Research on Roadside Environment Safety Based on Driver’s Attention Distribution Model

doi:10.12141/j.issn.1000-565X.20210802

Abstract

Abstract:

In order to explore the influence of the highway roadside environment on the driver’s attention，optimize the roadside landscape and traffic sign settings，and improve the driving safety，this study determined the roadside environment risk level interval by quantitatively analyzing the driver’s attention distribution. Four types of typical scene were selected according to the actual state of the roadside environment， and field driving tests were carried out to collect data such as driver’s eye movement parameters and heart rate. The driver’s eye movement on the corresponding road section was analyzed，including fixation behavior，scan behavior and blinking behavior. On this basis，the obvious eye movement index that characterizes the driver’s attention was determined as the fixation parameter. According to the actual scene corresponding to the driver’s fixation point and the position of the point in the visual field， the driver's visual field area was divided into three parts， namely the roadside area （S area），the way area （W area） and the car area （C area）. By constructing the driver’s attention distribution model，the roadside environment was quantified and expressed by the ratio of attention region. The relationship model between the ratio of attention region and the driver’s heart rate growth rate was established，and the risk level interval was divided. The results show that the complexity of the roadside environment has a significant impact on the driver’s eye movement behavior. Compared with scan and blink，the driver’s fixation parameter can significantly characterize the driver’s attention state. When driving on the road，the driver’s fixation point moves in the view field，the ratio of attention region is the ratio of cumulative fixation time in the S area and the total fixation time of the S area and the W area. Its safety interval is ［9.93%，62.10%］，the risk interval is ［6.44%，9.93%） and （62.10%，76.93%］，and the danger interval is ［0，6.44%） and （76.93%，100%］. This research can provide a reference for the safety evaluation and decision-making of roadside landscape improvement.

Key words: highway, roadside environment, safety, eye movement, attention distribution

CLC Number:

U491.2

WU Yanxia, ZHOU Tong, HUANG Shuai, et al. Research on Roadside Environment Safety Based on Driver’s Attention Distribution Model[J]. Journal of South China University of Technology(Natural Science Edition), 2022, 50(9): 49-57.

Figures/Tables 13

Table 1

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Table 2

Regression model correlation and significance indicators"

阶段	模型	R	R²	F	Sig.
第1阶段	η=-23.08ln $γ$ +82.97	0.694	0.482	17.655	0.000
第2阶段	η=8.993 5e^{0.019 4} $γ$	0.679	0.462	526.455	0.000

Table 2

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	年龄/年	驾龄/年	驾驶里程/10⁴ km	备注
平均值	35.81	9.69	6.69	为了佩戴眼动仪，所有驾驶员裸眼视力均在4.8以上，平常驾车无需佩戴眼镜
标准差	7.01	4.96	3.89	为了佩戴眼动仪，所有驾驶员裸眼视力均在4.8以上，平常驾车无需佩戴眼镜

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