Automotive research often takes place in driving simulators, where a high sense of feeling present in the virtual traffic situation has been hypothesized to foster a realistic driving behavior. Presence in driving simulators has been investigated using subjective questionnaires, but their validity for application in driving simulators has not yet been verified. In a first approach, we aimed at critically investigating whether presence questionnaires can or cannot be applied in driving simulation. Therefore, we conducted a within-subjects experiment with N = 50 participants comparing presence between a low- and a high-fidelity simulator, using two commonly used questionnaires: the Igroup Presence Questionnaire (IPQ) and the Slater-Usoh-Steed (SUS*) presence questionnaire. The wording of the SUS* questionnaire has been adopted for use in driving simulation prior to its use in the study. Results show a strong correlation between the adapted SUS* questionnaire and the IPQ. Both questionnaires reflected a significant difference in presence between the low-fidelity and the high-fidelity simulator. The reliability of both questionnaires was acceptable (Cronbach's alpha > .7). The present results are promising in that presence questionnaires, including in particular the adapted SUS* and the IPQ, can be used in driving simulation. The validity of the adapted SUS* questionnaire should be further investigated.

While augmented reality (AR) interfaces have been researched extensively over the last decades, studies on their application in vehicles have only recently advanced. In this article, we systematically review 12 years of AR research in the context of automated driving (AD), from 2009 to 2020. Due to the multitude of possibilities for studies with regard to AR technology, at present, the pool of findings is heterogeneous and non-transparent. From a review of the literature we identified N = 156 papers with the goal to analyze the status quo of existing AR studies in AD, and to classify the related literature into application areas. We provide insights into the utilization of AR technology used at different levels of vehicle automation, and for different users (drivers, passengers, pedestrians) and tasks. Results show that most studies focused on safety aspects, driving assistance, and designing non-driving-related tasks. AR navigation, trust in automated vehicles (AVs), and interaction experiences also marked a significant portion of the published papers; however, a wide range of different parameters was investigated by researchers. Among other things, we find that there is a growing trend toward simulating AR content within virtual driving simulators. We conclude with a discussion of open challenges, and give recommendations for future research in automated driving at the AR side of the reality-virtuality continuum.

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 ( N = 26 ) and then in rearward viewing ( N = 18 ) 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.

In the long history of subliminal messages and perception, many contradictory results have been presented. One group of researchers suggests that subliminal interaction techniques improve human–computer interaction by reducing sensory workload, whereas others have found that subliminal perception does not work. In this paper, we want to challenge this prejudice by first defining a terminology and introducing a theoretical taxonomy of mental processing states, then reviewing and discussing the potential of subliminal approaches for different sensory channels, and finally recapitulating the findings from our studies on subliminally triggered behavior change. Our objective is to mitigate driving problems caused by excessive information. Therefore, this work focuses on subliminal techniques applied to driver–vehicle interaction to induce a nonconscious change in driver behavior. Based on a survey of related work which identified the potential of subliminal cues in driving, we conducted two user studies assessing their applicability in real-world situations. The first study evaluated whether subtle (subliminal) vibrations could promote economical driving, and the second exposed drivers to very briefly flashed visual stimuli to assess their potential to improve steering behavior. Our results suggest that subliminal approaches are indeed feasible to provide drivers with added driving support without dissipating attention resources. Despite the lack of general evidence for uniform effectiveness of such interfaces in all driving circumstances, we firmly believe that such interfaces are valuable since they may eventually prevent accidents, save lives, and even reduce fuel costs and CO 2 emissions for some drivers. For all these reasons, we are confident that subliminally driven interfaces will find their way into cars of the (near) future.