User Demand Analysis of User-centered Automotive Cockpit Context Components

The perception technology of intelligent cockpit promotes the development of context-based technology, and reasonable analysis and application of context components can better benefit users by applying technology to products. This study focuses on drivers in the intelligent cockpit of automobiles, analyzes driving context and user demand, and proposes cockpit context segmentation and context components under modern perception technology. From the perspectives of researchers and users, the relationship between context components and the analysis results of user research are generated through focus group and questionnaire methods. The entropy method, which reflects objective weighting, is used to determine the weight vector of the indicators. It is found that among the major components of driving contexts, the weight of vehicle status (23.51%) is the highest, while the weight of vehicle attributes (3.38%) is the lowest. This article takes the intelligent cockpit as the starting point, and provides a theoretical and technical practical basis for users' driving experience through context construction and components analysis.