Face-Emoticons as Visual Display Stimuli for In-Vehicle Robots: A Perceived Usability Study Informed by Embodied Cognition

This study examined how face-emoticons displayed by in-vehicle robots support intelligible human–vehicle interaction in everyday driving. Grounded in embodied cognition, these emoticons were conceptualized as low-bandwidth, high-expressivity visual cues whose perceived usability depends on symbol stability and situated context. An experience-based online questionnaire comprising 11 constructs and 57 items was completed by 1,066 experienced users of a commercial in-vehicle robot in China. Partial least squares structural equation modeling and artificial neural network analysis were used to examine structural paths, mediation, predictive importance, and robustness. Symbol consistency was the strongest predictor of perceived usability. Information hierarchy, cultural universality, and accessibility formed a safety layer; multimodal integration and contextual adaptability formed a flow layer; and personalization, cuteification, and personification formed an engagement layer. Embodied cognition partially mediated four relationships. The findings offer an empirically supported usability model and practical guidance for automotive face-emoticon design.