Decision-Making in Augmented Reality: A Drift Diffusion Analysis of the Effects of Visualization and Hardware

Abstract

Augmented Reality (AR) is increasingly applied in real-world contexts that requires users to interpret visual information and make rapid decisions. However, little is known about how different AR visualization formats and hardware configurations influence underlying perceptual decision processes. This study addresses how AR-specific technical characteristics affect decision processes in a random-dot motion discrimination task, in which participants discriminate the coherent motion direction of a proportion of dots embedded in random noise, under multiple AR conditions and a real-world baseline condition. Behavioral data were analyzed using the drift-diffusion model to estimate latent decision parameters such as evidence accumulation and decision caution. The results show significant differences between AR configurations, indicating that visualization design and hardware characteristics likely affect the efficiency of evidence processing.