Formula One Racing and Artificial Intelligence

Formula One racing is one of the most popular motorsports, apart from NASCAR, Le Mans, and Moto GP. F1 is one sport that is known for its endless renovations and innovations. Be it on track or off track. Teams need to adhere to certain rules and caps when it comes to innovations and renovations, which maintain equity in the motorsport.

We have all been hearing about artificial intelligence taking over the world in every given domain. From influencing the kind of lights you want in your room according to your mood, to gradually taking over jobs like writing, calculating, cumulating, analyzing, and predicting outcomes, AI is everywhere. It is now becoming increasingly prevalent in motorsports, with its applications ranging from analyzing performance after races to tracking in-race activity and enhancing the fan experience.

AI became a prominent feature in Formula 1 in 2018. A collaboration between Amazon, the e-commerce giant, and F1 was formed to improve the sport’s racing tactics, data monitoring systems, and digital broadcasts. This tech marriage has led to groundbreaking advancements in motorsport. I will try to break down some of these advancements for you for a better understanding:

Using Amazon SageMaker and Amazon Web Services (AWS), F1’s data scientists have developed deep-learning models that can analyze race performance statistics. For the uninitiated, deep-learning models refer to advanced artificial intelligence algorithms that can learn to recognize patterns and make predictions based on large sets of data.

Amazon SageMaker, a cloud-based machine-learning platform, is utilized to construct, train, and deploy these models to generate precise race predictions. AWS will be used to store over 61 years of historical F1 race data, which researchers will utilize to conduct in-depth analysis and predict optimal driving strategies for the drivers.

Though there could be unique scenarios that play out on track, with an AI being used, there are multiple facets a team could consider to strategize to secure a position in the top 10 to secure points.

Pit stops are crucial moments for drivers and deciding when to make a pit stop depends on a lot of factors that the engineer and the team principal consider. During the initial days of F1, pit stops were long and frustrating times for drivers, as they lasted for more than a minute. With advancements, the time-lapse was reduced for good. But there are times when pit stops have gone menacingly wrong due to mechanical glitches. Sometimes the decision to change tires at the nick of time costs the driver his position, his lap time, and also the overall strategy, which is imperative for the team.

AI can analyze a vast amount of data to accurately predict the optimal time for a driver to make a pit stop and change their tyres. The Tyre Performance graphic displays real-time information on the current condition of each individual tyre on a selected car. The information is presented in percentage form, with the scale ranging from 100% for a new tire with no wear to 0% for a tire that has reached the end of its effective performance lifespan.

With graphics and data, this strong, strategy like double stacking could do wonders for teams!

In modern Grand Prix racing, tires are crucial and often a source of confusion due to the various sets allocated to teams for different times. The process of managing tire usage involves a significant team effort.

F1 has five tyre specifications, from C1 to C5, with C1 being the hardest and C5 the softest. Two types of rain tyres are also available: intermediates and full wets. Each event sees the allocation of three of the five dry-weather tyres, with the teams notified a few weeks prior. The tires are color-coded: white for the hardest with lettering on the side, yellow for the medium, and red for the softest. Intermediates and wets are also available at each event.

AI can be trained to predict what tire to change, depending on the weather conditions and also on the race conditions, such as what lap it is on at the time of the change and so on.

Back in 2018, Ross Brawn, the managing director of F1, aimed to enhance the fan experience through data, which led to his focus on granting fans access to the data already available to pit teams. He further believes that artificial intelligence can offer television viewers a distinctive perspective on races, enabling them to witness the split-second decisions made by their favorite racers and teams, which is crucial for achieving success in each competition.

To sum all of this up, I would quote Ariel Kelman, Chief Marketing Officer, Oracle,

And that’s artificial intelligence in Formula One racing for you.