Mean Glance Duration Research Articles

Multitasking While Driving: How Drivers Self-Regulate Their Interaction with In-Vehicle Touchscreens in Automated Driving

Driver assistance systems are designed to increase comfort and safety by automating parts of the driving task. At the same time, modern in-vehicle information systems with large touchscreens provide the driver with numerous options for entertainment, information, or communication, and are a potential source of distraction. However, little is known about how driving automation affects how drivers interact with the center stack touchscreen, i.e., how drivers self-regulate their behavior in response to different levels of driving automation. To investigate this, we apply multilevel models to a real-world driving dataset consisting of 31,378 sequences. Our results show significant differences in drivers’ interaction and glance behavior in response to different levels of driving automation, vehicle speed, and road curvature. During automated driving, drivers perform more interactions per touchscreen sequence and increase the time spent looking at the center stack touchscreen. Specifically, at higher levels of driving automation (level 2), the mean glance duration toward the center stack touchscreen increases by 36% and the mean number of interactions per sequence increases by 17% compared to manual driving. Furthermore, partially automated driving has a strong impact on the use of more complex UI elements (e.g., maps) and touch gestures (e.g., multitouch). We also show that the effect of driving automation on drivers’ self-regulation is greater than that of vehicle speed and road curvature. The derived knowledge can inform the design and evaluation of touch-based infotainment systems and the development of context-aware driver monitoring systems.

Driver response and recovery following automation initiated disengagement in real-world hands-free driving

Objective Advanced driver assistance systems are increasingly available in consumer vehicles, making the study of drivers’ behavioral adaptation and the impact of automation beneficial for driving safety. Concerns over driver’s being out-of-the-loop, coupled with known limitations of automation, has led research to focus on time-critical, system-initiated disengagements. This study used real-world data to assess drivers’ response to, and recovery from, automation-initiated disengagements by quantifying changes in visual attention, vehicle control, and time to steady-state behaviors. Methods Fourteen drivers drove for one month each a Cadillac CT6 equipped with Super Cruise (SC), a partial automation system that, when engaged, enables hands-free driving. The vehicles were instrumented with data acquisition systems recording driving kinematics, automation use, GPS, and video. The dataset included 265 SC-initiated disengagements identified across 5,514 miles driven with SC. Results Linear quantile mixed-effects models of glance behavior indicated that following SC-initiated disengagement, the proportions of glances to the Road decreased (Q50Before=0.91, Q50After=0.69; Q85Before=1.0, Q85After=0.79), the proportions of glances to the Instrument Cluster increased (Q50Before=0.14, Q50After=0.25; Q85Before=0.34, Q85After=0.45), and mean glance duration to the Road decreased by 4.86 sec in Q85. Multinomial logistic regression mixed-models of glance distributions indicated that the number of transitions between glance locations following disengagement increased by 43% and that glances were distributed across fewer locations. When driving hands-free, take over time was significantly longer (2.4 sec) compared to when driving with at least one hand on the steering wheel (1.8 sec). Analysis of moment-to-moment distributional properties of visual attention and steering wheel control following disengagement indicated that on average it took drivers 6.1 sec to start the recovery of glance behavior to the Road and 1.5 sec for trend-stationary proportions of at least one hand on the steering wheel. Conclusions Automation-initiated disengagements triggered substantial changes in driver glance behavior including shorter on-road glances and frequent transitions between Road and Instrument Cluster glance locations. This information seeking behavior may capture drivers’ search for information related to the disengagement or the automation state and is likely shaped by the automation design. The study findings can inform the design of more effective driver-centric information displays for smoother transitions and faster recovery.

Design and evaluation of visual guiding facilities along urban road tunnel horizontal curves based on vision and speed perception

With continuous increase in the number and length of urban road tunnels, traffic safety in the road tunnels has attracted ever greater attention. In particular, driver’s sight distance and sight zone along urban tunnel curves are constrained, and potential safety hazards are prominent. Herein, from the perspectives of active guidance, using visual guiding facilities to enable drivers to accurately perceive the orientation of the tunnel curve alignment and to control the speed reasonably have become a key research point with theoretical significance and practical application value. In this study, four types of schemes for urban road tunnel horizontal curves were constructed and evaluated by simulation experiments. Scene a was a rare scene without any visual guiding facility in practice, ordinary Scene b was a common scene in an urban road tunnel, Scene c included chevron alignment signs (additional to Scene b), and Scene d included LED arches (additional to Scene b). Glance location occupancy, mean glance duration, accuracy of speed perception and reaction time were used as driver performance indicators, in which the four types of scenes were analyzed and evaluated by visual test, speed perception test and subjective evaluation. The results showed that compared with Scenes a and b, Scene c with chevron alignment signs can improve alignment guidance along road tunnel horizontal curve, while the test results of Scene d with LED arches as proposed in this study had the best performance in all aspects. The research scheme and test results can provide reference for visual guiding facility design and traffic safety improvement along urban road tunnel horizontal curves.

Patterns in transitions of visual attention during baseline driving and during interaction with visual–manual and voice-based interfaces

Voice interfaces reduce visual demand compared with visual-manual interfaces, but the extent depends on design. This study compared visual demand during baseline driving with driving while using voice or manual inputs to place calls with Chevrolet MyLink, Volvo Sensus, or a smartphone. Mean glance duration and total eyes-off-road-time increased when using manual input compared with baseline driving; only eyes off road time increased with voice input. Confusion matrices developed with hidden Markov modelling characterise the similarity of glance sequences during baseline driving and while making phone calls. Glance sequences with the MyLink voice interface were misclassified as baseline driving more frequently than the other voice interfaces. Conversely, glance sequences with the Sensus and smartphone voice interfaces were more often misclassified as manual phone calling. Thus, the MyLink voice interface not only reduced the overall visual demand of placing calls, but produced glance patterns more similar to driving without another task. Practitioner Summary: The attention map and confusion matrix methodologies provide ways of characterising similarities and differences in glance behaviour across secondary task conditions, complementing traditional temporally based metrics (e.g. mean glance duration, long duration glances) while addressing some of the limitations of total-eyes-off-road-time (TEORT) for comparing secondary task behaviour to baseline driving.

Effects of secondary tasks and display position on glance behavior during partially automated driving

The driving task is becoming increasingly automated, thus changing the driver’s role. Moreover, in-vehicle information systems using different display positions and information processing channels might encourage secondary task engagement. During manual driving scenarios, varying secondary tasks and display positions could influence driver’s glance behavior. However, their impact on the driver’s capability to monitor the partially automated driving system has not yet been determined. The current study assessed both the effects of different secondary tasks (Surrogate Reference Task (SuRT) vs. text reading) and display positions (head-up display (HUD) vs. center console) on driver’s glance behavior during partially automated driving in a simulated car following task. Different automation system failures regarding the lateral and longitudinal control occurred while driving. Furthermore, participants’ reported advantages, disadvantages and preferences regarding the investigated display positions as well as regarding the secondary task engagement during partially automated driving in general. Mixed design ANOVAs revealed that the HUD yielded considerably longer eyes-on display time (total and mean glance durations) than the center console. Moreover, the text reading task resulted in longer total and mean glance durations than the SuRT. Similar to manual driving scenarios, the results showed a consistent effect of display position and secondary task on the driver’s glance behavior. Despite the longer eyes-on display time for the HUD, its proximity to the driving environment might enable a faster identification of and reaction to critical situations (e.g., due to system failures). Participants would prefer the HUD as display position compared to the center console. Regarding secondary task engagement during partially automated driving participants seemed to be aware of the benefits but also of the risks.

An Investigation of Driver Behavior on Urban General Road and in Tunnel Areas

The objective of this study is to examine experience-related differences in microscope driving behavior as drivers performed six separate maneuvers, namely 1) driving on general urban roads, 2) approaching a tunnel portal, 3) driving through a tunnel’s threshold zone, 4) driving in the interior tunnel zone, 5) driving in the zone ahead the tunnel exit and 6) driving after the tunnel exit. An on-road experiment was conducted with 20 drivers in two groups. The first group was made up of new licensed drivers, and the second group contained the more experienced drivers. The study consisted of one between-subject (experience) and five within-subject variables (drive environment type). The drivers’ behavior was measured through Mean Glance Duration, AOI Attention Ration, Horizontal Eye Activity, Vertical Eye Activity, Percentage of Eyelid Closure, and Heart Rate Variability. With respect to the relevant psychological measures, the results show that in general more attention is focused on the far left-hand side of the road and the near front road when driving through tunnel areas when compared with driving on general roads. In addition, the psychological measurements indicate that tunnel’s dark narrow environment causes anxiety on driving for lower heart rate variation coefficient (RRCV). New licensed drivers were more severely affected by the tunnel environment than the experienced drivers.

Developing Predictive Equations to Model the Visual Demand of In-Vehicle Touchscreen HMIs

ABSTRACTTouchscreen human–machine interfaces (HMIs) are commonly employed as the primary control interface and touch-point of vehicles. However, there has been very little theoretical work to model the demand associated with such devices in the automotive domain. Instead, touchscreen HMIs intended for deployment within vehicles tend to undergo time-consuming and expensive empirical testing and user trials, typically requiring fully functioning prototypes, test rigs, and extensive experimental protocols. While such testing is invaluable and must remain within the normal design/development cycle, there are clear benefits, both fiscal and practical, to the theoretical modeling of human performance. We describe the development of a preliminary model of human performance that makes a priori predictions of the visual demand (total glance time, number of glances, and mean glance duration) elicited by in-vehicle touchscreen HMI designs, when used concurrently with driving. The model incorporates information theoretic components based on Hick–Hyman Law decision/search time and Fitts’ Law pointing time and considers anticipation afforded by structuring and repeated exposure to an interface. Encouraging validation results, obtained by applying the model to a real-world prototype touchscreen HMI, suggest that it may provide an effective design and evaluation tool, capable of making valuable predictions regarding the limits of visual demand/performance associated with in-vehicle HMIs, much earlier in the design cycle than traditional design evaluation techniques. Further validation work is required to explore the behavior associated with more complex tasks requiring multiple screen interactions, as well as other HMI design elements and interaction techniques. Results are discussed in the context of facilitating the design of in-vehicle touchscreen HMI to minimize visual demand.

Assessing drivers' response during automated driver support system failures with non-driving tasks

IntroductionWith the increase in automated driver support systems, drivers are shifting from operating their vehicles to supervising their automation. As a result, it is important to understand how drivers interact with these automated systems and evaluate their effect on driver responses to safety critical events. This study aimed to identify how drivers responded when experiencing a safety critical event in automated vehicles while also engaged in non-driving tasks. MethodIn total 48 participants were included in this driving simulator study with two levels of automated driving: (a) driving with no automation and (b) driving with adaptive cruise control (ACC) and lane keeping (LK) systems engaged; and also two levels of a non-driving task (a) watching a movie or (b) no non-driving task. In addition to driving performance measures, non-driving task performance and the mean glance duration for the non-driving task were compared between the two levels of automated driving. ResultsDrivers using the automated systems responded worse than those manually driving in terms of reaction time, lane departure duration, and maximum steering wheel angle to an induced lane departure event. These results also found that non-driving tasks further impaired driver responses to a safety critical event in the automated system condition. ConclusionIn the automated driving condition, driver responses to the safety critical events were slower, especially when engaged in a non-driving task. Practical applicationTraditional driver performance variables may not necessarily effectively and accurately evaluate driver responses to events when supervising autonomous vehicle systems. Thus, it is important to develop and use appropriate variables to quantify drivers' performance under these conditions.

Evaluation of the effects of in‐vehicle traffic lights on driving performances for unsignalised intersections

Ground traffic lights are essential for maintaining traffic efficiency and safety at intersections. However, unsignallised intersections are still frequent in actual traffic environments. With the development of new forms of vehicular communication, in-vehicle traffic lights can assist drivers at unsignallised intersections. The authors proposed two types of in-vehicle traffic lights to assist drivers; these corresponded to two-way and all-way stop-controlled intersections. They adopted gap acceptance theory and a first-come-first-served strategy to determine passing priority for the two types of intersections, respectively. They then conducted a driving simulator experiment involving 23 participants, to investigate driver behaviours elicited by the proposed system. They prepared four experimental conditions with combinations of in-vehicle traffic lights and auditory warnings. The authors’ experimental results indicated that in-vehicle traffic lights were associated with significantly longer post-encroachment times and a significantly shorter maximum brake stroke. In terms of eye-gaze behaviours, the percentage of gaze concentration to the road centre area and mean glance durations were deemed acceptable for the avoidance of visual distraction, when in-vehicle traffic lights were presented via a head-up display. Therefore, their analysis of driver behaviours indicates that in-vehicle traffic lights can effectively provide driver assistance at unsignallised intersections.

Drivers' Visual Characteristics when Merging onto or Exiting an Urban Expressway.

The aim of this study is to examine drivers’ visual and driving behavior while merging onto or exiting an urban expressway with low and high traffic densities. The analysis was conducted according to three periods (approaching, merging or exiting, and accelerating or decelerating). A total of 10 subjects (8 males and 2 females) with ages ranging from 25 to 52 years old (M = 30.0 years old) participated in the study. The research was conducted in a natural driving situation, and the drivers’ eye movements were monitored and recorded using an eye tracking system. The results show that the influence of traffic density on the glance duration and scan duration is more significant when merging than when exiting. The results also demonstrate that the number of glances and the mean glance duration are mainly related to the driving task (e.g., the merging period). Therefore, drivers’ visual search strategies mainly depend on the current driving task. With regard to driving behavior, the variation tendencies of the duration and the velocity of each period are similar. These results support building an automated driving assistant system that can automatically identify gaps and accelerate or decelerate the car accordingly or provide suggestions to the driver to do so.

Pilots’ gaze strategies and manual control performance using occlusion as a measurement technique during a simulated manual flight task

The aim of this study was to analyze pilots' visual scanning under conditions visually restricted by the occlusion paradigm. During manual flight, pilots experienced interruptions in their panel scan due to concurring tasks and monitoring of distant displays. Eleven volunteer airline pilots performed several manual instrument landing system approaches in a fixed-base flight simulator. Some of these approaches were performed using the paradigm of occlusion with shutter glasses. Under occlusion, the gaze pattern analysis revealed that pilots demonstrated reduced mean glance durations, but did not reduce their attention to lesser information displays. The results also indicated that the attitude indicator (artificial horizon) as a preview instrument was less affected by occlusion compared to other areas of interest. A subsequent scanpath analysis revealed that vertical tracking was the predominant information acquisition strategy and corresponded to larger deviations on the glideslope. These results imply the need to optimize information even for short glances, and to be very cautious with adaptive layouts of free programmable or dynamic displays, and not to overburden the pilot flying with parallel tasks.

고속국도에서의 주행속도 차이에 따른 운전자 평균 주시시간 특성에 관한 연구

Drivers can receive diverse types of traffic information through a number of methods. However, there are not enough information services considering human factors. In this study, as a basic research on human factors of the drivers, characteristic analysis on drivers' mean glance (fixation) durations with different running speeds on the expressway was performed under diverse running environments. To control variables other than running speeds, running environments were categorized into 4 types: 'daytime running without preceding vehicles', 'daytime running with preceding vehicles', 'nighttime running without preceding vehicles', and 'nighttime running with preceding vehicles'. Furthermore, ANOVA Test was used to divide speed groups. As a result of performing a multiple comparison to compare differences in glance behavior per each group, the road item and the preceding vehicles item showed an increase in mean glance durations as the speed increased, while the front view showed a decrease in mean glance durations. It was confirmed that the road sign showed no statistically significant difference in glance durations as the speed varied.

Effects of Distance and Accuracy on Visual Search in Golf Putting

The purpose of this study was to examine the eye movement depending on putting distance and accuracy in golf putting. The subjects were semi-professional 5 golfers. Golfers had performed golf putting on 2 m and 15 m distances. Visual search had used in order to examine the eye movement in success and failure of putting by eye tracker (Dikablis 2.0). During golf putting, eye movement analysis had analyzed on the ball and the hole of putting distance and accuracy. Data were analyzed with analysis of variance for repeated measures using SPSS ver. 15.0 program. Visual search to distance and accuracy on ball were as followed. Duration was significant differences in putting distance. Number of glances was significant differences in accuracy. Percentaged glance proportion was significant differences in putting distance. Glance frequency was significant differences in putting distance. Visual search to distance and accuracy on hole were followed. Total glance time and number of glances were significant differences in putting distance. Mean glance duration was significant differences in putting distance, accuracy, and between interaction. Percentaged glance proportion was significant differences in putting distance and between interaction. Maximal glance duration was significant differences in putting distance, accuracy, and between interaction. Minimal glance duration was significant differences in accuracy, and between interaction. Glance frequency was significant differences in between interaction. This study will be expected to be utilized for putting performance improvement as a basis for developing an exercise program.

Visual Sampling of In-Vehicle Text Messages: Effects of Number of Lines, Page Presentation, and Message Control

Emerging in-vehicle technology associated with radio data systems, satellite radio, navigation aids, and infotainment systems will expose drivers to an increasing amount of textual information. The visual demands of driving make it critically important to understand how characteristics of such information affect visual sampling of the roadway. This study used a medium-fidelity driving simulator to evaluate the effect of scroll control (manual or automatic), the number of lines displayed (one, two, or four), and scrolling strategy (line by line or page by page) on drivers' visual sampling behavior of text messages. Fifteen men and 15 women aged 25 to 51 (mean 35.7, s.d. 7.5) participated. Consistent with previous models of sampling behavior, text message characteristics affected the number of glances much more strongly than the duration of glances, and drivers were able to protect driving performance even with a demanding secondary visual task. However, the number of lines of text displayed increased the mean glance duration, the variability of glance duration, and the number of glances greater than 2 s. Scrolling text line by line increased visual demand relative to scrolling page by page, particularly when scrolling is manually controlled by the driver. Manual control of scrolling by using a touch screen button led to greater visual demand compared with automatically scrolled text.

Visual Sampling of In-Vehicle Text Messages

Emerging in-vehicle technology associated with radio data systems, satellite radio, navigation aids, and infotainment systems will expose drivers to an increasing amount of textual information. The visual demands of driving make it critically important to understand how characteristics of such information affect visual sampling of the roadway. This study used a medium-fidelity driving simulator to evaluate the effect of scroll control (manual or automatic), the number of lines displayed (one, two, or four), and scrolling strategy (line by line or page by page) on drivers’ visual sampling behavior of text messages. Fifteen men and 15 women aged 25 to 51 (mean 35.7, s.d. 7.5) participated. Consistent with previous models of sampling behavior, text message characteristics affected the number of glances much more strongly than the duration of glances, and drivers were able to protect driving performance even with a demanding secondary visual task. However, the number of lines of text displayed increased the mean glance duration, the variability of glance duration, and the number of glances greater than 2 s. Scrolling text line by line increased visual demand relative to scrolling page by page, particularly when scrolling is manually controlled by the driver. Manual control of scrolling by using a touch screen button led to greater visual demand compared with automatically scrolled text.

THE EFFECT OF CELLULAR PHONE USE ON DRIVING PERFORMANCE

Many experiments using driving simulators or real roads have shown that using a cellular phone while driving may cause an accident because it delays visual information processing by the driver. In this research, we examined the influence on driving performance of cellular phone use on a course that simulated streets. Driving conditions were driving only, listening to the car radio, hands-free cellular phone use and using a cellular phone with the left hand. Driving performance measurements included braking response time to the brake lights of a preceding car, eye movement, distance from the vehicle in front and lane observance. The subjects were 50 drivers, including ten driving instructors. The mean glance duration when manipulating a cellular phone was longer than when manipulating a hands-free set or car stereo. Braking reaction delay time increased in the following order: driving only, car radio, hands-free and, longest of all, cellular phone. When the cellular phone was used, car speed was slowest, and the distance from the vehicle in front became the longest. Glance duration other than to the front, indicating divided attention, was shortest during the cellular phone use and there were also fewer instances of eye movement. In the case of cellular phone use, stable driving appeared to be more difficult, as there was substantial steering wheel deflection. In this experiment, it was confirmed that use of a hands-free set is effective to some extent, but driving performance was poorer than with driving only. Even though different forms of in-vehicle information apparatus were used, a delay in information processing was consistently found.