Off-road Glances Research Articles

Sonically-enhanced in-vehicle air gesture interactions: evaluation of different spearcon compression rates

Driver distraction is a major contributor to road vehicle crashes, and visual distraction caused by using in-vehicle infotainment systems (IVIS) degrades driving performance and increases crash risk. Air gesture interfaces have been developed to mitigate driver distraction, and using auditory displays showed a decrease in off-road glances and an improved perceived workload. However, the potential of auditory display was not fully investigated. The present paper presents directional research in the design of auditory displays for air-gesture IVIS through a dual-task experiment of driving a simulator and air-gesture menu navigation. Twenty-four participants utilized the in-vehicle air gesture interfaces while driving with four auditory display conditions (text-to-speech, 70% compressed spearcons, 40% compressed spearcson, and no sound). The results showed that 70% spearcon reduced visual distraction and increased menu navigation accuracy but with increased navigation time. 70% spearcon was most preferred by the participants. Driving performance or workload did not show any difference among the conditions. Implications are discussed with the design guidelines for future implementations.

Examining Patterns and Predictors of ADHD Teens' Skill-Learning Trajectories During Enhanced FOrward Concentration and Attention Learning (FOCAL+) Training.

Examine patterns and predictors of skill learning during multisession Enhanced FOrward Concentration and Attention Learning (FOCAL+) training. FOCAL+ teaches teens to reduce the duration of off-road glances using real-time error learning. In a randomized controlled trial, teens with ADHD received five sessions of FOCAL+ training and demonstrated significant reductions in extended glances (>2-s) away from the roadway (i.e., long-glances) and a 40% reduced risk of a crash/near-crash event. Teens' improvement in limiting long-glances as assessed after each FOCAL+ training session has not been examined. Licensed teen (ages 16-19) drivers with ADHD (n = 152) were randomly assigned to five sessions of either FOCAL+ or modified standard driver training. Teens completed driving simulation assessments at baseline, after each training session, and 1 month and 6 months posttraining. Naturalistic driving was monitored for one year. FOCAL+ training produced a 53% maximal reduction in long-glances during postsession simulated driving. The number of sessions needed to achieve maximum performance varied across participants. However, after five FOCAL+ training sessions, number of long-glances was comparable irrespective of when teens achieved their maximum performance. The magnitude of reduction in long-glances predicted levels of long-glances during simulated driving at 1 month and 6 months posttraining but not naturalistic driving outcomes. FOCAL+ training provided the most benefit during training to teens who were younger and had less driving experience. FOCAL+ training significantly reduces long-glances beginning at the 1st training session. Providing five FOCAL+ training sessions early on during teen driving may maximize benefit.

Comparing the Driving Skills of Adolescents with Obstructive Sleep Apnea to Healthy Controls: The Results of a Case-Controlled Observational Study.

Auto crashes are a leading cause of death and injury among adolescents. Untreated obstructive sleep apnea (OSA) can cause sleepiness and inattention, which could negatively impact novice drivers, but OSA-related studies have focused on older drivers. This study used a driving simulator to examine whether licensed 16-19-year-old adolescents with OSA have diminished driving skills. Twenty-one adolescents with OSA and twenty-eight without OSA (both confirmed using polysomnography) completed two randomly ordered driving trials in a simulator (with induced distractions versus without). A mixed ANOVA examined the between-subjects effect of the OSA group, the within-subjects effect of the distraction condition, and the group-by-condition interaction effect on the ability to maintain lane position and the frequency of extended eye glances away from the roadway. T-tests were also used to examine group differences in reported sleepiness and inattention during daily life. The distraction task increased extended off-road glances and difficulties maintaining lane position (p < 0.001). However, adolescents with OSA did not display worse eye glance or lane position than controls and there were no significant group-by-condition interactions. Although the groups differed on polysomonographic features, there were also no significant differences in reported sleepiness or inattention. The distraction task negatively impacted both groups of adolescent drivers, but those with OSA did not fare differentially worse. Most adolescents in our study had mild OSA (median obstructive apnea-hypopnea index = 4.4), the most common form in the community. It remains possible that youth with more severe OSA would show increased driving impairment.

Executive Functioning as a Predictor of Adverse Driving Outcomes in Teen Drivers With ADHD

Objective: The present study examined the association between executive functioning (EF) and risky driving behaviors in teens with ADHD. Method: Teens diagnosed with ADHD (n = 179; Mage = 17.4 years) completed two 15-min drives in a fixed-base driving simulator. EF was assessed using parent- and self-report Behavior Rating Inventory of Executive Functioning (BRIEF-2), a temporal reproduction task, and a Go/No-Go task (GNG). Driving outcomes included known predictors of crashes: count of long (>2 s) off-road glances, standard deviation (SD) of lane position (SDLP), mean speed, and SD speed. Generalized linear mixed models, controlling for intelligence and driving experience, were conducted. Results: Higher rates of GNG commission errors predicted higher rates of long off-road glances. Lower parent-rated EF and increased rates of GNG omission errors predicted SDLP. Higher rates of GNG commission errors also predicted faster average driving speed. Conclusion: Heterogeneity in EF is associated with differences in teen ADHD risky driving behaviors.

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.

Factors affecting drivers’ off-road glance behavior while interacting with in-vehicle voice interfaces

In-vehicle voice-based interfaces have been massively embedded in modern vehicles as a countermeasure to visual-manual distractions. However, limited data are available regarding the actual visual demands imposed on the driver when interacting with such an interface. How those factors that are associated with the drivers themselves affect their visual behavior when interacting with an in-vehicle voice-based interface remains understudied. This study focused on investigating factors affecting drivers’ off-road visual behavior while interacting with a voice-based interface. A secondary data analysis leveraging structural equation modeling was performed based on data collected from a large-scale field experiment wherein participants drove a vehicle on the highway and performed a series of tasks using an in-vehicle voice interface. The results indicate that while voice-based interfaces are designed to help reduce drivers’ visual demands, drivers can still direct their eyes off the road for a prolonged period of time during the interaction and exhibit potentially risky visual behavior. In addition, individual-level factors can exert influence on drivers’ off-road visual behavior in such a way that older drivers and drivers with higher trust in technologies are associated with more long eyes-off-road glances when interacting with a voice-based interface. To promote the general public’s adoption of in-vehicle voice interfaces and support safe interactions, we recommend relevant research and system design consider drivers’ trust in, perceptions, and previous usage of similar technologies, as well as their individual characteristics such as age.

Chinese handwriting while driving: Effects of handwritten box size on in-vehicle information systems usability and driver distraction

Objective Handwritten box size (HBS) is an essential Chinese handwriting interface element when interacting with touchscreen-based in-vehicle information systems (IVISs) since it is compactly bound up with driver distraction besides usability issues. Miscellaneous HBSs are commercially available on IVISs, yet the details of how the drivers interact with them in an in-vehicle display situation remain sparsely examined. Therefore, this study set out to investigate the effects of HBS on IVISs usability (task completion time, number of errors, number of protruding strokes, and NASA-TLX, a subjective workload assessment tool) and driver distraction (mean speed, lane position variation, total glance time, number of glances, mean glance time, and number of glances exceeding 1.6 s). Ultimately, the appropriate HBS on IVISs is determined. Methods A simulated driving experiment involving thirty drivers was launched. The primary task was lane-keeping with speed ranging from 40 to 60 km/h, and the secondary task was entering a 5-character text by Chinese handwriting input under five different HBS conditions: 25 × 25 mm, 30 × 30 mm, 35 × 35 mm, 40 × 40 mm, and 45 × 45 mm. A battery of one-way repeated measure analyses of variance (r-ANOVA) was used to examine which HBS can maximize IVISs usability and minimize driver distraction with the smallest HBS. Results Generally, the issues of IVISs usability and driver distraction improved progressively as the HBS increased to a specific size (40 × 40 mm in this study), at which they got to the asymptotes. Specifically, HBS below 40 × 40 mm was associated with longer text input time, more errors and protruding strokes, extended eyes-off-road time, excessive off-road glances, and deteriorative lateral driving performance. Nevertheless, there were no significant differences in mean glance time and longitudinal driving performance. No improvement measures were observed for HBS above 40 × 40 mm, except for a higher perceived workload. Conclusions Overall, the appropriate HBS of in-vehicle Chinese handwriting was found to be 40 × 40 mm. Considering that the in-vehicle human-machine interface (HMI) has limited display space and increasing visual complexity, these findings may help develop evidence-based design guidelines for driver-friendly IVISs and prevent distracted-related traffic injuries.

Simulator evaluation of an intersection maneuver assist system with connected and automated vehicle technologies

Intersection crashes can be potentially mitigated through vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) safety management systems. It is important, however, to consider some of the human factors related aspects of such systems to maximise potential safety benefits. In this study, Intersection Manoeuvre Assistance Systems were conceptualised and evaluated in a driving simulator. The systems were designed to assist drivers with intersection manoeuvres by making use of connected infrastructure and providing real-time feedback, guidance, and active vehicle controls. The study compared drivers’ confidence, workload, glances at the instrument panel, and hazard anticipation when driving using three systems—System A (no alert or assist); System B (alert only); and System C (alert and assist). Study results show differences in drivers’ confidence in such systems and potentially degraded visual gaze behaviours. Practitioner summary: Connected infrastructure-based intersection management assistance systems can potentially reduce crashes. This experimental driving simulation study evaluated drivers’ perceptions and reactions to intersection management systems. Results indicate reduced confidence in automated systems, reduced visual scanning for external hazards at intersections, and increased off-road glances towards the instrument panel.

Driver Visual Attention Before and After Take-Over Requests During Automated Driving on Public Roads.

This study aims to understand drivers' visual attention before and after take-over requests during automated driving (AD), when the vehicle is fully responsible for the driving task on public roads. Existing research on transitions of control from AD to manual driving has mainly focused on take-over times. Despite its relevance for vehicle safety, drivers' visual attention has received little consideration. Thirty participants took part in a Wizard of Oz study on public roads. Drivers' visual attention was analyzed before and after four take-over requests. Visual attention during manual driving was also recorded to serve as a baseline for comparison. During AD, the participants showed reduced visual attention to the forward road and increased duration of single off-road glances compared to manual driving. In response to take-over requests, the participants looked away from the forward road toward the instrument cluster. Levels of visual attention towards the forward road did not return to the levels observed during manual driving until after 15s had passed. During AD, drivers may look toward non-driving related task items (e.g., mobile phone) instead of forward. Further, when a transition of control is required, drivers may take over control before they are aware of the driving environment or potential threat(s). Thus, it cannot be assumed that drivers are ready to respond to events shortly after the take-over request. It is important to consider the effect of the design of take-over requests on drivers' visual attention alongside take-over times.

Computational modeling of driver pre-crash brake response, with and without off-road glances: Parameterization using real-world crashes and near-crashes

When faced with an imminent collision threat, human vehicle drivers respond with braking in a manner which is stereotypical, yet modulated in complex ways by many factors, including the specific traffic situation and past driver eye movements. A computational model capturing these phenomena would have high applied value, for example in virtual vehicle safety testing methods, but existing models are either simplistic or not sufficiently validated. This paper extends an existing quantitative driver model for initiation and modulation of pre-crash brake response, to handle off-road glance behavior. The resulting models are fitted to time-series data from real-world naturalistic rear-end crashes and near-crashes. A stringent parameterization and model selection procedure is presented, based on particle swarm optimization and maximum likelihood estimation. A major contribution of this paper is the resulting first-ever fit of a computational model of human braking to real near-crash and crash behavior data. The model selection results also permit novel conclusions regarding behavior and accident causation: Firstly, the results indicate that drivers have partial visual looming perception during off-road glances; that is, evidence for braking is collected, albeit at a slower pace, while the driver is looking away from the forward roadway. Secondly, the results suggest that an important causation factor in crashes without off-road glances may be a reduced responsiveness to visual looming, possibly associated with cognitive driver state (e.g., drowsiness or erroneous driver expectations). It is also demonstrated that a model parameterized on less-critical data, such as near-crashes, may also accurately reproduce driver behavior in highly critical situations, such as crashes.

A model for naturalistic glance behavior around Tesla Autopilot disengagements

We present a model for visual behavior that can simulate the glance pattern observed around driver-initiated, non-critical disengagements of Tesla's Autopilot (AP) in naturalistic highway driving. Drivers may become inattentive when using partially-automated driving systems. The safety effects associated with inattention are unknown until we have a quantitative reference on how visual behavior changes with automation. The model is based on glance data from 290 human initiated AP disengagement epochs. Glance duration and transition were modelled with Bayesian Generalized Linear Mixed models. The model replicates the observed glance pattern across drivers. The model's components show that off-road glances were longer with AP active than without and that their frequency characteristics changed. Driving-related off-road glances were less frequent with AP active than in manual driving, while non-driving related glances to the down/center-stack areas were the most frequent and the longest (22% of the glances exceeded 2 s). Little difference was found in on-road glance duration. Visual behavior patterns change before and after AP disengagement. Before disengagement, drivers looked less on road and focused more on non-driving related areas compared to after the transition to manual driving. The higher proportion of off-road glances before disengagement to manual driving were not compensated by longer glances ahead. The model can be used as a reference for safety assessment or to formulate design targets for driver management systems.

Role of Peripheral Vision in Brake Reaction Time During Safety Critical Events

The criticality of a rear end event depends on the brake reaction time (BRT) of the driver. Therefore, distracted driving poses greater threat in such events. Evidence accumulation model (EAM) that uses looming of the lead vehicle as main stimuli has shown significant success in estimating drivers’ BR Ts. It is often argued that drivers collect evidence for braking through peripheral vision, especially during off-road glances, and transition to forward. In this work, we have modeled evidence accumulation as a function of gaze eccentricity for off-road glances while approaching safety critical events. The model is tested with real world crash and near crash event data from SHRP2 naturalistic study. Our model shows that linear relation between gaze eccentricity and evidence accumulation rate during off road glances helps to improve EAM estimation in predicting BRT. We have also shown that brake-light onset does not influence EAM in presence of active looming.

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.

RETRACTED ARTICLE: Investigation of automotive digital mirrors ergonomics through laser shadowgraphy and driver’s real-road test questionnaire

This paper studied the effect of replacing automotive reflection mirrors with digital mirrors (DM) on the driver’s safety and comfort. In this perspective, a new classification for DMs was proposed in appendance with a brief overview of driver’s visual ergonomics, associated with comparison and criticism of automotive DM design causality. Automotive laser shadowgraphy from car interior was performed to measure the obscuration in the driver’s direct field of view, due to the presence of DM displays at nine different obscuration positions. The driver’s off-road glances time toward DM displays was measured using a digital video recorder system. The eye glances of thirty drivers of different ages during different traffic conditions and their opinion about each display position through a simple questionnaire were statistically analyzed. Some pilot solutions were also proposed to reduce the expected drawbacks of such technology.

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.

Individual Differences in Glance Patterns under Distraction in Level 2 Automated Driving

This paper investigated individual differences in attentional strategies during the non-driving-related tasks in Level 2 automated driving. Ward’s method was used to cluster participants into different groups according to the characteristics of their sequential off-road glances in the email-sorting task: duration, frequency, variance, and intensity. The clustering results showed two types of sequential off-road glance patterns in distracted Level 2 driving: infrequent long glances vs. frequent short glances. However, participants in the two groups showed similar workload, driving engagement, and email-sorting accuracy. They also reported similar feelings of safety and feedback about the Level 2 vehicle automation. The glance differences demonstrated the complexity of attentional strategies among individual drivers, which is a necessary aspect of driver state to be monitored in automated driving.

Searching for Street Parking: Effects on Driver Vehicle Control, Workload, Physiology, and Glances.

Urban areas that allow street parking exhibit a heightened crash risk that is often attributed to factors such as reduced road width, decreased visibility, and interruptions to traffic flow. No previous on-road studies have investigated how the demands of searching for parking affect driving performance, physiology, and visual attention allocation. We are interested in these effects on the driver and their possible influence on the safety of the environment. While simulator studies offer several benefits, the physical, mental and social pressures incurred by searching for parking in an urban streetscape cannot be emulated in a simulator. We conducted an on-road instrumented vehicle study with 28 participants driving in downtown Toronto, Canada to explore the effect of searching for street parking on drivers. During the experiment, participants drove two routes in a counterbalanced order: one route with a parking search task, and the other route as a baseline. Speed and lane position were measured via vehicle instrumentation, heart rate and galvanic skin response were measured through physiological sensors, and gaze position was collected through a head-mounted eye-tracker. Participants completed the NASA Task Load Index after each route. It was found that while searching for parking, participants drove slower and closer to the curb, and perceived higher workload. While there were no statistically significant effects in physiological measures, there was a rise in heart rate approaching statistical significance. A detailed analysis of eye-tracking data revealed a clear change in glance behavior while searching for parking, with an increase in long off-road glances (>2 s) and decrease in shorter off-road glances (<1.6 s). Some exhibited behaviors (e.g., slowing down) may be seen to compensate for the potentially negative effects of increased demands associated with parking search, while others (e.g., increase in long off-road glances) have the potential to increase crash risk. This study acts as an important first step in revealing changes in driving performance, physiology and glance behavior brought on by searching for parking in a real-world urban environment.

Mid-Air Tactile Feedback Co-Located With Virtual Touchscreen Improves Dual-Task Performance.

The use of haptic technology has recently become essential in Human-Computer Interaction to improve performance and user experience. Mid-air tactile feedback co-located with virtual touchscreen displays have a great potential to improve the performance in dual-task situations, such as when using a phone while walking or driving. The purpose of this article is to investigate the effects of augmenting virtual touchscreen with mid-air tactile feedback to improve dual-task performance where the primary task is driving in a simulation environment and the secondary task involves interacting with a virtual touchscreen. Performance metrics included primary task performance in terms of velocity error, deviation from the middle of the road, number of collisions, and the number of off-road glances, secondary task performance including the interaction time and the reach time, and quality of user experience for perceived difficulty and satisfaction. Results demonstrate that adding mid-air tactile feedback to virtual touchscreen resulted in statistically significant improvement in the primary task performance (the average speed error, spatial deviation, and the number of off-road glances), the secondary task (reach time), and the perceived difficulty. These results provide a great motivation for augmenting virtual touchscreens with mid-air tactile feedback in dual-task human-computer interaction applications.

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.

Characterising mobile phone calls while driving on limited-access roads based on SHRP 2 naturalistic driving data

Research has found that mobile phone call engagement while driving negatively affects driving performance. However, no studies exist characterising hand-held mobile phone calls while driving under naturalistic conditions that include aspects such as the duration of mobile phone subtasks and glance behaviour. Identifying the particularly distracting phases of hand-held telephoning and the nature of influencing factors are the basis for developing design recommendations (e.g. for an in-vehicle information system). Potential influencing factors on driving performance such as call type, mobile phone storage location, or any self-regulatory behaviour need to be taken into account. The present study aimed to draw a comprehensive picture of making hand-held mobile phone calls while driving on limited-access roads using SHRP 2 naturalistic driving data. Mobile phone phase duration, glance behaviour, call type, and mobile phone storage location were coded manually across 98 events. The results show that the handling phase of a mobile phone call (e.g. searching for contacts, dialling) was the most dangerous due to longer mean off- than on-road glances. Outgoing calls caused longer mean off-road glances than incoming; nevertheless, the 2 s critical threshold was not exceeded. A significant influence of mobile phone storage location on glance behaviour did not exist. Moreover, at least in free-flow driving conditions, drivers had enough spare capacity to conduct a mobile phone call without reducing vehicle speed. The results suggest that in low complexity traffic situations drivers can compensate for the increased driving task demand due to telephoning by making minor changes in glance behaviour.