Drunk driving is one of the leading causes contributing to traffic crashes. There are numerous issues that need to be resolved with the current method of identifying drunk driving. Driving behavior, with the characteristic of real-time, was extensively researched to identify impaired driving behaviors. In this paper, the drives with BACs above 0.05% were defined as drunk driving state. A detailed comparison was made between normal driving and drunk driving. The experiment in driving simulator was designed to collect the driving performance data of the groups. According to the characteristics analysis for the effect of alcohol on driving performance, seven significant indicators were extracted and the drunk driving was identified by the Fisher Discriminant Method. The discriminant function demonstrated a high accuracy of classification. The optimal critical score to differentiate normal from drinking state was found to be 0. The evaluation result verifies the accuracy of classification method.