A Systematic Review of Augmented Reality Applications for Automated Driving: 2009–2020

Abstract

Abstract 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.