This study was performed with the goal of delineating how drivers' interactions with an Automated Driving System were affected by a Driver Monitoring System (DMS), which provided alerts to the driver when he or she became inattentive to the driving environment. There were two specific research questions. The first was centered on addressing how drivers' trust and satisfaction with an Automated Driving System was affected by a DMS. The second was centered on addressing how drivers' abilities to detect changes in the driving environment that required intervention were affected by the presence of a DMS. Data were collected from fifty-six drivers during a test-track experiment with an Automated Driving System prototype that was equipped with a DMS. DMS attention prompt conditions were treated as the independent variable and trust, satisfaction, and driver performance during the experimenter triggered lane drifts were treated as dependent variables. The findings of this investigation suggested that drivers who receive attention prompts from a DMS have lower levels of trust and satisfaction with the Automated Driving System compared to drivers who do not receive attention prompts from a DMS. While the DMS may result in lower levels of trust and satisfaction, the DMS may help drivers detect changes in the driving environment that require attention. Specifically, drivers who received attention prompts after 7 consecutive seconds of inattention were 5 times more likely to react to a lane drift with no alert compared to drivers who did not receive attention prompts at all. / Master of Science

Understandings of road traffic interactions are largely based on human-human interactions. However, the development of vehicles controlled by highly auto- mated driving systems (ADS) would introduce a radically novel type of road user. This compilation thesis explores encounters between these “autonomous vehicles” (AVs) and human vulnerable road users (VRUs) such as pedestrians and cyclists. The included publications are connected to three research questions. First, empirical studies are reviewed to highlight existing interactive be- haviors and communication cues. This is followed by a methodological question of how to investigate AV-VRU interactions. Finally, VRUs’ experiences from initial experiments on AV crossing encounters are presented. While road user trajectories and kinematic behaviors are viewed as primary mechanisms to facilitate traffic interactions, they might also be influenced by cues such as appearances, gestures, eye-gaze, and external human-machine interfaces (eHMI). Using the Wizard-of-Oz approach, we are able to explore VRU encounters with a seemingly highly automated vehicle. Compared to meeting an attentive driver, AV encounters resulted in a reported lower willingness to cross, lower perceived safety, and less calm emotional state, indicating that the absence of driver-centric cues could lead to interaction issues and impede acceptance of AVs. To further explore this, we included light-based eHMI to signal the driving mode and intent of the vehicle (e.g., intent to yield). Future research should continue to investigate how AVs may co-exist with human road users focusing on aspects such as behavioral adaptations, research methodologies, and the role of various eHMI.