Off-road Glance Duration Research Articles

Impact of level 2 automation and ADHD symptomatology on young drivers’ attention maintenance

Attention Deficit Hyperactivity Disorder (ADHD) is a common mental disorder that affects drivers’ attention maintenance skills. Vehicle automation is another factor that has an increasingly important effect on drivers’ attention or concentration level during driving. This driving simulator study aimed to investigate how drivers’ glance behavior changed under different levels of vehicle automation and according to high or low ADHD symptomology. During the drive, participants were asked to complete a map task on a tablet while their glance behavior was recorded. Results imply that the participants tend to have a longer mean off-road glance duration and a larger long off-road glance ratio when they were under the L2 automation level compared to manual mode. ADHD symptomatology and the interaction between ADHD and vehicle automation were not found to be significant. These findings indicate that vehicle automation negatively impacts drivers’ attention maintenance skills. Future work would consider more kinds of secondary tasks that can assess the participants’ attention maintenance skills from various aspects.

Isolating the Effect of Off-Road Glance Duration on Driving Performance: An Exemplar Study Comparing HDD and HUD in Different Driving Scenarios.

We controlled participants' glance behavior while using head-down displays (HDDs) and head-up displays (HUDs) to isolate driving behavioral changes due to use of different display types across different driving environments. Recently, HUD technology has been incorporated into vehicles, allowing drivers to, in theory, gather display information without moving their eyes away from the road. Previous studies comparing the impact of HUDs with traditional displays on human performance show differences in both drivers' visual attention and driving performance. Yet no studies have isolated glance from driving behaviors, which limits our ability to understand the cause of these differences and resulting impact on display design. We developed a novel method to control visual attention in a driving simulator. Twenty experienced drivers sustained visual attention to in-vehicle HDDs and HUDs while driving in both a simple straight and empty roadway environment and a more realistic driving environment that included traffic and turns. In the realistic environment, but not the simpler environment, we found evidence of differing driving behaviors between display conditions, even though participants' glance behavior was similar. Thus, the assumption that visual attention can be evaluated in the same way for different types of vehicle displays may be inaccurate. Differences between driving environments bring the validity of testing HUDs using simplistic driving environments into question. As we move toward the integration of HUD user interfaces into vehicles, it is important that we develop new, sensitive assessment methods to ensure HUD interfaces are indeed safe for driving.

Detection and response to critical lead vehicle deceleration events with peripheral vision: Glance response times are independent of visual eccentricity

Studies show high correlations between drivers’ off-road glance duration or pattern and the frequency of crashes. Understanding drivers’ use of peripheral vision to detect and react to threats is essential to modelling driver behavior and, eventually, preventing crashes caused by visual distraction. A between-group experiment with 83 participants was conducted in a high-fidelity driving simulator. Each driver in the experiment was exposed to an unexpected, critical, lead vehicle deceleration, when performing a self-paced, visual-manual, tracking task at different horizontal visual eccentricity angles (12°, 40° and 60°). The effect of visual eccentricity on threat detection, glance and brake response times was analyzed. Contrary to expectations, the driver glance response time was found to be independent of the eccentricity angle of the secondary task. However, the brake response time increased with increasing task eccentricity, when measured from the driver’s gaze redirection to the forward roadway. High secondary task eccentricity was also associated with a low threat detection rate and drivers were predisposed to perform frequent on-road check glances while executing the task. These observations indicate that drivers use peripheral vision to collect evidence for braking during off-road glances. The insights will be used in extensions of existing driver models for virtual testing of critical longitudinal situations, to improve the representativeness of the simulation results.

Effects of Distraction in On-Road Level 2 Automated Driving: Impacts on Glance Behavior and Takeover Performance.

The paper aimed to investigate glance behaviors under different levels of distraction in automated driving (AD) and understand the impact of distraction levels on driver takeover performance. Driver distraction detrimentally affects takeover performance. Glance-based distraction measurement could be a promising method to remind drivers to maintain enough attentiveness before the takeover request in partially AD. Thirty-six participants were recruited to drive a Tesla Model S in manual and Autopilot modes on a test track while engaging in secondary tasks, including temperature-control, email-sorting, and music-selection, to impose low and high distractions. During the test drive, participants needed to quickly change the lane as if avoiding an immediate road hazard if they heard an unexpected takeover request (an auditory warning). Driver state and behavior over the test drive were recorded in real time by a driver monitoring system and several other sensors installed in the Tesla vehicle. The distribution of off-road glance duration was heavily skewed (with a long tail) by high distractions, with extreme glance duration more than 30 s. Moreover, being eyes-off-road before takeover could cause more delay in the urgent takeover reaction compared to being hands-off-wheel. The study measured off-road glance duration under different levels of distraction and demonstrated the impacts of being eyes-off-road and hands-off-wheel on the following takeover performance. The findings provide new insights about engagement in Level 2 AD and are useful for the design of driver monitoring technologies for distraction management.

Effects of visual complexity of in-vehicle information display: Age-related differences in visual search task in the driving context

We aimed to investigate the effects of the visual complexity of in-vehicle information display and driver's age in a driving context. A driving simulator study was conducted where participants performed visual search tasks at different visual complexity levels while driving. Two groups were included, 20 younger drivers (mean age = 28.75 years) and 14 older drivers (mean age = 54.87 years). Older drivers were found to be more vulnerable to the effects of increased visual complexity when performing a visual search task. The task completion time of the younger group increased by about 20% (from 7.69 s to 9.30 s), while the older group increased by about 47% (from 8.92 s to 13.14 s). Further, the driving performance of the older group deteriorated, unlike the younger group. The subjective workload score supported the results of the objective performance measures. These differences can be explained by glance behavior. The total off-road glance duration of older drivers was longer than that of younger drivers, but the average off-road glance duration of younger drivers was longer. In other words, older drivers have a more conservative strategy when dealing with increased visual complexity in a driving context so as not to affect their driving. The findings of this study show that the visual complexity level has a significant effect on driving behaviors, especially in older drivers, which provides insights for designing in-vehicle information displays.

Glances That Matter: Applying Quantile Regression to Assess Driver Distraction from Off-Road Glances

This study assessed whether quantile regression can identify design specifications that lead to particularly long glances, which might go unnoticed with traditional analyses focusing on conditional means of off-road glances. Although substantial research indicates that long glances contribute disproportionately to crash risk, few studies have directly assessed the tails of the distribution. Failing to examine the distribution tails might underestimate the disproportionate risk on long glances imposed by secondary tasks. We applied quantile regression to assess the effects of secondary task type (reading or entry), system delay (delay or no delay), and text length (long or short) on off-road glance duration at 15th, 50th, and 85th quantiles. The results show that entry task, long text, and some combinations of variables led to longer glances than that would be expected given the central tendency of glance distributions. Quantile regression identifies secondary task features that produce long glances, which might be neglected by traditional analyses with conditional means.

Revisiting Radio Tuning: A Secondary Analysis Comparing Glance Behavior Across Five Vehicles

Visual-manual demand placed on drivers through interactions with operational functions, embedded telematics, infotainment systems, and nomadic technologies has raised concerns associated with diverting attention from the roadway. This analysis draws on data from field studies of five different infotainment systems representing a range of screen placements and control characteristics that diverge in significant ways from the relatively standard car radio layout of previous generations. Participants performed a set of classic visual-manual radio tuning tasks under highway driving conditions. There were significant differences in task completion time, number of off-road glances, mean single off-road glance duration, and total off-road glance time across vehicles. These results highlight that the range of configurations appearing in modern infotainment systems have changed the extent to which they can be used in the classic radio tuning task to provide a standard demand benchmark.

Designing feedback to mitigate teen distracted driving: A social norms approach

ObjectiveThe purpose of this research is to investigate teens’ perceived social norms and whether providing normative information can reduce distracted driving behaviors among them. BackgroundParents are among the most important social referents for teens; they have significant influences on teens’ driving behaviors, including distracted driving which significantly contributes to teens’ crash risks. Social norms interventions have been successfully applied in various domains including driving; however, this approach is yet to be explored for mitigating driver distraction among teens. MethodForty teens completed a driving simulator experiment while performing a self-paced visual-manual secondary task in four between-subject conditions: a) social norms feedback that provided a report at the end of each drive on teens’ distracted driving behavior, comparing their distraction engagement to their parent’s, b) post-drive feedback that provided just the report on teens’ distracted driving behavior without information on their parents, c) real-time feedback in the form of auditory warnings based on eyes of road-time, and d) no feedback as control. Questionnaires were administered to collect data on these teens’ and their parents’ self-reported engagement in driver distractions and the associated social norms. ResultsSocial norms and real-time feedback conditions resulted in significantly smaller average off-road glance duration, rate of long (>2s) off-road glances, and standard deviation of lane position compared to no feedback. Further, social norms feedback decreased brake response time and percentage of time not looking at the road compared to no feedback. No major effect was observed for post-drive feedback. Questionnaire results suggest that teens appeared to overestimate parental norms, but no effect of feedback was found on their perceptions. ConclusionFeedback systems that leverage social norms can help mitigate driver distraction among teens. Overall, both social norms and real-time feedback induced positive driving behaviors, with social norms feedback outperforming real-time feedback.

On-Road Visual Sign Salience, Driver Attention Allocation, and Target Detection Accuracy

Previous studies have empirically assessed the effect of on-road signage on driver distraction and attention allocation through eye-tracking measures and driving simulations. However, state and federal agencies might be able to make use of simpler approaches to determining the potential visual load of on-road signs. This study compared different on-road signage (food, gas and attraction, and distance guide signs) with respect to visual salience, assessed the effect of the number of panels and logo format on signage salience, and analyzed associations between salience values for different sign types with target detection accuracy and off-road glance duration. Visual salience of signs was measured with the salience using the natural statistics (SUNs) method. For correlation analyses between sign salience, attention allocation, and detection accuracy, a sample of 120 drivers participated in two driving simulation studies. Results revealed food business signs, containing all pictorial logos, to be more salient than gas and attraction and distance guide signs. In addition, results revealed that increasing the number of sign panels from six to nine significantly increased visual salience. It was also found that attraction signs including all pictorial logos were more salient than signs with text-based logos. Results did not reveal statistically significant relationships between visual salience and attention allocation. In addition, there was no significant correlation between target detection accuracy and visual salience for various sign types. Future work with a higher sign-sampling rate is needed to assess whether the SUNs method is a useful measure for determining if roadway sign salience is a driving factor in distraction.

Sensation Seeking and Drivers’ Glance Behavior while Engaging in a Secondary Task

To investigate possible relationships between drivers’ sensation seeking and glance behavior while interacting with human-machine interfaces, a total of 70 drivers’ eye-glance data, Sensation Seeking Scale (SSS), and Driver Behavior Questionnaire (DBQ) data were collected and analyzed. Participants conducted radio tuning tasks with two standard production interfaces while driving on a highway, and their glance allocations to defined regions were recorded and manually annotated. Results showed that sensation seeking scores were related with self-reported violation scores, off-road glance patterns, and driving speed: (1) violation scores of DBQ were positively correlated with sensation seeking, (2) mean and standard deviation of off-road glance duration were positively correlated with sensation seeking for younger drivers (under 40 years), (3) total off-road glance time per minute and number of off-road glances per minute were positively correlated with sensation seeking for older drivers (over 40 years), and (4) percentage of speed change was negatively correlated with sensation seeking for both younger and older drivers. The results indicate that sensation seeking is associated with drivers’ off-road glance patterns and driving behavior. These observations further highlight the relationship between personal traits and driver behavior.

A Looming Crisis

Long glances away from the road present a significant risk to driving safety. The tail of the distribution for in-vehicle glance duration has been proposed to be more relevant to crash risk than the mean of the distribution. Using data collected in the 100-Car Naturalistic Driving Study (Dingus et al., 2006), this study examined the changes in the distribution of driver off-road glance duration, as well as in the frequency of such glances, at different time points before crash/near-crash events and compared with baseline (i.e., normal) driving. The results showed that the shape of the distribution of off-road glance duration at the onset of the precipitating factor of crashes/near-crashes was similar to the distribution in epochs during the preceding 25 seconds; nonetheless, the frequency of off-road glances increased in the approach to crashes/near-crash events. Compared with baseline epochs, drivers in crashes/near-crash events tended to look away from the forward road more often and with longer duration (i.e., with thicker tail end of the distributions; exceeding 1.7 seconds as observed in the distributions). It suggests that frequent off-road glances longer than 1.7 seconds present a high-risk glance pattern in the seconds preceding a safety- critical event and that the 2.0 second-threshold that is frequently cited in defining dangerously long off-road glances might be a liberal estimation.

Studying the Effects of Driver Distraction and Traffic Density on the Probability of Crash and Near-Crash Events in Naturalistic Driving Environment

Driver distraction detection and intervention are important for designing modern driver-assistance systems and for improving safety. The main research question of this paper is to investigate how the cumulative driver off-road glance duration can be controlled to reduce the probability of occurrences of crash and near-crash events. Based on the available data sets from the Virginia Tech Transportation Institute (VTTI) 100-car study, the conditional probability is calculated to study the chance of crash and near-crash events when the given cumulative off-road glance duration in 6 s has been reached. Different off-road eye-glance locations and traffic density levels are also evaluated. The results show that one linear relationship can be obtained between the cumulative off-road eye-glance duration in 6 s and the risk of occurrences of crash and near-crash events, which varies for different off-road eye-glance locations. In addition, the traffic density level is found to be one significant moderator to this linear relationship. Detailed comparisons are made for different traffic density levels, and one nonlinear equation is obtained to predict the probability of occurrences of crash and near-crash events by considering both cumulative off-road glance duration and traffic density levels.

How Dangerous Is Looking Away From the Road? Algorithms Predict Crash Risk From Glance Patterns in Naturalistic Driving

In this study, the authors used algorithms to estimate driver distraction and predict crash and near-crash risk on the basis of driver glance behavior using the data set of the 100-Car Naturalistic Driving Study. Driver distraction has been a leading cause of motor vehicle crashes, but the relationship between distractions and crash risk lacks detailed quantification. The authors compared 24 algorithms that varied according to how they incorporated three potential contributors to distraction--glance duration, glance history, and glance location--on how well the algorithms predicted crash risk. Distraction estimated from driver eye-glance patterns was positively associated with crash risk. The algorithms incorporating ongoing off-road glance duration predicted crash risk better than did the algorithms incorporating glance history.Augmenting glance duration with other elements of glance behavior--1.5th power of duration and duration weighted by glance location--produced similar prediction performance as glance duration alone. The distraction level estimated by the algorithms that include current glance duration provides the most sensitive indicator of crash risk. The results inform the design of algorithms to monitor driver state that support real-time distraction mitigation systems.

Methodology for Capturing Driver Eye Glance Behavior During In-Vehicle Secondary Tasks

Driving is a visual task; any driver behavior that takes the driver's visual attention from the driving environment is likely to increase the risk of a crash. Many new intelligent transportation systems telematics applications are now being installed in cars, and some of these may result in substantial degradation of visual attention. Accurately capturing driver eye glance behavior during the evaluation of these devices is critical to assessing the safety impact of engaging in secondary tasks while driving. The development of a methodology is reported; it reliably determines on-road and off-road eye glance duration by using video data collected during highway driving evaluation trials while drivers were engaged with secondary tasks. Human raters determined glance location and duration by detailed coding of the driver's eye movements on the videos. The raters agreed most of the time, but sufficient disagreement suggested that using the consensus of multiple raters significantly improved the reliability of ...