Jinghang Xiao

Predicting pupillary response and identifying lighting thresholds in road tunnels using bacterial foraging optimization-based stacking ensemble model

The lighting conditions of road tunnels vary sharply across threshold, interior, and exit zones, imposing substantial visual adaptation demands on drivers and directly affecting pupillary response. To improve the prediction accuracy of pupil diameter and identify the nonlinear th...

Visibility-driven compensation model for driver pupillary response in road tunnels: a GWO-XGBoost and SHAP-based interpretable framework

Pupil diameter, as a sensitive indicator integrating photometric stimulation and mental workload, provides an effective bridge between tunnel visual conditions and drivers’ psychophysiological states. This study conducted real-vehicle field experiments in four tunnels with differ...