研究雨天驾驶时司机视线变化，发现更频繁看仪表盘、盯得更久。
Weather-Dependent Variations in Driver Gaze Behavior: A Case Study in Rainy Conditions
- 分段聚类+元聚类分析司机视线点，结合马尔可夫矩阵建模
- 雨天视线停留时间变长，抬头角度更高，仪表盘注视更频繁
- 结果可优化驾驶监控系统，适合自动驾驶与ADAS研发者参考
雨天因能见度降低和车辆抓地力下降，显著增加交通事故风险。理解经验驾驶员在恶劣天气下如何通过视线行为调整视觉感知，对设计鲁棒的驾驶员监测系统（DMS）和高级驾驶辅助系统（ADAS）至关重要。本案例研究分析了一名驾驶员在相同高速路段于晴天与雨天条件下的眼动行为。采用两步聚类方法：先对10秒内的眼动点进行聚类，再将聚类中心聚合为元聚类。结合马尔可夫转移矩阵及凝视持续时间、视线仰角与方位分布等指标，揭示出有意义的行为变化。尽管整体视线仍集中于路面并偶有后视镜检查，但雨天条件下出现更频繁的仪表盘注视、更长的凝视时长和更高的视线仰角，表明认知注意力增强。这些发现为恶劣天气下的视觉注意力模式提供了重要洞见，并凸显了利用视线建模提升ADAS与DMS鲁棒性的潜力。
原文摘要 · Abstract (English)
Rainy weather significantly increases the risk of road accidents due to reduced visibility and vehicle traction. Understanding how experienced drivers adapt their visual perception through gaze behavior under such conditions is critical for designing robust driver monitoring systems (DMS) and for informing advanced driver assistance systems (ADAS). This case study investigates the eye gaze behavior of a driver operating the same highway route under both clear and rainy conditions. To this end, gaze behavior was analyzed by a two-step clustering approach: first, clustering gaze points within 10-second intervals, and then aggregating cluster centroids into meta-clusters. This, along with Markov transition matrices and metrics such as fixation duration, gaze elevation, and azimuth distributions, reveals meaningful behavioral shifts. While the overall gaze behavior focused on the road with occasional mirror checks remains consistent, rainy conditions lead to more frequent dashboard glances, longer fixation durations, and higher gaze elevation, indicating increased cognitive focus. These findings offer valuable insight into visual attention patterns under adverse conditions and highlight the potential of leveraging gaze modeling to aid in the design of more robust ADAS and DMS.
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