Neuroimaging and Physiological Data-driven Autonomous Vehicle Driving Simulation System in Extended Reality

This paper presents the design and implementation of an advanced driving simulation system integrating EEG, HRV, and eye tracking to capture physiological and cognitive responses during autonomous vehicle simulations. EEG monitors brain activity to assess emotional and cognitive states like stress, fatigue, and mental workload, while eye tracking provides complementary data on visual attention, revealing distraction, drowsiness, and stress. Together, these modalities offer a comprehensive under-standing of driver comfort, automation reliance, and human-machine interaction. This study serves as a proof of concept for future research, laying the foundation for evaluating driver behavior in intelligent transportation systems and supporting the development of user-friendly autonomous driving technologies for safer roadways.