In-vehicle Display Research Articles

A Driving Simulator Study to Examine the Impact of Visual Distraction Duration from In-Vehicle Displays: Driving Performance, Detection Response, and Mental Workload

This research explores the impact of visual distraction duration from multifunctional in-car displays on driver safety. Utilizing a driving simulator and eye-tracking technology, this study involved 35 participants in visual search and car-following tasks, assessing their performance and mental workload across different durations of distraction. The results show that distractions lead to a decrease in driving control and a rise in mental workload, characterized by deteriorated vehicle handling and longer reaction times. With continued exposure to distractions, drivers begin to adapt, indicating a non-linear relationship between the duration of distraction and its consequences. This adaptation points to a threshold beyond which the negative effects of distractions no longer intensify. This work aids in developing safer automotive interfaces by highlighting the effects of larger screen trends on driving behavior and proposing strategies to mitigate distractions. It enriches the discourse on human–machine interaction by offering fresh perspectives on how visual distraction duration from in-car displays influences driving dynamics and cognitive load, thereby enhancing road safety.

In-vehicle human–machine interface guidelines for augmented reality head-up displays: A review, guideline formulation, and future research directions

BackgroundThe augmented reality head-up display (AR-HUD) recently emerged as a state-of-the-art in-vehicle display. However, no comprehensive guidelines apply to the human–machine interface for AR-HUD. ObjectiveWe formulated guidelines for the human-vehicle interface to develop an AR-HUD. MethodsA review of existing literature on AR-HUD and applicable human factors and human–computer interaction guidelines was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. In total, 121 articles were selected, and an initial set of guidelines for developing an AR-HUD was drawn up. We analyzed AR-HUD development and categorized the articles based on HMI features relevant to in-vehicle AR-HUD: virtual image distance, field of view, and brightness. Furthermore, research findings on projected information and legibility were investigated. ResultsNine guidelines were devised for developing the AR-HUD human–machine interface. This study also compared the traditional AR-HUD and windshield AR-HUD, defining the requirements for future studies using the term AR-HUD and providing a framework for AR-HUD design. ConclusionsExisting research on AR-HUD is limited. Future research is needed on virtual image distance, field of view, brightness, and legibility. The findings of this study could be used to guide the design of a full-windshield AR-HUD interface and future research.

Text-based information design for in-vehicle displays: A systematic review

Reading short texts at a brief glance behaviour has been increasing, especially in the in-vehicle interface of the multitask context of driving. This behaviour led to a change in the approach of preparing and designing in-car information. Consequently, understanding the current status of existing design principles is necessary for designers to find the appropriate solution for text presentation on the in-vehicle display under driving conditions. Thus, the present study conducts a systematic review of text-based information design for in-vehicle displays. A total of 1,495 studies (1980–2022) were screened, and 360 emerged for full-text review; 27 studies met the inclusion criteria, including journal articles concerning the design of text-based information for in-vehicle displays involving text design and the effect on safe driving or reducing workload and distraction. The results were summarised in three themes of literature: existing design guidelines, design factors, and evaluation methodology. The existing guidelines and recommendations focus on the physical presence of text (modality, location, colour, typeface, font size), with few recommendations on the linguistic presence of the text (message style and message length). The discussion and future work section enables further work on developing usable and safe informational text displays on the in-vehicle interface and other short glance reading engagements.

Evaluating Driver Preferences for In-Vehicle Displays during Distracted Driving Using Driving Simulators

Research on the impact of distracted driving on in-vehicle displays was conducted through a user preference experiment based on simulated driving. The development of automotive automation and multi-screen in-vehicle displays has improved the driving experience but also increased distracted driving. Typical scenarios and information needs were identified through user research, and a simulated driving platform was used to record user choices of different display modes and their reaction times after being distracted. Questionnaires were analyzed using the Analytic Hierarchy Process (AHP). Results showed that in the manual driving group, users preferred Head-Up Display (HUD), which had the highest efficiency in terms of reaction time. The study confirmed that as automation levels increase, distraction scenarios will change, and user focus will shift from safety to experience.

In-vehicle displays for driving automation: a scoping review of display design and evaluation using driver gaze measures

ABSTRACT Recent research has extensively examined in-vehicle display designs for supporting the operation of driving automation. As automation relieves drivers from various driving tasks including vehicle control (e.g. steering, accelerating, and braking), driving performance measures (e.g. speed, lane deviations) may not be informative indicators for evaluating the effectiveness of in-vehicle displays. Gaze-based measures are a better alternative given their link to driver visual attention, an indication of driver engagement. A scoping review was conducted to review the literature on the design of displays for supporting the operation of driving automation and the evaluation of these displays using gaze-based measures. Forty-three articles were included in the review. Most of the studies investigated visual (and mixed visual-auditory) displays that provide alerts to the driver for when to intervene automation classified as Level 3. The adopted gaze measures mostly relied on static areas of interest (AOIs), with fewer studies looking at more fine-grained, context dependent AOIs. The paper summarises the findings of the review, including research trends and gaps, as well as recommendations for future research.

Evaluating the effectiveness of engineering countermeasures at yellow dilemma zone: a driving simulator-based study

ABSTRACT The indecisiveness of drivers at the yellow onset creates a dilemma zone (DZ) upstream of the signalized crossings. The yellow light dilemma negatively influences intersection safety, often leading to rear-end and right-angle collisions. This study explores the impact of upstream road marking and active in-vehicle warnings designed based on DZ boundaries. The prototype concepts of in-vehicle warning systems and upstream road marking were designed and implemented in the driving simulator environment. The driver responses from the experimental setup were captured to evaluate the effectiveness of the designed DZ countermeasures. Study results indicate that implemented DZ countermeasures (i.e. DZ road marking, in-vehicle display warning, and in-vehicle audio warning) significantly decreased the drivers’ crossing probability, resulting in a shorter dilemma zone. However, the proposed countermeasures did not show any improvement in the drivers’ red-light running (RLR) behavior. The driving simulator study showed promising results in reducing aggressive crossing responses at the yellow onset.

Drivers’ trust & reliance on automated braking at intersections: Effects of automation braking profile & in-vehicle displays

An online, video-based, within-subjects experiment was conducted to investigate the effects of three different automation braking profiles and three in-vehicle display designs on drivers’ trust and reliance on automated braking systems. 36 participants watched videos of automated braking at intersections (with different braking times and displays) and rated their trust in the automation and comfort with the automation’s braking time. They then watched the same videos and were asked to press the space bar and pause the video if they believed they should take over from the automation and brake. The braking profile had a significant effect on the trust and comfort ratings, while both the braking profile and display had a significant effect on the takeover time. The findings provide insights on drivers’ trust and reliance on automation that is designed to avoid lateral collision hazards at intersections.

Investigating effects of multimodal explanations using multiple In-vehicle displays for takeover request in conditionally automated driving

In conditionally automated driving, a human takeover transition is necessary in response to vehicle malfunction or other limitation. To mitigate the negative experience of this technological limitation, researchers have suggested providing an explanation along with the takeover request to increase drivers’ understanding and trust in an automated driving system (ADS). However, previous studies on the explanation have been limited to investigations of unimodal explanations that use either text or speech, while neglecting other various in-vehicle display options. The present study aims to investigate the effects of multimodal explanation using three in-vehicle displays—ambient light, cluster, and sound. The explanation given by each in-vehicle display was systemically manipulated into two levels (ambient light: constant color vs. variable color, cluster: no-text and no-background vs. text with colored background, sound: alert-only sound vs. speech with alert sound). To examine the effects of the explanation using these displays, we conducted mixed method research including a scenario-based experiment, questionnaires, and a follow-up interview for thematic analysis. In the experiment, eighty-two participants drove in a driving simulator and performed takeover tasks in several types of urgent situations for measuring their takeover time and error. The participants then responded to questionnaires on takeover workload and overall trust in automated vehicle. Next, fifty-six of them participated in the follow-up interview for discovering significant themes related to their experiences with the multimodal explanation. As results, we found that multimodal explanations that use two types of displays were more effective than unimodal explanations or multimodal explanations using three types of displays. Regarding the effects of each type of display, the speech-based explanation showed the best takeover performance in general. The explanation using the cluster was next most useful in performance. The ambient light explanation showed less significant to no effect in the takeover situation. We expect that these findings can contribute to theoretical understanding of driver response to multimodal explanations and to practical design of trustworthy explanations in various takeover situations.

Age differences in driver visual behavior and vehicle control when driving with in-vehicle and on-road deliveries of service logo signs

With the advances in vehicle technologies, more information is communicated in real-time to the driver via an in-vehicle interface. In-vehicle messaging may deliver safety-related information such as warnings as well as non-safety-related information such as an upcoming lodging place. While much research has focused on the design of messaging safety-related information, little is known about the best practice in in-vehicle messaging of non-safety-related information. This study investigated the effects of information source and load on driver signage logo identification, glance behavior, and vehicle control among younger, middle-aged and older drivers. The logos were presented on: (1) an on-road sign panel, (2) an in-vehicle display, or (3) a combination of both, with half of the drives showing logo only, and the other half of the drives showing logo plus additional text. The general findings support the use of in-vehicle displays, especially when it is presented simultaneously with on-road signs. In-vehicle displays did not lead to a higher workload or more visual distraction, and simultaneous presentations resulted in slightly better speed control. The findings also showed minimal negative impacts on logo identification from increased information load. Older drivers performed less well in signage identification and vehicle control, and they made longer glances to logo information suggesting design considerations should be made to accommodate specific driver characteristics.

Research and Design Considerations for Presentation of Non-Safety Related Information via In-Vehicle Displays during Automated Driving

As automated vehicles become more prevalent on roadways, it is necessary to study driver behaviors in interacting with such systems. With higher levels of vehicle automation, drivers may become less engaged with the roadway environment. As a result, how to effectively bring non-safety related information (e.g., guide and service sign content) to a driver’s attention is an open research question. In this review, we summarize current literature on three domains of research, including: (1) the design and effectiveness of traditional road signage, (2) human factors considerations in vehicle automation design, and (3) current design guidelines for in-vehicle information presentation. Based on the review, including empirical studies, we identify knowledge relevant to communicating road signage information in automated vehicles. We propose a framework highlighting various factors that could determine the effectiveness of in-vehicle messaging. The framework is intended to motivate future research on development of in-vehicle interfaces for highly automated driving.

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.

Using Glance Behaviour to Inform the Design of Adaptive HMI for Partially Automated Vehicles

Partially automated vehicles present a large range of information to the driver in order to keep them in-the-loop and engaged with monitoring the vehicle’s actions. However, existing research shows that this causes cognitive overload and disengagement from the monitoring task. Adaptive Human Machine Interfaces (HMIs) are an emerging technology that might address this problem, by prioritising the information presented. To date, research aiming to define the driver’s glance fixation behaviour in a partially automated vehicle to contribute towards an adaptive interface is scarce. This study used a unique three-day longitudinal driving simulator study design to explore which information drivers in a partially automated vehicle require. Twenty-seven participants experienced nine partially automated driving simulations over three consecutive days. Nine information types, developed from standards, previous studies and industry collaboration, were displayed as discrete icons and presented on a surrogate in-vehicle display. Unique to the literature, this study showed that the recorded eye-tracking data demonstrated that usage of the information types changed with longitudinal driving simulator use. This study provides three key contributions: first, the longitudinal study design suggest that single exposure HMI evaluations may be limited in their assessment. Secondly, this study has methodologically shortlisted a list of nine information types that can be used in future studies to represent future partially automated vehicle interfaces. Finally, this is one of the first studies to characterise glance behaviour for partially automated vehicles. With this knowledge, this study contributes important design recommendations for the development of adaptive interfaces.

Driving with Type 1 Diabetes: Real-World Evidence to Support Starting Glucose Level and Frequency of Monitoring During Journeys.

There is limited evidence supporting the recommendation that drivers with insulin-treated diabetes need to start journeys with glucose >90 mg/dL. Glucose levels of drivers with type 1 diabetes were monitored for 3 weeks using masked continuous glucose monitoring (CGM). Eighteen drivers (median [IQR] age 40 [35, 51] years; 11 men) undertook 475 trips (duration 15 [13, 21] min). Hypoglycemia did not occur in any trip starting with glucose >90 mg/dL (92%; n = 436). Thirteen drivers recorded at least one trip (total n = 39) starting with glucose <90 mg/dL. Among these, driving glucose was <70 mg/dL in five drivers (38%) during 10 trips (26%). Among five drivers (28%), a ≥ 36 mg/dL drop was observed within 20 min of starting their journey. Journey duration was positively associated with maximum glucose change. These findings support current guidelines to start driving with glucose >90 mg/dL, and to be aware that glucose levels may change significantly within 20 min. A CGM-based, in-vehicle display could provide glucose information and alerts that are compatible with safe driving. Clinical Trial Registration number: ACTRN12617000520336.

MORE CAMERAS, MORE CONNECTIONS, MORE TESTING

With the rapid development and roll-out of high speed in-vehicle display and sensor connections so more testing will be required, as Carrie Browen and Kevin Kershner explain

Dynamic is optimal: Effect of three alternative auto-complete on the usability of in-vehicle dialing displays and driver distraction

Objective Auto-complete (AC) has become ubiquitous on domain-specific systems and is mainly divided into two types (static-AC and dynamic-AC). Specifically, static-AC only presents the possible completions not changing with user input in the suggestion list for users to select. Dynamic-AC constantly filters out inconsistent content with user input and shows the possible completions at the top of the suggestion list. However, the details of the driver’s interactions with AC in the vehicle are poorly understood. Therefore, we investigated the effect of three alternative AC (non-AC, static-AC, and dynamic-AC) on the usability of in-vehicle dialing displays and driver distraction. As a reference, the baseline task (only driving) was also surveyed in each AC condition. Methods A simulated driving experiment consisting of 24 participants was conducted. The primary task was a lane-keeping task with speed ranging between 60 and 120 km/h over the stretch. The secondary task was dialing an 11-digit phone number. Usability metrics (task completion time and number of errors) and driver distraction metrics (NASA-reduced task load index (NASA-RTLX), mean speed, lateral position variation, total glance time, number of glances, mean glance time, and number of glances over 1.6 s) in each condition were measured. A series of one-way repeated measure analyses of variance was used to examine whether and which type of AC can maximize the usability of in-vehicle dialing displays and minimize driver distraction. Results Generally, the AC-based in-vehicle dialing display gains a more positive effect. Specifically, we observed that among the three alternative AC conditions, dynamic-AC performed optimally on usability metrics similar to previous studies and various driver distraction metrics, notwithstanding it is still not up to the level of the baseline condition. However, static-AC did not exhibit the advantages described in previous studies except for fewer errors and NASA-RTLX owing to the possibility of position bias and boundary effect. Conclusions This study provides valuable insights into drivers’ interactions with AC-based in-vehicle dialing displays and broadened its applications in safety-critical situations. More importantly, it informs the design of a more effective in-vehicle system, which positively contributes to mitigating driver distraction and preventing traffic accidents.

Driver behavior and performances on in-vehicle display based speed compliance

Traffic safety, and the inherent risks associated with speeding, continue to remain a national priority. Advances in both roadway and vehicle technology have created potential mechanisms to mitigate speeding behaviors. This driving simulator study evaluated the effects of alternative ways to increase driver safety by investigating the characteristics of specific driving cues and drivers’ response rates to those cues. The study builds upon existing approaches to symbolically deliver Traffic Control Devices (TCDs), specifically speed alerts, at different locations within the vehicle to reduce cognitive distraction and prevent visual crowding so that drivers can properly select their speed and focus upon the roadway environment. Twenty-three participants received five visual treatments (e.g., combinations of speed alert style, presentation, and location) in a simulated environment. Participants also responded to a set of survey questions following the simulated drive. Participants were evaluated on various response factors to each visual treatment. Results showed that younger participants of the age group 18–23 responded to the visual treatment and stayed within speed limits as compared to other older and more experienced participants. Results also showed that alerts falling in the mid-peripheral visual region and alerts that flashed received an increased response rate for observing speed limits.

Driver Logo Sign Detection and Hazard Responses during Partially Automated Driving

This study investigates the presentation of service logo information under partially automated driving. Drivers completed simulated drives with partial automation during which they had to detect target logo signs and react to hazards by taking over vehicle control when needed. Driver performance was measured in terms of sign detection rate, crash rate, and hazard response time. A number of factors, including sign information source, sign information load, and driver age group, were investigated. In general, our findings support the delivery of service logo information via in-vehicle display under partially automated driving, especially when the in-vehicle display occurred simultaneously with the on-road signage. Under this presentation condition, drivers were most accurate in detecting target logo signs, and showed little impairment from processing sign information as a secondary task when negotiating a hazard. Implications of the findings and future directions were discussed.

Eco-driving behaviors of electric vehicle users: A survey study

Previous research has shown that electric vehicle (EV) users could behave differently compared to internal combustion engine vehicle (ICEV) drivers due to their consciousness or practices of eco-driving, but very limited research has fully investigated this assumption. This research explores this topic through investigating EV drivers’ eco-driving behaviors and motivations. We first conducted a questionnaire survey on EV drivers’ driving behavior and some hypothetical decisions of their driving. It indicates various characteristics between EV and ICEV commuters, including self-reported daily driving habits, preferences of route choices, tradeoff between travel time and energy saving, and adoption of in-vehicle display (IVD) technologies. Then, through statistical analysis with Fisher’s exact test and Mann-Whitney U test, this research reveals that, compared to ICEV drivers, EV drivers possess significantly calmer driving maneuvers and more fuel-efficient driving habits such as trip chaining. The survey data also show that EV drivers are much more willing to save energy in compensation of travel time. Furthermore, the survey data indicate that EV drivers are more willing to adopt eco-friendly IVD technologies. All these findings are expected to improve the understanding of some unique behavior found in EV drivers.

On-Road and In-Vehicle Delivery of Service Signs: Effects of Information Source and Age

In-vehicle technologies for communicating information to drivers have realized increasing use in recent years. While most attention has been paid to in-vehicle displays for presenting safety-related information, such as warnings, few studies have explored communication of non-safety-related information with in-vehicle displays. This simulated driving study examined driver performance in vehicle control and sign identification, when processing service logo information from on-road signs or an in-vehicle display. Findings suggest that in-vehicle displays, on-road signage, or both allowed drivers to identify service logos with a high accuracy and a relatively low level of workload. The use of in-vehicle displays either alone or simultaneously with on-road signage produced lower speed deviations therefore better vehicle control. Age differences were observed in vehicle control as well, suggesting the need for personalization of sign messages according to individual characteristics. This study is an initial step to examine the use of in-vehicle displays for messaging service logos as an example of non-safety-related information. The study is ongoing, and findings could provide a basis for in-vehicle display and on-road sign design for non-safety-related information.

Driver Training for Automated Vehicle Technology – Knowledge, Behaviors, and Perceived Familiarity

Advanced driver-assistance systems and partial driving automation are becoming increasingly common, yet despite their growing prevalence, drivers seem to know very little about them. Previous studies have found that owners of ADAS equipped vehicles have demonstrated misperceptions or lack of awareness about system limitations, which may impact driver comfort with and reliance on these systems. The purpose of this study was to determine the effectiveness of two training strategies on drivers’ knowledge and perceived familiarity of vehicle automation as well as their environment monitoring behaviors during system use. Forty volunteers participated in a multi-stage research study in which they were exposed to either a conventional training protocol, self-learning through the owner’s manual, or an experimental (multimedia) training protocol, using the in-vehicle display technologies as training tools. Results indicate training strategy elicits limited differences in knowledge and no difference in driver behaviors or attitudes. Behaviors and attitudes were heavily influenced by time and experience with the driving automation system while knowledge of the vehicle systems remained unchanged.