The Evaluation of AR-HUD Visual Augmentation Method Based on Situation Awareness

Abstract

Augmented Reality Head-Up Display (AR-HUD) enhances driving safety and experience by overlaying virtual information into the driver’s forward view. However, AR-HUD may lead to attention capture, causing the driver to focus excessively on the AR-HUD and neglect other critical environmental information. Therefore, it is crucial to study how to balance the driver’s attention allocation between AR-HUD information and environmental information to ensure effective situational awareness (SA). The study based on Situational Awareness Theory, evaluates the impact of different AR-HUD augmentation methods (boxes, arrows, and shadows) on drivers' SA through analyzing eye movement data and Situation Awareness Rating Technique (SART) data. The results show that the different augmentation methods significantly affect drivers' SA levels. The box-type augmentation method performs the best overall and effectively improves the driver's SA. The study provides a theoretical foundation and practical guidance for the optimization and application of AR-HUD design.

Keywords: AR-HUD, situation awareness, human-computer interaction, visual attention allocation

DOI: 10.54941/ahfe1005854