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How drivers’ visual characteristics change as they pass tunnels was studied. Firstly, nine drivers’ test data at tunnel entrance and inside sections using eye movement tracking devices were recorded. Then the transfer function of BP artificial neural network was employed to simulate and analyze the variation of the drivers’ eye movement parameters. The relation models between eye movement parameters and the distance of the tunnels were established. In the analysis of the fixation point distributions, the analytic coordinates of fixations in visual field were clustered to obtain different visual area of fixations by utilizing dynamic cluster theory. The results indicated that, at 100 meters before the entrance, the average fixation duration increased, but the fixations number decreased substantially. After 100 meters into the tunnel, the fixation duration started to decrease first and then increased. The variations of drivers’ fixation points demonstrated such a pattern of change as scatter, focus, and scatter again. While driving through the tunnels, drivers presented a long time fixation. Nearly 61.5% subjects’ average fixation duration increased significantly. In the tunnel, these drivers pay attention to seven fixation points areas from the car dashboard area to the road area in front of the car

Study on Driver's Fixation Variation at Entrance and Inside Sections of Tunnel on Highway