# Experimental Analysis of Driver Visual Characteristics in Urban Tunnels
## 2 Literature Review  
Drivers obtain driving information mainly from the surrounding environment, more than 90% of which is visual. The purpose of tunnel lighting is to convey the necessary traffic information to the driver to ensure his driving safety and comfort. In this process, the driver's eyes act as a link, and their movement characteristics can accurately reflect the driver's real feelings during the process of entering the tunnel [13; 14; 15]. Tunnel driver vision is always a popular research topic, and numerous real and simulated car experiments have been carried out so far. [PERSON] and [PERSON] conducted a tunnel-driving simulation experiment, and the results showed that tunnel design and illumination had some influence on the drivers' behavior, but visual attention given to the driving task was the most crucial factor, giving rise to significant changes in both driving behavior and visual behavior [16; 17]. [PERSON] et al. used the change rate of driver pupil area to describe the influence of sunlight under the ventilation shaft of an urban tunnel on drivers and established a random selection model of deceleration behavior under strong solar light [18]. The variations in the drivers' eye movements and speed were much more significant in the entrance zone of a tunnel without spatial intervisibility than in a tunnel with spatial intervisibility [19; 20]. The least-squares method of change point analysis was used to detect the time and locations of sudden changes in eye movement characteristics, and it was found that changes in road environments could cause a significant increase in fixation count and fixation duration for female drivers, such as in scenarios with traffic accidents or sharp curves [21]. The results for pupil size in the daytime increased when approaching the tunnel entrance, while at night, pupil size decreased when approaching the tunnel entrance and then increased after entering the tunnel. The pupil size in the daytime has a significant negative correlation with vehicle speed, while the pupil size at night did not show any significant association with vehicle speed. Furthermore, the average fixation duration in the daytime increased when entering the tunnel and had a significant negative correlation with vehicle speed. Furthermore, the average number of fixations in the daytime decreased when entering the tunnel and had a significant negative correlation with vehicle speed. However, the average fixation duration and the average number of fixations at night did not show any significant association with vehicle speed [22]. The transfer function of a BP artificial neural network proposed by [PERSON] et al. was employed to simulate and analyze the variation of the drivers' eye movement parameters [23]. [PERSON] et al. established a mathematical model of tunnel drivers' fixation time and eye movement amplitude based on a BP neural network [24; 25]. [PERSON] et al. established a visual search pattern matrix and a comprehensive evaluation model of eye movement characteristics based on the experimental data of drivers' fixation and saccade behaviors, which could be used to quantitatively judge driving proficiency [26]. It was proposed that the combination of visual information of high and low frequencies could effectively improve the driver's speed perception ability, reducing the driver's reaction time and improving the tunnel-driving safety by placing multiple frequency markers on the sidewall and road surface of the tunnel [27; 28]. [PERSON] et al. established the relationship model between the driver's visual recognition distance and the brightness difference inside and outside of the tunnel and calculated the brightness difference threshold of the tunnel entrance section at night at different design speeds [29; 30]. These studies generally suggest that the human eye movement characteristics of drivers at the entrance and exit of tunnels have obvious changes.