Abstract
Augmented reality head-up display (AR-HUD) presents a more natural way to process images with breakthroughs in optics. The technology also become the primary development trend of automobile human-machine interface (HMI). However, too much virtual information might interfere with drivers’ attention to their surroundings and affect their driving judgments. To effectively manage the complexity of vehicle information systems while further improving driving safety, this study aims to establish the information architecture of two driver groups (beginner drivers and skilled drivers) in different road environments. We developed a priority classification model and recruited 60 university students to participate in a card sorting experiment based on the criteria of beginner and skilled drivers. The cluster analysis findings were used to determine the AR-HUD information's grouping structure and hierarchical connection for the two driving user groups. Additionally, we investigated the impact of common road types and driving experience on the diversity of information architecture. The findings of this study constructed a user-centered information architecture and provided a theoretical foundation and role for the automobile industry in managing AR-HUD information and interface design.
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Zhang, H., Yu, Z., Zhang, C., Zhang, R., Liu, Y., Lee, S.H. (2022). User-Centered Information Architecture of Vehicle AR-HUD Interface. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2022. Lecture Notes in Computer Science, vol 13335. Springer, Cham. https://doi.org/10.1007/978-3-031-04987-3_21
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