Overview
The machine learning group is working with one of the leading forumla one teams in analysis of data generated in Formula One races with the aim of improving strategy. With this aim we are running one or more projects this year focussed on Formula One data. Formula one is a data intensive sport, information about the location of each team’s car during the race is provided to the teams. Optimization of pit stop strategy can make the difference between winning and losing the race. There are commercial confidentiality issues over which areas will be studied, but interested students can discuss these areas directly with the supervisors.
FAQs
- What will I learn in this Project?
You will learn about making real time data-driven decisions using machine learning. You will develop an understanding of how the pipeline of decision making depends on good software, how to interact with a customer who needs to take action on those decisions.
- What is the objective of the project?
Project objectives vary according to current priorities for the team. Past project objectives have included providing estimates of qualifying cut off lap times (including uncertainties) and estimating the sensitivities of the race simulation.
- How does this fit into the bigger picture?
In academia it is rare to find a decision-making environment where the decision is based on the best-available knowledge, more often we are looking to give a developed understanding of a problem without time pressure. Strategy in Formula One races requires that the best-currently-available answer is provided and this project gives an opportunity to understand that process.
