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Connected and automated vehicles (CAVs) are expected to improve both traffic safety and efficiency by reducing the human driver errors. Recently, many researchers have focused on the simulation-based studies in order to evaluate the benefits of CAVs due to the lack of real-world data. However, none of the previous studies have attempted to differentiate the benefits of CAVs over automated vehicles (AVs) by incorporating multiple preceding vehicle information (i.e., acceleration, position, etc.). This paper aims to fill the existing gap by utilizing separate car-following models for both CAVs and AVs in order to approximate their driving behavior in the Aimsun Next simulation platform. Additionally, a different car-following model is used for the connected vehicles (CVs) without automation by addressing the human driver compliance factor. This study also utilizes mixed penetration of CAV and CV with no automation. A …