On the relationship between occlusion times and in-car glance durations in simulated driving.

Drivers have spare visual capacity in driving, and often this capacity is used for engaging in secondary in-car tasks. Previous research has suggested that the spare visual capacity could be estimated with the occlusion method. However, the relationship between drivers' occlusion times and in-car glance duration preferences has not been sufficiently investigated for granting occlusion times the role of an estimate of spare visual capacity. We conducted a driving simulator experiment (N = 30) and investigated if there is an association between drivers' occlusion times and in-car glance durations in a given driving scenario. Furthermore, we explored which factors and variables could explain the strength of the association. The findings suggest an association between occlusion time preferences and in-car glance durations in visually and cognitively low demanding unstructured tasks but that this association is lost if the in-car task is more demanding. The findings might be explained by the inability to utilize peripheral vision for lane-keeping when conducting in-car tasks and/or by in-car task structures that override drivers' preferences for the in-car glance durations. It seems that the occlusion technique could be utilized as an estimate of drivers' spare visual capacity in research - but with caution. It is strongly recommended to use occlusion times in combination with driving performance metrics. There is less spare visual capacity if this capacity is used for secondary tasks that interfere with the driver's ability to utilize peripheral vision for driving or preferences for the in-car glance durations. However, we suggest that the occlusion method can be a valid method to control for inter-individual differences in in-car glance duration preferences when investigating the visual distraction potential of, for instance, in-vehicle infotainment systems.

A Review of Occlusion as a Tool to Assess Attentional Demand in Driving.

OBJECTIVE: The aim of this review is to identify how visual occlusion contributes to our understanding of attentional demand and spare visual capacity in driving and the strengths and limitations of the method. BACKGROUND: The occlusion technique was developed by John W. Senders to evaluate the attentional demand of driving. Despite its utility, it has been used infrequently in driver attention/inattention research. METHOD: Visual occlusion studies in driving published between 1967 and 2020 were reviewed. The focus was on original studies in which the forward visual field was intermittently occluded while the participant was driving. RESULTS: Occlusion studies have shown that attentional demand varies across situations and drivers and have indicated environmental, situational, and inter-individual factors behind the variability. The occlusion technique complements eye tracking in being able to indicate the temporal requirements for and redundancy in visual information sampling. The proper selection of occlusion settings depends on the target of the research. CONCLUSION: Although there are a number of occlusion studies looking at various aspects of attentional demand, we are still only beginning to understand how these demands vary, interact, and covary in naturalistic driving. APPLICATION: The findings of this review have methodological and theoretical implications for human factors research and for the development of distraction monitoring and in-vehicle system testing. Distraction detection algorithms and testing guidelines should consider the variability in drivers' situational and individual spare visual capacity.

Neuroaesthetic exploration on the cognitive processing behind repeating graphics.

Repeating graphics are common research objects in modern design education. However, we do not exactly know the attentional processes underlying graphic artifacts consisting of repeating rhythms. In this experiment, the event-related potential, a neuroscientific measure, was used to study the neural correlates of repeating graphics within graded orderliness. We simulated the competitive identification process of people recognizing artifacts with graded repeating rhythms from a scattered natural environment with the oddball paradigm. In the earlier attentional processing related to the P2 component around the Fz electrode within the 150-250 ms range, a middle-grade repeating rhythm (Target 1) did not show a difference from a high-grade repeating rhythm (Target 2). However, in the later cognitive processes related to the P3b component around the Pz electrode within the 300-450 ms range, Target 1 had longer peak latency than Target 2, based on similar waveforms. Thus, we may suppose that the arrangement of the repeating graphics did not influence the earlier attentional processing but affected the later cognitive part, such as the categorization task in the oddball paradigm. Furthermore, as evidenced by the standard deviation wave across the trials, we suggest that the growing standard deviation value might represent the gradual loss of attentional focus to the task after the stimulus onset and that the zero-growth level may represent similar brain activity between trials.

Multitasking in Driving as Optimal Adaptation Under Uncertainty.

OBJECTIVE: The objective was to better understand how people adapt multitasking behavior when circumstances in driving change and how safe versus unsafe behaviors emerge. BACKGROUND: Multitasking strategies in driving adapt to changes in the task environment, but the cognitive mechanisms of this adaptation are not well known. Missing is a unifying account to explain the joint contribution of task constraints, goals, cognitive capabilities, and beliefs about the driving environment. METHOD: We model the driver's decision to deploy visual attention as a stochastic sequential decision-making problem and propose hierarchical reinforcement learning as a computationally tractable solution to it. The supervisory level deploys attention based on per-task value estimates, which incorporate beliefs about risk. Model simulations are compared against human data collected in a driving simulator. RESULTS: Human data show adaptation to the attentional demands of ongoing tasks, as measured in lane deviation and in-car gaze deployment. The predictions of our model fit the human data on these metrics. CONCLUSION: Multitasking strategies can be understood as optimal adaptation under uncertainty, wherein the driver adapts to cognitive constraints and the task environment's uncertainties, aiming to maximize the expected long-term utility. Safe and unsafe behaviors emerge as the driver has to arbitrate between conflicting goals and manage uncertainty about them. APPLICATION: Simulations can inform studies of conditions that are likely to give rise to unsafe driving behavior.

Inattention and Uncertainty in the Predictive Brain.

Negative effects of inattention on task performance can be seen in many contexts of society and human behavior, such as traffic, work, and sports. In traffic, inattention is one of the most frequently cited causal factors in accidents. In order to identify inattention and mitigate its negative effects, there is a need for quantifying attentional demands of dynamic tasks, with a credible basis in cognitive modeling and neuroscience. Recent developments in cognitive science have led to theories of cognition suggesting that brains are an advanced prediction engine. The function of this prediction engine is to support perception and action by continuously matching incoming sensory input with top-down predictions of the input, generated by hierarchical models of the statistical regularities and causal relationships in the world. Based on the capacity of this predictive processing framework to explain various mental phenomena and neural data, we suggest it also provides a plausible theoretical and neural basis for modeling attentional demand and attentional capacity "in the wild" in terms of uncertainty and prediction error. We outline a predictive processing approach to the study of attentional demand and inattention in driving, based on neurologically-inspired theories of uncertainty processing and experimental research combining brain imaging, visual occlusion and computational modeling. A proper understanding of uncertainty processing would enable comparison of driver's uncertainty to a normative level of appropriate uncertainty, and thereby improve definition and detection of inattentive driving. This is the necessary first step toward applications such as attention monitoring systems for conventional and semi-automated driving.

Expert Drivers' Prospective Thinking-Aloud to Enhance Automated Driving Technologies - Investigating Uncertainty and Anticipation in Traffic.

Current automated driving technology cannot cope in numerous conditions that are basic daily driving situations for human drivers. Previous studies show that profound understanding of human drivers' capability to interpret and anticipate traffic situations is required in order to provide similar capacities for automated driving technologies. There is currently not enough a priori understanding of these anticipatory capacities for safe driving applicable to any given driving situation. To enable the development of safer, more economical, and more comfortable automated driving experience, expert drivers' anticipations and related uncertainties were studied on public roads. First, driving instructors' expertise in anticipating traffic situations was validated with a hazard prediction test. Then, selected driving instructors drove in real traffic while thinking aloud anticipations of unfolding events. The results indicate sources of uncertainty and related adaptive and social behaviors in specific traffic situations and environments. In addition, the applicability of these anticipatory capabilities to current automated driving technology is discussed. The presented method and results can be utilized to enhance automated driving technologies by indicating their potential limitations and may enable improved situation awareness for automated vehicles. Furthermore, the produced data can be utilized for recognizing such upcoming situations, in which the human should take over the vehicle, to enable timely take-over requests.

On the Difference Between Necessary and Unnecessary Glances Away From the Forward Roadway: An Occlusion Study on the Motorway.

OBJECTIVE: The present study strove to distinguish traffic-related glances away from the forward roadway from non-traffic-related glances while assessing the minimum amount of visual information intake necessary for safe driving in particular scenarios. BACKGROUND: Published gaze-based distraction detection algorithms and guidelines for distraction prevention essentially measure the time spent looking away from the forward roadway, without incorporating situation-based attentional requirements. Incorporating situation-based attentional requirements would entail an approach that not only considers the time spent looking elsewhere but also checks whether all necessary information has been sampled. METHOD: We assess the visual sampling requirements for the forward view based on 25 experienced drivers' self-paced visual occlusion in real motorway traffic, dependent on a combination of situational factors, and compare these with their corresponding glance behavior in baseline driving. RESULTS: Occlusion durations were on average 3 times longer than glances away from the forward roadway, and they varied substantially depending on particular maneuvers and on the proximity of other traffic, showing that interactions with nearby traffic increase perceived uncertainty. The frequency of glances away from the forward roadway was relatively stable across proximity levels and maneuvers, being very similar to what has been found in naturalistic driving. CONCLUSION: Glances away from the forward roadway proved qualitatively different from occlusions in both their duration and when they occur. Our findings indicate that glancing away from the forward roadway for driving purposes is not the same as glancing away for other purposes, and that neither is necessarily equivalent to distraction.

Naturalistic study on the usage of smartphone applications among Finnish drivers.

We present results from a naturalistic study that tracked how Finnish drivers use their smartphones while on the move. We monitored 30 heavy in-car smartphone users in Finland during June-September 2016, recording the times that they used their phones, the application used at the time of touch (calls excluded), the location and driving speed. Touches per time unit were used as a proxy for estimating visual-manual distraction due to visual-manual tasks. Our data set allows the determining of whether drivers use their phones differently on varying road types (highway, main road, local rural road, urban road). We found that the road type has an effect on phone use but the effect is contrary to what we expected. Drivers produced more touches per hour on urban roads, yet the use instances tend to be shorter than on the highway or main roads. We also collected statistics on the applications that were used. By far the highest overall rankings in the number of drivers using, number of uses, and duration per use instance was associated with the WhatsApp messaging service. One instance of WhatsApp use had a median of 8 touches, and had a median duration of 35 s. In contrast, navigation application use included a median of 3 touches and lasted for 11 s. The findings suggest that the Finnish smartphone heavy-users do not decrease their phone use when the demands of the traffic conditions increase and that the greatest risk from smartphone use may be currently caused by messaging applications.

Network Entropy for the Sequence Analysis of Functional Connectivity Graphs of the Brain.

Dynamic representation of functional brain networks involved in the sequence analysis of functional connectivity graphs of the brain (FCGB) gains advances in uncovering evolved interaction mechanisms. However, most of the networks, even the event-related ones, are highly heterogeneous due to spurious interactions, which bring challenges to revealing the change patterns of interactive information in the complex dynamic process. In this paper, we propose a network entropy (NE) method to measure connectivity uncertainty of FCGB sequences to alleviate the spurious interaction problem in dynamic network analysis to realize associations with different events during a complex cognitive task. The proposed dynamic analysis approach calculated the adjacency matrices from ongoing electroencephalpgram (EEG) in a sliding time-window to form the FCGB sequences. The probability distribution of Shannon entropy was replaced by the connection sequence distribution to measure the uncertainty of FCGB constituting NE. Without averaging, we used time frequency transform of the NE of FCGB sequences to analyze the event-related changes in oscillatory activity in the single-trial traces during the complex cognitive process of driving. Finally, the results of a verification experiment showed that the NE of the FCGB sequences has a certain time-locked performance for different events related to driver fatigue in a prolonged driving task. The time errors between the extracted time of high-power NE and the recorded time of event occurrence were distributed within the range [-30 s, 30 s] and 90.1% of the time errors were distributed within the range [-10 s, 10 s]. The high correlation (r = 0.99997, p < 0.001) between the timing characteristics of the two types of signals indicates that the NE can reflect the actual dynamic interaction states of brain. Thus, the method may have potential implications for cognitive studies and for the detection of physiological states.

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.

The Attentional Demand of Automobile Driving Revisited: Occlusion Distance as a Function of Task-Relevant Event Density in Realistic Driving Scenarios.

OBJECTIVE: We studied the utility of occlusion distance as a function of task-relevant event density in realistic traffic scenarios with self-controlled speed. BACKGROUND: The visual occlusion technique is an established method for assessing visual demands of driving. However, occlusion time is not a highly informative measure of environmental task-relevant event density in self-paced driving scenarios because it partials out the effects of changes in driving speed. METHOD: Self-determined occlusion times and distances of 97 drivers with varying backgrounds were analyzed in driving scenarios simulating real Finnish suburban and highway traffic environments with self-determined vehicle speed. RESULTS: Occlusion distances varied systematically with the expected environmental demands of the manipulated driving scenarios whereas the distributions of occlusion times remained more static across the scenarios. Systematic individual differences in the preferred occlusion distances were observed. More experienced drivers achieved better lane-keeping accuracy than inexperienced drivers with similar occlusion distances; however, driving experience was unexpectedly not a major factor for the preferred occlusion distances. CONCLUSION: Occlusion distance seems to be an informative measure for assessing task-relevant event density in realistic traffic scenarios with self-controlled speed. Occlusion time measures the visual demand of driving as the task-relevant event rate in time intervals, whereas occlusion distance measures the experienced task-relevant event density in distance intervals. APPLICATION: The findings can be utilized in context-aware distraction mitigation systems, human-automated vehicle interaction, road speed prediction and design, as well as in the testing of visual in-vehicle tasks for inappropriate in-vehicle glancing behaviors in any dynamic traffic scenario for which appropriate individual occlusion distances can be defined.

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

The effects of alternative navigation device display features on drivers' visual sampling efficiency while searching forpoints of interest were studied in two driving simulation experiments with 40 participants. Given that the number of display items was sufficient, display features that facilitate resumption of visual search following interruptions were expected to lead to more consistent in-vehicle glance durations. As predicted, compared with a grid-style menu, searching information in a list-style menu while driving led to smaller variance in durations of in-vehicle glances, in particular with nine item displays. Kinetic touch screen scrolling induced a greater number of very short in-vehicle glances than scrolling with arrow buttons. The touch screen functionality did not significantly diminish the negative effects of the grid-menu compared with physical controls with list-style menus. The findings suggest that resumability of self-paced, in-vehicle visual search tasks could be assessed with the measures of variance of in-vehicle glance duration distributions. Statement of Relevance: The reported research reveals display design factors affecting safety-relevant variability of in-vehicle glance durations and provides a theoretical framework for explaining the effects. The research can have a significant methodical value for driver distraction research and practical value for the design and testing of in-vehicle user interfaces.