Automated vehicle testing in real-world driving scenarios is required for system development but may not always be able to be performed due to safety or other concerns. Testing scenarios can be replicated at a closed test track as an alternative to the real-world driving scenarios. While safer, the maneuvers performed may not be able to completely match those of the actual road. A simulated testing environment can be created to perform testing on a complete digital replica of the real-world roads. Scenes can be created to accurately match the real-world roads and surroundings. Simulated testing can be the first step in validating the automated driving functionality performance and safety for eventual implementation on a physical vehicle. The Ohio State University team in the Advanced Research Projects Agency - Energy (ARPA-E) Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) program is working on utilizing Level 4 automated driving technology to improve upon their energy saving and mobility benefits of a Plugin Hybrid Electric Vehicle (PHEV) platform. A test route representative of real-world driving scenarios is selected to measure the increased energy efficiency of the system. The automated driving platform has additional limitations that must be taken into consideration when selecting a route for testing. To reach the point at which a simulation can occur, the autonomous driving platform being used must be configured properly and a model scene must be created for simulated maneuvers to be performed. This thesis covers the initialization steps for the automated driving platform, the creation of a digital replica for a selected test route, and the validation of automated driving features in the simulated environment. Multiple open-source autonomous vehicle platforms exist for interested teams to work with the systems that enable autonomous driving. The Robot Operating System (ROS) is utilized by Autoware to allow for easier communication between the different automated driving sensors and modules. Open-source software provides clear information about the structure of the system and how modifications can be made to different modules to produce desired energy saving results. Once the automated driving platform is properly set up, simulations are run. ROSBag playback consists of replaying the Light Detection and Ranging (LiDAR) point scan values for a given time window and testing accuracy of point cloud maps through localization. The SVL Simulator is used to test automated driving functionality using a virtual vehicle in a custom-made virtual environment. Corresponding point cloud and high-definition maps were created to provide necessary road and positioning information to Autoware. Various tools including OpenStreetMap, MathWorks RoadRunner, and the Unity game engine ease the process of creating a virtual replica of the real-world test route. With localization possible, additional automated driving functions were performed using Autoware's mission and motion planning modules.