Research on Intelligent Cabin Design of Camper Vehicle Based on Kano Model and Generative AI

This study analyzes the functional requirements of different types of camping users in China based on the Kano model and improves the user experience of intelligent cabins using generative AI technology. The research adopts a combination of questionnaire surveys, literature review, and user interviews to construct a Kano model evaluation system. The Better-Worse coefficient method is used to analyze different functional attributes and identify priority sequences. Simultaneously, a detailed analysis is conducted on how generative AI affects interaction modes and interface design. The results reveal that cabin environment adjustment and entertainment functions are basic attributes, while voice navigation and intelligent voice assistants are expected attributes. Information push, intelligent recommendation, emotion recognition, and personalized experience are attractive attributes. Generative AI enables smarter voice interactions and more interesting personalized interfaces. Additionally, this study discusses smart cabin design strategies for camping vehicles based on the differences in functional priority among different user groups. Meeting basic needs is crucial, while customization of software and content design should be emphasized. The introduction of generative AI technology will drive interaction towards personalization, better satisfying diverse user needs.