Dynamic Optimization of Adaptive Vehicle Lighting Systems: A Multimodal Assessment of Driver Performance and Well-being

Abstract: This study introduces a pioneering method for optimizing Adaptive Vehicle Lighting Systems (AVLS) by integrating eye-tracking technology and physiological indicators to assess driver performance and safety comprehensively. Building upon previous research on AVLS's impact on driving outcomes, this study employs a multimodal evaluation strategy that captures the intricate interplay between visual attention, cognitive load, and stress response under various lighting conditions. The primary objective is to identify personalized lighting configurations that enhance situational awareness and diminish cognitive demands on drivers.Participants engaged in a series of simulated driving tasks under controlled AVLS settings designed to emulate a diverse array of road scenarios. The preliminary findings of this research highlight the intricate relationship between AVLS settings and driver performance. The study reveals that optimal lighting conditions can notably reduce pupil dilation, a physiological marker of cognitive load, improve scanning efficiency, and enhance visual search capabilities. Moreover, personalized lighting adjustments have been shown to alleviate stress levels and enhance driver comfort, as indicated by reductions in heart rate variability and skin conductance responses.This study underscores the significance of a multidimensional evaluation of AVLS parameters. By overcoming the limitations inherent in current research, this method aspires to offer a more precise and effective optimization of AVLS. The ultimate goal is to bolster road safety and driver assistance. Through extensive testing under diverse conditions and a comprehensive assessment of performance indicators, this study sets the foundation for the progression of AVLS technology. The advancement of AVLS technology, in turn, can better adapt to the dynamic and ever-changing characteristics of road environments, ensuring a safer and more comfortable driving experience for all.

Keywords: Adaptive Vehicle Lighting Systems, Eye-Tracking, Physiological Metrics, Driver Performance, Personalized Lighting, Real-Time Analytics

DOI: 10.54941/ahfe1005855

Cite this paper:

​