The impact of roadside advertising density on driver visual attention and safety in Kuwait: An AI-driven analysis of simulator and eye-tracking data

OBJECTIVES: Driver distraction associated with roadside advertising remains a significant road safety concern, yet the precise physiological markers distinguishing stimulus-driven distraction from baseline driving are complex to isolate. This study quantified the impact of roadside advertising density on driver cognitive load and visual attention using a high-fidelity driving simulator and wearable eye-tracking technology. METHODS: A cohort of 60 licensed drivers navigated simulated environments under three continuous conditions: high-density advertising, low-density advertising, and a baseline with no advertisements. Approximately 2.4 million continuous physiological samples including pupil diameter, blink density, and gaze velocity were analyzed using statistical variance testing and an ensemble of machine learning architectures. RESULTS: ). CONCLUSIONS: The findings highlight the cognitive cost of dense visual clutter and advocate for the integration of cognitive load metrics into next-generation Advanced Driver Assistance Systems (ADAS). Furthermore, the data underscores the need to establish precise advertising safety thresholds, utilizing the 200 m spacing as a preliminary baseline for evaluating expanded zoning ordinances.