Modeling driver operation behavior by linear prediction analysis and auto associative neural network

This paper presents a new method for modeling driver operation behavior. The proposed method is based on using the predictor coefficients as feature vectors extracted from driving operation signal by linear prediction analysis (LPA). The distribution of the feature vectors is captured by employing auto associative neural networks (AANN) model. The performance of the model was evaluated through driver identification process and the results obtained demonstrate that the model can grasp the individual characteristics of the driver.