Reprogramming the race: An algorithm behind speed
- Justyna Rosak
- Jul 17
- 3 min read
Written by Justyna Rosak, Edited by Aaron Carroll
Algorithms in a way are like sets of rules - procedures to be followed enabling computation.
You can think of an algorithm as a set of instructions, no different to the ones you’d follow when baking a cake or tying your laces - no different to the process of getting into your car, stepping on the clutch and starting ignition before shifting gears. They’re automatic.
But in the world of software engineering and in the context of Formula One, algorithms can be seen as significantly more complex. They are more than a manual of instructions for taking a seat behind the wheel and securing a position on track.
So how exactly does software engineering come into play when the stakes are high and the cost of losing even higher?
The answer: data.
On the surface, the importance of data collection, transmission and processing isn’t that obvious. But without data, keeping track during a race would be pretty difficult, making it hard for drivers and their teams to make decisions that ultimately separate taking part in a race from securing a podium finish.
But to work with data, modes of measurement and data types have to be considered first.
Various types of data are processed and communicated using different types of sensors, all key in influencing the outcome of a race. From Drag Reduction Systems (DRS) to engine controls and tyre wear, everything starts with sensors and telemetry.
Sensors can be defined as detection devices that respond to changes in internal and external stimuli. For example, sensors can be used to measure and deliver temperature and pressure data.
Some examples of sensors:
- Thermal imaging sensors on the floor and wings of an F1 car are used to measure surface temperature.
- FIA mandated, standardised Tyre Pressure Monitoring Systems (TPMS) are installed inside wheels, to monitor tyre pressure during a race.
- Colour-changing, heat sensitive stickers can also be used where other thermal imaging sensors cannot be installed, informing engineers on whether maximum temperatures have been reached in different parts of the car.
Telemetry on the other hand, involves the in-situ, automatic collection of data at remote points using sensors and the transmission of this data to receiving equipment through communication systems where it is monitored and further analysed.
This is where the Engine Control Unit (ECU), AKA ‘the brain of the car’, comes into play.
An F1 car is equipped with an average of 250-300 sensors producing up to 1.5 terabytes of data in a given race weekend. An ECU will use antennas dotted around a track to transmit this real-time data from the track to the teams.
Engineers will then use various software such as the Advanced Telemetry Linked Acquisition System (ATLAS) by McLaren Applied, to rapidly process the mathematical output into a human-readable format.
This allows teams to understand in-depth what is happening on track, aiding real-time decision-making that is supported by real-time data.
How does it all come together? The DRS is a perfect example.
Sensors are critical in determining the position of a driver on track, especially when relating this to other drivers. If data indicates that a driver is at ‘striking distance’- within a second of the car in front, a driver can activate DRS. This will allow the driver to open the car’s rear wing, reducing drag, increasing straight line speed and promoting overtaking.
In 2021, during the Saudi Arabian GP, Verstappen and Hamilton showed the importance of DRS. Relaying the importance of software engineering in the sport, displaying just how essential sensors and telemetric communication of data is to be able to reach conclusions regarding speed, distance and time, ultimately enhancing race performance.
However, data is also used in relation beyond internal communication. Broadcasting information involves the processing of complex data into a format that makes sense to all fans.
This directly feeds into fan-focused systems such as the F1 live timing screen, available for fans for every race- showcasing the importance of data processing in the sport.
The use of sensors and telemetry in F1 is, without a doubt, critical - not only for ensuring that each race runs smoothly and is understood by teams and fans alike, but also in driving continuous understanding and improvement.
As F1 continues to push the boundaries between precision and speed, the demand for acquiring and processing of more data, faster will grow.
Algorithms aren’t only accelerating the cars; they’re driving change and steering the future of the sport.
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