As vehicles become increasingly automated, the relationship between driver and machine must evolve to remain intuitive, safe, and trustworthy. This session explores how multimodal user state understanding can enable truly adaptive Human-Machine Interaction (HMI). Through a human-centered research approach, we study real drivers in realistic scenarios to understand emotional, cognitive, and attentional states—insights that guide the development of context-aware, personalized HMI systems. These systems adapt in real time to individual needs, supporting safety, comfort, and trust in automated driving.

You will hear more about:

• Adaptive HMI tailored to dynamic user states and driving contexts
• Human-in-the-loop research methodology for human-centered development
• Enhancing trust, safety, and user acceptance in automated vehicles