F1 has transformed over the years and the drivers hit speeds of up to 230 mph with an unmissable frequency. In below two seconds, they take a pit stop.
When the F1 racing cars take a turn, they have a force of 5G. F1, indeed, is a very fast sport. The technology providers for F1 need to match pace with the sport’s speed.
F1, it is easy to see, is a contest among the drivers who are the best in the world. But, surprisingly, we can also perceive F1 as a contest among the most innovative engineers from all across the globe.
Now that AWS is at the avail of F1, it utilizes the most innovative technologies available globally. A few such technologies include High Performance Computing (HPC) and Machine Learning (ML) models, and these technologies are transforming the sport digitally. It will be interesting to see what AWS is doing for F1.
Transforming F1
Powered by the scintillating speed of innovation alongside the deepest and broadest functionalities of AWS, the processes involved with the collection and analysis of data have now transformed. By leveraging this data and content, F1 racing car manufacturers, drivers, coaches and teams are empowered to make smarter decisions.
Nowadays, we have 300 data sensors on each F1 racing car. Correspondingly, in each second, 1.1 million data points transmit from the car, which is then captured in the pit. So, now, F1 is a data-driven sport.
The degree of action enhances on the track
With AWS and F1 operating in unison, the driver’s performance enhances, and so does the vehicle’s. F1 being able to run aerodynamic simulations is a direct outshot of AWS’s high-performing computing. This way, F1 and AWS together came up with the car for the new generation which would perform 70% higher in terms of speed. In this car that they created, the downforce loss is reduced to 15% from 50%.
The reduction is, no doubt, dramatic. A chasing driver is hence empowered to overtake more easily. For the fans, the sight is a delight and they can treat on more action, wheel-to-wheel.
It was recently, in 2022, that this next-generation car was launched. Further, F1 has plans to make ML a part of its simulation processes. So, the organizations will receive additional insights. Herein, over 5,000 multicar and single-car simulations will be involved, with the number of data points being collected being as high as 550 million.
Adding to the fans’ delight
Through the span of the race weekend, the fan experience is also transforming. It becomes more engaging, primarily because from the trackside and the cars, millions of data points are transmitted. F1 insights can be derived using the same.
It is surprising to note that F1 now leverages historic data that spans seven decades, and is now stored on Amazon S3. Complex models are analyzed here, such that with the fans, rich insights can be shared over the data. With these insights, the value of decisions made in split second can be revealed. Advanced stats help highlight the performances and single out high performers.
Keeping fans engaged
So, before a race begins, while it lasts and after it is through, F1 insights, powered by AWS, is transforming the fan experience. Fans can now instantly grasp how, in real-time, teams are devising and implementing race strategies.
Let us take a look at a few of the top examples and specify how it all materializes.
Race Strategy:
When timing data is used, F1 brings to us visual insights. This puts the fans in a position to perceive driver and individual team performances objectively. The overall race outcomes are impacted by these tactics and strategies.
Competitor Analysis:
With data analysis, F1 can compare how the different cars in a race perform. It further spans to the drivers. So, across the desired parameters, the different drivers can be compared and a leaderboard can be created. This will be an attractive proposition for the fans.
Car Performance:
With F1 closely analyzing the aerodynamics, power unit, tyre performance, vehicle optimization and vehicle dynamics, overall car performance becomes easier to understand for the fans.
Pit Window:
Estimated pit stop windows can be calculated. These calculations are based on tyre compound, the spread of cars, and lap times. The viewers will have a clearer idea of how race dynamics alter a race. These race dynamics include yellow flags, safety cars and other teams.
Car Performance Scores:
With this insight, the individual performance of a car is isolated. Fans can compare the performance of any particular car to other cars. This will be a head-to-head comparison. It covers the building blocks that define a car’s performance. A few examples of the same include handling or balancing performance, straight-line performance and cornering performance.
Driver Performance:
In Driver Performance, we come to see the drivers that take their cars to their ultimate performance limits. This is when being compared with their competitors and teammates. While a lap lasts, a car’s tyres generate forces that are calculated. These calculations are then compared to the maximum that the car can churn out. So, we come to know that up to what limit the driver is leveraging the performance of the car. The three most important parameters covered under this statistic include corners, braking and acceleration. These three parameters render the maximum effect over a driver’s lap time.
Braking Performance:
Braking Performance delivers insights for us on a driver’s braking style when he is manoeuvring a corner. So, we come to see if cornering is advantageous or not. The main criterion observed in Braking Performance is how closely the driver is approaching a corner’s apex before the brakes. So, when cornering, we can observe both, how the car is performing and how the driver is performing. This way, the top speed on approach can be calculated, and we can also calculate the braking power utilized. Similarly, a reduction in speed while braking can be calculated. We can also come to know of the tremendous G-forces that a driver is encountering upon braking.