<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>

Advanced Vehicle Systems promise improved safety and comfort for drivers. Steady advancements in technology are resulting in increasing levels of vehicle automation capabilities, furthering safety benefits. In fact, some of these vehicle automation systems are already deployed and available, but with promised benefits, such systems can potentially change driving behaviors. There is evidence that drivers have increased secondary task engagements while driving with automated vehicle systems, but there is a need for a clearer scientific understanding of any potential correlations between the use of automated vehicle systems and potentially negative driver behaviors. Therefore, this thesis aims to understand the state of knowledge on automated vehicle systems and their possible impact on drivers’ distraction behaviors. I have conducted two systematic literature reviews to examine this question. This thesis reports these reviews and examines the effects of secondary task engagement on driving behaviors such as take-over times, visual attention, trust, and workload, and discusses the implications on driver safety.