A Multimodal Interaction Experience Design Approach for Negative Emotional Driving Situations

Abstract

To investigate the effect of a multimodal interaction balance model on improving the emotional driving experience when users perform a high load driving task in a negative driving emotion context. The questionnaire analysis was used to obtain the main negative emotions and the corresponding driving situations. Combined with the STAR interview method to understand the user's interaction task in specific contexts, the user's cognitive load was assessed by the SWAT subjective load assessment technique to obtain a high cognitive load task, and the VACP model was used to establish a balanced model of interaction task and interaction modality. Simulated multimodal interaction physiological experiments were conducted to analyze the impact of the multimodal balance model on participants' physiological data when they performed high cognitive load tasks with different emotions, and the physiological data were analyzed to assess participants' emotional experience. The emotional experience design of an intelligent vehicle robot is used as an example to validate the method. The results show that the multimodal interaction balance model can effectively reduce the user's cognitive load and improve the pleasantness of the interaction experience, and find a breakthrough for the development of intelligent vehicle-mounted robots in emotional experience.

Keywords: Emotional experience；Interaction design；Driving Situations；

DOI: 10.54941/ahfe1002005