Beyond Overt Reactions: Analyzing Subtle User Emotional Response to Unexpected In-Vehicle System Behavior

Abstract

Modern vehicles, with advanced AI voice and autonomous navigation features, extend beyond traditional driving but, like any autonomous system, can potentially make mistakes or behave in ways unexpected by users. Although providing real-time explanations can alleviate some confusion, constant information can overwhelm users and potentially cause unnecessary distractions. Some situations may require explanations or corrective vehicle behavior, and thus, recognizing user response to unexpected vehicle behavior is critical. To investigate such user responses, our study focused on collecting and analyzing user behavioral responses to unexpected events while interacting with a fully autonomous vehicle in a driving simulator. We also aimed to address the lack of datasets capturing subtle user responses (facial, spoken language, physiological signals) to in-vehicle events, as existing datasets primarily focus on strong emotional signals in conventional human-driven cars and user response to external road and traffic conditions. Users were exposed to stimuli designed to induce surprise, confusion, and frustration while performing a secondary task on a tablet and interacting with the vehicle through voice commands and in-vehicle displays. We collected a multi-modal dataset with video, audio, and heart rate data and gained insights into subtle user responses that underscored the need for further investigation of nuanced user behaviors. These observations highlight the importance of designing vehicles that recognize and adapt to occupants' behavior, potentially improving their experience.