A Perceptual Color-Matching Method for Examining Color Blending in Augmented Reality Head-Up Display Graphics.

Augmented reality (AR) offers new ways to visualize information on-the-go. As noted in related work, AR graphics presented via optical see-through AR displays are particularly prone to color blending, whereby intended graphic colors may be perceptually altered by real-world backgrounds, ultimately degrading usability. This work adds to this body of knowledge by presenting a methodology for assessing AR interface color robustness, as quantitatively measured via shifts in the CIE color space, and qualitatively assessed in terms of users' perceived color name. We conducted a human factors study where twelve participants examined eight AR colors atop three real-world backgrounds as viewed through an in-vehicle AR head-up display (HUD); a type of optical see-through display used to project driving-related information atop the forward-looking road scene. Participants completed visual search tasks, matched the perceived AR HUD color against the WCS color palette, and verbally named the perceived color. We present analysis that suggests blue, green, and yellow AR colors are relatively robust, while red and brown are not, and discuss the impact of chromaticity shift and dispersion on outdoor AR interface design. While this work presents a case study in transportation, the methodology is applicable to a wide range of AR displays in many application domains and settings.

Augmented Reality Interface Design Approaches for Goal-directed and Stimulus-driven Driving Tasks.

The automotive industry is rapidly developing new in-vehicle technologies that can provide drivers with information to aid awareness and promote quicker response times. Particularly, vehicles with augmented reality (AR) graphics delivered via head-up displays (HUDs) are nearing mainstream commercial feasibility and will be widely implemented over the next decade. Though AR graphics have been shown to provide tangible benefits to drivers in scenarios like forward collision warnings and navigation, they also create many new perceptual and sensory issues for drivers. For some time now, designers have focused on increasing the realism and quality of virtual graphics delivered via HUDs, and recently have begun testing more advanced 3D HUD systems that deliver volumetric spatial information to drivers. However, the realization of volumetric graphics adds further complexity to the design and delivery of AR cues, and moreover, parameters in this new design space must be clearly and operationally defined and explored. In this work, we present two user studies that examine how driver performance and visual attention are affected when using fixed and animated AR HUD interface design approaches in driving scenarios that require top-down and bottom-up cognitive processing. Results demonstrate that animated design approaches can produce some driving gains (e.g., in goal-directed navigation tasks) but often come at the cost of response time and distance. Our discussion yields AR HUD design recommendations and challenges some of the existing assumptions of world-fixed conformal graphic approaches to design.