Analysis and Modeling of Drivers'Visual Load at Entrance and Exit Areas of Undersea Tunnel
In order to explore the changing rules in the physiological characteristics and visual load of drivers in the entrance and exit areas of the undersea tunnel,in this paper a real vehicle experiment in an undersea tunnel is conducted,the data of vehicle speed,tunnel illumination and driver eye-movement characteristics parameters are collected,and their changing characteristics in the process of entering and leaving the tunnel entrance are studied.By comparing the differences of evaluation indicators,the relative change rate of eyelid closure is selected as the visual load evaluation index,and a fitting function model of vehicle speed,illumination and relative change rate of eyelid closure is constructed,and the relative change of vehicle speed,illumination and eyelid closure is quantified.The visual load characteristics of drivers in the tunnel entrance and exit areas are analyzed,and the single factor analysis method is used to analyze the sensitivity of the independent variables of illumination in the model.The research results show that when driving in the entrance and exit areas of the undersea tunnel,the relative change rates of vehicle speed,illumination and eyelid closure under different road sections are different to a certain extent.In the process of driving into or out of the tube,the relative change rate of vehicle speed and eyelid closure show a sharp decrease trend,and tend to rise steadily after passing through the portal.The relative change rate of the driver's eyelid closure is more sensitive to illumination than its sensitivity to vehicle speed.The fluctuation of illumination is more likely to cause fluctuations in the relative change rate of eyelid closure than the vehicle speed.The driver's visual load is more significantly affected by the illumination factor at 50 m in front of the tunnel portal.
urban trafficundersea tunnelentrance and exit sectionvisual loadeyelid closuresensitivity analysis
NETL
NSTL
万方数据
