Analysis of driving styles of a GP2 car via minimum lap-time direct trajectory optimization


This paper addresses the problem of the link between the driving style of an ideal driver, modelled as an optimal controller, and fundamental set-up parameters of a vehicle in the GP2 motorsport class. The aim is to evaluate quantitatively how set-up parameters, like distribution of aerodynamic loads, weight and roll stiffness between front and rear axles, affect the driving style, encoded in the shape of the optimal trajectory and in the acceleration, brake and steer inputs.

To this aim, we develop an optimization code that includes a double-track vehicle model capable of solving the minimum lap-time problem (MLTP) on a given track. The track is represented via NURBS curves and the MLTP is framed and solved as an optimal control problem by transcription into a nonlinear program using direct collocation. To assess the accuracy of the vehicle model and the optimization pipeline, we also validate our results against real telemetry data.

The developed software framework lends itself to easily perform both sensitivity analysis and concurrent trajectory planning and set-up parameter optimization: this is obtained by simple promotion of static parameters of interests to variables in the optimal control problem. Some results along these lines are also included.

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    The driving style is assumed to be encoded in his telemetry data.

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    Here and in the remaining of the paper, we assume that \(s_{N-1}=1\) is always associated to the finish line of the particular track sector under investigation. This can be either the whole track or a part of it and can be elicited from the context.


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Correspondence to M. Gabiccini.

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Gabiccini, M., Bartali, L. & Guiggiani, M. Analysis of driving styles of a GP2 car via minimum lap-time direct trajectory optimization. Multibody Syst Dyn (2021).

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  • Optimal trajectory planning
  • Minimum lap-time simulation
  • Driving style
  • Variable set-up parameters
  • Vehicle model
  • Race car