Visual Factors Influencing Trust and Reliance with Augmented Reality Systems

Augmented Reality (AR) systems are increasingly used for simulations, training, and operations across a wide range of application fields. Unfortunately, the imagery that current AR systems create often does not match our visual perception of the real world, which can make users feel like the AR system is not believable. This lack of belief can lead to negative training or experiences, where users lose trust in the AR system and adjust their reliance on AR. The latter is characterized by users adopting different cognitive perception-action pathways by which they integrate AR visual information for spatial tasks. In this work, we present a series of six within-subjects experiments (each N=20) in which we investigated trust in AR with respect to two display factors (field of view and visual contrast), two tracking factors (accuracy and precision), and two network factors (latency and dropouts). Participants performed a 360-degree visual search-and-selection task in a hybrid setup involving an AR head-mounted display and a CAVE-like simulated real environment. Participants completed the experiments with four perception-action pathways that represent different levels of the users’ reliance on an AR system: AR-Only (only relying on AR), AR-First (prioritizing AR over real world), Real-First (prioritizing real world over AR), and Real-Only (only relying on real world). Our results show that participants’ perception-action pathways and objective task performance were significantly affected by all six tested AR factors. In contrast, we found that their subjective responses for trust and reliance were often more affected by slight AR system differences than would elicit objective performance differences, and participants tended to overestimate or underestimate the trustworthiness of the AR system. Participants showed significantly higher task performance gains if their sense of trust was well-calibrated to the trustworthiness of the AR system, highlighting the importance of effectively managing users’ trust in future AR systems.