scholarly journals Augmented Reality Displays for Communicating Uncertainty Information in Automated Driving

Author(s):  
Alexander Kunze ◽  
Stephen J. Summerskill ◽  
Russell Marshall ◽  
Ashleigh J. Filtness
i-com ◽  
2021 ◽  
Vol 20 (3) ◽  
pp. 295-318
Author(s):  
Andreas Riegler ◽  
Andreas Riener ◽  
Clemens Holzmann

Abstract There is a growing body of research in the field of interaction between drivers/passengers and automated vehicles using augmented reality (AR) technology. Furthering the advancements and availability of AR, the number of use cases in and around vehicles rises. Our literature review reveals that in the past, AR research focussed on increasing road safety and displaying navigational aids, however, more recent research explores the support of immersive (non-)driving related activities, and finally enhance driving and passenger experiences, as well as assist other road users through external human-machine interfaces (HMIs). AR may also be the enabling technology to increase trust and acceptance in automated vehicles through explainable artificial intelligence (AI), and therefore help on the shift from manual to automated driving. We organized a workshop addressing AR in automotive human-computer interaction (HCI) design, and identified a number of challenges including human factors issues that need to be tackled, as well as opportunities and practical usages of AR in future mobility. We believe that our status-quo literature analysis and future-oriented workshop results can serve as a research agenda for user interface designers and researchers when developing automotive AR interfaces.


2019 ◽  
Vol 11 (2) ◽  
pp. 75-97
Author(s):  
Alexander Kunze ◽  
Stephen J. Summerskill ◽  
Russell Marshall ◽  
Ashleigh J. Filtness

Conveying the overall uncertainties of automated driving systems was shown to improve trust calibration and situation awareness, resulting in safer takeovers. However, the impact of presenting the uncertainties of multiple system functions has yet to be investigated. Further, existing research lacks recommendations for visualizing uncertainties in a driving context. The first study outlined in this publication investigated the implications of conveying function-specific uncertainties. The results of the driving simulator study indicate that the effects on takeover performance depends on driving experience, with less experienced drivers benefitting most. Interview responses revealed that workload increments are a major inhibitor of these benefits. Based on these findings, the second study explored the suitability of 11 visual variables for an augmented reality-based uncertainty display. The results show that particularly hue and animation-based variables are appropriate for conveying uncertainty changes. The findings inform the design of all displays that show content varying in urgency.


Author(s):  
Nayara de Oliveira Faria ◽  
Coleman Merenda ◽  
Richard Greatbatch ◽  
Kyle Tanous ◽  
Chihiro Suga ◽  
...  

In the present paper, we present a user study with an advanced-driver assistance system (ADAS) using augmented reality (AR) cues to highlight pedestrians and vehicles when approaching intersections of varying complexity. Our major goal is to understand the relationship between the presence and absence of AR, driver-initiated takeover rates and glance behavior when using a SAE Level 2 autonomous vehicle. Therefore, a user-study with eight participants on a medium-fidelity driving simulator was carried out. Overall, we found that AR cues can provide promising means to increase the system transparency, drivers’ situation awareness and trust in the system. Yet, we suggest that the dynamic glance allocation of attention during partially automated vehicles is still challenging for researchers as we still have much to understand and explore when AR cues become a distractor instead of an attention guider.


2022 ◽  
pp. 1002-1026
Author(s):  
Alexander Kunze ◽  
Stephen J. Summerskill ◽  
Russell Marshall ◽  
Ashleigh J. Filtness

Conveying the overall uncertainties of automated driving systems was shown to improve trust calibration and situation awareness, resulting in safer takeovers. However, the impact of presenting the uncertainties of multiple system functions has yet to be investigated. Further, existing research lacks recommendations for visualizing uncertainties in a driving context. The first study outlined in this publication investigated the implications of conveying function-specific uncertainties. The results of the driving simulator study indicate that the effects on takeover performance depends on driving experience, with less experienced drivers benefitting most. Interview responses revealed that workload increments are a major inhibitor of these benefits. Based on these findings, the second study explored the suitability of 11 visual variables for an augmented reality-based uncertainty display. The results show that particularly hue and animation-based variables are appropriate for conveying uncertainty changes. The findings inform the design of all displays that show content varying in urgency.


2019 ◽  
Vol 27 (1) ◽  
pp. 46-62 ◽  
Author(s):  
Philipp Wintersberger ◽  
Anna-Katharina Frison ◽  
Andreas Riener ◽  
Tamara von Sawitzky

Lack of trust in or acceptance of technology are some of the fundamental problems that might prevent the dissemination of automated driving. Technological advances, such as augmented reality aids like full-sized windshield displays or AR contact lenses, could be of help to provide a better system understanding to the user. In this work, we picked up on the question of whether augmented reality assistance has the potential to increase user acceptance and trust by communicating system decisions (i.e., transparent system behavior). To prove our hypothesis, we conducted two driving simulator studies to investigate the benefit of scenario augmentation in fully automated driving—first in normal ([Formula: see text]) and then in rearward viewing ([Formula: see text]) direction. Quantitative results indicate that the augmentation of traffic objects/participants otherwise invisible (e.g., due to dense fog), or the presentation of upcoming driving maneuvers while sitting backwards, is a feasible approach to increase user acceptance and trust. Results are further backed by qualitative findings from semistructured interviews and UX curves (a method to retrospectively report experience over time). We conclude that the application of augmented reality, in particular with the emergence of more powerful, lightweight, or integrated devices, is a good opportunity with high potential for automated driving.


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