Li Hao, Yang Jiabao, Jiang Heng
School of Civil Engineering Architecture and the Environment, Hubei University of Technology, Wuhan 430068, China.
Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan 430068, China.
Sensors (Basel). 2025 Jan 9;25(2):335. doi: 10.3390/s25020335.
The green vision rate of rural highway greening landscape is a key factor affecting the driver's visual load. Based on this, this paper uses the eye tracking method to study the visual characteristics of drivers in different green vision environments on rural highways in Xianning County. Based on the HSV color space model, this paper obtains four sections of rural highway with a green vision rate of 1020%, green vision rate of 2030%, green vision rate of 3040%, and green vision rate of 4050%. Through the real car test, the pupil area, fixation time, saccade time, saccade angle, saccade speed, and other visual indicators of the driver's green vision rate in each section were obtained. The visual load quantization model was combined with factor analysis to explore the influence degree of the green vision rate in each section on the driver's visual load. The results show that the visual load of the driver in the four segments with different green vision rate is as follows: Z1020% > Z2030% > Z3040% > Z4050%. When the green vision rate is 10~20%, the driver's fixation time becomes longer, the pupil area becomes larger, the visual load is the highest, and the driving is unstable. When the green vision rate is 40% to 50%, the driver's fixation time and pupil area reach the minimum, the visual load is the lowest, and the driving stability is the highest. The research results can provide theoretical support for the design of rural highway landscape green vision rate and help to promote the theoretical research of traffic safety.
农村公路绿化景观的绿视率是影响驾驶员视觉负荷的关键因素。基于此,本文采用眼动追踪方法研究咸宁县农村公路不同绿视环境下驾驶员的视觉特性。基于HSV颜色空间模型,本文获取了绿视率为10%20%、20%30%、30%40%、40%50%的四段农村公路。通过实车测试,得到了各路段驾驶员绿视率下的瞳孔面积、注视时间、扫视时间、扫视角度、扫视速度等视觉指标。将视觉负荷量化模型与因子分析相结合,探讨各路段绿视率对驾驶员视觉负荷的影响程度。结果表明,不同绿视率的四段路驾驶员视觉负荷情况为:Z1020%>Z2030%>Z3040%>Z4050%。当绿视率为10%~20%时,驾驶员注视时间变长,瞳孔面积变大,视觉负荷最高,驾驶不稳定。当绿视率为40%至50%时,驾驶员注视时间和瞳孔面积达到最小值,视觉负荷最低,驾驶稳定性最高。研究结果可为农村公路景观绿视率设计提供理论支持,有助于推动交通安全理论研究。