Effects of menu structure and touch screen scrolling style on the variability of glance durations during in-vehicle visual search tasks

Effects of In-Vehicle Touchscreen Location on Driver Task Performance, Eye Gaze Behavior, and Workload During Conditionally Automated Driving: Nondriving-Related Task and Take-Over

OBJECTIVE

This study investigated the effects of nondriving-related task (NDRT) touchscreen location and NDRT difficulty level on the driver task performance, eye gaze behavior, and workload during SAE Level 3 conditionally automated driving. Two driver tasks were considered: a visuomanual NDRT and a take-over task.

BACKGROUND

Touchscreens are expected to play important roles inside automated vehicles. However, few studies have investigated the driver-touchscreen interaction during automated driving.

METHOD

A driving simulator experiment was conducted. The experimental task consisted of two successive subtasks: an NDRT followed by a take-over task. NDRT touchscreen location (Upper Left, Upper Right, and Lower Right) and NDRT difficulty level (Easy and Hard) were the independent variables. A set of driver task performance, eye gaze behavior, and perceived workload measures were employed for each subtask as the dependent variables.

RESULTS

NDRT touchscreen location significantly affected both the NDRT and the take-over task performance. Lower Right was superior to Upper Right in the NDRT performance but was inferior in the take-over task performance. NDRT touchscreen location affected the perceived physical workload of the NDRT. NDRT difficulty level affected the perceived workload of the take-over task.

CONCLUSION

The research findings enhance our understanding of how NDRT touchscreen location and NDRT difficulty level impact the driver task performance during conditionally automated driving, and, further provide useful design implications and knowledge.

APPLICATION

The study results would inform the NDRT touchscreen interface design and the NDRT design for conditionally automated vehicles.

Gaze entropy metrics for mental workload estimation are heterogenous during hands-off level 2 automation

As the level of vehicle automation increases, drivers are more likely to engage in non-driving related tasks which take their hands, eyes, and/or mind away from the driving task. Consequently, there has been increased interest in creating Driver Monitoring Systems (DMS) that are valid and reliable for detecting elements of driver state. Workload is one element of driver state that has remained elusive within the literature. Whilst there has been promising work in estimating mental workload using gaze-based metrics, the literature has placed too much emphasis on point estimate differences. Whilst these are useful for establishing whether effects exist, they ignore the inherent variability within individuals and between different drivers. The current work builds on this by using a Bayesian distributional modelling approach to quantify the within and between participants variability in Information Theoretical gaze metrics. Drivers (N = 38) undertook two experimental drives in hands-off Level 2 automation with their hands and feet away from operational controls. During both drives, their priority was to monitor the road before a critical takeover. During one drive participants had to complete a secondary cognitive task (2-back) during the hands-off Level 2 automation. Changes in Stationary Gaze Entropy and Gaze Transition Entropy were assessed for conditions with and without the 2-back to investigate whether consistent differences between workload conditions could be found across the sample. Stationary Gaze Entropy proved a reliable indicator of mental workload; 92 % of the population were predicted to show a decrease when completing 2-back during hands-off Level 2 automated driving. Conversely, Gaze Transition Entropy showed substantial heterogeneity; only 66 % of the population were predicted to have similar decreases. Furthermore, age was a strong predictor of the heterogeneity of the average causal effect that high mental workload had on eye movements. These results indicate that, whilst certain elements of Information Theoretic metrics can be used to estimate mental workload by DMS, future research needs to focus on the heterogeneity of these processes. Understanding this heterogeneity has important implications toward the design of future DMS and thus the safety of drivers using automated vehicle functions. It must be ensured that metrics used to detect mental workload are valid (accurately detecting a particular driver state) as well as reliable (consistently detecting this driver state across a population).

Interruption in visual search: a systematic review

Visual search, the process of trying to find a target presented among distractors, is a much-studied cognitive task. Less well-studied is the condition in which the search task is interrupted before the target is found. The consequences of such interruptions in visual search have been investigated across various disciplines, which has resulted in diverse and at times contradictory findings. The aim of this systematic review is to provide a more cohesive understanding of the effects of interruptions in visual search. For this purpose, we identified 28 studies that met our inclusion criteria. To facilitate a more organized and comprehensive analysis, we grouped the studies based on three dimensions: the search environment, the interruption aftermath, and the type of the interrupting event. While interruptions in visual search are variable and manifest differently across studies, our review provides a foundational scheme for a more cohesive understanding of the subject. This categorization serves as a starting point for exploring potential future directions, which we delineate in our conclusions.

Evaluation of the optimal quantity of in-vehicle information icons using a fuzzy synthetic evaluation model in a driving simulator

In-Vehicle Information (IVI) features such as navigation assistance play an important role in the travel of drivers around the world. Frequent use of IVI, however, can easily increase the cognitive load of drivers. The interface design, especially the quantity of icons presented to the driver such as those for navigation, music, and phone calls, has not been fully researched. To determine the optimal number of icons, a systematic evaluation of the IVI Human Machine Interface (HMI) was examined using single-factor and multivariate analytical methods in a driving simulator. When one-way ANOVA was performed, the results showed that the 3-icon design scored best in subjective driver assessment, and the 4-icon design was best in the steering wheel angle. However, when a new method of analyzing the data that enabled a simultaneous accounting of changes observed in the dependent measures, 3 icons had the highest score (that is, revealed the overall best performance). This method is referred to as the fuzzy synthetic evaluation model (FSE). It represents the first use of it in an assessment of the HMI design of IVI. The findings also suggest that FSE will be applicable to various other HMI design problems.

Tracking and discrete dual task performance for different visual spatial stimulus-response mappings with focal and ambient vision

The effect of spatial compatibility for various display-control configurations on human performance was studied with a dual-task paradigm using a tracking task and a discrete response task. Degradation of performance on both tasks within the visual modality was observed and was considered to be most likely due to resource competition resulting from simultaneous task operation. It was found that the more complicated the mapping for the discrete spatial compatibility response task, the more severe the interference with the tracking task. Although performance on both the tracking and spatial response tasks was impaired, the magnitude of impairment was not as great as expected, implying that focal and ambient vision required for the tracking task and spatial task, respectively, might be deployed, at least partly, from separate resources. Participants here seemed to successfully use focal vision for tracking and ambient vision for identifying signal lights concurrently, reducing the expected keen competition for visual resources.

Semantic distance as a critical factor in icon design for in-car infotainment systems

In-car infotainment systems require icons that enable fluent cognitive information processing and safe interaction while driving. An important issue is how to find an optimised set of icons for different functions in terms of semantic distance. In an optimised icon set, every icon needs to be semantically as close as possible to the function it visually represents and semantically as far as possible from the other functions represented concurrently. In three experiments (N = 21 each), semantic distances of 19 icons to four menu functions were studied with preference rankings, verbal protocols, and the primed product comparisons method. The results show that the primed product comparisons method can be efficiently utilised for finding an optimised set of icons for time-critical applications out of a larger set of icons. The findings indicate the benefits of the novel methodological perspective into the icon design for safety-critical contexts in general.

Staying Connected on the Road: A Comparison of Different Types of Smart Phone Use in a Driving Simulator

Previous research on smart phone use while driving has primarily focused on phone calls and texting. Drivers are now increasingly using their phone for other activities during driving, in particular social media, which have different cognitive demands. The present study compared the effects of four different smart phone tasks on car-following performance in a driving simulator. Phone tasks were chosen that vary across two factors: interaction medium (text vs image) and task pacing (self-paced vs experimenter-paced) and were as follows: Text messaging with the experimenter (text/other-paced), reading Facebook posts (text/self-paced), exchanging photos with the experimenter via Snapchat (image, experimenter -paced), and viewing updates on Instagram (image, experimenter -paced). Drivers also performed a driving only baseline. Brake reaction times (BRTs) were significantly greater in the text-based conditions (Mean = 1.16 s) as compared to both the image-based conditions (Mean = 0.92 s) and the baseline (0.88 s). There was no significant difference between BRTs in the image-based and baseline conditions and there was no significant effect of task-pacing. Similar results were obtained for Time Headway variability. These results are consistent with the picture superiority effect found in memory research and suggest that image-based interfaces could provide safer ways to “stay connected” while driving than text-based interfaces.

Modelling the hare and the tortoise: predicting the range of in-vehicle task times using critical path analysis

Analytic models can enable predictions about important aspects of the usability of in-vehicle information systems (IVIS) to be made at an early stage of the product development process. Task times provide a quantitative measure of user performance and are therefore important in the evaluation of IVIS usability. In this study, critical path analysis (CPA) was used to model IVIS task times in a stationary vehicle, and the technique was extended to produce predictions for slowperson and fastperson performance, as well as average user (middleperson) performance. The CPA-predicted task times were compared to task times recorded in an empirical simulator study of IVIS interaction, and the predicted times were, on average, within acceptable precision limits. This work forms the foundation for extension of the CPA model to predict IVIS task times in a moving vehicle, to reflect the demands of the dual-task driving scenario.

PRACTITIONER SUMMARY

The CPA method was extended for the prediction of slowperson and fastperson IVIS task times. Comparison of the model predictions with empirical data demonstrated acceptable precision. The CPA model can be used in early IVIS evaluation; however, there is a need to extend it to represent the dual-task driving scenario.

Visual and memory search in complex environments: determinants of eye movements and search performance

Previous research on visual and memory search revealed various top down and bottom up factors influencing performance. However, utilising abstract stimuli (e.g. geometrical shapes or letters) and focussing on individual factors has often limited the applicability of research findings. Two experiments were designed to analyse which attributes of a product facilitate search in an applied environment. Participants scanned displays containing juice packages while their eye movements were recorded. The familiarity, saliency, and position of search targets were systematically varied. Experiment 1 involved a visual search task, whereas Experiment 2 focussed on memory search. The results showed that bottom up (target saliency) and top down (target familiarity) factors strongly interacted. Overt visual attention was influenced by cultural habits, purposes, and current task demands. The results provide a solid database for assessing the impact and interplay of fundamental top down and bottom up determinants of search processes in applied fields of psychology. Practitioner Summary: Our study demonstrates how a product (or a visual item in general) needs to be designed and placed to ensure that it can be found effectively and efficiently within complex environments. Corresponding product design should result in faster and more accurate visual and memory based search processes.

Effect of display polarity and luminance contrast on visual lobe shape characteristics

The effect of display polarity and luminance contrast on visual lobe (effective visual field) shape characteristics was studied using three levels of luminance contrast with combinations of positive and negative polarities. The binocular effective visual field for a detection task, with a peripherally presented target (V) embedded in a homogeneous competing background (Xs), was mapped on 24 imaginary axes passing through the fixation point. The results showed that visual lobes mapped using positive polarity were statistically larger in area, rounder and more regular in shape than those for negative polarity. The medium contrast condition lobes were more symmetric and regular than low contrast condition lobes, and lobe area and perimeter increased with increasing luminance contrast ratio. Under the interaction of positive polarity and high luminance contrast, visual lobes were found to be larger, smoother and rounder. The high level of luminance and contrast however resulted in a higher degree of visual discomfort. The results indicated that positive polarity and contrast of medium (26:1) to high (41:1) levels are possible display settings for better visual lobe characteristics and better anticipated search performance. Practitioner Summary: The effect of display polarity and luminance contrast on visual lobe shape characteristics was examined with uniform stimulus materials in this study. The results help to identify the optimum display settings for luminance contrast and display polarity to enhance lobe shape characteristics and hence search performance in industrial inspection tasks.