User Interaction Mode Selection and Preferences in Different Driving States of Automotive Intelligent Cockpit

The purpose of this study is to investigate the user’s interaction modality choices and preferences in vehicle intelligent cockpits under different driving states. The driving state is divided into three driving scenarios: before departure, during driving, and halfway parking through a user-centered user journey approach, combining Don Norman’s theory of emotional systems. Data collection is conducted using questionnaire and interview methods to produce outputs on preference frequencies and correlations. In the questionnaire, it is found that users show significant interaction preferences in different driving states. Users have the most task preferences while driving, with the interaction behavior of navigating to a destination being the most frequent. A qualitative study in the interview indicates users’ modal preferences in different tasks as well as users’ focus on topics. After conducting user research, a multimodal combination method has been proposed to partition the input and output modes of interaction. The findings provide targeted guidance for automakers and designers to better meet user interaction needs in different driving scenarios and enhance the user experience and safety of automotive smart cockpits.