A Review of Automotive AR-HUD Interfaces Across Driver Roles and Vehicle Automation Levels

Augmented Reality Head-Up Displays (AR-HUDs) have emerged as a transformative technology in the automotive sector, significantly enhancing driver awareness and safety by seamlessly integrating critical information into the driver's direct line of sight. However, implementing effective AR-HUD systems presents several challenges, including designing intuitive yet minimally distracting user interfaces, ensuring accurate spatial registration, and adapting visualizations to different contexts and levels of vehicle automation. This article provides a comprehensive overview of the current literature on automotive AR-HUDs and offers a structured taxonomy that classifies existing studies along two main dimensions: the specific features of the AR-HUD interface, which capture the relationship between display-related and interaction-related characteristics across tasks and driving contexts, and the human-automation roles, which frame the evolving shift of control, attention, and responsibility between the human and the automated system as vehicle autonomy increases. Additionally, we critically analyze existing testing methodologies and identify significant gaps, such as the overreliance on testing in virtual environments and the lack of standardized frameworks for the progressive evaluation of AR-HUD interfaces, from conceptual designs to immersive virtual simulations and real-world assessments. We conclude by discussing key open research questions and future research directions needed to overcome current limitations and realize the full potential of AR-HUD technology.