Effects of RealWorld Visual Fidelity on AR Interface Assessment: A Case Study Using AR Headup Display Graphics in Driving Recent AR research efforts have explored the use of virtual environments to test augmented reality (AR) user interfaces. However, it is yet to be seen what effects the visual fidelity of such virtual environments may have on AR interface assessment, and specifically to what degree assessment results observed in a virtual world would apply to the real world. Automotive AR headup (HUD) interfaces provide a meaningful application area to examine this problem, especially given that immersive, 3Dgraphicsbased driving simulators are established tools to examine invehicle interfaces safely before testing in real vehicles. In this work, we present an argument that adequately assessing AR interfaces requires a suite of different measures, and that such measures should be considered when debating the appropriateness of virtual environments for AR interface assessment. We present a case study that examines how an AR interface presented via HUD effects driver performance and behavior in different virtual and real environments. Twelve participants completed the study measuring driver task performance, eye gaze behavior and situational awareness during AR guided navigation in lowand highfidelity virtual simulation, and an onroad environment. Our results suggest that the visual fidelity of the environmental in which an AR interface is assessed, could impact some measures of effectiveness. Discussion is guided by a proposed initial assessment classification for AR user interfaces that may serve to guide future discussions on AR interface evaluation, as well as the suitability of virtual environments for AR assessment.

The Effects of a Predictive HMI and Different Transition Frequencies on Acceptance, Workload, Usability, and Gaze Behavior During Urban Automated Driving Automated driving research as a key topic in the automotive industry is currently undergoing change. Research is shifting from unexpected and timecritical takeover situations to human machine interface (HMI) design for predictable transitions. Furthermore, new applications like automated city driving are getting more attention and the ability to engage in nondriving related activities (NDRA) starting from SAE Level 3 automation poses new questions to HMI design. Moreover, future introduction scenarios and automated capabilities are still unclear. Thus, we designed, executed, and assessed a driving simulator study focusing on the effect of different transition frequencies and a predictive HMI while freely engaging in naturalistic NDRA. In the study with 33 participants, we found transition frequency to have effects on workload and acceptance, as well as a small impact on the usability evaluation of the system. Trust, however, was not affected. The predictive HMI was used and accepted, as can be seen by eyetracking data and the poststudy questionnaire, but could not mitigate the abovementioned negative effects induced by transition frequency. Most attractive activities were window gazing, chatting, phone use, and reading magazines. Descriptively, window gazing and chatting gained attractiveness when interrupted more often, while reading magazines and playing games were negatively affected by transition rate.