Performance analysis of the Moto GP motorcycle by means of identification of its racing line

The identification of the racing line of a MotoGP motorcycle is a key factor in performance analysis, as it provides crucial insights into the motorcycle's behaviour. This project focuses on validating, improving, and expanding the capabilities of a model developed by Marta Gianassi, which reconstructs the 2D racing line of a MotoGP motorcycle based on available measurements and onboard sensors. Initially, a validation analysis is performed by comparing the reconstructed trajectory with the actual GPS data to assess the model's accuracy and consistency. Based on the validation results, the model is then refined through the development of new trajectory reconstruction strategies. Additionally, the model’s functionality to compare two different motorcycle trajectories, useful for analysing riding styles or optimizing lap times, is also validated and enhanced. Finally, the model’s reconstruction logic is extended to 3D to capture the impact of elevation changes on the circuit. In the end, the model can provide a more realistic and comprehensive analysis leading to a better understanding of how the motorcycle behaves under different conditions.