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Voice interfaces reduce visual demand compared with visual-manual interfaces, but the extent depends on design. This study compared visual demand during baseline driving with driving while using voice or manual inputs to place calls with Chevrolet MyLink, Volvo Sensus, or a smartphone. Mean glance duration and total eyes-off-road-time increased when using manual input compared with baseline driving; only eyes off road time increased with voice input. Confusion matrices developed with hidden Markov modelling characterise the similarity of glance sequences during baseline driving and while making phone calls. Glance sequences with the MyLink voice interface were misclassified as baseline driving more frequently than the other voice interfaces. Conversely, glance sequences with the Sensus and smartphone voice interfaces were more often misclassified as manual phone calling. Thus, the MyLink voice interface not only reduced the overall visual demand of placing calls, but produced glance patterns more similar to driving without another task. Practitioner Summary: The attention map and confusion matrix methodologies provide ways of characterising similarities and differences in glance behaviour across secondary task conditions, complementing traditional temporally based metrics (e.g. mean glance duration, long duration glances) while addressing some of the limitations of total-eyes-off-road-time (TEORT) for comparing secondary task behaviour to baseline driving.

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Modern digital interfaces display typeface in ways new to the 500 year old art of typography, driving a shift in reading from primarily long-form to increasingly short-form. In safety-critical settings, such at-a-glance reading competes with the need to understand the environment. To keep both type and the environment legible, a variety of 'middle layer' approaches are employed. But what is the best approach to presenting type over complex backgrounds so as to preserve legibility? This work tests and ranks middle layers in three studies. In the first study, Gaussian blur and semi-transparent 'scrim' middle layer techniques best maximise legibility. In the second, an optimal combination of the two is identified. In the third, letter-localised middle layers are tested, with results favouring drop-shadows. These results, discussed in mixed reality (MR) including overlays, virtual reality (VR), and augmented reality (AR), considers a future in which glanceable reading amidst complex backgrounds is common. Practitioner summary: Typography over complex backgrounds, meant to be read and understood at a glance, was once niche but today is a growing design challenge for graphical user interface HCI. We provide a technique, evidence-based strategies, and illuminating results for maximising legibility of glanceable typography over complex backgrounds. Abbreviations: AR: augmented reality; VR: virtual reality; HUD: head-up display; OLED: organic light-emitting diode; UX: user experience; MS: millisecond; CM: centimeter.

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Typography plays an increasingly important role in today's dynamic digital interfaces. Graphic designers and interface engineers have more typographic options than ever before. Sorting through this maze of design choices can be a daunting task. Here we present the results of an experiment comparing differences in glance-based legibility between eight popular sans-serif typefaces. The results show typography to be more than a matter of taste, especially in safety critical contexts such as in-vehicle interfaces. Our work provides both a method and rationale for using glanceable typefaces, as well as actionable information to guide design decisions for optimised usability in the fast-paced mobile world in which information is increasingly consumed in a few short glances. Practitioner summary: There is presently no accepted scientific method for comparing font legibility under time-pressure, in 'glanceable' interfaces such as automotive displays and smartphone notifications. A 'bake-off' method is demonstrated with eight popular sans-serif typefaces. The results produce actionable information to guide design decisions when information must be consumed at-a-glance. Abbreviations: DOT: department of transportation; FAA: Federal Aviation Administration; GHz: gigahertz; Hz: hertz; IEC: International Electrotechnical Commission; ISO: International Organization for Standardization; LCD: liquid crystal display; MIT: Massachusetts Institute of Technology; ms: milliseconds; OS: operating system.

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The impact of using a smartwatch to initiate phone calls on driver workload, attention, and performance was compared to smartphone visual-manual (VM) and auditory-vocal (AV) interfaces. In a driving simulator, 36 participants placed calls using each method. While task time and number of glances were greater for AV calling on the smartwatch vs. smartphone, remote detection task (R-DRT) responsiveness, mean single glance duration, percentage of long duration off-road glances, total off-road glance time, and percent time looking off-road were similar; the later metrics were all significantly higher for the VM interface vs. AV methods. Heart rate and skin conductance were higher during phone calling tasks than "just driving", but did not consistently differentiate calling method. Participants exhibited more erratic driving behavior (lane position and major steering wheel reversals) for smartphone VM calling compared to both AV methods. Workload ratings were lower for AV calling on both devices vs. VM calling.

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Reading at a glance, once a relatively infrequent mode of reading, is becoming common. Mobile interaction paradigms increasingly dominate the way in which users obtain information about the world, which often requires reading at a glance, whether from a smartphone, wearable device, or in-vehicle interface. Recent research in these areas has shown that a number of factors can affect text legibility when words are briefly presented in isolation. Here we expand upon this work by examining how legibility is affected by more crowded presentations. Word arrays were combined with a lexical decision task, in which the size of the text elements and the inter-line spacing (leading) between individual items were manipulated to gauge their relative impacts on text legibility. In addition, a single-word presentation condition that randomized the location of presentation was compared with previous work that held position constant. Results show that larger text was more legible than smaller text. Wider leading significantly enhanced legibility as well, but contrary to expectations, wider leading did not fully counteract decrements in legibility at smaller text sizes. Single-word stimuli presented with random positioning were more difficult to read than stationary counterparts from earlier studies. Finally, crowded displays required much greater processing time compared to single-word displays. These results have implications for modern interface design, which often present interactions in the form of scrollable and/or selectable lists. The present findings are of practical interest to the wide community of graphic designers and interface engineers responsible for developing our interfaces of daily use.

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Applied research on driving and basic vision research have held similar views on central, fovea-based vision as the core of visual perception. In applied work, the concept of the Useful Field, as determined by the Useful Field of View (UFOV) test, divides vision between a "useful" region towards the center of the visual field, and the rest of the visual field. While compelling, this dichotomization is at odds with findings in vision science which demonstrate the capabilities of peripheral vision. In this paper, we examine driving research from this new perspective, and argue for the need for an updated understanding of how drivers acquire information about their operating environment using peripheral vision. The concept of the Useful Field and the UFOV test are not discarded; instead we discuss their strengths, limitations, and future directions. We discuss key findings from vision science on peripheral vision, and a theory that provides insights into its capabilities and limitations. This more complete basic science understanding of peripheral vision informs appropriate use of the UFOV and the Useful Field in driving research going forward.

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Recent research on the legibility of digital displays has demonstrated a "positive polarity advantage", in which black-on-white text configurations are more legible than their negative polarity, white-on-black counterparts. Existing research in this area suggests that the positive polarity advantage stems from the brighter illumination emitted by positive polarity displays, as opposed to the darker backgrounds of negative polarity displays. In the present study, legibility thresholds were measured under glance-like reading conditions using a lexical decision paradigm, testing two type sizes, display polarities, and ambient illuminations (near-dark and daylight-like). Results indicate that legibility thresholds, quantified as the amount of time needed to read a word accurately, were highest for the negative polarity configurations under dark ambient illumination, indicated worse performance. Conversely, the positive polarity conditions under dark ambient illumination and all conditions under bright illumination demonstrated significantly reduced thresholds, indicating greater legibility. These results are consistent with the hypothesis that the "positive polarity advantage" arises because brighter illumination produces pupillary contraction that reduces optical aberrations as light enters the eye. These results have implications for the design of automotive interfaces and other scenarios in which an interface must be optimized for glance-like reading under variations in ambient lighting conditions.

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There is limited research on trade-offs in demand between manual and voice interfaces of embedded and portable technologies. Mehler et al. identified differences in driving performance, visual engagement and workload between two contrasting embedded vehicle system designs (Chevrolet MyLink and Volvo Sensus). The current study extends this work by comparing these embedded systems with a smartphone (Samsung Galaxy S4). None of the voice interfaces eliminated visual demand. Relative to placing calls manually, both embedded voice interfaces resulted in less eyes-off-road time than the smartphone. Errors were most frequent when calling contacts using the smartphone. The smartphone and MyLink allowed addresses to be entered using compound voice commands resulting in shorter eyes-off-road time compared with the menu-based Sensus but with many more errors. Driving performance and physiological measures indicated increased demand when performing secondary tasks relative to 'just driving', but were not significantly different between the smartphone and embedded systems. Practitioner Summary: The findings show that embedded system and portable device voice interfaces place fewer visual demands on the driver than manual interfaces, but they also underscore how differences in system designs can significantly affect not only the demands placed on drivers, but also the successful completion of tasks.

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Psychophysical research on text legibility has historically investigated factors such as size, colour and contrast, but there has been relatively little direct empirical evaluation of typographic design itself, particularly in the emerging context of glance reading. In the present study, participants performed a lexical decision task controlled by an adaptive staircase method. Two typefaces, a 'humanist' and 'square grotesque' style, were tested. Study I examined positive and negative polarities, while Study II examined two text sizes. Stimulus duration thresholds were sensitive to differences between typefaces, polarities and sizes. Typeface also interacted significantly with age, particularly for conditions with higher legibility thresholds. These results are consistent with previous research assessing the impact of the same typefaces on interface demand in a simulated driving environment. This simplified methodology of assessing legibility differences can be adapted to investigate a wide array of questions relevant to typographic and interface designs. Practitioner Summary: A method is described for rapidly investigating relative legibility of different typographical features. Results indicate that during glance-like reading induced by the psychophysical technique and under the lighting conditions considered, humanist-style type is significantly more legible than a square grotesque style, and that black-on-white text is significantly more legible than white-on-black.

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One purpose of integrating voice interfaces into embedded vehicle systems is to reduce drivers' visual and manual distractions with 'infotainment' technologies. However, there is scant research on actual benefits in production vehicles or how different interface designs affect attentional demands. Driving performance, visual engagement, and indices of workload (heart rate, skin conductance, subjective ratings) were assessed in 80 drivers randomly assigned to drive a 2013 Chevrolet Equinox or Volvo XC60. The Chevrolet MyLink system allowed completing tasks with one voice command, while the Volvo Sensus required multiple commands to navigate the menu structure. When calling a phone contact, both voice systems reduced visual demand relative to the visual-manual interfaces, with reductions for drivers in the Equinox being greater. The Equinox 'one-shot' voice command showed advantages during contact calling but had significantly higher error rates than Sensus during destination address entry. For both secondary tasks, neither voice interface entirely eliminated visual demand. Practitioner Summary: The findings reinforce the observation that most, if not all, automotive auditory-vocal interfaces are multi-modal interfaces in which the full range of potential demands (auditory, vocal, visual, manipulative, cognitive, tactile, etc.) need to be considered in developing optimal implementations and evaluating drivers' interaction with the systems. Social Media: In-vehicle voice-interfaces can reduce visual demand but do not eliminate it and all types of demand need to be taken into account in a comprehensive evaluation.

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Aging-related changes in the visual system diminish the capacity to perceive the world with the ease and fidelity younger adults are accustomed to. Among many consequences of this, older adults find that text that they could once read easily proves difficult to read, even with sufficient acuity correction. Building on previous work examining visual factors in legibility, we examine potential causes for these age-related effects in the absence of other ocular pathology. We asked participants to discriminate words from non-words in a lexical decision task. The stimuli participants viewed were either blurred or presented in a noise field to simulate, respectively, decreased sensitivity to fine detail (loss of acuity) and detuning of visually selective neurons. We then use the differences in performance between older and younger participants to suggest how older participants' performance could be approximated to facilitate maximally usable designs.

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Text-rich driver-vehicle interfaces are increasingly common in new vehicles, yet the effects of different typeface characteristics on task performance in this brief off-road based glance context remains sparsely examined. Subjects completed menu selection tasks while in a driving simulator. Menu text was set either in a 'humanist' or 'square grotesque' typeface. Among men, use of the humanist typeface resulted in a 10.6% reduction in total glance time as compared to the square grotesque typeface. Total response time and number of glances showed similar reductions. The impact of typeface was either more modest or not apparent for women. Error rates for both males and females were 3.1% lower for the humanist typeface. This research suggests that optimised typefaces may mitigate some interface demands. Future work will need to assess whether other typeface characteristics can be optimised to further reduce demand, improve legibility, increase usability and help meet new governmental distraction guidelines. Practitioner Summary: Text-rich in-vehicle interfaces are increasingly common, but the effects of typeface on task performance remain sparsely studied. We show that among male drivers, menu selection tasks are completed with 10.6% less visual glance time when text is displayed in a 'humanist' typeface, as compared to a 'square grotesque'.

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Visual perceptual learning (VPL) is defined as a long-term performance enhancement on a visual task, and is typically thought of as a manifestation of plasticity in visual processing. It is thought that neural representations relevant to a recently learned task are consolidated over the course of hours or days and made robust against the effects of deterioration and interference. However, recent work has shown that when these representations are reactivated by further task exposure, they become plastic again and are vulnerable to deterioration effects. Here we used a perceptual learning paradigm in combination with performance feedback (knowledge of task accuracy provided to the observer in real-time) to investigate behavioral factors that influence consolidation. Subjects were trained to detect two coherent motion directions embedded in noise over several days. It was found that without feedback, performance improvements accrued during training rapidly deteriorated upon exposure to novel, neighboring motion directions. However, when one of the two directions was consistently paired with feedback during training, the paired direction was resilient against the effects of deterioration. This benefit coincides with a gradual inhibition of learning for the unpaired stimuli. Furthermore, this stabilizing effect operates independently of the magnitude of performance gains during training and suggests a useful behavioral marker for the study of consolidation processes.

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Classification image analysis is a psychophysical technique in which noise components of stimuli are analyzed to produce an image that reveals critical features of a task. Here we use classification images to gain greater understanding of perceptual learning. To achieve reasonable classification images within a single session, we developed an efficient classification image procedure that employed designer noise and a low-dimensional stimulus space. Subjects were trained across ten sessions to detect the orientation of a grating masked in noise, with an eleventh, test, session conducted using a stimulus orthogonal to the trained stimulus. As with standard perceptual learning studies, subjects showed improvements in performance metrics of accuracy, threshold, and reaction times. The clarity of the classification images and their correlation to an ideal target also improved across training sessions in an orientation-specific manner. Furthermore, image-based analyses revealed aspects of performance that could not be observed with standard performance metrics. Subjects with threshold improvements learned to use pixels across a wider area of the image, and, apposed to subjects without threshold improvements, showed improvements in both the bright and dark parts of the image. We conclude that classification image analysis is an important complement to traditional metrics of perceptual learning.

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