Automated vehicle technology can not only transform vehicle behavior on roadways, but also transform users from an active driver to a passenger, with increase in automation levels, such as going from SAE Levels 0 through 2, to Levels 3 through 5. As passengers engage in non-driving related tasks (NDRTs) inside a moving vehicle, they experience limited vehicle control and external awareness. Such conditions can lead to passengers becoming motion sick. Since two out of three passengers are prone to motion sickness, even mild symptoms of motion sickness can severely influence users’ experience in automated vehicles. This dissertation includes four studies to investigate the human factors challenge of motion sickness in passengers of automated vehicles. The first study consists of a systematic literature review following the PRISMA framework. Forty-one papers were selected to be qualitatively analyzed based on which an overarching research framework was proposed. The second study focused on verifying if driving styles simulated on a motion-based driving simulator could be used to artificially induce motion sickness in a safe controlled manner. The third study investigated two driving styles with and without an NDRT to corroborate the findings from the previous study. In the fourth and final study, the focus shifted to mitigating motion sickness. A novel auditory display was developed based on existing literature to reduce motion sickness. Findings from the second and third studies confirmed that strong lateral accelerations could indeed induce motion sickness, and engagement in a cognitively demanding task could lower motion sickness. Based on these findings, the Cognitive Distraction Effect was proposed in the third study. The fourth study, that utilized the verified motion sickness inducing condition from the second and third studies, found that the presence of repeated spatialized anticipatory auditory cues increased motion sickness due to the added sense of vection from the auditory stimuli. This was a unique observation that aligned with recent literature. Furthermore, the fourth study also found evidence in support of the Cognitive Distraction Effect. In summary, this dissertation provides a comprehensive investigation into developing our understanding of motion sickness in passengers of automated vehicles. Three unique contributions are proposed. One, it is possible to induce motion sickness in a safe replicable manner in a laboratory without the need for real-world driving. Second, cognitive engagement in a demanding task can suppress physiological symptoms of motion sickness, suggesting NDRT engagement could have benefits for mitigating motion sickness. Finally, the dissertation sheds new light on the senses that contribute towards development of motion sickness, in that even the hearing system has a role to play in maintaining balance and orientation, in addition to the visual and vestibular systems. / Doctor of Philosophy / The rise of automated vehicle technologies such as Advanced Drives Assistance Systems (ADAS), has the potential to transform drivers into passengers, with increased automation levels requiring less and less user input. These features can benefit users allowing them to utilize their transportation time in a manner of their choosing, while also improving safety. However, when engaging in such tasks that do not allow vehicle occupants to maintain control of their vehicle, or disconnect them from the external environment, passengers can become motion sick, influencing their overall wellbeing. Such conditions can cause users to not want to utilize the advance vehicle automation technologies. To improve users' comfort and experience, the current dissertation undertook research on the topic of motion sickness in passengers of automated vehicles. To that end, four studies were conducted. The first study reviewed the existing literature to identify 41 scientific papers. These papers were analyzed to reveal an overarching research framework that could guide future researchers and students. The second study developed aggressive and soft driving scenarios on a motion-based driving simulator to artificially induce motion sickness in a safe controlled manner. It was verified that the aggressive driving scenario producing sufficiently large lateral accelerations could induce motion sickness. It was also tested if performing a phone task would increase motion sickness, but this did not turn out to be the case. The third study built upon the second study, and tested the effect of being engaged and not engaged on a phone task in both the aggressive and soft driving scenarios. The results showed the effectiveness of the aggressive driving scenario to induce motion sickness, and that engagement in the phone task actually had a mitigating effect on motion sickness. This was explained by the mental distraction presented by the task that led to lower motion sickness. In the last study, the same aggressive driving scenario was used to induce motion sickness, but participants also received spatial auditory alerts before turning; it was expected to lower motion sickness by informing participants about the turn. However, the alerts showed an increase in motion sickness because participants felt increased sense of motion from the auditory alerts before the turns, which aligned with previous findings as well. In addition, the effect of mental distraction on lowering motion sickness was also observed here, confirming findings from the previous studies. Overall, the studies in this dissertation found a way to safely induce motion sickness without the dangers of real-world driving, it identified how being occupied in a task inside the vehicle may have a positive effect on motion sickness, and that auditory alerts should be developed within reason to inform passengers about upcoming motion.

<p dir="ltr">Automated Driving Systems (ADS) have evolved significantly over the past decade. With conditionally automated driving systems still requiring constant driver supervision and human intervention upon system request, a driver’s readiness to take over from an ADS has significant safety implications. Research suggests that drivers using ADS are more likely to engage in non-driving-related tasks (NDRTs), and this engagement can deteriorate takeover performance. However, different NDRTs can involve engagement of physical, visual and/or cognitive resources, which all can affect the takeover process in different ways. The potential interaction effects among these factors may be the cause of mixed empirical findings regarding the influence of NDRT engagement on takeover readiness and performance. Additionally, with more advanced ADS, takeover scenarios are likely to be less urgent. Yet, the ways in which drivers behave in response to a takeover request to intervene during such less urgent scenarios while engaged in NDRTs is still not well understood.</p><p dir="ltr">The purpose of this dissertation is to provide a better understanding of drivers’ response behavior during a conditionally automated vehicle takeover process by analyzing drivers’ motor, visual, and cognitive readiness in response to a takeover request (TOR). The work was completed in two phases. The first phase focused on the effects of pre-takeover visual engagement on takeover readiness in urgent situations. Two experiments were conducted as part of this first phase. Particularly, Study 1 investigated drivers’ post-TOR visual attention allocation and cognitive readiness after continuous visual NDRT engagement before a TOR. Study 2 examined drivers’ pre-TOR visual attention allocation and takeover performance both during and after voluntary engagement with visual NDRTs. The second phase used a non-urgent takeover scenario to investigate drivers’ takeover behavior and visual attention allocation when prioritizing the engagement of visual-manual NDRTs that differed in terms of cognitive engagement levels.</p><p dir="ltr">Study 1 required continuous visual attention in NDRTs and manipulated only the location of visual attention before an auditory TOR. Dependent measures included duration, location, and directness eye-tracking measures after the TOR, as well as freeze-probe cognitive readiness scores. Overall, delayed visual attention re-allocation in the driving scene, less dispersed gaze patterns, and worse perception and comprehension of road hazards were associated with off-road visual NDRT engagement. In addition, no significant benefit of enforcing on-road visual attention before the TOR, compared to the baseline condition without NDRT requirements, were found. These findings highlight the need to investigate the effects of more naturalistic NDRT engagement on takeover attention reallocation and takeover performance.</p><p dir="ltr">Study 2 complemented Study 1 by allowing voluntary switching of visual attention between the NDRT and the driving scene prior to the TOR, with the driving task being a priority. In addition, Study 2 investigated drivers’ takeover quality and understanding of the takeover scene using the appropriateness of their takeover decisions. Dependent measures were pre- and post-takeover eye-tracking measures, aligning to those used in Study 1, in addition to motor response measures, longitudinal and lateral vehicle control measures, and decisions made in response to a road obstacle. Overall, the driver’s post-TOR behaviors were not significantly affected by NDRT conditions, but visual NDRT-induced differences in gaze distribution were associated with the appropriateness of takeover decisions.</p><p dir="ltr">Finally, Study 3 used knowledge from prior studies to isolate the effects of different levels of cognitive engagement in real-world visual-manual NDRTs. The purpose was to investigate the effects of cognitive engagement on drivers’ visual attention allocation before and during the takeover, as well as on takeover performance in non-urgent takeover scenarios, where NDRT engagement was a priority. Dependent measures included eye-tracking measures, takeover response time, and vehicle control measures, used in prior studies. In summary, engagement in NDRTs with higher levels of cognitive engagement resulted in significant differences in pre-TOR visual attention allocation and less stable takeover maneuvers.</p><p dir="ltr">The findings from this work contribute to a better understanding of the effects of different components of NDRT engagement on takeover performance in conditionally automated driving systems. Ultimately, this work can contribute to improving the design of next-generation human-machine interfaces in surface transportation, including driver monitoring systems and in-vehicle displays, that promote safer human-automation integration in future ADS.</p>