The job of a package delivery driver (PDD) is complex and demanding. These drivers must possess many skills in order to succeed in their work, including physical stamina, appropriate decision-making, positive customer interaction, and most importantly, operational safety. Companies must use significant resources, not only to provide insurance for existing drivers, but also to train new drivers to use their visual attention effectively while driving, and companies have a vested interest in ensuring that the most capable trainees are selected for jobs. Currently, subjective assessments of supervisors or managers are typically used to make these determinations. While these are valuable methods for assessing drivers, an objective measure of how well the driver is using his/her visual attention would both assist evaluators in making judgments, as well as make those judgments more accurate. The purpose of the study described herein was to 1) conduct a task analysis of the driving component of the PDD job responsibilities, and 2) create and test an objective measure that a package delivery company could use to evaluate the performance of its drivers. A detailed task analysis based on numerous observations of drivers in their normal work routines was conducted for this research in order to understand these complex tasks. A framework was created for understanding this system of tasks, which was then used to organize all tasks that drivers were observed to perform into more general, goal-oriented activities. Using this task analysis, incidents were identified that were observed while drivers were behind the wheel. This information demonstrated that breakdowns were occurring within the tasks drivers were performing and that improved methods of training and evaluations may be needed as a result. A construct of visual behavior called Head Down Time (HTD) was then created and tested. An individual HDT is defined as the sum of time of all eye gazes away from the primary display (i.e. windshield) between two distinct eye gazes at the primary display while the vehicle is in motion. HDT was evaluated for its ability to differentiate levels of experience between drivers, its relationship to types of route on which drivers delivered, and its relationship to the driving-related incidents that were observed. HDTs were shown to be differed significantly between drivers of low and high experience, with experienced drivers displaying shorter durations of HDT when compared to inexperienced drivers. HDTs also differed in duration when analyzed by the type of route upon which drivers operated. Commercial and urban routes, while not significantly different with respect to HDT, were shown to have increased HDT durations when compared to rural routes and, in turn, residential routes were found to have significantly longer HDTs than did rural routes and may have significantly shorter durations compared to commercial and urban. Finally, HDTs that were associated with observed driving incidents in terms of chronological proximity were shown to be of significantly longer duration than were HDTs that were not associated with incidents. All tests were conducted using appropriate statistical measures, including t-tests at a level of α = 0.05 for each dataset. Applications of this research include: 1) improvement of PDD training and evaluation methods through use of a detailed task analysis, 2) improvement in how package delivery companies define incidents and train PDD toward the prevention of incidents based on task analysis and observations as to incident frequency, and 3) the further development of HDT as a possible objective measure to supplement the training and evaluation of PDD. / Master of Science

Two interesting properties of the distribution of spatially selective attention have been noted in the behavioral and electrophysiological literature. First, there is a graded field of attention that expands from the center of the attended area. Second, the size of the attended area can be adjusted to be either larger or smaller in order to match the demands of the current task. Five event-related potential (ERP) studies are presented that extend these findings in several important ways; 1) The time frame of these two distribution properties is different. Results are consistent with a two stage model of spatial attention in which visual processing is initially enhanced for all stimuli presented near the center of the attended area as indexed by the amplitude of the first negative peak in the waveform (N1). Subsequently, the effects of narrowing or expanding the attentional field to the relevant size affects visual processing as indexed by the amplitude of the second negative peak (N2). 2) Object boundaries had limited impact on either the spread of the initial gradient of spatial selection or the scale of attention. 3) When selecting visual stimuli for attentive processing based on features such as color and size there is also a gradient of facilitation, but the impact of this graded selection on visual processing is not observed until later in processing, and is indexed by the amplitude of the selection negativity (SN). Furthermore, similar to the lack of interaction between object boundaries and the range of cued locations, the gradients of feature-based selection are not affected by the range of cued features.

Three studies examined the impact of social stimuli on visual attention. Chapter two confirmed that, hands, feet, and bodies exhibited equivalent attentional pull in a dot probe detection, two-alternative forced choice paradigm. Chapter three utilized a Posner style covert attentional cueing paradigm to examine the impact of directed human action (throwing a ball) on spatial attention. We manipulated the effect of context by including social (humans) or non-social (trees) flanking images and probed the uniquely social nature of the processing in this task by including individuals with autism spectrum disorder (ASD), a group with known social deficits, as a comparison group. We also manipulated predictability using predictive and non-predictive cue blocks between subjects. Participants with and without ASD demonstrated similar cueing effects when cues were predictive. ASD participants showed no cueing advantage when cues were non-predictive while neurotypical participants experienced cueing only in social contexts when cues were non-predictive – consistent with automatic social processing. Intelligence as measured by the FSIQ from the WAIS 4 was also analyzed. Unexpectedly, higher IQ resulted in slower RTs with the ASD group. We examined this relationship further by examining severity of diagnosis measured by ADOS-G and FSIQ in participants with ASD. In a final study we looked at the relationship between RT and eye movements in visual search for social stimuli like faces and bodies. Consistent with previous results, faces resulted in faster RTs when they were the targets. They also elicited more first fixations and shorter fixation durations. Faces were not, however, more distracting when they appeared in irrelevant singleton frames. Unexpectedly, the bodies images used in this experiment did not result in attentional capture. Possible reasons for this are discussed. / Dissertation / Doctor of Psychology (PsyD) / As humans, other humans are among the most important things we visually perceive. They are sources of threat, alliance, uncertainty, and love. Because we cannot attend to all of the things we see at once, evolution has prepared us with mental traits that favour rapid processing of complex social scenes. Across three studies, we examine how other humans affect our attention. In the first study we confirm that human bodies and their parts (like feet or hands) are equally capable of drawing our attention. Our second study examines the ability of dynamic human poses to direct our attention in the direction of the depicted action. We note that an implied social interaction leads to better performance among typically developing individuals, but leads to deficits in individuals with autism spectrum disorder, a condition characterized by social delays and impairments. Finally, we look at how important social images, like human faces or bodies, unconsciously attract and influence our eyes movements when searching among distracting images.

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Much research has examined how rate affects visual preferences in human infants and auditory preferences in avian infants. In the visual domain, it seems that human infants prefer stimuli (e.g., flashing displays) presented at faster relative rates. Research using avian species has shown that ducklings, for example, prefer their species- specific maternal call only when it is presented at values close to the species-typical mean. These studies have shown that experience affects ducklings'­ preferences for rate in auditory events. Researchers in the areas of human infant preferences for visual rate and avian infant preferences for auditory rate have suggested that an effective window of frequencies exists for which infants show maximal attention. Unlike these two areas, little research has addressed how rate affects human infants' preferences for auditory events. A study by Cooper and Cooper (1997) was the first to find that infants attend to rates of speaking infant directed (ID) speech. Specifically, infants preferred ID speech at its normal rate to ID speech at a faster rate. The present study was intended to further investigate how rate of speaking affected infants' preferences for ID speech. More specifically, this study sought to determine whether a window of effective rates also exists for infant preferences for rate in ID speech. Using an infant-controlled preference procedure, 20 six- to eight-week old infants were presented with ID-normal speech (ID speech as its normal rate) and ID- slow speech (ID speech slowed to half the normal rate). It was found that infants looked longer to a visual display when it was paired with ID-slow speech than when it was paired with ID-normal speech. How these results relate to research and theory on visual rate preferences in human infants and auditory rate in avian species is discussed, as well as future directions for this line of research. / Master of Science

Benefit from the recent advancements of artificial intelligence (AI) methods, industrial automation has replaced human labors in many tasks. However, humans are still placed in the central role when visual searching tasks are highly involved for manufacturing decision-making. For example, highly customized products fabricated by additive manufacturing processes have posed significant challenges to AI methods in terms of their performance and generalizability. As a result, in practice, human visual searching tasks are still widely involved in manufacturing contexts (e.g., human resource management, quality inspection, etc.) based on various visualization techniques. Quantitatively modeling the visual searching behaviors and performance will not only contribute to the understanding of decision-making process in a visualization system, but also advance AI methods by incubating them with human expertise. In general, visual searching can be quantitatively understood from multiple scales, namely, 1) the population scale to treat individuals equally and model the general relationship between individual's physiological signals with visual searching decisions; 2) the individual scale to model the relationship between individual differences and visual searching decisions; and 3) the attention scale to model the relationship between individuals' attention in visual searching and visual searching decisions. The advancements of wearable sensing techniques enable such multiscale quantitative analytics of human visual searching performance. For example, by equipping human users with electroencephalogram (EEG) device, eye tracker, and logging system, the multiscale quantitative relationships among human physiological signals, behaviors and performance can be readily established. This dissertation attempts to quantify visual searching process from multiple scales by proposing (1) a data-fusion method to model the quantitative relationship between physiological signals and human's perceived task complexities (population scale, Chapter 2); (2) a recommender system to quantify and decompose the individual differences into explicit and implicit differences via personalized recommender system-based sensor analytics (individual scale, Chapter 3); and (3) a visual language processing modeling framework to identify and correlate visual cues (i.e., identified from fixations) with humans' quality inspection decisions in human visual searching tasks (attention scale, Chapter 4). Finally, Chapter 5 summarizes the contributions and proposes future research directions. The proposed methodologies can be readily extended to other applications and research studies to support multi-scale quantitative analytics. Besides, the quantitative understanding of human visual searching behaviors performance can also generate insights to further incubate AI methods with human expertise. Merits of the proposed methodologies are demonstrated in a visualization evaluation user study, and a cognitive hacking user study. Detailed notes to guide the implementation and deployment are provided for practitioners and researchers in each chapter. / Doctor of Philosophy / Existing industrial automation is limited by the performance and generalizability of artificial intelligence (AI) methods. Therefore, various human visual searching tasks are still widely involved in manufacturing contexts based on many visualization techniques, e.g., to searching for specific information, and to make decisions based on sequentially gathered information. Quantitatively modeling the visual searching performance will not only contribute to the understanding of human behaviors in a visualization system, but also advance the AI methods by incubating them with human expertise. In this dissertation, visual searching performance is characterized from multiple scales, namely, 1) the population scale to understand the visual searching performance in regardless of individual differences; 2) the individual scale to model the performance by quantifying individual differences; and 3) the attention scale to quantify the human visual searching-based decision-making process. Thanks to the advancements in wearable sensing techniques, this dissertation attempts to quantify visual searching process from multiple scales by proposing (1) a data-fusion method to model the quantitative relationship between physiological signals and human's perceived task complexities (population scale, Chapter 2); (2) a recommender system to suggest the best visualization design to the right person at the right time via sensor analytics (individual scale, Chapter 3); and (3) a visual language processing modeling framework to model humans' quality inspection decisions (attention scale, Chapter 4). Finally, Chapter 5 summarizes the contributions and proposes future research directions. Merits of the proposed methodologies are demonstrated in a visualization evaluation user study, and a cognitive hacking user study. The proposed methodologies can be readily extended to other applications and research studies to support multi-scale quantitative analytics.

A atenção visual é um conjunto de processos que permite processar preferencialmente uma informação visual em um dado momento. Muitos modelos de atenção visual propõem que a atenção pode ser destinada e focalizada a uma única localização no espaço por vez quando dicas espaciais são usadas para orientar esse deslocamento. Porém, diferentes estudos têm encontrado evidências de que em circunstâncias apropriadas, a atenção pode ser destinada a áreas não adjacentes do campo visual. O objetivo deste estudo foi investigar a distribuição da atenção por estas áreas quando o tamanho e a localização de dicas espaciais periféricas foram manipulados. Os resultados sugerem que a atenção visual pode ser destinada a mais de uma localização ao mesmo tempo como um gradiente com picos de processamento, mas que o tamanho das áreas indicadas não deve ser determinante para isso ocorrer. Os resultados indicam também que a habilidade para dividir a atenção pode depender da localização em que os eventos ocorrem em relação aos lados do campo visual. Eventos que ocorrem em lados opostos têm uma chance maior de serem beneficiados por focos independentes de atenção, enquanto eventos que ocorrem do mesmo lado do campo visual parecem ter mais chance de serem processados por um foco único de atenção, mas essa diferença parece ser relativa do que absoluta. Este estudo traz também contribuições para o entendimento do processo de focalização quando diferentes tarefas são solicitadas, revelando que o ajuste da atenção ao tamanho de uma área indicada é mais facilmente verificado em tarefas que requerem a detecção rápida de um alvo do que quando julgamentos de ordem temporal são solicitados. / Visual attention is a set of processes which permits a preferential processing of visual information in a given moment. Several models of visual attention propose that attention might be allocated and focused in only one location by time when spatial cues are used to orient this displacement. However, different studies have been finding evidences that in appropriate circumstances, attention can be deployed to non-adjacent areas of the visual field. The main objective of the present study was to investigate the distribution of attention on these areas when the size and the localization of peripheral spatial cues were manipulated. The results suggest that visual attention can be deployed to more than one location simultaneously as a gradient with peaks in processing quality. The results also indicate that the ability to divide attention might depend on the localization in which the events occur in relation to each hemifield. Events that occur in different hemifields have more chance to take advantage of independent focus of attention while events that happen on the same hemifield have more chance to be processed by a single attentional focus but that this difference seems to be relative than absolute. This study have also contributions for the understanding of the focalization process when different tasks are requested revealing that the adjustment of the attentional focus to the size of a cued area is more easily verified in tasks that require fast detection of an target than when temporal order judgments are requested.

A atenção visual é um conjunto de processos que permite processar preferencialmente uma informação visual em um dado momento. Muitos modelos de atenção visual propõem que a atenção pode ser destinada e focalizada a uma única localização no espaço por vez quando dicas espaciais são usadas para orientar esse deslocamento. Porém, diferentes estudos têm encontrado evidências de que em circunstâncias apropriadas, a atenção pode ser destinada a áreas não adjacentes do campo visual. O objetivo deste estudo foi investigar a distribuição da atenção por estas áreas quando o tamanho e a localização de dicas espaciais periféricas foram manipulados. Os resultados sugerem que a atenção visual pode ser destinada a mais de uma localização ao mesmo tempo como um gradiente com picos de processamento, mas que o tamanho das áreas indicadas não deve ser determinante para isso ocorrer. Os resultados indicam também que a habilidade para dividir a atenção pode depender da localização em que os eventos ocorrem em relação aos lados do campo visual. Eventos que ocorrem em lados opostos têm uma chance maior de serem beneficiados por focos independentes de atenção, enquanto eventos que ocorrem do mesmo lado do campo visual parecem ter mais chance de serem processados por um foco único de atenção, mas essa diferença parece ser relativa do que absoluta. Este estudo traz também contribuições para o entendimento do processo de focalização quando diferentes tarefas são solicitadas, revelando que o ajuste da atenção ao tamanho de uma área indicada é mais facilmente verificado em tarefas que requerem a detecção rápida de um alvo do que quando julgamentos de ordem temporal são solicitados. / Visual attention is a set of processes which permits a preferential processing of visual information in a given moment. Several models of visual attention propose that attention might be allocated and focused in only one location by time when spatial cues are used to orient this displacement. However, different studies have been finding evidences that in appropriate circumstances, attention can be deployed to non-adjacent areas of the visual field. The main objective of the present study was to investigate the distribution of attention on these areas when the size and the localization of peripheral spatial cues were manipulated. The results suggest that visual attention can be deployed to more than one location simultaneously as a gradient with peaks in processing quality. The results also indicate that the ability to divide attention might depend on the localization in which the events occur in relation to each hemifield. Events that occur in different hemifields have more chance to take advantage of independent focus of attention while events that happen on the same hemifield have more chance to be processed by a single attentional focus but that this difference seems to be relative than absolute. This study have also contributions for the understanding of the focalization process when different tasks are requested revealing that the adjustment of the attentional focus to the size of a cued area is more easily verified in tasks that require fast detection of an target than when temporal order judgments are requested.