An Analysis of Visual Characteristics of Drivers Over Continuous Highway Tunnels
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摘要: 为了提高高速公路隧道群的行车安全,研究隧道群环境下驾驶人的视觉特性,在实际高速公路隧道群场景中,设计了驾驶人眼动特性实验方案,借助TobiiGlass2眼动仪与ErgoLAB数据分析平台采集了20名实验者的注视、扫视及瞳孔变化等眼动行为数据,对比分析了视觉特性变量在不同隧道、不同区段的差异。结果显示,在水平方向上第1条隧道的视野角度均值高于第2条隧道,而在垂直方向上则相反;第2条隧道的平均扫视时间比第1条隧道缩短47.75%,第1条隧道的平均瞳孔直径比第2条隧道大7.89%;第1条隧道入口段的瞳孔面积变化率平均值与方差大于第2条隧道入口段。实验结果表明,驾驶人在连续隧道群中通行到第2条隧道时视觉负荷降低,视觉稳定性提高。Abstract: In order to improve traffic safety of highway segments with continuous tunnels, visual characteristics of drivers are analyzed. An experimentfor collecting characteristics of drivers'eye movement is designed in actual highway scenes. Eye movement data of 20 drivers, such as fixation, scanning, and pupil area change is collected with TobiiGlass2 and ErgoLAB data analytics tool. The visual characteristics of drivers inside different tunnels and at different sections are compared and analyzed. Study results show that the average view angle is higher in the first tunnel than that in the second tunnel in the horizontal direction, but it is opposite in the vertical direction. Average saccade time of the second tunnel is 47.75% shorter than that of the first tunnel. Average pupil diameter of the first tunnel is 7.89% larger than that of the second tunnel. Mean and variance of change rate of the pupil area at the entrance segment of the first tunnel are larger than that of the second tunnel. It can be concluded that when driving through the second tunnel over continuous highway tunnels, drivers' visual load isreduced, and visual stability is improved, when compared to those observed over the first tunnel.
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Key words:
- traffic safety /
- continuous highway tunnels /
- visual characteristics
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表 1 眼动仪输出数据指标
Table 1. Output data index of eye-moving instrument
输出指标 单位 注视次数(fixation count) 次 单次注视时间(single fixation time) s 总共扫视时间(total saccade time) s 眨眼次数(blink count) 次 聚焦点(focus point) 平均瞳孔直径(average pupil diameter) mm 表 2 隧道群各区段驾驶人扫视特性表
Table 2. Scanning characteristics of drivers in each section of tunnel group
变量 隧道接近段 第1条隧道 开敞段 第2条隧道 驶离段 长度/m 300 452 227 263 150 通行时间/s 16.61 25.03 9.88 12.57 8.31 扫视次数/次 18 16 10 8 34 平均扫视时间/ms 94.5 69.85 48.05 36.5 109.5 扫视比例/% 6.27 2.42 2.91 2.11 13.98 表 3 隧道群各区段驾驶人瞳孔直径表
Table 3. Pupil diameter of drivers in each section of tunnel group
单位: mm 区段划分 平均瞳孔直径 最大瞳孔直径 最小瞳孔直径 隧道接近段 3.74 4.52 0.85 第1条隧道 5.06 6.81 2.45 开敞段 4.31 6.44 1.38 第2条隧道 4.69 6.23 2.06 驶离段 4.42 5.32 1.26 表 4 茅山隧道群区段划分表
Table 4. Section division of maoshan tunnel group
单位: m 区段划分 第1条隧道 第2条隧道 人口段长度 162 81 中间段长度 198 122 出口段长度 92 60 表 5 隧道内各区段驾驶人扫视速度
Table 5. Scanning speed of drivers in each section of the tunnel
单位: (°) /s 指标 第1条隧道路段 第2条隧道路段 人口段 中间段 出口段 人口段 中间段 出口段 平均值 171.8 113.8 215.7 160.2 94.6 176.6 极小值 112 87 157 108 59 127 极大值 253 154 299 228 136 221 标准差 40.8 21.3 40.4 33.1 19.4 33.8 方差 1 747.3 446.6 1 648.6 1128.3 375.2 1 212.2 表 6 隧道内各区段驾驶人瞳孔面积变化率
Table 6. Change rate of pupil area of drivers in each section of tunnel
单位: % 指标 第1条隧道路段 第2条隧道路段 人口段 中间段 出口段 人口段 中间段 出口段 平均值 44.81 15.17 34.23 34.50 12.93 30.87 极小值 21.39 5.68 14.71 19.30 5.40 7.88 极大值 66.93 22.60 58.92 47.22 22.34 55.11 标准差 13.31 5.10 10.89 9.51 4.82 11.70 方差 1.80 0.30 1.20 0.90 0.20 1.40 -
[1] 杜志刚, 余昕宇, 向一鸣, 等. 基于交通事故预防的高速公路隧道光环境优化研究[J]. 武汉理工大学学报(交通科学与工程版), 2018, 42(5): 715-719.DU Z G, YU X Y, XIANG Y M, XU Wanwan. Research on light environment optimization of highway tunnel based on traffic accident prevention[J]. Journal of Wuhan University of Technology(Transportation Science & Engineering), 2018, 42(5): 715-719. (in Chinese) [2] 王志杰, 王如磊, 舒永熙, 等. 高速公路特长隧道及隧道群运营安全风险评估研究[J]. 现代隧道技术, 2019, 56(增刊2): 36-43. https://www.cnki.com.cn/Article/CJFDTOTAL-XDSD2019S2006.htmWANG Z J, WANG R L, SHU Y X, et. al. Study on operation safety risk assessment of the extra-long expressway tunnel and tunnel group[J]. Modern Tunnelling Technology, 2019, 56 (S2): 36-43. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XDSD2019S2006.htm [3] 钱勇, 马健霄, 赵顗, 等. 基于集对可拓物元模型的公路隧道运营环境安全评价方法[J]. 森林工程, 2020, 36(1): 87-95.QIAN Y, MA J X, ZHAO Y, et al. Safety evaluation method for highway tunnel operation environment based on set-pair extension matter element model[J]. Forest Engineering, 2020, 36(1): 87-95. (in Chinese) [4] 方松, 马健霄. 城市隧道路段驾驶行为综合风险研究[J]. 森林工程, 2019, 35(6): 67-71. https://www.cnki.com.cn/Article/CJFDTOTAL-SSGC201906011.htmFANG S, MA J X. Research on comprehensive risk of driving behavior of urban tunnel[J]. Forest Engineering, 2019, 35(6): 67-71. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SSGC201906011.htm [5] 王羽尘, 马健霄, 刘宇航. 公路隧道火灾环境人群逃生行为分析及多项Logit建模[J]. 中国安全生产科学技术, 2020, 16 (12): 129-135. https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK202012028.htmWANG Y C, MA J X, LIU Y H. Analysis of crowd escape behavior in highway tunnel fire environment and multinomial Logit modeling[J]. Journal of Safety Science and Technology, 2020, 16(12): 129-135. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK202012028.htm [6] CHAKRABARTY N, GUPTA K. Analysis of driver behaviour and crash characteristics during adverse weather conditions[J]. Social and Behavioral Sciences, 2013(104): 1048- 1057. http://www.sciencedirect.com/science/article/pii/S1877042813045916/pdfft?md5=6ce8f8ac0360f6f5f68301ea9d48b673&pid=1-s2.0-S1877042813045916-main.pdf [7] KIM H S, HWANG Y, YOON D, et. al. Driver workload characteristics analysis using EEG data from an urban road[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(4): 1844-1849. doi: 10.1109/TITS.2014.2333750 [8] 王玉化, 戚春华, 朱守林, 等. 驾驶疲劳恢复时间的心电信号分析[J]. 中国安全科学学报, 2017, 27(8): 7-12. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201708002.htmWANG Y H, QI C H, ZHU S L, et. al. Study on driving fatigue recovery time based on ecg analysis[J]. China Safety Science Journal, 2017, 27(8): 7-12. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201708002.htm [9] 杜志刚, 潘晓东, 郭雪斌. 高速公路隧道进出口视觉适应实验[J]. 哈尔滨工业大学学报, 2007, 39(12): 1998-2001. https://www.cnki.com.cn/Article/CJFDTOTAL-HEBX200712034.htmDU Z G, PAN X D, GUO X B. Experimental studies of visual adaptation on driving through freeway tunnels entrance and exit[J]. Journal of Harbin Institute of Technology, 2007, 39 (12): 1998-2001. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HEBX200712034.htm [10] 李显生, 孟凡淞, 郑雪莲, 等. 基于应激响应的驾驶人视觉特性[J]. 吉林大学学报(工学版), 2017, 47(5): 1403-1410. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201705011.htmLI X S, MENG F S, ZHENG X L, et. al. Driver's visual characteristics based on stress response[J]. Journal of Jilin University(Engineering and Technology Edition), 2017, 47 (5): 1403-1410. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201705011.htm [11] 胡月琦, 刘浩学, 朱彤, 等. 高速公路特长隧道环境中驾驶员视觉特性研究[J]. 中国安全科学学报, 2017, 27(6): 31-36. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201706006.htmHU Y Q, LIU H X, ZHU T, et. al. Research on visual characteristics of drivers driving through extremely long expressway tunnel[J]. China Safety Science Journal, 2017, 27(6): 31-36. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201706006.htm [12] HU Y Q, LIU H X, ZHU T. Influence of spatial visual conditions in tunnel on driver behavior: Considering the route familiarity ofdrivers[J]. Advances in Mechanical Engineering, 2019, 11(5): 1-9. http://www.researchgate.net/publication/333490310_Influence_of_spatial_visual_conditions_in_tunnel_on_driver_behavior_Considering_the_route_familiarity_of_drivers [13] 朱可宁, 龚波. 高速公路特长隧道出口段驾驶人心理负荷变化规律[J]. 交通科技与经济, 2017, 19(3): 6-9. https://www.cnki.com.cn/Article/CJFDTOTAL-KJJJ201703002.htmZHU K W, GONG B. Research on driver mental load in exit of super long tunnel[J]. Technology & Economy in Areas of Communications, 2017, 19(3): 6-9. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KJJJ201703002.htm [14] 陈孟柯, 马健霄, 陆涛, 等. 高速公路隧道行车视觉特性分析[J]. 交通信息与安全, 2019, 37(3): 86-92. doi: 10.3963/j.issn.1674-4861.2019.03.011CHEN M K, MA J X, LU T, et. al. Visual characteristics of drivers for driving through freeway tunnel[J]. Journal of Transport Information and Safety, 2019, 37(3): 86-92. (in Chinese) doi: 10.3963/j.issn.1674-4861.2019.03.011 [15] HE S, LIANG B, PAN G, et al. Influence of dynamic highway tunnel lighting environment on driving safetybased on eye movement parameters of the driver[J]. Tunnellingand Underground Space Technology, 2017(67): 52-60. http://www.sciencedirect.com/science/article/pii/S0886779817301372 [16] 方松, 马健霄. 城市隧道长度对驾驶人视觉特性影响分析[J]. 交通信息与安全, 2020, 38(6): 24-30. doi: 10.3963/j.jssn.1674-4861.2020.06.004FANG S, MA J X. Influences of urban tunnel length on visual characteristics of drivers[J]. Journal of Transport Information and Safety, 2020, 38(6): 24-30. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2020.06.004 [17] 周智文, 马健霄, 谭婷. 公路毗邻隧道群路段驾驶人视觉稳定性评价[J]. 森林工程, 2020, 36(4): 116-122. https://www.cnki.com.cn/Article/CJFDTOTAL-SSGC202004016.htmZHOU Z W, MA J X, TAN T. Evaluation of drivers'visual stability in highway adjacent tunnel group section[J]. Forest Engineering, 2020, 36(4): 116-122. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-SSGC202004016.htm [18] LIU H, DING G, ZHAO W, et al. Variation of drivers visualfeatures in long-tunnel entrance section on expressway[J]. Journal of Transportation Safety & Security, 2011, 3(1): 27-37. http://www.researchgate.net/publication/269081952_Drivers'_Visual_Feature_Variation_in_Long-Tunnel_Exit_of_Expressway [19] 杜志刚, 潘晓东, 郭雪斌. 公路隧道进出口行车安全评价指标应用研究[J]. 同济大学学报(自然科学版), 2008, 36 (3): 325-329. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ200803010.htmDU Z G, PAN X D, GUO X B. Evaluation index's application studies on safety at highway tunnel's entrance and exit[J]. Journal of Tongji University(Natural Science), 2008, 36(3): 325-329. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ200803010.htm [20] 施丽莎, 陆涛, 周智文, 等. 基于视觉追踪的导向标志评价体系设计[J]. 交通运输研究, 2019, 5(2): 36-44. https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH201902005.htmSHI L S, LU T, ZHOU Z W, et. al. Evaluation system of guidance signs based on visual tracking[J]. Transport Research, 2019, 5(2): 36-44. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH201902005.htm [21] 焦方通, 杜志刚, 王首硕, 等. 城市水下特长隧道出入口视觉及舒适性研究[J]. 中国公路学报, 2020, 33(6): 147-156. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202006015.htmJIAO F T, DU Z G, WANG S S, et al. Visual characteristic and comfort at the entrance and exit of the extra-long urban underwater tunnel[J]. China Journal of Highway and Transport, 2020, 33(6): 147-156. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202006015.htm [22] 刘琦, 赵卫斌, 马非, 等. 自然光对公路短隧道照明环境的影响研究[J]. 公路交通技术, 2017, 33(3): 92-97. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJT201703025.htmLIU Q, ZHAO W B, MA F, et al. Study on influence of natural light on lighting environment of expressway short tunnels[J]. Technology of Highway and Transport, 2017, 33 (3): 92-97. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJT201703025.htm [23] 杜志刚, 梅家林, 倪玉丹, 等. 基于视觉需求的城市水下特长隧道光环境评价与优化综述[J]. 交通运输工程学报, 2020, 20(6): 48-61. https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202006007.htmDU Z G, MEI J L, NI Y D, et al. Research on evaluation and optimization of light environment of extra-long urban underwater tunnel based on visual demands[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 48-61. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202006007.htm [24] 潘义勇, 丁袁, 陈璐. 景区与城市道路环境下驾驶人眼动特性差异性分析[J]. 重庆交通大学学报(自然科学版), 2019, 38(6): 84-89. https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201906015.htmPAN Y Y, DING Y, CHEN L. Difference of eye movement characteristic of driver's in the environment of scenic area and urban road[J]. Journal of Chongqing Jiaotong University (Natural Science), 2019, 38(6): 84-89. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201906015.htm [25] 中华人民共和国交通运输部. 公路隧道照明设计细则: JTG/T D70/2-01-2014[S]. 北京: 人民交通出版社, 2014.Ministry of Transport, People's Republic of China. Guidelines for design of lighting of highway tunnels: JTG/T D70/ 2-01-2014[S]. Beijing: China Communications Press, 2014. (in Chinese)