Glance Behavior Research Articles

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.

Effect of instructing system limitations on the intervening behavior of drivers in partial driving automation

Proper understanding of automation limitations is vital in order for drivers to deal with unexpected critical situations. The present study focuses on explanation-based knowledge of the limitations given to novice drivers who have no knowledge and experience of using driving automation systems. The knowledge is discussed considering (1) the possibility of the automation failing to issue an alert when the driving automation cannot handle the situation and (2) the manner of describing the limitations from either a functional or scenic point of view. An experiment conducted under 2 × 2 conditions of explanation-based knowledge (n = 24 participants per condition, average age of the participant = 55.9 ± 16.2 years) is implemented in a driving simulator. Data on transition time from automated control to manual control are collected. The results reveal that drivers could intervene more safely if the knowledge is described from a scenic point of view (average ratio of safe intervention = 95%, average reaction time = 2.0 s), as compared to a functional description (88%, 2.3 s). Explicit/scenic knowledge was found to be more beneficial in responding to alerts in such situations involving system limitations as well as in dealing with critical system failures. Further investigation of glance behavior and interviews revealed that novice drivers with explicit/functional knowledge are prone to be over-reliant on the automation’s capability. Therefore, the present study clarified that providing a driver with knowledge about system limitations/failures explicitly while giving is instructive for perceiving and responding to system limitations as well as unexpected hazards due to system failures.

Effect of Visual and Auditory Alerts on Older Drivers’ Glances toward Latent Hazards while Turning Left at Intersections

Older drivers are known to make significantly fewer glances toward hazards that are hidden from view (latent hazards) than middle-aged drivers. This is especially true when the driver is making a left turn at an intersection at that critical point in the turn immediately after the driver enters the intersection. This has led to the development of training programs that can increase the frequency of these glances toward latent hazards at intersections. However, training programs can require time and money that many older adults may not have. Advances in machine vision and vehicle-to-vehicle communications technologies make possible the use of alerts that warn older drivers of the location of latent hazards at intersections. This driving simulator study investigates the effect of auditory and visual warning alerts on older drivers’ primary (before entering the intersection) and secondary (just after entering the intersection) glance behavior when making a left turn at an intersection. In a between-subjects design, forty older drivers navigated eight unique scenarios containing latent hazards either in the presence or in the absence of combined auditory and visual hazard warning alerts. The results showed that older drivers anticipated a significantly greater proportion of latent hazards in the presence of warning alerts both before they enter the intersection and after they enter the intersection. The results of this study suggest that a combination of auditory and visual alerts may be effective at improving older drivers’ glance behavior while making left turns at intersections.

The Effect of Partial Automation on Driver Attention: A Naturalistic Driving Study.

This naturalistic driving study investigated how drivers deploy visual attention in a partially automated vehicle. Vehicle automation is rapidly increasing across vehicle fleets. This increase in automation will likely have both positive and negative consequences as drivers learn to use the new technology. Research is needed to understand how drivers interact with partially automated vehicle systems and what impact new technology has on driver attention. Ten participants drove a Tesla Model S for 1 week during their daily commute on a stretch of busy interstate. Drivers were instructed to use Autopilot, a system that provides both lateral and longitudinal control, as much as they felt comfortable while driving on the interstate. Driver-facing video data were recorded and manually reduced to examine glance behavior. Drivers primarily allocated their visual attention between the forward roadway (74% of glance time) and the instrument panel (13%). With partial automation engaged, drivers made longer single glances and had longer maximum total-eyes-off-road time (TEORT) associated with a glance cluster. These results provide a window into the nature of visual attention while driving with partial vehicle automation. The results suggest that drivers may be more willing to execute long, "outlier" glances and clusters of glances to off-road locations with partial automation. The findings highlight several important human factors considerations for partially automated vehicles.

Design and evaluation of auditory-supported air gesture controls in vehicles

Using touchscreens while driving introduces competition for visual attention that increases crash risk. To resolve this issue, we have developed an auditory-supported air gesture system. We conducted two experiments using the driving simulator to investigate the influence of this system on driving performance, eye glance behavior, secondary task performance, and driver workload. In Experiment 1 we investigated the impact of menu layout and auditory displays with 23 participants. In Experiment 2 we compared the best systems from Experiment 1 with equivalent touchscreen systems with 24 participants. Results from Experiment 1 showed that menus arranged in 2 × 2 grids outperformed systems with 4 × 4 grids across all measures and also demonstrated that auditory displays can be used to reduce visual demands of in-vehicle controls. In Experiment 2 auditory-supported air gestures allowed drivers to look at the road more, showed equivalent driver workload and driving performance, and slightly decreased secondary task performance compared to touchscreens. Implications are discussed with multiple resources theory and Fitts’s law.

A Bayesian Reference Model for Visual Time-Sharing Behaviour in Manual and Automated Naturalistic Driving

Visual time-sharing (VTS) behavior characterizes an inattentive driver. Because inattention has been identified as the major contributing factor in traffic crashes, understanding the relationship between VTS and crash risk could help reduce the crash risk through the development of inattention countermeasures. The aims of this paper are: 1) to develop a reference model of the VTS behavior and 2) reveal if vehicle automation influences the VTS behavior. The reference model was based on naturalistic eye-tracking data. The VTS sequences were extracted from routine driving data (including manual and automated driving). We used Bayesian generalized linear mixed models for a range of on- and off-path glance-based metrics. Each parameter was estimated with a probability distribution and summarized with credible intervals containing the model parameters with 95% probability. The reference model not only corroborates previous findings from the driving simulator experiments and on-road studies, but also captures the characteristics of on-path and off-path glance behavior in greater detail. The model demonstrated that: 1) there was minimal change in the VTS behavior due to automation and 2) the percentage of time that glances fell on-path (PRC) was greater for all routine driving (~80%) than for the VTS sequences (~50%). The PRC was the only metric that was sensitive to the VTS, but it did not differentiate between manual and automated driving. Our model, by describing a measure of inattention (VTS behavior), can be used in future driver models to improve the computer simulations used to design ADASs and evaluate their safety benefits. In addition, the model could serve as a detailed reference for inattention guidelines.

Evaluation of Gesture-Based In-Vehicle Interaction: User Experience and the Potential to Reduce Driver Distraction.

We observe the effects of in-vehicle system gesture-based interaction versus touch-based interaction on driver distraction and user experience. Driver distraction is a major problem for traffic safety, as it is a contributing factor to a number of accidents. Visual distraction in particular has a highly negative impact on the driver. One possibility for reducing visual driver distraction is to use new forms of interaction in the vehicle, such as gesture-based interaction. In this experiment, participants drove on a motorway or in a city scenario while using touch-based interaction or gesture-based interaction. Subjective data, such as acceptance and workload, and objective data, including glance behavior, were gathered. As a result, participants rated their subjective impressions of safe driving as higher when using gesture-based interaction. More specifically, acceptance and attractiveness were higher, and workload was lower. The participants performed significantly fewer glances to the display and the glances were much shorter. Gestures are a positive alternative for in-vehicle interaction since effects on driver distraction are less significant when compared to touch-based interaction. Potential application of this research includes interaction design of typical in-vehicle information and entertainment functions.

Effects of alcohol at 0.05% blood alcohol concentration (BAC) on low speed urban driving

ABSTRACTObjective: Alcohol-impaired driving presents a continued risk for traffic safety and results in a significant proportion of fatalities on the roadway. We examined how alcohol at a 0.05% blood alcohol concentration (BAC) compares to 0.10% BAC (above the current U.S. legal limit) in terms of impact on driving performance.Methods: Utilizing a within-subjects design, we recruited 108 healthy experienced drivers who were moderate to heavy drinkers. In a double-blind, placebo-controlled crossover design, we administered placebo and alcohol at the 0.05% and 0.10% BAC levels in a standardized simulated driving protocol. Drives occurred on the descending limb of the blood alcohol curve. This analysis focuses on the urban portion of the driveResults: The study observed clear differences in performance for lateral and longitudinal driving performance and glance behavior. Variability in lane keeping and average speed increased with BAC level, with degraded performance observed at 0.05% BAC. The frequency of lane departures and percentage of time focused on the forward roadway at 0.05% BAC did not differ from placebo but differed from the 0.10% BAC level.Conclusions: Overall, our results show that there is degraded performance in the urban driving environment and that much of that begins at or below the 0.05% BAC level.

The effects of age, interface modality, and system design on drivers’ attentional demand when making phone calls while driving on a limited-access highway

In-vehicle information systems that allow drivers to use a single voice command to complete a task rather than multiple commands better keep drivers’ attention toward the road, especially compared with when drivers complete the task manually. However, single voice commands are longer and more complex and may be difficult for older drivers to use. The current study examined the glance behavior, workload, and driving performance of drivers age 20–66 years when they placed a call using their hands or voice with the Chevrolet MyLink or Volvo Sensus information system during highway driving. In general, as age increased, drivers took longer to complete phone calls, reported greater workload when using voice commands, and made significantly more off-road glances lasting longer than two seconds when placing calls relative to younger drivers. Both the voice-command systems of MyLink and Sensus increased the proportion of time that drivers were looking at the road when calling compared with manual phone calling, but the relative increase was greater when using MyLink’s single-voice-command system compared with the multiple-command system of Sensus, and this advantage grew as drivers aged. The findings indicate that placing calls while driving using voice commands helps drivers of all ages keep their attention toward the road better than doing so manually, and that, contrary to expectation, using a single-command system like MyLink’s worked better than a multiple-command system like Sensus for older drivers as well as younger ones.

A distraction index for quantification of driver eye glance behavior: A study using SHRP2 NEST database

Distracted driving behavior and driving inattention are two leading causes of roadway crashes. The state-of-the-art safety research made several attempts to understand and quantify distracted driving and driver inattention. While each attempt had its limitation, there was a consensus on the relevance of eye glance behavior as a promising parameter in understanding distracted driving. In this study, a renewal cycle approach is implemented to provide deeper insights into how drivers allocate their attention while driving. This approach is then applied to the Naturalistic Engagement in Secondary Tasks (NEST) dataset to analyze drivers’ eye glance patterns and determine the relationship between their visual behavior and engagement in different types of secondary tasks (activities performed while driving). The analysis revealed that distracted driving behavior could be well characterized by two new measures: the number of renewal cycles per event (NRC) and a distraction level index (DI). Consequently, mixed-effects modeling is implemented to test the effectiveness of the two measures to differentiate crash/near-crash events from non-crash events. The analysis showed that the two measures increase significantly for crash/near-crash events compared to non-crash driving events with p-values less than 0.0001. The findings of this paper are promising to the quantification of the risk associated with distraction related visual behavior. The finding can also help build reliable algorithms for in-vehicle driving assistance systems to alert drivers before crash/near-crash events.

Effects of an in-vehicle eco-safe driving system on drivers’ glance behaviour

We have designed a new in-vehicle eco-safe driving system and shown its effectiveness in prompting drivers to execute a fuel-saving and safe driving style (Vaezipour et al., 2018, submitted for publication). However, the system could also bring potential negative outcomes, i.e. driver distraction. This simulator study investigated drivers’ glance behaviours as indicators of driver distraction when using our Eco-Safe Human-Machine-Interface (HMI). Four types of eco-safe information display conditions (baseline, advice only, feedback only, both advice and feedback) were tested on different traffic situations with varied road traffic complexity. Results showed that the eco-safe HMI system did not cause visual distraction. In contrast, the advice only or feedback only information improved forward gazing on the roadway. In addition, drivers tended to adapt their visual scanning strategies according to the traffic situations. In the car-following situation they paid longer glances to the forward roadway, while in the intersections they spent more time to look at the HMI system. The findings indicated that our eco-safe driving system improved drivers’ eco-safe behaviours and meanwhile enhanced their visual attention on road while no evidence showed that drivers were distracted by it.

A Reference Model for Driver Attention in Automation: Glance Behavior Changes During Lateral and Longitudinal Assistance

This paper introduces a reference model of glance behavior for driving safety assessment. This model can improve the design of automated and assistive systems. Technological limitations have previously hindered the use of unobtrusive eye trackers to measure glance behavior in naturalistic conditions. This paper presents a comprehensive analysis of eye-tracking data collected in a naturalistic field operation test, using an eye tracker that proved to be robust in real-world driving scenarios. We describe a post-processing technique to enhance the quality of naturalistic eye-tracker data, propose a data-analysis procedure that captures the important features of glance behavior, and develop a model of glance behavior (based on distribution fitting), which was lacking in the literature. The model and its metrics capture key defining characteristics of, and differences between, on- and off-path glance distributions, and during manual driving and driving with adaptive cruise control and lane keeping aid active. The results show that drivers’ visual response is tightly coupled to the driving context (vehicle automation, car-following, and illumination).

Assessing Driving Simulator Validity: A Comparison of Multi-Modal Smartphone Interactions across Simulated and Field Environments

The use of a driving simulator as a tool to evaluate secondary task performance elicits the question of simulator validity. After upgrading an existing driving simulator from a medium-fidelity to a high-fidelity configuration with a new software environment, a study was run to benchmark this simulator against previously published highway-driving data. A primary goal was to assess relative and absolute validity in a simulated highway environment. Data from 72 participants who performed manual and voice-based contact dialing tasks with a center-stack-mounted smartphone in either the driving simulator or driving on the highway in one of two vehicles is considered. This analysis compared secondary task demand between the simulator and on-road vehicles by primarily considering driver off-road glance behavior. Mean total eyes-off-road time, mean single-glance duration, and the number of long off-road glances showed similar patterns relative to the manual versus voice-based tasks in the simulator and the two on-road vehicles. A driving performance metric, percentage change of standard deviation of velocity, showed differing results between the simulator and on-road vehicles. It is concluded that these data make a strong argument for relative validity, and in some cases absolute validity, for this simulator for studying glance behavior associated with in-vehicle devices under a highway-driving scenario.

Calibration in Older and Middle-aged Drivers: Relationship between Subjective and Objective Glance Performance at Complex Intersections

Older drivers are an at-risk population for automobile crashes, especially at intersections. Intersection maneuvers demand a series of motor and visual responses executed at specific proximities and timings during a turn. Previous research indicates that older drivers are more likely than middle-aged drivers to neglect anticipatory glances to areas where latent hazards could materialize at intersections. Calibration, which reflects the degree of agreement (or discordance) between a driver’s self-perception of their driving ability and their actual ability, might be a factor that drives the age-related differences in visual scanning at intersections. This study examined relationships between eye movement patterns while driving through intersection scenarios in a medium-fidelity simulator and their subjective performance scores for middle-aged and older drivers. The data indicated no difference in calibration scores between older and middle-aged drivers. However, data showed that older drivers with higher subjective performance executed fewer secondary glances: this pattern was not present for middle aged drivers. Further research is necessary to identify psychological mechanisms involving driver calibration that control the age-related declines in anticipatory glance behavior at intersections.

Evaluation and Validation of Distraction Detection Algorithms on Multiple Data Sources

Many researchers have developed algorithms to detect distraction, but they have yet to be validated on multiple data sources. This study aims to evaluate these algorithms by comparing their ability to detect distraction and predict event likelihood. Four algorithms that use measures of cumulative glance, past glance behavior, and glance eccentricity were used to understand the distracted state of the driver and were validated on two separate data sources: naturalistic and experimental data. Results showed that there was a higher likelihood of event detection when cumulative glances were considered. Glance eccentricity was best for predicting distraction. Future research can use these findings to design mitigation systems that give drivers feedback in instances of high crash likelihood.

Glance behavior as design indices of in-vehicle visual support system: A study using crane simulators

A prediction model is used to predict subjective responses of crane operators with respect to different designs of In-Vehicle Visual Support (IVVS). Selected gaze metrics are used as objective metrics to minimize prejudice, which is commonly caused by subjective measures. Experiments are carried out using crane simulator to measure glance behavior of novice operators and the 3D perspective projection method is used for autonomous mapping of gaze fixations to dynamic Area-of-Interests (AOIs). Subjective responses, such as operators' emotion and usability of IVVS, are evaluated using the Likert scale of the Semantic Differential method. Correlation between gaze metrics and subjective responses is established using multiple linear regression. Glance behavior exhibits a statistically significant difference when information on IVVS is perceived as useful to ease operation and reduce tension. Despite this, there are no significant signs of distraction. Glance behavior is found to be a reliable sub-conscious indicator of subjective response and distraction. More importantly, the proposed gaze metrics are found to be a good representation of glance behavior, such as randomness and distribution of attention. The methods and findings are useful to evaluate impact of IVVS, which is becoming more common in many other applications.

Changes in driver glance behavior when using a system that automates steering to perform a low-speed parallel parking maneuver

Drivers adapt their glance behavior when using automation, which may detract attention from their surroundings. Glance behavior during parallel parking maneuvers performed with and without automated steering was compared. Drivers directed a smaller proportion of their glances toward the parking space and spent less time looking at it when using automation than when not using automation. The proportion of glances and time spent looking at the instrument cluster containing information from the automation increased significantly. Drivers also spent a significantly larger proportion of time looking at the instrument cluster and a smaller proportion looking forward and rearward when using automation while approaching a parking space. The system selected the parking space in the approach phase, which may have drawn attention to the instrument cluster. In conclusion, when using automated steering during parallel parking drivers monitored their surroundings less and looked at system displays more presumably to supervise the automation. The safety implications of these changes in glance behavior should be explored in future research.

A study in real traffic examining glance behaviour of teenage cyclists when listening to music: Results and ethical considerations

Listening to music while cycling impairs cyclists’ auditory perception and may decrease their awareness of approaching vehicles. If the impaired auditory perception is not compensated by the cyclist himself or other road users involved, crashes may occur. The first aim of this study was to investigate in real traffic whether teenage cyclists (aged 16–18) compensate for listening to music by increasing their visual performance. Research in real traffic may pose a risk for participants. Although no standard ethical codes exist for road safety research, we took a number of ethical considerations into account to protect participants. Our second aim was to present this study as a case study demonstrating ethical dilemmas related to performing research in real traffic. The third aim was to examine to what extent the applied experimental set-up is suitable to examine bicyclists’ visual behaviour in situations crucial for their safety. Semi-naturalistic data was gathered. Participants’ eye movements were recorded by a head-mounted eye-tracker during two of their regular trips in urban environments. During one of the trips, cyclists were listening to music (music condition); during the other trip they were ‘just’ cycling (the baseline condition). As for cyclists’ visual behaviour, overall results show that it was not affected by listening to music. Descriptive statistics showed that 21–36% of participants increased their visual performance in the music condition, while 43–64% decreased their visual performance while listening to music. Due to ethical considerations, the study was therefore terminated after fourteen cyclists had participated. Potential implications of these results for cycling safety and cycling safety research are discussed. The methodology used in this study did not allow us to investigate cyclists’ behaviour in demanding traffic environment. However, for now, no other research method seems suitable to address this research gap.

The impact of an in-vehicle display on glance distribution in partially automated driving in an on-road experiment

One of the major challenges of designing an HMI for partially automated vehicles is the trade-off between a sufficient level of system information and avoidance of distracting the driver. This study aimed to investigate drivers’ glance behavior as an indicator of distraction when vehicle guidance is partially automated. Therefore, an on-road experiment was conducted comparing two versions of an in-vehicle display (during partially automated driving) and no display (during manual driving) on a heavy congested highway segment. The distribution of drivers’ total glance durations on the HMI showed that visual attention was shifted away from monitoring the central road scene towards looking at the in-vehicle display to a considerable extent. However, an analysis of the distribution of single glance durations supports the view that using partial automation and a respective HMI does not lead to a critical increase in distraction. Driving with a simplified version of the HMI had the potential to reduce glance duration on and thus potential distraction of the in-vehicle display.

Effects of Quantity and Size of Buttons of In-Vehicle Touch Screen on Drivers’ Eye Glance Behavior

ABSTRACTThis article investigates the effects of the quantity and size of touch screen buttons and the task-interleaving strategies on drives’ eye glance behavior. An experiment was conducted on a fixed-base driving simulator with 20 participants. The participants were asked to perform a button search-and-press task on an in-vehicle touch screen while driving. A full-factorial within-subject design was used with three button quantities (4, 8, and 15) and three button sizes (14 mm, 24 mm, and 33 mm). Although a normal distribution was often assumed for the eye glance data in previous studies, our results show that the total eyes-off-road time (TEORT) and glance durations are generally not normally distributed (positively skewed) even after a log transformation. The results show that the number of buttons has an increasing effect on task completion time, TEORT, and long (2+ s) glances. However, in general, no such differences were found for button sizes. Further analysis shows that long glances were strongly associated with drivers completing the task with a single glance. It seems to suggest that a major cause of long glances is that drivers are reluctant to switch the task back to driving at subtask boundaries that are probably associated with the high cost of interruption. These findings confirm the importance of task resumability for in-vehicle user interfaces and have implications that careful task analysis needs to be conducted in the context of multitasking. Certain subtask combinations, such as a visual search followed by pressing the search target, may discourage task interleaving and ultimately compromise driving safety.