This repository organises various projects exploring race strategy optimisation techniques in motorsport. Each project addresses a unique challenge, such as pit stop timing, fuel load management, and energy deployment strategies.
Optimises pit stop strategies using dynamic programming, Monte Carlo simulations, and Bayesian optimisation to minimise race time.
Explores the trade-offs between fuel load, car weight, and lap time to optimise race performance.
Simulates optimal strategies during safety car periods, accounting for time gaps and tyre temperature changes.
Models energy deployment strategies for electric race vehicles, focusing on efficient energy usage across race distances.
Predicts overtaking opportunities using track layout, car performance, and driver behavior data.
Visit each project's repository for detailed instructions and analysis.