Evaluation of ambient light displays for requests to intervene and minimal risk maneuvers in highly automated urban driving
Driver take-overs at system limits and the corresponding requests to intervene are not obligatory in highly automated driving. Therefore, minimal risk maneuvers may occur. In order to clearly communicate the automation status and the driver's task at such system limits, ambient light displays seem to have a high potential. Therefore, two ambient light displays were investigated in a driving simulation experiment, mounted either at the bottom of the windshield or on the steering wheel. Forty participants experienced two request to intervene scenarios, and two minimal risk maneuver scenarios during a highly automated drive. In general, both ambient light displays seem to ensure correct driver's reactions and safety, and lead to positive subjective ratings. Results revealed no significant differences between the two ambient light display positions regarding the take-over behavior, gaze behavior and subjective rating, except in terms of the perceived brightness.
Expert drivers’ prospective thinking-aloud to enhance automated driving technologies–Investigating uncertainty and anticipation in traffic
Current automated driving technology cannot cope in numerous conditions that are basic daily driving situations for human drivers. Previous studies show that profound understanding of human drivers’ capability to interpret and anticipate traffic situations is required in order to provide similar capacities for automated driving technologies. There is currently not enough a priori understanding of these anticipatory capacities for safe driving applicable to any given driving situation. To enable the development of safer, more economical, and more comfortable automated driving experience, expert drivers’ anticipations and related uncertainties were studied on public roads. First, driving instructors’ expertise in anticipating traffic situations was validated with a hazard prediction test. Then, selected driving instructors drove in real traffic while thinking aloud anticipations of unfolding events. The results indicate sources of uncertainty and related adaptive and social behaviors in specific traffic situations and environments. In addition, the applicability of these anticipatory capabilities to current automated driving technology is discussed. The presented method and results can be utilized to enhance automated driving technologies by indicating their potential limitations and may enable improved situation awareness for automated vehicles. Furthermore, the produced data can be utilized for recognizing such upcoming situations, in which the human should take over the vehicle, to enable timely take-over requests.
Eye-based interaction in graphical systems: 20 years later gaze applications, analytics, & interaction
The course starts with an overview of eye-tracking applications, distinguishing eye movement analysis from synthesis in virtual reality, games, and other venues including mobile eye tracking. The focus is on four forms of applications: diagnostic (off-line measurement), active (selection, look to shoot), passive (foveated rendering, a.k.a. gaze-contingent displays), and expressive (gaze synthesis). The course covers basic eye movement analytics, e.g., fixation count and dwell time within AOIs, as well as advanced analysis using ambient/focal attention modeling. The course concludes with an overview and a demo of how to build an interactive application using Python.
Gaze recognition
Gaze tracking systems are being researched for more than a hundred years. Yet, there is still more to be learned and improved upon. They are at this time mostly used in the medical and scientific fields. There has been recent research in less confined methods of usage for these systems. The least confined method of gaze tracking, having a camera placed independently from the observed, is probably the least researched method. If this method would achieve high degrees of accuracy even people who would act unusually while wearing an eye tracker could have their gaze tracked easily. Therefore, this method is suitable for analyzing the gaze of the severely psychologically impaired under natural circumstances. In this master thesis currently existent methods of gaze tracking are going to be compared against one another. There will be a focus on gaze tracking methods utilizing cameras placed independently from the observed. Further several machine learning-based prototypes designed for this situation will be presented. The development of gaze tracking methods utilizing cameras placed independently from the observed is a complex issue. None of the in this thesis developed prototypes give decent results in their analysis of images. There are however other systems presented in this thesis where the best has a mean angular error of 17,6◦ on the chosen dataset.
Gender aspects of trust in and use of advanced driver assistance systems/submitted by Gina Nathalie Schnücker
Increasing automation in vehicles promises an equal increase in driving safety and comfort. Current research aims to identify factors that influence if and how in-vehicle automation is adopted by the human operator. Trust in automation was identified to be one of those factors. Still, there is a need to understand the relationship between system-trust and actual reliance behavior. Therefore, the first aim of this thesis was to investigate the relationship between trust in Advanced Driver Assistance Systems and actual reliance behavior. The second aim was to address the inconsistencies in previous research regarding gender differences in automation trust by introducing the concept of gender roles. The concept of gender roles addresses stereotypical behavior associated with masculinity and femininity rather than biological sex and has already been identified to explain variance in addition and beyond biological sex in manual driving, risk-taking, and technology adoption. Qualitative, quantitative, and psychophysiological data were integrated in an experiment with 100 participants (49 females) in a 25-minute field-drive. We assessed attitudes and behavior in interaction with a Lane Keeping Assist (LA), that supports the driver to keep the vehicle within the lane and the Adaptive Cruise Control (ACC) that maintains a set speed and keeps a set distance to preceding vehicles. The results show that trust after the automated drive was positively related to the use of the LA and the simultaneous use of LA and ACC. It also showed that there were no sex differences in trust and reliance behavior. In contrast, masculinity was positively related to trust before the automated drive, while femininity was positively related to trust after the drive. These findings have implications for trust measurement and the promotion of a safe adoption of in-vehicle automation.
Human Factors Studies on Automotive Head-Up Display Design
Human Factors Studies on Automotive Head-Up Display Design Juhee Park Department of Industrial Engineering The Graduate School Seoul National University Head-up display (HUD) systems were introduced into the automobile industry as a means for improving driving safety. They superimpose safety-critical information on top of the driver’s forward field of view and thereby help drivers keep their eyes forward while driving. Since the first introduction about three decades ago, automotive HUDs have been available in various commercial vehicles. Despite the long history and potential benefits of automotive HUDs, however, the design of useful automotive HUDs remains a challenging problem. In an effort to contribute to the design of useful automotive HUDs, this doctoral dissertation research conducted four studies. In Study 1, the functional requirements of automotive HUDs were investigated by reviewing the major automakers' automotive HUD products, academic research studies that proposed various automotive HUD functions, and previous research studies that surveyed drivers’ HUD information needs. The review results indicated that: 1) the existing commercial HUDs perform largely the same functions as the conventional in-vehicle displays, 2) past research studies proposed various HUD functions for improving driver situation awareness and driving safety, 3) autonomous driving and other new technologies are giving rise to new HUD information, and 4) little research is currently available on HUD users’ perceived information needs. Based on the review results, this study provides insights into the functional requirements of automotive HUDs and also suggests some future research directions for automotive HUD design. In Study 2, the interface design of automotive HUDs for communicating safety-related information was examined by reviewing the existing commercial HUDs and display concepts proposed by academic research studies. Each display was analyzed in terms of its functions, behaviors and structure. Also, related human factors display design principles, and, empirical findings on the effects of interface design decisions were reviewed when information was available. The results indicated that: 1) information characteristics suitable for the contact-analog and unregistered display formats, respectively, are still largely unknown, 2) new types of displays could be developed by combining or mixing existing displays or display elements at both the information and interface element levels, and 3) the human factors display principles need to be used properly according to the situation and only to the extent that the resulting display respects the limitations of the human information processing, and achieving balance among the principles is important to an effective design. On the basis of the review results, this review suggests design possibilities and future research directions on the interface design of safety-related automotive HUD systems. In Study 3, automotive HUD-based take-over request (TOR) displays were developed and evaluated in terms of drivers’ take-over performance and visual scanning behavior in a highly automated driving situation. Four different types of TOR displays were comparatively evaluated through a driving simulator study - they were: Baseline (an auditory beeping alert), Mini-map, Arrow, and Mini-map-and-Arrow. Baseline simply alerts an imminent take-over, and was always included when the other three displays were provided. Mini-map provides situational information. Arrow presents the action direction information for the take-over. Mini-map-and-Arrow provides the action direction together with the relevant situational information. This study also investigated the relationship between driver’s initial trust in the TOR displays and take-over and visual scanning behavior. The results indicated that providing a combination of machine-made decision and situational information, such as Mini-map-and-Arrow, yielded the best results overall in the take-over scenario. Also, drivers’ initial trust in the TOR displays was found to have significant associations with the take-over and visual behavior of drivers. The higher trust group primarily relied on the proposed TOR displays, while the lower trust group tended to more check the situational information through the traditional displays, such as side-view or rear-view mirrors. In Study 4, the effect of interactive HUD imagery location on driving and secondary task performance, driver distraction, preference, and workload associated with use of scrolling list while driving were investigated. A total of nine HUD imagery locations of full-windshield were examined through a driving simulator study. The results indicated the HUD imagery location affected all the dependent measures, that is, driving and task performance, drivers’ visual distraction, preference and workload. Considering both objective and subjective evaluations, interactive HUDs should be placed near the driver's line of sight, especially near the left-bottom on the windshield.
Human-Computer Interaraction Series – Wearable Interaction
This chapter begins with the goals and objectives of wearable technologies, describing the different disciplines that contribute to constitute and advance wearable computing. This chapter includes also multiple dimensions that must be considered in the design, development, and evaluation of wearable technologies. Concerning hardware aspects, six implementation layers are defined and illustrated with examples from the literature. Concerning software aspects, systems, and applications, this chapter provides the objectives, features, and functionalities implemented with wearable computers. Concerning network and connectivity, this chapter provides examples of protocols and approaches for physical and virtual connections that enable data sharing and device synchronization. Additional topics discussed in the chapter include energy requirements and considerations for wearables, contexts of use where wearers interact with their devices, and common tasks they execute, emphasizing the advantages of wearable computers to support activities of daily living. This chapter highlights the diversity of users who benefit from wearables and the inherent trade-offs that emerge when universal design and customization must be considered altogether to ensure acceptability among diverse users’ profiles. The chapter ends with an in-depth discussion of the main challenges faced by users when interacting with a wearable technology and by stakeholders when creating those technologies during the implementation phases. The main challenges highlighted cut across six different concerns: usability and wearability, implementation, power, network and sensors, safety, and privacy aspects.
Impact of urban undersea tunnel longitudinal slope on the visual characteristics of drivers
This study aims to investigate the impact of the urban undersea tunnel longitudinal slope on the visual characteristics of drivers. 20 drivers were enrolled to conduct the real vehicle test of the urban undersea tunnel. First, the data of average fixation time and visual lobe were collected by an eye tracker. The differential significance was tested using the one-way repeated measures analysis of variance (ANOVA). Then, the difference between the up-and-down slope (direction) factor and the longitudinal slope (percent) factor on the two indexes were analyzed using the two-way repeated measures ANOVA. Second, by constructing a Lorentz model, the impact of the longitudinal slope on the average fixation time and the visual lobe were analyzed. Besides, a three-dimensional model of the longitudinal slope, average fixation time, and visual lobe was quantified. The results showed that the average fixation time and visual lobe under different longitudinal slopes markedly differed when driving on the uphill and downhill sections. The average fixation time and visual lobe under two factors were markedly different. Moreover, with an increase in the longitudinal slope, the average fixation time exhibited a trend of increasing first then decreasing; the visual lobe exhibited a trend of decreasing first and then increasing. The average fixation time reached the minimum and maximum value when the slope was 2.15% and 4.0%, whereas the visual lobe reached the maximum and minimum value when the slope was 2.88% and 4.0%. Overall, the longitudinal slope exerted a great impact on the visual load of the driver.
Impacts of touch screen size, user interface design, and subtask boundaries on in-car task’s visual demand and driver distraction
Visual distraction by secondary in-car tasks is a major contributing factor in traffic incidents. In-car user interface design may mitigate these negative effects but to accomplish this, design factors’ visual distraction potential should be better understood. The effects of touch screen size, user interface design, and subtask boundaries on in-car task's visual demand and visual distraction potential were studied in two driving simulator experiments with 48 participants. Multilevel modeling was utilized to control the visual demands of driving and individual differences on in-car glance durations. The 2.5” larger touch screen slightly decreased the in-car glance durations and had a diminishing impact on both visual demand and visual distraction potential of the secondary task. Larger relative impact was discovered concerning user interface design: an automotive-targeted application decreased the visual demand and visual distraction potential of the in-car tasks compared to the use of regular smartphone applications. Also, impact of subtask boundaries was discovered: increase in the preferred number of visual or visual-manual interaction steps during a single in-car glance (e.g., pressing one button vs. typing one word) increased the duration of the in-car glance and its visual distraction potential. The findings also emphasize that even if increasing visual demand of a task – as measured by in-car glance duration or number of glances – may increase its visual distraction potential, these two are not necessarily equal.
