This project offers an innovative approach to leverage knowledge for the development of driver monitoring system. In this context, only supervised learning techniques used to identify driver distraction (support vector machine and Bayesian network) obtain encouraging results but these analyses are still often too difficult because the effect of inattention can vary greatly from a driving situation to another and from one type to another conductor. By developing an experimental approach to master certain parameters of influence, this project will allow substantial progress.