Optimization of visibility-adaptive expressway early warning schemes under sand-dust weather considering driver workload

Objective: Sand-dust weather conditions severely reduce visibility and pavement friction on desert expressways, substantially increasing crash risks. Existing early warning systems rely primarily on fixed thresholds and single-modal information, often neglecting driver cognitive and physiological workload. This study aimed to develop and optimize a visibility-adaptive multimodal early warning scheme for desert expressways under sand-dust weather conditions, with a focus on balancing driving safety and human workload.Methods: A high-fidelity driving simulator was used to construct four visibility scenarios: 500, 300, 100, and 50 m, representing typical sand-dust weather conditions on the Wuma Expressway. Thirty-six licensed drivers completed 64 orthogonal test conditions combining variable message signs (VMS), LED linear guidance, and voice navigation. Eye movement, driving behavior, and physiological indices (ECG and EEG) were synchronously collected. ACriteria Importance Through Intercriteria Correlation (CRITIC)-weighted multidimensional evaluation system was established, incorporating speed compliance, steering stability, heart rate (HR), and EEG β/θ ratio, to screen the optimal scheme via Euclidean distance decision-making.Results: Visibility significantly deteriorated driving performance and elevated workload. The optimal multimodal schemes varied by visibility: 500 m (60 flashes/min LEDs + speed/distance voice); 300–100 m (120 flashes/min LEDs + steering/fog-light voice); 50 m (constant LEDs + operational guidance). Compared with single-modal warnings, the optimized scheme demonstrated statistically significant improvements at 500 m and 300 m visibility (p < 0.0031, Bonferroni-corrected), increasing speed compliance by 10.6 percentage points (to 89.2%), reducing steering angle deviation by 0.005–0.01 rad and lateral acceleration deviation by 0.05–0.1 m/s2, lowering heart rate by 4.28 bpm, and raising the β/θ ratio by 0.14. At 100 m and 50 m visibility, nonsignificant but directionally consistent trends were observed (p = 0.011 and p = 0.034, respectively; Cohen’s d = 0.43 and 0.37), indicating a practical reduction in overall physiological load of approximately 15–20% that warrants further validation under stringent statistical thresholds.Conclusions: The visibility-adaptive multimodal early warning scheme effectively improves driving stability and mitigates driver workload under sand-dust weather conditions. Tiered information delivery and dynamic LED parameters enhance information perception and reduce visual fatigue. The findings offer a cognitive-load-informed framework to guide the parameter tuning of traffic management strategies and safety improvement on desert expressways during extreme sand-dust weather.