Exploring Empathy for Emotion-Aware Vehicles: How Should a Car Respond?

Abstract

Empathic vehicles aim to enhance driving by addressing both emotional and functional needs. Yet, current systems such as Advanced Driver Assistance Systems (ADAS) often overlook drivers’ dynamic emotional states, which strongly influence behaviour and decision-making. Existing research largely focuses on detecting emotions rather than responding to them in meaningful ways. This study applies a human-centered design approach to explore how multimodal feedback can support drivers through context-sensitive, emotion-aware interactions. Two groups – daily commuters and young drivers (18-24 years) – were investigated using a mixed-methods approach. Semi-structured interviews (n = 23) identified emotional triggers, coping strategies, and expectations, informing a driving simulator prototype featuring visual, auditory, and tactile feedback. 18 participants evaluated these strategies in three emotionally challenging driving scenarios. Results show that adaptive music was perceived as the most effective strategy for influencing emotions, followed by ambient lighting, whereas emojis and seat vibrations were rated less effective. No statistically significant differences were found between groups. Participants stressed the need for empathic systems that are transparent, subtle, and customisable, with strong concerns regarding data privacy. The findings underline the potential of multimodal, context-sensitive feedback and highlight the need for further testing in real-world driving environments.

Keywords: Empathic Interaction Design, Human-Machine-Interaction (HMI), Emotional Intelligence in Vehicles, Human-Centered Design, Multimodal Feedback

DOI: 10.54941/ahfe1007158