The effects of age and workload on 3D spatial attention in dual-task driving

Spatial attention in three-dimensional space: A meta-analysis for the near advantage in target detection and localization

Studies have explored how human spatial attention appears allocated in three-dimensional (3D) space. It has been demonstrated that target distance from the viewer can modulate performance in target detection and localization tasks: reaction times are shorter when targets appear nearer to the observer compared to farther distances (i.e., near advantage). Times have reached to quantitatively analyze this literature. In the current meta-analysis, 29 studies (n = 1260 participants) examined target detection and localization across 3-D space. Moderator analyses included: detection vs localization tasks, spatial cueing vs uncued tasks, control of retinal size across depth, central vs peripheral targets, real-space vs stereoscopic vs monocular depth environments, and inclusion of in-trial motion. The analyses revealed a near advantage for spatial attention that was affected by the moderating variables of controlling for retinal size across depth, the use of spatial cueing tasks, and the inclusion of in-trial motion. Overall, these results provide an up-to-date quantification of the effect of depth and provide insight into methodological differences in evaluating spatial attention.

Peripheral target detection can be modulated by target distance but not attended distance in 3D space simulated by monocular depth cues

Most studies of visuo-spatial attention present stimuli on a 2D plane, and less is known about how attention varies in 3D space. Previous studies found better peripheral detection performance for targets at a near compared to a far depth, simulated by pictorial cues and optical flow. The current study examined whether target detectability is monotonically related to distance along the depth axis, and whether the attended distance modulates the effect of target distance. We investigated these questions in two experiments that measured how apparent distance and target eccentricity affects peripheral target detection when performed alone during passive simulated self-motion, or during a simultaneous, active central car-following task. Experiment 1 found that targets at an apparent distance of 18.5 virtual meters were detected faster and more accurately than targets at 9.25 and 37 virtual meters, and detectability declined with eccentricity. Experiment 2 examined the effect of the attended location by varying the distance between the viewer and the lead car on which participants were instructed to fixate (i.e. the headway) while equating target distances across headway conditions. Experiment 2 replicated the effects found in Experiment 1, and headway did not modulate the effect of target distance. These results are consistent with the hypothesis that target detection depends non-monotonically on the distance between the viewer and the target, and is not affected by the distance between the target and attended location. However, target detection may also have been affected by stimulus characteristics that co-varied with apparent depth, rather than depth per se.

The effect of apparent distance on peripheral target detection

Previous research suggests that peripheral target detection is modulated by viewing distance and distance simulated by pictorial cues and optic flow. In the latter case, it is unclear what cues contribute to the effect of distance. The current study evaluated the effect of distance on peripheral detection in a virtual three-dimensional environment. Experiments 1–3 used a continuous, dynamic central task that simulated observers traveling either actively or passively through a virtual environment following a car. Peripheral targets were flashed on checkerboard-covered walls to the left and right of the path of motion, at a near and a far distance from the observer. The retinal characteristics of the targets were identical across distances. Experiment 1 found more accurate and faster detection for near targets compared to far targets, especially for larger eccentricities. Experiment 2 equated the predictability of target onset across distances and found the near advantage for larger eccentricities in accuracy but a much smaller effect in reaction time (RT). Experiment 3 removed the checkerboard background implemented in Experiments 1 and 2, and Experiment 4 manipulated several static, monocular cues. Experiments 3 and 4 found that the variation in the density of the checkerboard backgrounds could explain the main effect of distance on accuracy but could not completely account for the interaction between target distance and eccentricity. These results suggest that attention is modulated by target distance, but the effect is small. Finally, there were consistent divided attention costs in the central car-following task but not the peripheral detection task.

Monotonous driving induces shifts in spatial attention as a function of handedness

Current evidence suggests that the ability to detect and react to information under lowered alertness conditions might be more impaired on the left than the right side of space. This evidence derives mainly from right-handers being assessed in computer and paper-and-pencil spatial attention tasks. However, there are suggestions that left-handers might show impairments on the opposite (right) side compared to right-handers with lowered alertness, and it is unclear whether the impairments observed in the computer tasks have any real-world implications for activities such as driving. The current study investigated the alertness and spatial attention relationship under simulated monotonous driving in left- and right-handers. Twenty left-handed and 22 right-handed participants (15 males, mean age = 23.6 years, SD = 5.0 years) were assessed on a simulated driving task (lasting approximately 60 min) to induce a time-on-task effect. The driving task involved responding to stimuli appearing at six different horizontal locations on the screen, whilst driving in a 50 km/h zone. Decreases in alertness and driving performance were evident with time-on-task in both handedness groups. We found handedness impacts reacting to lateral stimuli differently with time-on-task: right-handers reacted slower to the leftmost stimuli, while left-handers showed the opposite pattern (although not statistically significant) in the second compared to first half of the drive. Our findings support suggestions that handedness modulates the spatial attention and alertness interactions. The interactions were observed in a simulated driving task which calls for further research to understand the safety implications of these interactions for activities such as driving.

Visual attention in realistic driving situations: Attentional capture and hazard prediction

In real life, many objects catch our attention involuntarily or exogenously. Exogenous attention occurs fast and its effects are short-lived. In the laboratory, when attentional orientation is studied, both valid and invalid attentional signals are used: the valid ones direct the attention to a location where something relevant is going to appear. The invalid ones occur in a location where nothing relevant is going to happen. Usually, performance is improved when valid signals rather than invalid ones are presented. This work is novel in that it explores the effects of attentional capture and driving experience in situations of day-to-day driving while participants carry out a Hazard Prediction task. We created new Hazard Prediction (HPr) and Risk Estimation (RE) tests when driving by selecting 48 short videos recorded in a realistic way from the perspective of a car driver. We created valid and invalid trials by selecting videos in which a what?? was presented in the same spatial location as the one where the hazard was beginning to develop or in a different location. Simple situations, with only one developing hazard, were also presented. A total of 92 participants (30 experienced drivers, 32 novices and 30 with no experience) were placed in the position of the driver and answered the questions: 1) What will happen after the video is cut? 2) To what extent do you consider this situation risky? The results from the Hazard Prediction test replicate the attentional capture effect in complex driving situations, with invalid trials obtaining the worst results, followed by valid and simple ones. Participants with experience obtained better scores than novices, and novices were better than drivers without experience. No interaction between attentional orientation and experience was found, suggesting the obligatory and automatic nature of orientation processes, which do not appear to be compensated for by driving experience. No significant differences were found for the Risk Estimation test.

Driving Accidents, Driving Violations, Symptoms of Attention-Deficit-Hyperactivity (ADHD) and Attentional Network Tasks

Background: Iran has serious problems with traffic-related injuries and death. A major reason for traffic accidents is cognitive failure due to deficits in attention. In this study, we investigated the associations between traffic violations, traffic accidents, symptoms of attention-deficit/hyperactivity disorder (ADHD), age, and on an attentional network task in a sample of Iranian adults. Methods: A total of 274 participants (mean age: 31.37 years; 80.7% males) completed questionnaires covering demographic information, driving violations, traffic accidents, and symptoms of ADHD. In addition, they underwent an objective attentional network task (ANT), based on Posner’s concept of attentional networks. Results: More frequent traffic violations, correlated with lower age and poorer performance on the attentional network tasks. Higher symptoms of ADHD were associated with more accidents and more traffic violations, but not with the performance of the attentional tasks. Higher ADHD scores, a poorer performance on attentional network tasks, and younger age predicted traffic violations. Only higher symptoms of ADHD predicted more traffic accidents. Conclusions: In a sample of Iranian drivers, self-rated symptoms of ADHD appeared to be associated with traffic violations and accidents, while symptoms of ADHD were unrelated to objectively assessed performance on an attentional network task. Poor attentional network performance was a significant predictor of traffic violations but not of accidents. To increase traffic safety, both symptoms of ADHD and attentional network performance appear to merit particular attention.

Gaze Control During Simulator Driving in Adolescents With and Without Attention Deficit Hyperactivity Disorder

Importance: Attention deficit hyperactivity disorder (ADHD) is associated with driving deficits. Visual standards for driving define minimum qualifications for safe driving, including acuity and field of vision, but they do not consider the ability to explore the environment efficiently by shifting the gaze, which is a critical element of safe driving.

Objective: To examine visual exploration during simulated driving in adolescents with and without ADHD.

Design: Adolescents with and without ADHD drove a driving simulator for approximately 10 min while their gaze was monitored. They then completed a battery of questionnaires.

Setting: University lab.

Participants: Participants with (n = 16) and without (n = 15) ADHD were included. Participants had a history of neurological disorders other than ADHD and normal or corrected-to-normal vision. Control participants reported not having a diagnosis of ADHD. Participants with ADHD had been previously diagnosed by a qualified professional.

Outcomes and Measures: We compared the following measures between ADHD and non-ADHD groups: dashboard dwell times, fixation variance, entropy, and fixation duration.

Results: Findings showed that participants with ADHD were more restricted in their patterns of exploration than control group participants. They spent considerably more time gazing at the dashboard and had longer periods of fixation with lower variability and randomness.

Conclusions and Relevance: The results support the hypothesis that adolescents with ADHD engage in less active exploration during simulated driving.

What This Article Adds: This study raises concerns regarding the driving competence of people with ADHD and opens up new directions for potential training programs that focus on exploratory gaze control.

Identifying the Causes of Drivers' Hazardous States Using Driver Characteristics, Vehicle Kinematics, and Physiological Measurements

Drivers’ hazardous physical and mental states (e.g., distraction, fatigue, stress, and high workload) have a major effect on driving performance and strongly contribute to 25–50% of all traffic accidents. They are caused by numerous factors, such as cell phone use or lack of sleep. However, while significant research has been done on detecting hazardous states, most studies have not tried to identify the causes of the hazardous states. Such information would be very useful, as it would allow intelligent vehicles to better respond to a detected hazardous state. Thus, this study examined whether the cause of a driver’s hazardous state can be automatically identified using a combination of driver characteristics, vehicle kinematics, and physiological measures. Twenty-one healthy participants took part in four 45-min sessions of simulated driving, of which they were mildly sleep-deprived for two sessions. Within each session, there were eight different scenarios with different weather (sunny or snowy), traffic density and cell phone usage (with or without cell phone). During each scenario, four physiological (respiration, electrocardiogram, skin conductance, and body temperature) and eight vehicle kinematics measures were monitored. Additionally, three self-reported driver characteristics were obtained: personality, stress level, and mood. Three feature sets were formed based on driver characteristics, vehicle kinematics, and physiological signals. All possible combinations of the three feature sets were used to classify sleep deprivation (drowsy vs. alert), traffic density (low vs. high), cell phone use, and weather conditions (foggy/snowy vs. sunny) with highest accuracies of 98.8%, 91.4%, 82.3%, and 71.5%, respectively. Vehicle kinematics were most useful for classification of weather and traffic density while physiology and driver characteristics were useful for classification of sleep deprivation and cell phone use. Furthermore, a second classification scheme was tested that also incorporates information about whether or not other causes of hazardous states are present, though this did not result in higher classification accuracy. In the future, these classifiers could be used to identify both the presence and cause of a driver’s hazardous state, which could serve as the basis for more intelligent intervention systems.

Driver's Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case Study of the Highways in China

Complex traffic situations and high driving workload are the leading contributing factors to traffic crashes. There is a strong correlation between driving performance and driving workload, such as visual workload from traffic signs on highway off-ramps. This study aimed to evaluate traffic safety by analyzing drivers' behavior and performance under the cognitive workload in complex environment areas. First, the driving workload of drivers was tested based on traffic signs with different quantities of information. Forty-four drivers were recruited to conduct a traffic sign cognition experiment under static controlled environment conditions. Different complex traffic signs were used for applying the cognitive workload. The static experiment results reveal that workload is highly related to the amount of information on traffic signs and reaction time increases with the information grade, while driving experience and gender effect are not significant. This shows that the cognitive workload of subsequent driving experiments can be controlled by the amount of information on traffic signs. Second, driving characteristics and driving performance were analyzed under different secondary task driving workload levels using a driving simulator. Drivers were required to drive at the required speed on a designed highway off-ramp scene. The cognitive workload was controlled by reading traffic signs with different information, which were divided into four levels. Drivers had to make choices by pushing buttons after reading traffic signs. Meanwhile, the driving performance information was recorded. Questionnaires on objective workload were collected right after each driving task. The results show that speed maintenance and lane deviations are significantly different under different levels of cognitive workload, and the effects of driving experience and gender groups are significant. The research results can be used to analyze traffic safety in highway environments, while considering more drivers' cognitive and driving performance.