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It is well known that not all drivers drive the same and that the same driver has different driving characteristics with different vehicles. Identifying the characteristics that are unique to each driver/vehicle response opens the way for more personalized and accurate driver assistance systems. In this paper, we consider the problem of identifying the driver/vehicle characteristics by processing real-time driving response data. We propose the use of a Gaussian mixture model combined with the knowledge of dynamic characteristics modeled as probability distributions together with additional logic and appropriate thresholds in order to implement a real-time driver/vehicle response diagnostics system. We focus our efforts on the vehicle-following part of driving. The system is tested on a customized vehicle using different drivers under different driving conditions. We demonstrated that the system can distinguish between different drivers and can classify driver aggressiveness during vehicle following.