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Performance Indices for Motorsport Drivers Analysis

  • Flavio Farroni
  • Ernesto Rocca
  • Aleksandr Sakhnevych
  • Francesco TimponeEmail author
Conference paper
Part of the Mechanisms and Machine Science book series (Mechan. Machine Science, volume 68)

Abstract

The present paper aims to propose performance indices able to characterize the driving abilities of a car driver in the motorsport ambit. These indices could be used both to improve drivers performances and to conduct comparative analyses between professional and non-professional drivers. The data used for the analysis come from a Formula 4 vehicle and have been acquired by means of a specific data logger. Some indices, suggested by the specific literature in the motorsport vehicles, have been analyzed and employed on the data acquired on track during races. The results were not so satisfactory especially to evaluate the performance of a non-professional driver. The proposed indicators defined as the product of the accelerations along one determined direction (longitudinal or lateral) for the corresponding velocities seem to be suitable to be used as performance indices for the pilot in all the three main phases of a curve. The analysis of the data shows that these indices are quite reliable even if, in some particular cases, they show little discrepancies. This happens because the indices must be interpreted differently in dependence of the various types of curve, which are diversely approached (e.g. a chicane or a hairpin). Further development will improve the indicators according to the type of curve, trying to give an overall performance indicator for each curve.

Keywords

Driver Key Performance Indices (DKPI) Vehicle dynamics Travelling in curve 

Notes

Acknowledgments

The authors want to thank Ing. Vincenzo Izzo, Mr. Gennaro Stingo and Mr. Giuseppe Iovino for their support.

The authors also thank the motorsport team. The data in the paper have been scaled and de-personalized for confidentiality reasons to protect and guarantee privacy. A Non-Disclosure Agreement was signed.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Flavio Farroni
    • 1
  • Ernesto Rocca
    • 1
  • Aleksandr Sakhnevych
    • 1
  • Francesco Timpone
    • 1
    Email author
  1. 1.University of NapoliNaplesItaly

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