In-vehicle Display Research Articles

Driving errors and gaze behavior during in-vehicle object and spatial distractions

Driving is a complex task performed in a dynamic environment whereby visuospatial information is a critical aspect of driver cognition. Drivers’ interaction with the in-vehicle interfaces challenges their ability to respond to the dynamic traffic scenes efficiently. This study examines the effect of in-vehicle object and spatial distractions on drivers’ gaze behavior and driving performance. An experimental paradigm named as direction following in distracted driving – object and spatial (D3-OS) was developed for this study. An instrumented vehicle was voluntarily driven by 47 drivers on a two-lane test-track (data from seven participants were invalid, hence not included in the analysis). Four direction signboards were installed on the left side along the track and the drivers were required to drive according to the directions displayed on these signboards. Drivers were instructed to provide responses to the distracting stimuli shown on an in-vehicle display monitor that was attached to the dashboard. Novice and expert drivers (20 in each group) were randomly assigned to object and spatial distractions. The results demonstrate that compared to spatial distraction, during object distraction, fixation durations and fixation counts on area of interest (AOI) are significantly reduced and driving errors (i.e., both slips and lapses) are significantly increased. Novice drivers committed significantly more slips and lapses as compared to expert drivers. Furthermore, an increased cognitive workload (CWL) is associated with an increase in the occurrence of slips and lapses. On the whole, the results of the study signify the importance of strict enforcement of traffic regulations related to distracted driving more stringently in the case of novice drivers.

Benefits of Redundant Visual In-Vehicle Information in Pedestrian–Vehicle Conflict Scenarios

The paper provides information relevant to the development of driver and pedestrian safety systems by examining drivers’ responses to infrastructure-based safety messages (DII) with a redundant in-vehicle display component. A driving simulator was used to create a conflict situation which required an immediate driver response to avoid a collision. At the start of the event, a pedestrian was occluded by a truck at an intersection. Partway through the event, the pedestrian dashed into the road and into the driver’s path. When redundant visual in-vehicle alerting messages were provided, drivers released the throttle more quickly, engaged the brake more quickly, and had longer minimum time to collision relative to the baseline condition which lacked visual alerts. This was an improvement over the DII-only condition, where drivers did not brake more quickly relative to baseline and had only marginally longer minimum time to collision compared with the baseline condition. The findings suggest that redundant in-vehicle message information provides a benefit to many drivers over systems that use only infrastructure-based safety systems in vehicle–pedestrian conflicts.

Influence of Driving Experience on Distraction Engagement in Automated Vehicles

State-of-the-art vehicle automation requires drivers to visually monitor the driving environment and the automation (through interfaces and vehicle’s actions) and intervene when necessary. However, as evidenced by recent automated vehicle crashes and laboratory studies, drivers are not always able to step in when the automation fails. Research points to the increase in distraction or secondary-task engagement in the presence of automation as a potential reason. However, previous research on secondary-task engagement in automated vehicles mainly focused on experienced drivers. This issue may be amplified for novice drivers with less driving skill. In this paper, we compared secondary-task engagement behaviors of novice and experienced drivers both in manual (non-automated) and automated driving settings in a driving simulator. A self-paced visual-manual secondary task presented on an in-vehicle display was utilized. Phase 1 of the study included 32 drivers (16 novice) who drove the simulator manually. In Phase 2, another set of 32 drivers (16 novice) drove with SAE-level-2 automation. In manual driving, there were no differences between novice and experienced drivers’ rate of manual interactions with the secondary task (i.e., taps on the display). However, with automation, novice drivers had a higher manual interaction rate with the task than experienced drivers. Further, experienced drivers had shorter average glance durations toward the task than novice drivers in general, but the difference was larger with automation compared with manual driving. It appears that with automation, experienced drivers are more conservative in their secondary-task engagement behaviors compared with novice drivers.

Effectiveness of In-Vehicle Displays as Replacement of Automotive Side Mirrors

Effectiveness of In-Vehicle Displays as Replacement of Automotive Side Mirrors

Quantifying Distraction Potential of Augmented Reality Head-Up Displays for Vehicle Drivers

Background: A recent National Highway Traffic & Safety Administration (NHTSA) report states that 10% of fatal crashes and 18% of injury crashes were reported as distraction-affected crashes. In that same year, 3,179 people were killed and an estimated 431,000 injured in motor vehicle crashes involving distracted drivers, many of which involved secondary visual displays (NHTSA, 2016). Augmented reality (AR) head-up displays (HUD) promise to be less distractive than traditional in-vehicle displays since they do not take drivers’ eyes off the road (Gabbard, Fitch, & Kim, 2014). However, empirical studies have reported possible negative consequences of AR HUDs, in part, due to AR graphics’ salience (Sharfi & Shinar, 2014), frequent changes (Wolffsohn, McBrien, Edgar, & Stout, 1998), and visual clutter (Burnett & Donkor, 2012). Moreover, current in-vehicle display assessment methods which are based on eye-off-road time measures (NHTSA, 2012), cannot capture this unique challenge. Objective: This work aims to propose a new method for the assessment of AR HUDs by quantifying both positive (informing drivers) and negative (distracting drivers) consequences of AR HUDs which might not be captured by current in-vehicle display assessment methods. Method: We proposed a new way of quantifying the distraction potential of AR HUDs by measuring driver situation awareness with operational improvements on the situation awareness global assessment technique (Endsley, 2012) to suit AR usability evaluations. A human-subject experiment was conducted in a driving simulator to apply the proposed method and to evaluate two AR HUD interfaces for pedestrian collision warning. The AR warning interfaces were prototyped by the augmented video technique (Soro, Rakotonirainy, Schroeter, & Wollstdter, 2014). Twenty-four participants drove while interacting with different types of AR pedestrian collision warning interfaces (no warning, bounding box, and virtual shadow). Drivers’ situation awareness, confidence, and workload were measured and compared to the no warning condition. Results: Only one of the warning interface designs, the virtual shadow (Kim, Isleib, & Gabbard, 2016), improved driver situation awareness about pedestrians which were cued by the AR HUD, not affecting situation awareness about other environmental elements which were not augmented by the HUD. The experiment also showed drivers’ overconfidence bias while interacting with the bounding box which is another warning interface design. The empirical user study did not provide any evidence for reduced driver workload when AR warnings were given. Conclusion: Our initial human-subject study demonstrated a potential of the proposed method in quantifying both positive and negative consequences of AR HUDs on driver cognitive processes. More importantly, the experiment showed that AR interfaces can have both positive and negative consequences on driver situation awareness depending upon how we design perceptual forms of graphical elements. Application: The proposed assessment methods for AR HUDs can inform not only comparative evaluation among design alternatives but also assist in incrementally improving design iterations to better support drivers’ information needs, situation awareness, and in turn, performance, and safety.

Enhanced performance for in-vehicle display placed around back mirror by means of tactile warning

In-vehicle displays have been found more effective in terms of reaction time, accuracy and subjective visibility rating when the size of such displays was moderate and placed around a steering wheel. To date, however, little data has been reported on the safety and efficiency of replacing side mirrors with in-vehicle displays placed around a back or room mirror. Although back mirror displays save space for installing other display features, it is expected that they would be inferior to in-vehicle displays placed around side mirrors, around the driver’s center position, or around a steering wheel in accuracy and reaction time, because back mirror displays require drivers to execute more vertical eye movement than other in-vehicle displays or side mirrors, and eventually the perceptual and recognition time of hazard becomes longer. The primary purpose of this study was to improve the reaction time and accuracy of in-vehicle displays placed around a back mirror with the support of a tactile warning system. First, participants were instructed to engage in a primary, simulated driving task. Simultaneously with the primary task, participants were required to undertake a secondary, discrimination task. The secondary task involved the discrimination of a pre-specified vehicle displayed on either a side mirror or an in-vehicle liquid crystal display (LCD) placed around a back mirror or steering wheel. Second, reaction time and accuracy of in-vehicle displays placed around a back mirror were examined to determine whether they could be improved with the addition of a tactile warning to the displays. Participants were directed to carry out a driving task (run a straight second lane of three-lane highway) similar to that performed in the first experiment. As expected, in-vehicle displays placed around a back mirror produced inferior accuracy as compared to in-vehicle displays placed around a steering wheel. The tactile warning effectively compensated for the shortcomings of the 4.3-in. in-vehicle displays placed around a back mirror, and it further improved both reaction time and accuracy.

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.

Validation of Essential Acoustic Parameters for Highly Urgent In-Vehicle Collision Warnings.

Objective The aim of this study was to validate the importance of key acoustic criteria for use as in-vehicle forward collision warning (FCW) systems. Background Despite recent advances in vehicle safety, automobile crashes remain one of the leading causes of death. As automation allows for more control of noncritical functions by the vehicle, the potential for disengagement and distraction from the driving task also increases. It is, therefore, as important as ever that in-vehicle safety-critical interfaces are intuitive and unambiguous, promoting effective collision avoidance responses upon first exposure even under divided-attention conditions. Method The current study used a driving simulator to assess the effectiveness of two warnings, one that met all essential acoustic parameters, one that met only some essential parameters, and a no-warning control in the context of a lead vehicle-following task in conjunction with a cognitive distractor task and collision event. Results Participants receiving an FCW comprising five essential acoustic components had improved collision avoidance responses relative to a no-warning condition and an FCW missing essential elements on their first exposure. Responses to a consistently good warning (GMU Prime) improved with subsequent exposures, whereas continued exposure to the less optimal FCW (GMU Sub-Prime) resulted in poorer performance even relative to receiving no warning at all. Conclusions This study provides support for previous warning design studies and for the validity of five key acoustic parameters essential for the design of effective in-vehicle FCWs. Application Results from this study have implications for the design of auditory FCWs and in-vehicle display design.

Measuring information demand of a dynamic in-vehicle display while driving – A study evaluating the MARS (Masking Action Relevant Stimuli) method

The MARS (Masking Action Relevant Stimuli) method assesses information demand for dynamic stimuli while driving. An action relevant stimulus is masked and the driver presses a button to unmask the stimulus for a limited period. We interpreted button presses as information demand. Following our previous research (Rittger, Kiesel, Schmidt, & Maag, 2014), the current study further evaluates the method. We applied the MARS method to a dynamic in-vehicle display containing recommendations from a traffic light assistant. In a driving simulator, drivers approached intersections with different traffic light phasing. The display either presented simple or complex information. In half of the drives, the participants used the MARS method. The study had a full within subjects design and fixations were recorded in all conditions. The results showed that the information demand varied according to the information in the display and the traffic light phase. A comparison of button presses with fixations showed that one unmasking interval came along with one fixation on the display. Asa conclusion, the MARS method can distinguish between conditions with high and low information demand for the display. Button presses relate to fixations on the display. Hence, the MARS method is a promising tool to assess the information demand in dynamic environments and can be applied asan extension or alternative for eye tracking.

Driver information system: a combination of augmented reality, deep learning and vehicular Ad-hoc networks

Improving traffic safety is one of the important goals of Intelligent Transportation Systems (ITS). In vehicle-based safety systems, it is more desirable to prevent an accident than to reduce severity of injuries. Critical traffic problems such as accidents and traffic congestion require the development of new transportation systems. Research in perceptual and human factors assessment is needed for relevant and correct display of this information for maximal road traffic safety as well as optimal driver comfort. One of the solutions to prevent accidents is to provide information on the surrounding environment of the driver. Augmented Reality Head-Up Display (AR-HUD) can facilitate a new form of dialogue between the vehicle and the driver; and enhance ITS by superimposing surrounding traffic information on the users view and keep drivers view on roads. In this paper, we propose a fast deep-learning-based object detection approaches for identifying and recognizing road obstacles types, as well as interpreting and predicting complex traffic situations. A single convolutional neural network predicts region of interest and class probabilities directly from full images in one evaluation. We also investigated potential costs and benefits of using dynamic conformal AR cues in improving driving safety. A new AR-HUD approach to create real-time interactive traffic animations was introduced in terms of types of obstacle, rules for placement and visibility, and projection of these on an in-vehicle display. The novelty of our approach is that both global and local context information are integrated into a unified framework to distinguish the ambiguous detection outcomes, enhance ITS by superimposing surrounding traffic information on the users view and keep drivers view on roads.

Intelligent Interactive Displays in Vehicles with Intent Prediction: A Bayesian framework

Using an in-vehicle interactive display, such as a touch screen, typically entails undertaking a freehand pointing gesture and dedicating a considerable amount of attention, that can be otherwise available for driving, with potential safety implications. Due to road and driving conditions, the user's input can also be subject to high levels of perturbations resulting in erroneous selections. In this article, we give an overview of the novel concept of an intelligent predictive display in vehicles. It can infer, notably early in the pointing task and with high confidence, the item the user intends to select on the display from the tracked freehand pointing gesture and possibly other available sensory data. Accordingly, it simplifies and expedites the target acquisition (pointing and selection), thereby substantially reducing the time and effort required to interact with an in-vehicle display. As well as briefly addressing the various signal processing and human factor challenges posed by predictive displays in the automotive environment, the fundamental problem of intent inference is discussed, and a Bayesian formulation is introduced. Empirical evidence from data collected in instrumented cars is shown to demonstrate the usefulness and effectiveness of this solution.

H7-4 車載表示器によるドライバの違和感の推定

H7-4 車載表示器によるドライバの違和感の推定

운전 경력에 따른 차량 내 디스플레이 정보표시 요구사항 비교

운전 경력에 따른 차량 내 디스플레이 정보표시 요구사항 비교

Towards Mitigating Teenagers’ Distracted Driving Behaviors

Distraction contributes significantly to teens’ crash risks. Previous studies show that feedback can help mitigate distraction among young and adult drivers; however, the type of feedback that is effective for teenagers remains unexamined. This paper investigates whether real-time and post-drive feedback can mitigate teens’ driver distraction and reports preliminary findings from an ongoing simulator study. Data reported was collected in a between-subjects experiment with three conditions: real-time (n= 8), post-drive (n= 8), and no feedback (n= 9). Real-time feedback was provided as auditory warnings when teens had long offroad glances (>2 sec). Post-drive feedback was an end-of-trip report on teens’ off-road glances and driving performance provided on an in-vehicle display. Compared to no feedback, real-time feedback resulted in significantly smaller number of long off-road glances (>2 sec), smaller average duration of off-road glances, and smaller standard deviation of lane position. The effects observed for post-drive feedback were relatively minor.

Gaming to Safety

The risk of crash or near-crash significantly increases when drivers make long off-road glances to engage in distracting tasks. Providing drivers with feedback that integrates elements of game design could increase driver motivation for adopting safer behaviors. In an ongoing between-subjects simulator study with young drivers ( n=29 reported in this paper), we compare four conditions for off-road glance behaviors: no feedback, real-time feedback system, post-drive feedback system (real-time feedback + post-drive feedback), and gamification feedback system (real-time feedback + post-drive feedback + game design elements). Shorter average glance duration and less frequent risky (≥2 s) glances to an in-vehicle display were observed for the post-drive system, compared to no feedback and real-time feedback, and for the gamification system, compared to no feedback. Although no added benefit of gamification over the post-drive feedback system was observed for these eye glance metrics, longer-term exposure and assessment could show improvements to be more stable with the inclusion of game design elements.

Identifying cognitive distraction using steering wheel reversal rates

The influence of driver distraction on driving performance is not yet well understood, but it can have detrimental effects on road safety. In this study, we examined the effects of visual and non-visual distractions during driving, using a high-fidelity driving simulator. The visual task was presented either at an offset angle on an in-vehicle screen, or on the back of a moving lead vehicle. Similar to results from previous studies in this area, non-visual (cognitive) distraction resulted in improved lane keeping performance and increased gaze concentration towards the centre of the road, compared to baseline driving, and further examination of the steering control metrics indicated an increase in steering wheel reversal rates, steering wheel acceleration, and steering entropy. We show, for the first time, that when the visual task is presented centrally, drivers’ lane deviation reduces (similar to non-visual distraction), whilst measures of steering control, overall, indicated more steering activity, compared to baseline. When using a visual task that required the diversion of gaze to an in-vehicle display, but without a manual element, lane keeping performance was similar to baseline driving. Steering wheel reversal rates were found to adequately tease apart the effects of non-visual distraction (increase of 0.5° reversals) and visual distraction with offset gaze direction (increase of 2.5° reversals). These findings are discussed in terms of steering control during different types of in-vehicle distraction, and the possible role of manual interference by distracting secondary tasks.

A driving simulator study to explore the effects of text size on the visual demand of in-vehicle displays

Modern vehicles increasingly utilise a large display within the centre console, often with touchscreen capability, to enable access to a wide range of driving and non-driving-related functionality. The text provided on such displays can vary considerably in size, yet little is known about the effects of different text dimensions on how drivers visually sample the interface while driving and the potential implications for driving performance and user acceptance. A study is described in which sixteen people drove motorway routes in a medium-fidelity simulator and were asked to read text of varying sizes (9mm, 8mm, 6.5mm, 5mm, or 4mm) from a central in-vehicle display. Pseudo-text was used as a stimulus to ensure that participants scanned the text in a consistent fashion that was unaffected by comprehension. There was no evidence of an effect of text size on the total time spent glancing at the display, but significant differences arose regarding how glances were distributed. Specifically, larger text sizes were associated with a high number of relatively short glances, whereas smaller text led to a smaller number of long glances. No differences were found in driving performance measures (speed, lateral lane position). Drivers overwhelmingly preferred the ‘compromise’ text sizes (6.5mm and 8mm). Results are discussed in relation to the development of large touchscreens within vehicles.

Perceived Visual Complexity of In-Vehicle Information Display and Its Effects on Glance Behavior and Preferences

ABSTRACTDespite enhancements in the visual complexity of in-vehicle information display in recent years, few studies have examined the effects of such increased complexity. We conducted this study with the following objectives: (1) to suggest a framework for predicting the perceived visual complexity (PVC) of in-vehicle information display; (2) to examine the effects of PVC on the visual behavior of human operators; (3) to investigate the relationship between preferences and PVC. A theoretical framework to evaluate PVC was developed, and a survey study was used to collect participants’ perceptions on visual complexity. A regression analysis was employed to find the relationship between each of three factors and PVC. Two of the factors—quantity and variety—showed a positive correlation with PVC, whereas the third factor, relation, exhibited a negative correlation. Visual search experiments were conducted to test the effects of PVC on the performance of visual search tasks and glance behavior. The results showed that the high level of PVC leads to more time-on-task and number of fixations. We also found that preference for in-vehicle information displays was inversely proportional to PVC. The results enable us to predict how human operators perceive visual complexity and explain the influence of PVC on human behavior.

Comparison of Traditional Psychophysical and Sorting Methods for In-Vehicle Display Design

Modern vehicles can present an ever-changing plethora of information, making it of the utmost importance that signals are evaluated efficiently in the early stages of design. The current study investigates the relationship between traditional methods of physchophysical scaling and newer methods of sorting or categorization. Participants sorted a sample of sounds into “Alarms”, “Status Notifications” and “Social Notifications”. Following the sorting task, participants were asked to rate each individual sound (using a 1-100 scale) on urgency, annoyance and acceptability. Results indicate extremely high correlations between alarm categorization and urgency level where sounds categorized as alarms by more participants were also rated as more urgent by all participants.

Drivers’ Reliance on Lane-Keeping Assistance Systems as a Function of the Level of Assistance

We investigated drivers’ willingness to allocate control to a lane-keeping assistance system as a function of the level of assistance. Operators were found to increasingly rely on automation with higher reliability. We assume a similar effect of the level of assistance on reliance resulting from operators’ perception of a reduced need to engage in automation controlled processes. Forty five participants drove in a moving base driving simulator wiTheither a lane-keeping control (LKC) system (high level of assistance), a lane departure warning (LDW) system (low level of assistance) or without lane-keeping assistance. The allocation of visual attention away from the road scene towards an in-vehicle display of a secondary task was used as an indicator of drivers’ reliance on the systems. We found that drivers diff ered significantly in their reliance on and trust in the LKC system. Individual driver characteristics, i.e., self reported driving style, had a significant influence on drivers’ trust. Drivers placed more trust in the LKC system the more they regarded themselves as anxious and unconfident drivers, and more trust in the LDW system the more they regarded themselves as unobservant drivers. A major conclusion is that self-reported driving style is an important factor to predict if drivers are prone to place their trust in, and rely on, higher level driving assistance. Study results call for transparency in the design of driver assistance systems to avoid false expectations regarding system capabilities. Functional system limits should be made easily identifiable for drivers in order to reduce the likelihood of overreliance.