A number of studies have shown that driving an unfamiliar vehicle has the potential to introduce additional risks, especially for novice drivers. However, these studies have generally used statistical methods in analyzing crash and near-crash data from different driver groups, and therefore the evaluation might be subjective and limited. For a more objective perspective, we suggested that it would be worthwhile to consider the vehicle dynamic signals from the CAN-Bus. In this study, 20 drivers participated in our experiment, where a Gaussian model was used to model individual driver behavior, as well as using a dissimilarity score, which is measured by the squared Euclidean distance in the vehicle dynamical feature space, to evaluate driving performance. Results show that the variation of driving performance caused by driver experience and vehicle familiarity (i.e., driver experienced vs. non-experienced; familiar vs. unfamiliar with vehicle) was clearly observed. Additionally, among the signals examined, we found that the brake signal better represents this variation, which could be used for advanced vehicle technology to reduce accidents and improve road safety.