Experts’ and Community Insights on Measuring Comfort and Perceived Safety in Automated Driving: Synthesis of a Participatory Workshop
TL;DR
Critical themes include, for example, the need for context-specific, deliberate selection of subjective measures; the promise and practical limitations of physiological signals; the ground truth challenge that complicates subjective-objective combination; and the emerging role of artificial intelligence for real-time inference and multimodal combination.
Abstract
Accurately measuring comfort and perceived safety in automated vehicles (AVs) is critical for understanding user experience, accommodating various needs, and eventually contributing to the public acceptance of AVs. However, methodological practices vary largely across the field. To address this gap, we organised a workshop at AutomotiveUI 2025, where three expert talks covered subjective measurements, objective and physiological measures, and AI-driven models, followed by two structured group discussion sessions on current practices and future methodologies. This work-in-progress synthesises key insights from both the expert talks and community discussions. Critical themes include, for example, the need for context-specific, deliberate selection of subjective measures; the promise and practical limitations of physiological signals; the ground truth challenge that complicates subjective-objective combination; and the emerging role of artificial intelligence (AI) for real-time inference and multimodal combination. We offer these insights to provide the community with a common methodological landscape and to promote more robust practices.