Abstract
In autonomous driving vehicles, the heterogeneity between human and automation agents can cause conflicts in decision-making and behaviour due to the difference in perception of hazardous situations. Augmented Reality Human-Machine Interfaces (AR-HMI) provide an opportunity to support driving performance by enabling drivers to intuitively access shared perception and explanation of the automated vehicle. One possible approach to AR-HMI design is to simplify the information of driving tasks based on vehicle context understanding, although there is currently a lack of systematic understanding of how collaborative mechanisms or cognitive features contribute to AR-HMI information design. Therefore, this work develops an augmented reality cognitive interface design method for autonomous driving. It aims to identify novel collaborative interface information visualization and provide a common language and inspiration for the design space.
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