Abstract
The cognitive load of drivers is examined based on Multiple-Resource Theory by building the Human-Machine Interaction model of intelligent vehicles in order to improve the driving experience of this group and prevent traffic accidents as much as possible. The Multiple-Resource Theory is used to analyze the interaction modes of intelligent vehicles in this study, and the role of Physical Stuff interaction, Touch-screen Interaction, Voice Interaction, System-initiative, and Multimodal Interaction on the driver’s cognitive load is evaluated using simulated driving experiments and a Likert 5-point Likert scale. Among them, Multimodal Interaction evaluates the effect of physical Stuff interaction with Touch-screen Interaction and Physical Stuff Interaction with Voice Interaction. The principles of HMI design for Intelligent vehicles are investigated and deduced. Finally, an intelligent vehicle HMI system is developed based on the research and analysis findings, and the system is evaluated once again to demonstrate that the research findings may give relevant design ideas for intelligent vehicle HMI development.
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Liu, M., Qi, B. (2023). Design Study on the Effect of Intelligent Vehicles Interaction Mode on Drivers’ Cognitive Load. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2023. Lecture Notes in Computer Science, vol 14049. Springer, Cham. https://doi.org/10.1007/978-3-031-35908-8_4
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DOI: https://doi.org/10.1007/978-3-031-35908-8_4
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