Abstract
Multi-source information fusion was introduced for the evaluation on driver fatigue which is divided into sub-systematic and systematic evaluation by integrating information from visual cues in common use and steering wheel behavior and vehicle’s trajectory information. Neural network is combined with Dempster-Shafer evidence theory to finish character fusion and decision fusion. In the phrase of fusion, analytic hierarchy process (AHP) is applied to determine the basic weight, at the same time, considering the impact of data reliability on weight, the nonstatic weight is adapted the system to the current situation by the combination data reliability with basic weight. According to the simulation experiment on the drive simulator, compared with the single index, the adaptation of the evaluation method to monitor driver fatigue was more accurate, reliable and robust.