Brawn: Machine learning the future for Formula 1

Machine learning will be used to study numerous factors regarding Formula 1, including ways in which circuits changes will impact quality of racing, how different race formats will play out among of a myriad of potential scenarios.

Speaking at the re:Invent 2018 conference hosted by F1 partner Amazon Web Services’ in Las Vegas, Brawn revealed, “Further down the road, what’s really exciting is we are going to investigate the influence of the tracks and the racing formats on the quality of the racing."

"Can we create tracks that achieve better racing and better overtaking? Can we build models that allow us to do that?

“Can we change the format of racing to make it more exciting and less predictable? For instance, what happens if we change the format of the starting grid, so instead of being spread out it’s bunched up? We believe that using machine learning, AWS is enabling us to do these things.”

Brawn went on to explain how these developments will be passed on to fans, “We are training machine learning models using this huge amount of data that we have in Formula 1, and we’re using those models to make predictions of what’s going to happen in the race"

“We are digging deeper to show you where the performance is coming from. When is a car faster? Why is it faster?"

“For next season we are expanding ‘F1 Insights’ for our viewers. By further integrating the telemetry data such as the car position, the tire condition, even the weather, we can use Sagemaker to predict car performance, pit stops and race strategy."

F1 TV broadcasts will be spiced up to include "exciting new AI integrations" within the graphics elements of the coverage, which will enhance and add value to the viewer experience as well as the storyline of the grand prix.

Brawn explained, “We know that somebody is in trouble: his rear tires are overheating. We can look at the history of the tires and how they have worked and where he is in the race, and machine learning can help us apply a proper analysis of a situation.

“We can bring that information to the fans and help them understand if the guy is in trouble or if he can manage the situation. These are insights the teams always had but we are going to bring them out to the fans and show them what’s happening.”

“Wheel-to-wheel racing is the essence and critical aspect of the sport. And now with machine learning and using live data and historical data, we can make predictions about what is going to happen."

“What we expect is going to happen in an event. What is great about this, is that the teams don’t have all this data. We as F1 know the data from both cars and we can make this comparison and this has never been done before."

“The pit stop is the major strategic element of the race... Stopping at the right time and fitting the right tyre can win or lose a race."

"We are going to take all the data and give the fans an insight into why they stopped and when they stopped – did the team and driver make the right call?” added Brawn.