With the continuous development of technology, we have the opportunity to quantitatively study the internal behaviors of personnel, such as attention, in a suitable way, in order to better solve the "machine compensation" for workers and achieve the development of human-machine fusion. An exploration of how varying lighting conditions directly affect the eyes and, by extension, the individual's attention has been undertaken in this study. Image sensors capture the subject's eye movements during task participation, with the location of the eye's (pupil's) center aiding in gaze point recognition and facilitating the quantification of attention. A quantifiable model of "lighting-attention" has been developed through controlled lighting conditions and replicable experimental circumstances, thereby studying the alteration of attention under different lighting and road conditions. An initial calibration of a monocular vision gaze tracking system was achieved with two commercialgrade eye trackers and calibration software, achieving a precision level of 2 cm. Nine college students aged 20-21, divided into male and female control test groups, exhibited similar attention characteristics under various lighting conditions. Overall, a negative correlation between illumination intensity and attention is observed when exceeding a certain threshold. On average, female participants maintained higher attention levels for longer durations. The efficacy of the model proposed in this study has been proven through a series of tests, providing a quantifiable reference for the mechanisms influencing attention. So it can provide the basis for the study of the benefits of factory workers.