Modeling research on driver fatigue

The aim of this paper is to build a Hidden Markov Model of normal driving state of drivers from the perspective of driving behavior to reduce traffic accidents caused by driver fatigue. Driving behavior data which drivers at normal driving state and the fatigues ones is analyzed. The vehicle control strategies of drivers are selected as hidden states. Data of driving behavior are denoted as observable output sequences. Large amount of driving behavior data is quantified with LBG VQ algorithm. Model parameters are estimated to use Baum-Welch algorithm. The model is evaluated in driving state identification experiments using signals collected in a driving simulator with forward algorithm and backward algorithm. Simulation results indicate that abnormal driving state of drivers can be identified.