AI RESEARCH
Human Centered Non Intrusive Driver State Modeling Using Personalized Physiological Signals in Real World Automated Driving
arXiv CS.LG
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ArXi:2604.11549v1 Announce Type: cross In vehicles with partial or conditional driving automation (SAE Levels 2-3), the driver remains responsible for supervising the system and responding to take-over requests. Therefore, reliable driver monitoring is essential for safe human-automation collaboration. However, most existing Driver Monitoring Systems rely on generalized models that ignore individual physiological variability. In this study, we examine the feasibility of personalized driver state modeling using non-intrusive physiological sensing during real-world automated driving.