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The next decade will see a rapid increase in the prevalence of partial and conditional vehicle automation, specifically SAE Levels 2 and 3. In these levels of automation, the driver is expected to act as the fallback in situations that exceed the operational capacity of the automation or during unexpected automation failures. The automation must transfer control back to the driver in these situations, and therefore drivers must remain aware of the driving situation even though they are not controlling the vehicle. The goal of the human-machine interfaces in automation is to provide feedback to the operator. Feedback can make the driver aware of low-level sensor function (e.g., sensing lane lines in the image below) and aid higher-level decision making tasks that include control transitions to or from the automation. The goal of this project is to investigate the effectiveness of different human-machine interfaces for maintaining situation awareness during automate driving.