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A Bermuda Triangle?: A Review of Method Application and Triangulation in User Experience Evaluation
(2018)
WeCARe: Workshop on Inclusive Communication between Automated Vehicles and Vulnerable Road Users
(2021)
While virtual reality (VR) interfaces have been researched extensively over the last decades, studies on their application in vehicles have only recently advanced. In this paper, we systematically review 12 years of VR research in the context of automated driving (AD), from 2009 to 2020. Due to the multitude of possibilities for studies with regard to VR technology, at present, the pool of findings is heterogeneous and non-transparent. We investigated N = 176 scientific papers of relevant journals and conferences with the goal to analyze the status quo of existing VR studies in AD, and to classify the related literature into application areas. We provide insights into the utilization of VR technology which is applicable at specific level of vehicle automation and for different users (drivers, passengers, pedestrians) and tasks. Results show that most studies focused on designing automotive experiences in VR, safety aspects, and vulnerable road users. Trust, simulator and motion sickness, and external human-machine interfaces (eHMIs) also marked a significant portion of the published papers, however a wide range of different parameters was investigated by researchers. Finally, we discuss a set of open challenges, and give recommendation for future research in automated driving at the VR side of the reality-virtuality continuum.
There is a growing body of research in the field of interaction between automated vehicles and other road users in their vicinity. To facilitate such interactions, researchers and designers have explored designs, and this line of work has yielded several concepts of external Human-Machine Interfaces (eHMI) for vehicles. Literature and media review reveals that the description of interfaces is often lacking in fidelity or details of their functionalities in specific situations, which makes it challenging to understand the originating concepts. There is also a lack of a universal understanding of the various dimensions of a communication interface, which has impeded a consistent and coherent addressal of the different aspects of the functionalities of such interface concepts. In this paper, we present a unified taxonomy that allowsa systematic comparison of the eHMI across 18 dimensions, covering their physical characteristics and communication aspects from the perspective of human factors and human-machine interaction. We analyzed and coded 70eHMI concepts according to this taxonomy to portray the state of the art and highlight the relative maturity of different contributions. The results point to a number of unexplored research areas that could inspire future work. Additionally, we believe that our proposed taxonomy can serve as a checklist for user interface designers and researchers when developing their interfaces.
(1) Background: Primary driving tasks are increasingly being handled by vehicle automation so that support for non-driving related tasks (NDRTs) is becoming more and more important. In SAE L3 automation, vehicles can require the driver-passenger to take over driving controls, though. Interfaces for NDRTs must therefore guarantee safe operation and should also support productive work.
(2) Method: We conducted a within-subjects driving simulator study (N=53) comparing Heads-Up Displays (HUDs) and Auditory Speech Displays (ASDs) for productive NDRT engagement. In this article, we assess the NDRT displays’ effectiveness by evaluating eye-tracking measures and setting them into relation to workload measures, self-ratings, and NDRT/take-over performance.
(3) Results: Our data highlights substantially higher gaze dispersion but more extensive glances on the road center in the auditory condition than the HUD condition during automated driving. We further observed potentially safety-critical glance deviations from the road during take-overs after a HUD was used. These differences are reflected in self-ratings, workload indicators and take-over reaction times, but not in driving performance.
(4) Conclusion: NDRT interfaces can influence visual attention even beyond their usage during automated driving. In particular, the HUD has resulted in safety-critical glances during manual driving after take-overs. We found this impacted workload and productivity but not driving performance
Es wurden bereits einige Lösungen vorgestellt, um die Kommunikation zwischen automatisierten Fahrzeugen und ungeschützten Verkehrsteilnehmern (sog. „Vulnerable Road Users“, VRUs) zu unterstützen. Noch ist jedoch unklar, ob diese Systeme den Anforderungen zukünftiger Benutzer auch gerecht werden. Ziel dieser Arbeit war es, Benutzeranforderungen von VRUs nach direktem Kontakt mit einem automatisierten Fahrzeug zu erfassen. Hierfür wurde eine Feldstudie mit 32 Teilnehmern durchgeführt. Die Resultate, welche sowohl auf subjektiven (Fragebögen, Interviews) als auch objektiven (Videoanalyse) Daten basieren, legen nahe, dass ungeschützte Verkehrsteilnehmer einfache und bekannte Konzepte (beispielsweise Ampelsysteme oder Hupen) zur Kommunikation bevorzugen. Des Weiteren wurden diverse Problemszenarien identifiziert, welche für eine Bereitstellung von automatisierten Fahrzeugen in „Shared Spaces“ von besonderer Bedeutung sind.
Towards Personalized 3D Augmented Reality Windshield Displays in the Context of Automated Driving
(2022)
As vehicle automation advances, drivers of automated vehicles become more disengaged from the primary driving task. Windshield displays provide a large screen space supporting drivers in non-driving related activities. This article presents user preferences as well as task and safety issues for 3D augmented reality windshield displays in automated driving. Participants of a user study (n = 24) customized two modes of content presentation (multiple content-specific windows vs. one main window), and could freely adjust visual parameters for these content windows using a simulated “ideal” windshield display in a virtual reality driving simulator. We found that user preferences differ with respect to contextual aspects. Additionally, using one main content window resulted in better task performance and lower take-over times, but the subjective user experience was higher for the multi-window user interface. These findings help automotive interface designers to improve experiences in automated vehicles.
Context-Aware Profiles
(2006)
Content presentation on 3D augmented reality windshield displays in the context of automated driving
(2022)
This paper provides a framework for examining human-vehicle interactions with respect to three dimensions that can involve models or simulations: the agents, the environments, and the scenarios. Agents are considered on a spectrum from human to artificial actors. Environments are considered on a spectrum from simulated to real. Scenarios are considered on a spectrum from constrained to unconstrained. It is argued that these three dimensions capture key differences in research approaches within the field of human-vehicle interaction, and that explicitly situating research and discussions within this framework will allow researchers to better compare and contrast research outcomes and contributions. The framework is used to locate different disciplines in the community with respect to one another, and to identify areas which are as-yet unexplored.
Although automated vehicles (AVs) come with many promises such as enabling the driver-passenger to perform non-driving-related-tasks or increased safety, the public’s acceptance of AVs will have a crucial impact on whether or not AVs will be ultimately adopted. In particular, the personality trait desire for control may influence the acceptance of AVs, which has received scant research attention to date. Therefore, we independently carried out two questionnaire studies: Study 1 in Germany and Study 2 in the U.S. In both studies, we applied the self-driving car acceptance scale (SCAS) and the desirability of control scale (DoCS). In Study 1, we queried 114 participants (60 female) and in Study 2 we sampled data from 601 participants (322 female). In both studies, our findings consistently indicate that the overall DoCS factor was not associated with the overall SCAS factor. We only uncovered a weak positive correlation in Study 1, but only for a reduced overall acceptance factor with 10 items obtained by factor analyses instead of the 24 items of the SCAS. Furthermore, our results revealed that women assign significantly lower ratings to the overall acceptance factor of AVs as well as to the desirability for control factor than men, both in Germany and in the U.S., respectively. Despite the influence of gender on acceptance of AVs and DoCS, we conclude that there might be either no or only a weak association between desire for control and acceptance of AVs, which needs to be further investigated in future studies.
Automated vehicles (AVs) are expected to enter the market within the next few years. However, their introduction would not only be a technological, but also a societal one – and it is therefore crucial to examine the public’s attitudes, opinions, and beliefs about AVs. It is particularly interesting to study when AVs are estimated to be accepted and adopted, and to query the willingness to pay for them. Hence, we applied a mixed-methods approach to collect quantitative and qualitative data and carried out a cross-sectional survey study. We focused on collecting an almost balanced sample across age and gender from 725 respondents (351 female, 374 male) with an age range from 18 to 96 years. Our results revealed that AVs are estimated to be accepted and adopted in about 10 years at SAE level L3 and in about 20 years at L5. Moreover, on average we found that the participants would be willing to pay 10.6 % more for an AV at L3 and 14.5 % at L5, but those estimates are affected by large outlier values. Nevertheless, we also observed that between 40 and 33 % of women and 41 and 33 % of men would not be willing to pay any more for an AV neither at L3 nor at L5, respectively. Ultimately, manufacturers and policymakers will have to take these findings into account if they really want to establish AVs as a widespread technological and societal revolution.