A user experience map design method based on emotional quantification of in-vehicle HMI

Abstract

The emotional experience of the driver is influenced by the design of the in-vehicle interaction interface. User experience journey maps are commonly used by designers to reveal interface design pain points and refine user needs, and further studies are required to effectively characterize and quantify user emotional needs. This study provides a method for accurately presenting a driver’s emotional experience through a human–machine interface using Kansei engineering and user experience journey. Firstly, the semantic difference approach was used to match the relationship between user behavioral touchpoints and Kansei imagery words of the interface. And then the emotional quantification curve was built to generate an average value for Kansei imagery word evaluation. Finally, design pain points were identified and iterative design was carried out. A validation study was implemented to ensure the method’s validity. The study demonstrated that a quantitative map of user emotional experience could efficiently quantify and depict the findings of emotional quantification. This method enables designers to accurately recognize user needs while also facilitating product iterations.