A few weeks ago, we finally had the opportunity to do so and joined the final track test for Roborace’s Season Alpha.

DevBot 2.0 at Zala Zone in Hungary, Photo: Roborace

But first, the basics. Roborace is an autonomous-vehicle racing series that combines fully-electric race cars with artificial intelligence, the first series of its kind in the world. Roborace was established to “accelerate the development of autonomous software by pushing the technology to its limits in a range of controlled environments.”

In 2018, one of Roborace’s driverless vehicles, the RoboCar, completed the first-ever autonomous hill climb at Goodwood Festival of Speed. Using only computer vision, sensors and artificial intelligence algorithms, the vehicle successfully navigated the famous 1.86-km hill climb track in West Sussex, England. Besides the stunning maturity of the prototype, it also looks as pioneering as Roborace’s vision: RoboCar was designed by the German designer Daniel Simon who is probably most famous for creating iconic automotive vehicles for Hollywood blockbusters such as Tron: Legacy and Captain America: The First Avenger.

Robocar Concept I: First Media Release, Photo: Roborace & Daniel Simon

A racing league for human and AI drivers

In the winter of last year, Roborace unveiled its latest prototype, the DevBot 2.0. Roborace’s racing cars are powered by Nvidia Drive, an autonomous vehicle development platform, and four electric motors that generate a combined 500-plus horsepower. In contrast to its unmanned counterpart Robocar, DevBot 2.0 is equipped with a cockpit for a human pilot. This now allows human pilots to race together with AI drivers. The AI “driver” is, in this case, the intelligent software that gathers all data from the sensors and other touchpoints to “drive” the car. What is more, digital maps of the environment can be created by manually driving the car, meaning that the human drivers can push the car to edge and teach the AI driver where the limits are.

The second-generation all-electric vehicle made its first public appearance at the start of Season Alpha earlier this year at Monteblanco Circuit in Spain. Season Alpha is Roborace’s inaugural racing competition, which premiered just this year and takes place at various locations in Europe and North America. It involves three challenges: wheel-to-wheel, object avoidance and localization. As its name suggests, it is currently in its alpha stage, with a beta planned for next year. Season Beta will feature more teams and increasingly ground-breaking formats and challenges being trialed across the globe.

The localization challenge, or: the battle of algorithms

To understand, explore and manage the complexities inherent in writing software for autonomous vehicles, Roborace has partnered up with our colleagues at Data:Lab Munich and Italdesign. For a period of four months, Roborace, Italdesign and Data:Lab worked together to develop new Machine Learning functionalities regarding perception, trajectory planning and torque vectoring. Why? Machine Learning is extremely important for autonomous vehicles, of course. Satellite navigation is a core technology for automated driving systems in this respect. Yet, sometimes GPS signals are blocked by tall buildings, tree tops or other obstacles. This poses a significant challenge to automated driving systems, and this is where the Roborace localization challenge comes in.