Abstract
Vehicle automation is one of the major trends in the automotive industry and beyond. In our study, we investigate how future users with different levels of initial trust evaluate design features of level 4 automated vehicles in regards to the features’ ability to create passenger well-being. For this purpose, we identified potential design features from existing automated vehicle concepts and asked experts (n = 15) to rate them regarding their relevance to passenger well-being. In a second step, we conducted a user study (n = 69) to investigate how future users classify those features deemed relevant by the experts. Using the Kano method, the subsample with low initial trust rated 14 of 28 features as relevant, while the subsample with high initial trust rated 20 of 28 features as relevant. Further, the results indicate that the features deemed important for passenger well-being differ depending on the level of initial trust.
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