How Artificial Intelligence, Data And Analytics Are Transforming Formula One In 2023

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    As with all industries today, artificial intelligence (AI) is unleashing a wave of disruption, transforming car design, racing performance and fan experience alike.

    Oracle Red Bull Racing CEO Christian Horner said: “Data is the lifeblood of a team. Every aspect of performance – how we run races, how we develop our cars, how we select and analyze our drivers – all depend on data.”

    As a F1 fan myself, I am very excited to have the opportunity to visit and work with some of the world class teams. More recently, that includes Red Bull and McLaren.

    This provides some interesting insight into how cutting-edge technologies, especially AI and data analytics, are being used to build a competitive advantage and push cars to the finish line faster than ever before. I was able to get In this article, we’ll share some of them and explain what the future holds for the most technology-driven sport on the planet.

    computational fluid dynamics

    A car’s aerodynamics is one of the most important factors when it comes to track performance. Modeling how airflow interacts with a car as it travels at high speed is part of the field of research known as computational fluid dynamics (CFD). Advanced research into this element of car performance is an important use case for technology in Formula 1 today.

    Data is collected from cars participating in real races and practice sessions. The average car has over 300 sensors, sending around 3 GB of telemetry data per race.

    Recently, I spoke with Rob Smedley. His F1 career moved from Williams to Ferrari, where he currently holds a position as a technical consultant for F1.

    One of the key developments in the field over the past year has been the application of CFD to change the direction of the sport in line with fan expectations. This was possible because F1 knew, thanks to fan feedback, that race spectators wanted to see the ‘wheel to wheel’ race action up close. However, the aerodynamic ‘wake model’, which was widely used until recently, was not suitable for this type of racing as it created strong turbulence in the wake of the vehicle, making it difficult for opponents to follow closely behind.

    This will allow Formula 1, the governing body the FIA ​​and its technology partners to determine what changes can be made to the car’s aerodynamics to enable closer racing for the 2022-2023 season. A joint project between AWS has been launched.

    The result, Smedley told me, was “a product that actually allows for tighter racing.”

    There are three main uses of CFD in F1. They are part of the new car design process and are done to test the performance of new components to study their impact on aerodynamics and to troubleshoot problems when the car is not functioning properly. increase.

    It’s not without its challenges. Performing CFD requires access to large amounts of high-performance computing power and highly skilled experts to perform complex simulations.

    However, the team acknowledges that the benefits far outweigh the costs, acknowledging that the technology will save the team significant amounts of both time and money.


    F1 teams use AI-powered simulation to model billions of potential race parameters and determine which variables are most likely to lead to favorable outcomes.

    State-of-the-art data and analytics expertise from partners such as AWS, Dell, and Oracle can help you better understand all the effects of weather, competitor behavior, pit stop strategy, road conditions, collisions, mechanical failures, and more. It means that it can be predicted accurately. ever.

    Simulations are used to test the car’s durability and assess how well the new design holds up to the rigors of high-speed racing. This allows engineering teams to identify weaknesses and potential points of failure during the simulation phase. This is much cheaper than finding it on the track.This is because the team severe restrictions About how much money you can spend on developing and designing cars per season.

    Williams boss James Vowels said AI was the only technology that could unlock the value hidden in the vast amounts of data generated and transmitted during modern F1 racing.he recently told the BBC“We will be using a prototype car that changes almost every race…different tracks, different tires…the right way to do that is with modeling tools that run millions of race scenarios. That’s it.”

    AI-powered models and simulations are also used to train drivers, helping them learn the course and improve their racing skills without risking injury or costly damage to their vehicles. Teams are permitted to keep much of the data generated and collected during the race confidential, but are obligated to disclose certain information not only to F1 but also to opposing teams. This includes his GPS data of the route taken by the car around the circuit on race day. This real-world data allows drivers to race and train simulated models of their opponents.

    One of the interesting developments in this area is recent. Introduction of F1 In your AWS Deep Racer project. This is a cloud-based HIM 3D Racing HIM simulator powered by machine learning, where racers pit simulated autonomous vehicles against each other in an attempt to complete the lap in the fastest time. Smedley was one of the people involved in the project, working with driver Daniel Ricciardo to generate data to help navigate the car. he told me “This program has big plans… to bring it closer to F1… and even have a full-fledged F1 car drive autonomously on the track.”

    the power of partnership

    Building partnerships with technology providers is an essential strategy for both F1 teams and the racing leagues themselves.

    Talk about partnership with his team Data Specialist AlteryxZak Brown, Managing Director of McLaren, told me, “Alteryx helps us … take data and integrate it, get it faster, and find the most relevant Getting the data is another thing, otherwise it’s just getting the data.” A lot of noise.

    “The more accurate data we have, the more different kinds of data we have and the better decisions we can make.”

    Choosing the right strategic partner gives teams not only technical expertise, but new insights into where and how technology can be applied, giving them the freedom to run their business to win races. You will be able to concentrate.

    Another McLaren partner is Dell, which provides high-performance computing solutions that power many of the team’s simulation and CFD initiatives. One of his systems, which collects data from driving cars and feeds it into a simulation to create a more accurate digital twin, has streaming capabilities. 100,000 data points every second.

    For six years, the Mercedes-AMG Petronas team has partnered with A data specialist, TIBCO enables you to turn data into insights that influence race strategy and vehicle design.

    And another hugely successful partnership is between last year’s Drivers’ and Constructors’ winners Red Bull Racing and Oracle. The team leverages the technical expertise of the US software and database giant to racing simulation The same goes for engineering development and fan engagement work.

    This partnership is so important to the team’s success that it is incorporated into the team name (now called Oracle Red Bull Racing) CEO Christian Horner said: increase. We have won every Grand Prix this year and with important results. “

    Cloud Insights and Engagement

    The final use case for data in F1 covered here revolves around providing insights that drive deeper fan engagement and interaction.

    Formula 1 is a complex sport, and there is often so much going on in racing that it’s not even apparent to the spectators watching on their TV at home. After all, the camera can only cover his one leg of the track at a time. If you’re watching live from the grandstands, your visibility is even more limited.

    Thanks to a five-year partnership with AWS, F1 is leveraging information such as real-world car position and timing data to insight During the race, broadcast camera coverage and commentary will be delivered to viewers.

    Zak Brown said: “The F1 track is 5km long and has 20 cars, so the TV can only focus on 1, 2 or 3 cars at a time…another 4.5km. There is a course in which various actions are taking place,” he said. That could be a very important key to how the race strategy unfolds.”

    Identifying and highlighting these insights requires the use of machine learning algorithms that use all available data sources to create a narrative about the race.

    “We pop these data insights on the screen so that the fans can understand.

    The future of technology in F1

    Generative AI is currently a hot topic in the tech world, thanks to the transformative potential and popularity of applications such as ChatGPT and Stable Diffusion. In Formula 1, organizers are equally excited about what this technology means for the future of the sport, especially for the fan experience.

    Smedley told me, “We’re using AI techniques and generative AI to model that demographic – his 500 million fans around the world – and try to understand them better and give them the products they actually want. .”

    “As you know, Formula 1 should never lose its DNA. About 20 gladiators sorties in these … ‘ground fighters’ … will race for two hours on Sunday afternoon.

    “We should never lose that DNA. But we should be able to tune around it to give our fans, especially the new fan base, more of what they want.”

    As we’ve seen, AI and machine learning certainly have the potential to do just that. One thing is certain, thanks to technology, not only will we continue to create more intense racing action, but we will also deliver faster, more powerful and aerodynamic cars that will give fans an exciting and immersive experience. that it can be produced.


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