Застосування штучних нейронних мереж для прогнозування стану шин в умовах автомобільних перегонів

Abstract

The paper considers the problem of predicting the rate of tyre degradation in Formula 1 motor racing. The wear and degradation process is influenced by a number of factors, including track characteristics, rubber compounds, temperature conditions, etc. Using the absolute lap time as an estimate of the degradation rate is complicated by the influence of fuel load and differences in track length. It is proposed to use the lap time difference as an indicator of rate change. A recurrent neural network is used to predict the rate of degradation. The results demonstrate the potential of using artificial intelligence methods to analyse racing data.