his work is focused on racing cars driver's training. Nine different tracks are considered and six drivers. Each driver drives on every track and performs consecutive trial sessions on each track; each session is made of various laps, and lap times are fitted using an exponential model, yielding an estimate of the initial performance, the learning constant, and the asymptotic performance. According to results, the learning curve varies significantly among pilots and among tracks; all pilots reach their session asymptotic performance in less than nine laps. The asymptotic performance in consecutive trial sessions improves significantly, and it is strongly correlated to the initial session performance (r2>0.99). As a conclusion, it is more profitable to perform separated sessions made of few laps (less than 10) rather than performing a smaller number of longer sessions. Whenever the initial lap time stops decreasing systematically, trial sessions should end because the asymptotic performance is not likely to improve further.
|Titolo:||Learning curves of elite car racers|
|Data di pubblicazione:||2017|
|Digital Object Identifier (DOI):||10.1177/1747954117694929|
|Appare nelle tipologie:||1.1 Articolo in rivista|
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