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Methods: Thirty-two subjects were recruited for this study, and fixation data were recorded using eye movement tracking devices. A back-propagation artificial neural network was employed to predict and analyze the influence of special light zones on the variations in the fixation duration and pupil area of drivers. The analytic coordinates of focus points at different light zones were clustered to obtain different visual fixation regions using dynamic cluster theory.
Results: The findings of this study indicated that the special light zones had different influences on fixation duration and pupil area compared to other sections. Drivers gradually changed their fixation points from a scattered pattern to a narrow and zonal distribution that mainly focused on the main visual area at the center, the road just ahead, and the right side of the main visual area while approaching the special light zones. The results also showed that the variation in illumination and landscape in light zones was more important than driving experience to yield changes in visual cognition and driving behavior.
Conclusions: It can be concluded that the special light zones can help relieve drivers' vision fatigue to some extent and further develop certain visual stimulus that can enhance drivers' attention. The study would provide a scientific basis for safety measurement implementation in extra-long tunnels. 相似文献