Research on Age-Friendly Design of In-Vehicle Human-Machine Interface Based on Kano-AHP Model—Focusing on the Elderly Driver Group
Abstract
The in-vehicle human-machine interface (HMI) plays a crucial role in driving safety and operational experience. However, existing designs mainly target young users and fail to fully consider the actual needs of the elderly group. This study takes elderly drivers as the research object, adopts a combined method of Kano model and Analytic Hierarchy Process (AHP) to construct an analysis framework for demand identification and priority ranking. After establishing a demand pool through literature review and interviews, the Kano model is used for attribute classification, and AHP is combined to calculate demand weights. The results show that the primary needs of elderly drivers focus on safety-related functions and simplified operation processes, among which functions such as emergency braking assistance, voice correction, and fatigue monitoring have the highest priority; demands such as adjustable font size, haptic feedback, and voice interaction play an important role in reducing cognitive burden and optimizing experience. Based on this, the study proposes core design strategies of "safety first, simple operation, clear presentation, multimodal support, and emotional care". The contribution of this research lies in the first systematic application of the Kano-AHP model in the age-friendly design of in-vehicle HMI, proposing a comprehensive method that combines qualitative and quantitative analysis, and providing empirically based design suggestions. The results not only expand the theoretical dimension of age-friendly design research but also provide practical references for the intelligent automobile industry to address the aging challenge.
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