基于反应时间的公路隧道接近段停车视距研究

文森; 梁波; 肖尧; 蒲俊勇

doi:10.3963/j.jssn.1674-4861.2021.02.006

基于反应时间的公路隧道接近段停车视距研究

doi: 10.3963/j.jssn.1674-4861.2021.02.006

文森^1,,
梁波^{1, 2, ,},
肖尧^{1, 3},
蒲俊勇¹

1.
重庆交通大学土木工程学院重庆 400074
2.
重庆交通大学山区桥梁与隧道工程国家重点实验室重庆 400074
3.
重庆市轨道交通（集团）有限公司重庆 400042

基金项目:

国家自然科学基金项目 51878107

详细信息

作者简介:
文森(1995—), 硕士研究生.研究方向: 隧道交通安全.E-mail: 1104208215@qq.com

通讯作者:
梁波(1964—), 博士, 教授.研究方向: 隧道与地下工程理论和技术.E-mail: liang_laoshi@126.com

中图分类号: U459.2
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出版历程
- 收稿日期: 2020-12-07

A Stopping Sight Distance in Access Zone of Highway Tunnel Based on the Reaction Time

LIANG Bo^1
,,
LIANG Bo^{1, 2
, ,},
XIAO Yao^{1, 3},
PU Junyong¹

1.
College of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, China
2.
State Key Laboratory of Mountain and Bridge Engineering, Chongqing Jiaotong University, Chongqing 400074, China
3.
Chongqing Rail Transit(Group)Co. Ltd., Chongqing 400042, China

摘要

摘要: 反应时间是停车视距的1个重要影响因素，现有的停车视距模型较少考虑公路隧道洞外环境对驾驶员反应时间的影响。为研究公路隧道接近段的反应时间分布特性，选取25名驾驶人开展在公路隧道洞外不同距洞口距离、测试时刻和植被面积占比等条件下的室内仿真试验。利用公路隧道反应时间测量试验平台采集驾驶人的反应时间，应用重复测量方差分析对数据进行差异性显著检验，构建测试时刻、距洞口距离和反应时间关系度量模型，并在此基础上修正现有停车视距模型并进行验证。结果表明：①不同测点（距洞口距离）对应的反应时间存在总体显著性差异，反应时间随距洞口距离的减小呈先减小后增大的趋势，其中距离洞口40~60 m时反应时间达到最小；②不同植被面积占比对应的反应时间没有总体显著差异；③不同测试时刻对应的反应时间存在总体显著性差异，且测试时刻与测点间没有交互作用，反应时间随测试时刻增加呈先减小后增加的趋势，在16：00反应时间达到最小；④基于反应时间建立的新停车视距模型的校正系数为0.62，其计算值小于规范计算值，二者差值随设计速度的增加而增大；⑤经过新隧道实测值的验证，模型的预测值和实测值无显著差异，说明模型具有较好的预测能力。
- 交通安全 /
- 公路隧道 /
- 停车视距 /
- 室内仿真试验
Abstract: The reaction time is an important factor of stopping sight distance. The existing models of stopping sight distance seldom consider the influences of the environment outside the highway tunnel on reaction time of drivers. Twenty-five drivers are selected to carry out indoor simulation tests under different distances from the tunnel entrance, test time points, and vegetation area outside the tunnel to study the distribution of reaction time in the access zone of the highway tunnel. The platform for measurement of reaction time in the road tunnel is used to collect the reaction time of drivers, and ANOVA is used to test the significant differences in the data. A model of the relationship among the reaction time, distance, and time points is developed to quantify the impacts of distance and time on the reaction time. The results show that: ① The reaction time corresponding to different test points(distances from the entrance)has an overall significant difference. The reaction time first decreases and then increases with the decreased distance from the entrance, and reaches the minimum between 40 and 60 m from the entrance. ② The reaction timecorresponding to different vegetation area percentages has no overall significant difference. ③ The reaction time corresponding to different test time points has an overall significant difference, and there is no interaction between the test time point and the test point. The reaction time first decreases and then increases with the increase of time point, and reaches the minimum at 4 pm. ④ The correction coefficient of the new stopping sight distance model based on the reaction time is 0.62, with its calculated value less than the standard calculated value. The difference between the two increases with the increase of the design speed. ⑤ After verifying the measured value of the new tunnel, there is no significant difference between predicted and measured values, indicating that the model has a good predictive ability.
- traffic safety /
- highway tunnel /
- stopping sight distance /
- indoor simulation test

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图 1 洞外环境模拟装置和模拟驾驶设备

Figure 1. External environment simulated devices and simulated driving equipment

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图 2 反应时间测量程序界面

Figure 2. Measurement program interface to measure the response time

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图 3 不同方向的红色光斑示意图

Figure 3. Schematic diagram of red spots in different directions

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图 4 驾驶员反应时间布点

Figure 4. Distribution of drives'response time

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图 5 隧道仿真度评价

Figure 5. Evaluation on tunnel simulation

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图 6 测点与反应时间的关系

Figure 6. Relationship between the measuring points and reaction time

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图 7 不同植被面积占比与反应时间的关系

Figure 7. Relationship between different vegetation area proportions and reaction time

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图 8 隧道不同时刻的洞外亮度变化

Figure 8. Luminance changes outside the tunnel at different times

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图 9 测试时刻与反应时间的关系

Figure 9. Relationship between test time and reaction time

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图 10 反应时间与测试时刻和距隧道入口的距离综合作用下的三维曲面图

Figure 10. Three dimensional surface graph under the combined action of reaction time, test time, and distance from the tunnel entrance

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图 11 模型残差图

Figure 11. Residual plot of the model

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图 12 模型和规范的停车视距对比

Figure 12. Comparison of stopping sight distances between the model and specification

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图 13 停车视距散点图

Figure 13. Scatter plot of the stopping sight distance

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表 1 不同影响因素的总体显著性检验

Table 1. Overall significance test of different influencing factors

影响因素	统计量F	p
测点	19.785	0.000
测试时刻	7.032	0.000
植被面积占比	0.315	0.736
测点*测试时刻	0.915	0.583

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表 2 不同测点的反应时间均值

Table 2. Significance test between different measuring points

测点	反应时间均值/ms	标准差
测点1	905.35	47.32
测点2	881.99	48.40
测点3	835.12	36.78
测点4	833.32	34.56
测点5	917.87	47.58

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表 3 不同植被面积占比的反应时间均值

Table 3. Significance test among different vegetation area percentages

植被面积占比/%	反应时间均值/ms	标准差
48	868.03	40.19
50	886.43	70.48
62	869.73	50.19

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表 4 不同测试时刻的反应时间均值

Table 4. Significance test for different test time

测试时刻	反应时间均值/ms	标准差
10:00	901.62	58.30
12:00	875.29	57.36
13:00	883.71	55.94
14:00	882.49	63.04
15:00	891.71	52.61
16:00	823.38	22.97
17:00	864.88	36.99

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表 5 模型方差分析结果

Table 5. Variance analysis of the model

方差来源	自由度	平方和	均方	F值	p
回归	2	22 028.16	11 014.07	3.762	0.02
剩余	102	324 679.80	2 928.09
未修订和	104	349 974.90

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表 6 独立样本检验

Table 6. Independent sample test

量表	检验假设	方差方程的levene检验		均值方程的t检验
量表	检验假设	F检验值	显著性	t检验值	自由度	P值
停车视距	方差相等	17.82	0.001	-0.46	18	0.651
停车视距	方差不等			-0.46	9	0.656

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