A Study on HMI Design of Intelligent Networked Vehicles Based on KJ-AHP
Guo Yu, Chengjun Zhou · 2025
With the rapid development of intelligent connected vehicle technology, the user experience requirements for in-vehicle human-machine interface (HMI) are increasing. In order to systematically elicit and satisfy user requirements, this study proposes a hybrid research method that integrates the KJ method and the hierarchical analysis method (AHP). The original demand data is collected through in-depth interviews and brainstorming, and the KJ method is used to conduct a three-level cluster analysis to construct an affinity diagram of HMI requirements for intelligent connected vehicles; on this basis, the AHP model is used to quantify the demand priorities, and cognitive load control and safety level anti-distraction design are identified as the core requirements. Based on the analysis results, the design strategy of “safety priority, functional integration, emotional support” is proposed. The study verifies the feasibility of the KJ-AHP method in in-vehicle HMI design, which not only provides a quantitative analysis framework for intelligent cockpit interaction design, but also provides a practical reference for improving driving safety and user experience.