Klaus Schoeffmann

The paper uses eye-movement data in virtual driving to analyze human behavior through information-theoretic measures, finding that system-level information flow correlates stronger with performance than individual metrics.

The paper uses transfer entropy to measure causality from head motion to eye movement and shows it correlates with driving performance.

The paper introduces new metrics for visual scanning efficiency and cognitive effort using eye tracking data in virtual driving tasks.