Part 1: Data-Driven Decision Making During a F1 Race
by Dharpan Randhawa
During a F1 race, teams can generate a large amount of data, which can vary depending on the specific race and the team's data collection methods. However, it is estimated that each car can produce over 1 terabyte of data per race weekend, including video and ancillary information. This data is generated from various sources such as the car's onboard systems, telemetry, sensor data, cameras, and GPS.
Once teams do the necessary post-processing of some of the data during or after the event, the total amount of data increases substantially, often by two or three times. This data is critical for teams to analyze and understand the performance of the car and make adjustments for future races.
What technologies do Formula 1 race engineers and technicians use to extract insights from millions of data points and adjust the race strategy in real-time during a F1 race?
Those who have watched a live F1 race from a team’s garage will understand that data plays a pivotal role in race strategy, and can be the difference between winning and losing. Formula 1 race engineers and technicians use a variety of technologies to extract insights from the millions of data points generated during a race and adjust the race strategy in real-time. These include (but not limited to):
Telemetry Systems | Cars are equipped with a wide range of sensors that collect data on various aspects of the car's performance, such as engine RPM, tire temperature, and suspension movement. This data is transmitted in real-time back to the team's pit wall via telemetry systems.
Data Analysis Software | Teams use specialized software to analyze the data collected from the car in real-time. These programs can display the data in a variety of formats, such as graphs and charts, and allow engineers to quickly identify patterns and trends.
Simulation & Modeling | Teams use simulation and modeling software to predict how changes to the car's set up will affect its performance. This allows engineers to make adjustments to the car's set up in real-time and make predictions about future performance.
Machine Learning | Some teams may also use machine learning algorithms to extract insights from the data. The algorithms can help teams identify patterns and anomalies that might not be immediately apparent to engineers.
Automated Decision-Making Systems | Teams may also use automated decision-making systems that can automatically adjust the car's settings based on data. This allows the engineers to focus on other important aspects of the race.
Why is real-time decision making conducted away from the F1 garage?
In F1, real-time decisions about a race are typically made thousands of miles away from the track, in the team's control center located at the factory. There are several reasons for this:
Data Analysis | The control center is equipped with powerful data analysis tools that allow engineers to analyze the large amounts of data generated during the race. This data is collected from the car's onboard systems, telemetry, sensor data, cameras, and GPS, and is analyzed in real-time to understand the performance of the car and make adjustments to the race strategy.
Better Infrastructure | The control center is equipped with better infrastructure such as high-performance computers, high-speed internet and specialized software that is not available in the team garage at the track. This allows the engineers to process data faster and make more accurate decisions.
Comfort and Concentration | The control center provides a more comfortable and less distracting environment for the engineers and analysts to work. They can focus on their work without the distractions of the race and the noise of the pit lane.
Remote Collaboration | The control center allows engineers and analysts located at different locations to collaborate in real-time. This allows teams to leverage the expertise of engineers and analysts located at different locations, and make better decisions as a team.
Cost | Having a control center at the factory rather than a dedicated one at the track is more cost-effective as it allows teams to share resources and avoid the high costs of setting up and maintaining a control center at each race location.
Overall, the control center at the factory is the hub of the team's operations during a race. It allows teams to analyze data in real-time, make better decisions, and collaborate more effectively with engineers and analysts located at different locations. This allows teams to make more informed decisions and optimize the performance of their cars during the race.