Browsing by Author "Smith, Missie"

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    AR DriveSim: An Immersive Driving Simulator for Augmented Reality Head-Up Display Research
    Gabbard, Joseph L.; Smith, Missie; Tanous, Kyle; Kim, Hyungil; Jonas, Bryan (Frontiers, 2019-10-23)
    Optical see-through automotive head-up displays (HUDs) are a form of augmented reality (AR) that is quickly gaining penetration into the consumer market. Despite increasing adoption, demand, and competition among manufacturers to deliver higher quality HUDs with increased fields of view, little work has been done to understand how best to design and assess AR HUD user interfaces, and how to quantify their effects on driver behavior, performance, and ultimately safety. This paper reports on a novel, low-cost, immersive driving simulator created using a myriad of custom hardware and software technologies specifically to examine basic and applied research questions related to AR HUDs usage when driving. We describe our experiences developing simulator hardware and software and detail a user study that examines driver performance, visual attention, and preferences using two AR navigation interfaces. Results suggest that conformal AR graphics may not be inherently better than other HUD interfaces. We include lessons learned from our simulator development experiences, results of the user study and conclude with limitations and future work.
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    Intelligent Augmented Reality (iAR):Context-aware Inference and Adaptation in AR
    Davari-Najafabadi, Shakiba (Virginia Tech, 2024-09-12)
    Augmented Reality (AR) transforms the entire 3D space around the user into a dynamic screen, surpassing the limitations of traditional displays and enabling efficient access to multiple pieces of information simultaneously, all day, every day. Recent developments in AR eyeglasses promise that AR could become the next generation of personal computing devices. To realize this vision of pervasive AR, the AR interface must address the challenges posed by constant and omnipresent virtual content. As the user's context changes, the virtual content in AR head-worn displays can occasionally become obtrusive, hindering the user's perception and awareness of their surroundings and their interaction with both the virtual and physical worlds. An intelligent interface is needed to adapt the presentation and interaction of AR content. This dissertation outlines a roadmap towards effective, efficient, and unobtrusive AR through intelligent AR (iAR) systems that automatically learn and adapt the interface to the user's context. To achieve this goal, we: %(1) Design multiple context-aware AR interfaces and explore their design and effectiveness in various contexts through four experiments; (1) Identify multiple AR design principles and guidelines that maintain efficiency while addressing challenges such as occlusion, social interaction, and content placement in AR. (2) Demonstrate the impact of context on AR effectiveness, validating the advantages of context-awareness and highlighting the complexities of implementing a context-aware approach in pervasive AR, particularly in scenarios involving context-switching. (3) Propose a design space for XR interfaces; (4) Develop a taxonomy of quantifiable contextual components and a framework for designing iAR interfaces.