As the automotive industry moves toward the car of the future, technology companies are developing cutting-edge systems, in vehicle and out, that aim to make driving safer, more pleasant, and more convenient. While we are already seeing some successful video-based augmented reality (AR) auxiliary displays (e.g., center-mounted backup aid systems), the application opportunities of optical see-through AR as presented on a drivers' windshield are yet to be fully tapped; nor are the visual perceptual and attention challenges fully understood. As we race to field AR applications in transportation, we should first consider the perceptual and distraction issues that are known in both the AR and transportation communities, with a focus on the unique and intersecting aspects for driving applications. This paper describes the some opportunities and driver challenges associated with AR applications in the automotive domain. We first present a basic research space to assist in these inquiries, which delineates head-mounted from heads-up and center-mounted displays; video from optical see-through displays; and world-fixed from screen-fixed AR graphics. We then address benefits of AR related to primary, secondary, and tertiary driver tasks as well as driver perception and cognition challenges inherent in automotive AR systems.

A challenge in presenting augmenting information in outdoor augmented reality (AR) settings lies in the broad range of uncontrollable environmental conditions that may be present, specifically large-scale fluctuations in natural lighting and wide variations in likely backgrounds or objects in the scene. In this paper, we present a active AR testbed that samples the user's field of view, and collects outdoor illuminance values at the participant's position. The main contribution presented herein is a user-based study (conducted using the testbed) that examined the effects on user performance of four outdoor background textures, four text colors, three text drawing styles, and two text drawing style algorithms for a text identification task using an optical, see-through AR system. We report significant effects for all these variables, and discuss design guidelines and ideas for future work