Research on prediction methods for motor vehicle driver training demand based on an S-curve

Motor vehicle training demand in China is beginning to change. Traditional forecasting methods are unable to adapt to the changing context and therefore cannot correctly predict the future trend. This paper (i) provides an analysis of the characteristics of driver training demand in China and (ii) proposes a new forecasting method based on an S-curve and saturation theory. A case study of small car driver training volume in the city of Huai'an is used as an example to validate this method and compare its predictive value with the traditional method. The traditional method shows continued growth in demand, while the new model indicates a turning point following which demand declines. Given the conditions applying in 2013, the new method provides a more accurate match with the actual situation.