The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing Autonomous Vehicles (AV) hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging autonomous lateral control and autonomous longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions . However, the driver is still required to monitor the driving environment and handle scenarios where control is handed over to the driver due to subsystem faults of the autonomous system. Due to the disadvantages of vehicle testing being expensive, time-consuming and hazardous for testing such scenarios, an alternative method of development and validation is required. Therefore, the objectives of this research are two-fold. The first objective focuses on a real-time powertrain-based Hardware-in-the-Loop (HIL) implementation and validation of an SAE Level 2 autonomous vehicle. The second objective focuses on studying the performance of SAE Level 2 autonomous vehicles during takeover scenarios due to subsystem faults. To accomplish these objectives, an acceleration-based Adaptive Cruise Control (ACC) was combined with a path-following lateral control along with supervisory control for system mode transitions due to system deactivations and faults. This research presents system modes in which longitudinal control only and lateral control only are engaged as fallback states to the full autonomous system being faulted for lateral control and longitudinal control failures respectively. Simulations were conducted to evaluate the performance of the autonomous controls when subjected to these faults. A powertrain subsystem representative of the 2017 Ford Fusion Hybrid was used as the hardware simulation platform using a dSPACE HIL simulator and CarSim RT.