<p>Emerging technologies such as real-time travel information systems and automated vehicles (AVs) have profound impacts on driver decision-making behavior. While they generally have positive impacts by enabling drivers to make more informed decisions or by reducing their driving effort, there are several concerns related to inadequate consideration of cognitive and psychological aspects in their design. In this context, this dissertation analyzes different aspects of driver cognition and psychology that arise from drivers’ interactions with these technologies using physiological data collected in two sets of driving simulator experiments.</p> <p>This research analyzes the latent cognitive and psychological effects of real-time travel information using electroencephalogram (EEG) data measured in the first set of driving simulator experiments. Using insights from the previous analysis, a hybrid route choice modeling framework is proposed that incorporates the impacts of the latent information-induced cognitive and psychological effects along with other explanatory variables that can be measured directly (i.e., route characteristics, information characteristics, driver attributes, and situational factors) on drivers’ route choice decisions. EEG data is analyzed to extract two latent cognitive variables that capture the driver’s cognitive effort during and immediately after the information provision, and cognitive inattention before implementing the route choice decision. </p> <p>Several safety concerns emerge for the transition of control from the automated driving system to a human driver after the vehicle issues a takeover warning under conditional vehicle automation (SAE Level 3). In this context, this study investigates the impacts of driver’s pre-warning cognitive state on takeover performance (i.e., driving performance while resuming manual control) using EEG data measured in the second set of driving simulator experiments. However, there is no comprehensive metric available in the literature that could be used to benchmark the role of driver’s pre-warning cognitive state on takeover performance, as most existing studies ignore the interdependencies between the associated driving performance indicators by analyzing them independently. This study proposes a novel comprehensive takeover performance metric, Takeover Performance Index (TOPI), that combines multiple driving performance indicators representing different aspects of takeover performance. </p> <p>Acknowledging the practical limitations of EEG data to have real-world applications, this dissertation evaluates the driver’s situational awareness (SA) and mental stress using eye-tracking and heart rate measures, respectively, that can be obtained from in-vehicle driver monitoring systems in real-time. The differences in SA and mental stress over time, their correlations, and their impacts on the TOPI are analyzed to evaluate the efficacy of using eye-tracking and heart rate measures for estimating the overall takeover performance in conditionally AVs.</p> The study findings can assist information service providers and auto manufacturers to incorporate driver cognition and psychology in designing safer real-time information and their delivery systems. They can also aid traffic operators to incorporate cognitive aspects while devising strategies for designing and disseminating real-time travel information to influence drivers’ route choices. Further, the study findings provide valuable insights to design operating and licensing strategies, and regulations for conditionally automated vehicles. They can also assist auto manufacturers in designing integrated in-vehicle driver monitoring and warning systems that enhance road safety and user experience.

<p> Although interest in brain-computer interfaces (BCIs) from researchers and consumers continues to increase, many BCIs lack the complexity and imaginative properties thought to guide users towards successful brain activity modulation. In this research, an experimental story brain-computer interface (ES-BCI) was developed, with which users could interact using cognitive strategies; specifically, thinking about the story and engaging with the main character of the story through their thought processes. In this system, the user’s frontal alpha asymmetry (FAA) measured with electroencephalography (EEG) was linearly mapped to the color saturation of the main character in the story. Therefore, the color saturation of the main character increased as FAA recorded from the participant’s brain activity increased above the FAA threshold required to receive visual feedback. A user-friendly experimental design was implemented using a comfortable EEG device and short neurofeedback (NF) training protocol. Eight distinct story scenes, each with a View and Engage NF component were created, and are referred to as blocks. In this system, seven out of 19 participants successfully increased FAA during the course of the study, for a total of ten successful blocks out of 152. Results concerning left (Lact) and right (Ract) prefrontal cortical activity contributions to FAA in both successful and unsuccessful blocks were examined to understand FAA measurements in greater detail. Additionally, electrodermal activity data (EDA) and self-reported questionnaire data were investigated to understand the user experience with this ES-BCI. Results suggest the potential of ES-BCI environments for engaging users and allowing for FAA modulation. New research directions for artistic BCIs investigating affect are discussed. </p>

The aim of this thesis was to help elucidate the mechanisms that underlie age-related decline in visual selective attention and working memory (WM). Older and younger adults completed a behavioural WM task, after which electroencephalogram (EEG) was recorded as participants perform a localized attentional interference (LAI) task – competition/attentional interference was manipulated by systematically altering the distance between targets and distractors. Older adults showed impaired accuracy and reaction time on the WM and LAI tasks. Two event-related-potentials, indexing spatial attention (N2pc) and target processing (Ptc), displayed attenuated amplitude and increased latency in older adults. Thus, spatial selection, target enhancement and processing speed deficits may contribute to age-related attentional impairments. Furthermore, an unexpected component was found between the N2pc and Ptc in the older adult waveforms. Preliminary analyses suggest this may be the PD, implicated in distractor suppression, which may be differentially contributing to older and younger adults’ electrophysiology and attentional processing.

The aim of this thesis was to help elucidate the mechanisms that underlie age-related decline in visual selective attention and working memory (WM). Older and younger adults completed a behavioural WM task, after which electroencephalogram (EEG) was recorded as participants perform a localized attentional interference (LAI) task – competition/attentional interference was manipulated by systematically altering the distance between targets and distractors. Older adults showed impaired accuracy and reaction time on the WM and LAI tasks. Two event-related-potentials, indexing spatial attention (N2pc) and target processing (Ptc), displayed attenuated amplitude and increased latency in older adults. Thus, spatial selection, target enhancement and processing speed deficits may contribute to age-related attentional impairments. Furthermore, an unexpected component was found between the N2pc and Ptc in the older adult waveforms. Preliminary analyses suggest this may be the PD, implicated in distractor suppression, which may be differentially contributing to older and younger adults’ electrophysiology and attentional processing.

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