Growable design of passenger vehicle interior space based on FAHP and FQFD

Abstract

The increasingly shortened development cycle of smart vehicles has led to a qualitative shift in the nature of automotive products. Growing spatial design of vehicle interiors can effectively satisfy users’ personalisation preferences and increase their willingness to buy, as well as mitigating the environmental pollution caused by the problem of rapid replacement. Considering the subjectivity and uncertainty of users’ emotional needs, this study adopts the FAHP method to comprehensively analyse and rank the SET series of factors, then combines the grey correlation method with the correlation analysis of the areas related to the interior space of the automobile, constructs the sample of the interior space of the automobile and extracts the kansei words of the space sample. Intentional vocabulary mean scores were calculated to factor analyses through kansei engineering, next the fuzzy QFD quality house was built to make affective semantic design associations and derive design weights, which are then used to guide the design and ultimately realise the design of a dynamic automotive interaction scenario. The results of the study show that the integration of different theories can reduce the uncertainties in accessing users’ emotional needs. At the same time, it can provide systematic guidance for the interaction design of a growable automobile in terms of multiple dimensions of interior space connectivity, spatial layout, and perceptual experience, as well as provide valuable suggestions for the subsequent development of interior spaces.