Zhang, ZhenweiZhu, Zimeng2020-08-102020-08-102020-05Zhang_cornell_0058O_10810http://dissertations.umi.com/cornell:10810Zhu_cornell_0058O_10807http://dissertations.umi.com/cornell:10807https://hdl.handle.net/1813/7022425 pagesWith fully autonomous vehicles coming in the near future, and highly automated vehicles being tested on public roads, it is imperative to study the behavior of operators of highly automated vehicles. Driver behavior is also susceptible to prolonged duration of monitoring the autonomous vehicle. In the study presented here, we will investigate the changes in driver state and behavior over multiple sessions of automated vehicle operation. We plan to employ a longitudinal study design, with five driving sessions (of 20-30 minutes each) conducted on five consecutive days. We will analyze the changes in driver state and behavior over these five sessions using video data observations and physiological data we collected through wearable measuring instruments. The study was built on a Unity-based full cab driving simulator. In a Unity-based full car driving simulator, we implemented the function of waypoints following, switch between the automated driving mode and the manual driving mode, information visualization on the digital instrument cluster and output data log indicating participant behavior to support the entire process of the study.enAutomated VehiclesHumman Computer Interactiondissertation or thesishttps://doi.org/10.7298/2s4t-3v48