Volume 41 Issue 2
Apr.  2023
Turn off MathJax
Article Contents
Article Navigation >  Journal of Transport Information and Safety  > 2023  >  41(2): 50-58
PAN Fuquan, YANG Jingzhou, ZHANG Lixia, LI Weicong, YANG Xiaoxia, BING Qichun. Influence of Horizontal and Vertical Alignments of Undersea Tunnel on Driver's Visual Characteristics and Vehicle Speed[J]. Journal of Transport Information and Safety, 2023, 41(2): 50-58. doi: 10.3963/j.jssn.1674-4861.2023.02.005
Citation: PAN Fuquan, YANG Jingzhou, ZHANG Lixia, LI Weicong, YANG Xiaoxia, BING Qichun. Influence of Horizontal and Vertical Alignments of Undersea Tunnel on Driver's Visual Characteristics and Vehicle Speed[J]. Journal of Transport Information and Safety, 2023, 41(2): 50-58. doi: 10.3963/j.jssn.1674-4861.2023.02.005
shu

Influence of Horizontal and Vertical Alignments of Undersea Tunnel on Driver's Visual Characteristics and Vehicle Speed

doi: 10.3963/j.jssn.1674-4861.2023.02.005

  • School of Civil Engineering, Qingdao University of Technology, Qingdao 266520, Shandong, China

  • Received Date: 2022-09-01
    Available Online: 2023-06-19
    Abstract
  • The combination of horizontal and vertical alignments of the undersea tunnel is complex and diverse, which can easily lead to adverse reactions such as distraction and fatigue for drivers. To this end, the data of 30 drivers are collected to quantify and analyze the effect of the cross-harbor tunnel flat and longitudinal alignment on drivers' visual characteristics and vehicle speed. The Facelab eye tracker, GPS X10 vehicle-mounted inclinometer, tachograph, and other equipment are used to collect the drivers' blink frequency, percentage of eye closure over the pupil per unit time (PERCLOS), tunnel slope, vehicle speed, and other data. The correlation and significance between the slope and curvature of the undersea tunnel and the drivers' blink frequency, PERCLOS, and vehicle speed are analyzed using partial correlation analysis. Then, Ploy 2D nonlinear surface fitting is used to establish mathematical models of blink frequency, PERCLOS, and vehicle speed with slope curvature. The relationship between blink frequency, PERCLOS, vehicle speed, and the horizontal and vertical alignments of the undersea tunnel is quantitatively analyzed, thus reflecting the influence of different combinations of horizontal and vertical alignments of the undersea tunnel on the driver's mental state and driving condition. Study results indicate that: Under the combination of a slope of 1.3% and the radius of the circular curve of 4 348 m, the drivers' blink frequency is highest, and their mental state is most relaxed. The driver's tension will be increased by appropriately increasing the positive slope and decreasing the curvature radius. Under the combination of a slope of 3.05% and the radius of the circular curve of 3 521 m, the drivers' PERCLOS is the largest and the fatigue degree is the highest. By appropriately increasing the negative slope and reducing the curvature radius the driver's tension will be relieved. Under the combination of a slope of 1.78% and the radius of the circular curve of 2 433 m, the vehicle speed is found to be the highest. The vehicle's speed will be reduced by appropriately increasing the positive slope and curvature radius. The constructed visual characteristics and speed model can reflect the changes in the driver's mental state and driving condition with the changes in horizontal and vertical alignments, which shall provide theoretical support for the horizontal and vertical alignments' safe design and operation management of the undersea tunnel.

     

    • FullText(HTML)
  • loading
    • References(24)
  • [1]
    张顶立. 隧道及地下工程的基本问题及其研究进展[J]. 力学学报, 2017, 49(1): 3-21. https://www.cnki.com.cn/Article/CJFDTOTAL-LXXB201701002.htm

    ZHANG D L. Essential issues and their research progress in tunnel and underground engineering[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(1): 3-21. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-LXXB201701002.htm
    [2]
    潘福全, 泮海涛, 王铮, 等. 照度与纵坡耦合作用下海底隧道出入口段驾驶人视觉特征分析与建模[J]. 交通运输系统工程与信息, 2021, 21(1): 142-148. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202101023.htm

    PAN F Q, PAN H T, WANG Z, et al. Analysis and modeling of drivers' visual characteristicsat entrance and exit of undersea tunnel withcoupling of illuminance and longitudinal slope[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(1): 142-148. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202101023.htm
    [3]
    REN Y, LI X, ZHENG X, et al. Analysis of drivers'eye-movement characteristics when driving around curves[J]. Discrete Dynamics in Nature and Society, 2015, 2015(1): 1-10.
    [4]
    YU H, WANG F, REN Y, et al. Gaze characteristics of drivers in curved sections[C]. 19th COTA International Conference of Transportation, Nanjing, China: COTA, 2019.
    [5]
    WANG S, DU Z, JIAO F, et al. Impact of urban undersea tunnel longitudinal slope on the visual characteristics of drivers[J]. Journal of Advanced Transportation, 2020(7): 1-11.
    [6]
    JIAO F, DU Z, WANG S, et al. Research on drivers' visual characteristics in different curvatures and turning conditions of the extra-long urban underwater tunnels[J]. Tunnelling and Underground Space Technology, 2020, 99(5): 103360.
    [7]
    SHAO X, CHEN F, MA X, et al. The impact of lighting and longitudinal slope on driver behaviour in underwater tunnels: A simulator study[J]. Tunnelling and Underground Space Technology, 2022, 122(4): 104367.
    [8]
    李显生, 李明明, 任有, 等. 城市不同道路线形下的驾驶人注视特性[J]. 吉林大学学报(工学版), 2016, 46(5): 1447-1452. https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201605010.htm

    LI X S, LI M M, REN Y, et al. Driver's fixation characteristics in different urban road alignments[J]. Journal of Jilin University(Engineering and Technology Edition), 2016, 46(5): 1447-1452. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JLGY201605010.htm
    [9]
    高建平, 窦浩然, 何云勇, 等. 基于驾驶员人因的高速公路长大连续下坡路段线形组合设计方法[J]. 公路, 2021, 66(11): 7-13. doi: 10.12361/2661-3514-03-11-07

    GAO J P, DOU H R, HE Y Y, et al. Research on the alignment combination method of long downhill section in mountainous express based on driver's human factor[J]. Highway, 2021, 66(11): 7-13. (in Chinese) doi: 10.12361/2661-3514-03-11-07
    [10]
    SCOTT C H, ERIC T D. Speed prediction models for multilane highway: Simu-ltaneous equations approach[J]. Journal of Transportation Engineering, 2010, 136 (10) : 856-862.
    [11]
    HASHIM I H, ABDEL T A, MOUSTAFA Y. Toward an operating speed profile model for rural two-lane roads in Egypt[J]. Journal of Traffic & Transportation Engineering, 2016, 3(1): 82-88.
    [12]
    BOROUJERDIAN A M, SEYEDABRISHAMI E, AKBARPOUR H. Analysis of geometric design impacts on vehicle operating speed on two-lane rural roads[J]. Procedia Engineering, 2016, 161(3): 1144-1151.
    [13]
    吴艳霞, 刘剑, 黄帅, 等. 雨天高速公路纵坡对驾驶员心率及行车速度影响[J]. 交通信息与安全, 2021, 39(4): 35-42. doi: 10.3963/j.jssn.1674-4861.2021.04.005

    WU Y X, LIU J, HUANG S, et al. Influences of longitudinal slopes of highways on drivers' heart rate and driving speeds on rainy days [J]. Journal of Transport Information and Safety, 2021, 39(4): 35-42. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2021.04.005
    [14]
    徐进, 邵毅明, 赵军, 等. 山区道路弯坡组合路段重载车辆行驶速度模型[J]. 长安大学学报(自然科学版), 2015, 35(2): 67-74. https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201502012.htm

    XU J, SHAO Y M, ZHAO J, et al. Speed perdition model of heavy truck driving on curved segment with a slope of mountains highway[J]. Journal of Chang'an University(Natural Science Edition), 2015, 35(2): 67-74. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201502012.htm
    [15]
    赵晓华, 鞠云杰, 李佳, 等. 基于驾驶行为和视觉特性的长大隧道突起路标作用效果评估[J]. 中国公路学报, 2020, 33(6): 29-41. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202006004.htm

    ZHAO X H, JU Y J, LI J, et al. Evaluation of the effect of RPMs in extra-long tunnels based on driving behavior and visual characteristics[J]. China Journal of Highway and Transport, 2020, 33(6): 29-41. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202006004.htm
    [16]
    王首硕, 杜志刚, 冯守中, 等. 高速公路隧道入口区域视线诱导系统有效性研究[J]. 交通运输工程学报, 2021, 21(2): 267-277. https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202102026.htm

    WANG S S, DU Z G, FENG S Z, et al. Research on effectiveness of visual guiding system in entrance zone of freeway tunnel[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 267-277. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JYGC202102026.htm
    [17]
    徐萌, 潘晓东, 陈丰, 等. 彩色灯光视觉调节对长隧道驾驶催眠缓解作用的试验[J]. 中国公路学报, 2020, 33(11): 235-244. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202011022.htm

    XU M, PAN X D, CHEN F, et al. Experimental study on the effect of color light vision regulation on hypnotic relief of long tunnel driving[J]. China Journal of Highway and Transport, 2020, 33(11): 235-244. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202011022.htm
    [18]
    潘福全, 李炜聪, 闫仕源, 等. 信号交叉口处公交车驾驶员视觉特性分析[J]. 交通科技与经济, 2021, 23(5): 30-37. https://www.cnki.com.cn/Article/CJFDTOTAL-KJJJ202105005.htm

    PAN F Q, LI W C, YAN S Y, et al. Visual characteristics analysis of bus drivers at signalized intersections[J]. Technology & Economy in Areas of Communications, 2021, 23(5): 30-37. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KJJJ202105005.htm
    [19]
    王鹏, 神和龙, 尹勇, 等. 基于深度学习的船舶驾驶员疲劳检测算法[J]. 交通信息与安全, 2022, 40(1): 63-71. doi: 10.3963/j.jssn.1674-4861.2022.01.008

    WANG P, SHEN H L, YIN Y. A detection algorithm for the fatigue of ship officers based on deep learning technique[J]. Journal of Transport Information and Safety, 2022, 40(1): 63-71. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2022.01.008
    [20]
    严凡. 基于云模型的驾驶疲劳检测方法[J]. 交通科技与经济, 2019, 21(3): 15-18. https://www.cnki.com.cn/Article/CJFDTOTAL-KJJJ201903004.htm

    YAN F. Driving fatigue detection method based on cloud model[J]. Technology & Economy in Areas of Communications, 2019, 21(3): 15-18. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KJJJ201903004.htm
    [21]
    刘明周, 蒋倩男, 扈静. 基于面部几何特征及手部运动特征的驾驶员疲劳检测[J]. 机械工程学报, 2019, 55(2): 18-26. https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201902003.htm

    LIU M Z, JIANG Q N, HU J. Based on facial geometric features and hand motion characteristics driver fatigue detection[J]. Journal of Mechanical Engineering, 2019, 55(2): 18-26. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB201902003.htm
    [22]
    SUGIYANTO G, MALKHAMAH S. Determining the maximum speed limit in urban road to increase traffic safety[J]. Journal Teknologi, 2018, 80(5): 67-77.
    [23]
    刘拥华, 姚逸豪, 孙静怡, 等. 基于实际速度运行特征的山区高速公路交通安全性分析[J]. 昆明理工大学学报(自然科学版), 2021, 46(6): 125-131, 143. https://www.cnki.com.cn/Article/CJFDTOTAL-KMLG202106015.htm

    LIU Y H, YAO Y H, SUN J Y, et al. Analysis of the traffic safety of mountain expressway based on the actual speed operation characteristics[J]. Journal of Kunming University of Science and Technology(Natural Sciences), 2021, 46(6): 125-131, 143. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KMLG202106015.htm
    [24]
    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.htm

    JIAO F T, DU Z G, WANG S S, et al. Visual characteristics 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
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(9)  / Tables(6)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (863) PDF downloads(29) Cited by()
    Proportional views
    Related

    Copyright Editorial Office of Transport Information and Safety鄂ICP备05003336号-2

    Address：No. 1178，Heping Avenue, Wuchang, Wuhan, CHINA (430063)

    Tel：027-86580355 Email：jtjsj@vip.163.com

    Supported by: Beijing Renhe Information Technology Co. Ltd  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return