The aim of this study was to investigate how vehicle speed influences the characteristics of driver’s eye movement at highway tunnel entrances during day and night. In this study, six drivers’ eye movement data (from 200 m before tunnel entrance to 200 m inside tunnel entrance) under five predetermined vehicle speeds (40, 50, 60, 70 and 80 km/h) in the daytime and three predetermined vehicle speeds (40, 60 and 80 km/h) in the nighttime were recorded using the non-intrusive Dikablis Professional eye-tracking system. Pupil size, the average fixation duration time and the average number of fixation were analyzed and then the influence of the vehicle speed on these parameters was evaluated by means of IBM SPSS Statistics 20.0. The results for pupil size in daytime increased when approaching the tunnel entrance, while as for nighttime, pupil size decreased when approaching the tunnel entrance and then increased after entering the tunnel. The pupil size in daytime has a significant negative correlation with vehicle speed, while the pupil size in nighttime did not show a significant association with vehicle speed. Furthermore, the average fixation duration in daytime increased when entering the tunnel, and had a significant negative correlation with vehicle speed. Also, the average number of fixations in daytime decreased when entering the tunnel and has a significant negative correlation with vehicle speed. However, the average fixation duration and the average number of fixations in nighttime did not show any significant association with vehicle speed. Moreover, limitations and future directions of the study are discussed for the further investigation.
This paper presents an intelligent control method for tunnel lighting based on traffic volume. The monitoring data for a period of 12 days of the Chibai tunnel (located in the Jilin province of China) under different weather conditions was selected as the case study. The data used in the analysis included traffic volume, vehicle speed, the time of light-emitting diodes (LEDs) operating at their lowest luminance level, and the average time interval between two consecutive vehicles. The traffic flow analysis indicated that the tunnel has a relatively heavy traffic volume in the daytime (7:00 a.m. to 6:00 p.m.) and a relatively low traffic volume in the nighttime (12:00 a.m. to 6:00 a.m. and 7:00 p.m. to 12:00 a.m.). Thus, we propose a tunnel lighting control method that distinguishes day and night operational strategies. In the daytime, the luminance of tunnel zones depends on tunnel exterior luminance, traffic volume and vehicle speed regardless of vehicle presence. In the night, the “vehicle in, light brightens; vehicle out, light darkens” control method is adopted for the tunnel luminance, which depends on vehicle presence.
The aim of this study was to investigate the impact of correlated color temperature (CCT) of LED light source on human vision performance in mesopic region. First, six CCTs (3500, 4000, 4500, 5000, 5700, and 6500 K) were assessed using mesopic photometry model MES-2. The calculation results indicated that the mesopic luminance had a positive correlation with CCT. Then, reaction time experiment was conducted in an experimental box designed to simulate the mesopic application environments. Ten observers of different ages and gender participated to make response after target appears under different lighting conditions. Experiment results showed that reaction time had a negative correlation with CCT, which is coherent with that the mesopic luminance increased with the increasing of CCT.
1 March 2020 in Environmental Modelling & Software