基于自然驾驶试验的公路螺旋隧道驾驶人心理旋转效应分析

doi:10.19721/j.cnki.1001-7372.2025.03.011

PDF全文下载(7769 KB)

中国公路学报 ›› 2025, Vol. 38 ›› Issue (3) : 150-164. DOI: 10.19721/j.cnki.1001-7372.2025.03.011

道路交通安全专栏

基于自然驾驶试验的公路螺旋隧道驾驶人心理旋转效应分析

韩磊¹, 杜志刚², 杨永正², 梅家林², 贺世明²

作者信息 +

Analysis of Mental Rotation Effects on Drivers in Highway Spiral Tunnels Based on a Naturalistic Driving Experiment

HAN Lei¹, DU Zhi-gang², YANG Yong-zheng², MEI Jia-lin², HE Shi-ming²

Author information +

文章历史 +

摘要

为探究公路螺旋隧道行车时驾驶人的心理旋转效应，招募了30名被试开展自然驾驶试验，采集驾驶人在曲线隧道和螺旋隧道行车时的视觉特性数据和心电特性数据，构建因子模型选取驾驶人心理旋转效应的敏感评价指标，对比驾驶人的主观负荷强度和弯坡错觉程度，并构建数据包络分析模型(DEA)，识别和探究公路螺旋隧道行车环境对驾驶人心理旋转效应的影响特征。结果表明：驾驶人心理旋转效应的敏感视觉特性指标为注视持续时间、瞳孔直径、扫视持续时间和扫视幅度，敏感心电特性指标为HR、SDNN、LF/HF和SampEn；曲线隧道与螺旋隧道条件下驾驶人视觉和心电表现存在显著差异，相较于曲线隧道，驾驶人在螺旋隧道行车时表现出更大的注视持续时间、瞳孔直径、扫视持续时间和更小的扫视幅度，以及更大的HR、LF/HF和更小的SDNN、SampEn；驾驶人在螺旋隧道行车时的视觉注意水平更高、视认反应时间更长，信息感知和处理难度更大、心理努力程度更大、视觉搜索效率下降，辨识能力减弱，同时更容易引起紧张和焦虑，从而导致自主神经调节能力减弱、心率变异性降低；此外，驾驶人主观评价结果显示，螺旋隧道行车时的弯坡错觉程度和主观心理负荷程度均大于曲线隧道；基于DEA的综合评价显示，曲线隧道在技术效益、规模效益和综合效益方面均优于螺旋隧道，这表明螺旋隧道行车环境对驾驶人视觉和心理绩效有损害，需要采取措施加以改善。

Abstract

To investigate mental rotation effects on drivers navigating a highway spiral tunnel, a naturalistic driving study was conducted with 30 participants. Visual and electrocardiographic (ECG) data were collected from drivers traversing curved and spiral tunnels. A factor model was constructed to identify the sensitive indicators of the drivers' mental rotation effects. Subjective workload intensity and curvature-slope illusion severity were compared, and a data envelopment analysis (DEA) model was established to identify and investigate the characteristic impacts of the driving environment in a highway spiral tunnel on the drivers' mental rotation effects. The results revealed that the sensitive visual indicators of the drivers' mental rotation effects included fixation duration, pupil diameter, saccade duration, and saccade amplitude. Sensitive ECG indicators included the HR, SDNN, LF/HF, and SampEn. Significant differences in visual and ECG performance were observed between curved and spiral tunnels. Drivers in a spiral tunnel exhibit longer fixation durations, larger pupil diameters, longer saccade durations, smaller saccade amplitudes, higher HR, higher LF/HF ratios, lower SDNN, and lower SampEn values than do those in a curved tunnel. Moreover, drivers in spiral tunnels demonstrate increased visual attention levels, longer recognition response times, greater difficulty in information perception and processing, increased mental effort, decreased visual search efficiency, and weakened discrimination abilities. In addition, they are more prone to feelings of tension and anxiety, which leads to decreased autonomic nervous system regulation and reduced heart rate variability. Furthermore, subjective evaluations by the drivers indicate that the curvature slope illusion severity and subjective psychological workload are greater in the spiral tunnel than in the curved tunnel. A comprehensive evaluation based on DEA reveals that the curved tunnel outperforms the spiral tunnel in terms of technical, scale, and overall benefits. These results suggest that the driving environment in a spiral tunnel adversely affects the visual and psychological performance of drivers and thus necessitates the implementation of improvement measures.

导出引用

韩磊, 杜志刚, 杨永正, 梅家林, 贺世明. 基于自然驾驶试验的公路螺旋隧道驾驶人心理旋转效应分析[J]. 中国公路学报, 2025, 38(3): 150-164 https://doi.org/10.19721/j.cnki.1001-7372.2025.03.011

HAN Lei, DU Zhi-gang, YANG Yong-zheng, MEI Jia-lin, HE Shi-ming. Analysis of Mental Rotation Effects on Drivers in Highway Spiral Tunnels Based on a Naturalistic Driving Experiment[J]. China Journal of Highway and Transport, 2025, 38(3): 150-164 https://doi.org/10.19721/j.cnki.1001-7372.2025.03.011

中图分类号： U491

参考文献

[1] 宋中强.坡度与曲率对在建螺旋隧道内污染物扩散特性的影响研究[D].重庆:重庆大学,2019. SONG Zhong-qiang. Study on the influence of slope and curvature on the diffusion characteristics of pollutants in a spiral tunnel Under construction [D]. Chongqing: Chongqing University, 2019.
[2] HAN L, DU Z G, ZHENG H R, et al. Reviews and prospects of human factors research on curve driving [J]. Journal of Traffic and Transportation Engineering (English Edition), 2023, 10 (5): 808-834.
[3] PERVEZ A, HUANG H L, HAN C Y, et al. Revisiting freeway single tunnel crash characteristics analysis: A six-zone analytic approach [J]. Accident Analysis & Prevention, 2020, 142: 105542.
[4] 马壮林,张祎祎,杨杨,等.公路隧道交通事故严重程度预测模型研究[J].中国安全科学学报,2015,25(5):75-79. MA Zhuang-lin, ZHANG Yi-yi, YANG Yang, et al. Research on models for predicting severity of traffic accident in highway tunnel [J]. China Safety Science Journal, 2015, 25 (5): 75-79.
[5] CALIENDO C, DE GUGLIELMO M L, GUIDA M. Comparison and analysis of road tunnel traffic accident frequencies and rates using random-parameter models [J]. Journal of Transportation Safety & Security, 2016, 8 (2): 177-195.
[6] KIRCHER K, AHLSTROM C. The impact of tunnel design and lighting on the performance of attentive and visually distracted drivers [J]. Accident Analysis & Prevention, 2012, 47: 153-161.
[7] 阎莹,叶飞,王晓飞,等.隧道群路段环境光照度与驾驶人瞳孔面积分析[J].华南理工大学学报(自然科学版),2016,44(12):89-96. YAN Ying, YE Fei, WANG Xiao-fei, et al. Analysis of ambient illumination and driver's pupil area in tunnel group [J].Journal of South China University of Technology (Natural Science Edition), 2016, 44 (12): 89-96.
[8] 万红亮,杜志刚,冯超,等.基于视错觉的公路隧道中部安全控速方法[J].交通信息与安全,2014,32(5):146-153. WAN Hong-liang, DU Zhi-gang, FENG Chao, et al. Approaches for vehicle speed control based on visual illusion in highway tunnel [J]. Journal of Transport Information and Safety, 2014, 32 (5): 146-153.
[9] 梅家林,汤振农,杜志刚,等.高速公路隧道入口区域交通工程设施改善对策与应用[J].隧道建设(中英文),2020,40(4):545-551. MEI Jia-lin, TANG Zhen-nong, DU Zhi-gang, et al. Improvement countermeasures and application of traffic engineering facilities at entrance section of expressway tunnel [J]. Tunnel Construction, 2020, 40 (4): 545-551.
[10] XU X L, KANG X J, WANG X P, et al. Research on spiral tunnel exit speed prediction model based on driver characteristics [J]. Sustainability, 2022, 14 (23): 15736.
[11] HAN L, DU Z G, WANG S S, et al. The effects of tunnel radius, turn direction, and zone characteristics on drivers' visual performance [J]. Tunnelling and Underground Space Technology, 2024, 152: 105912.
[12] XING G Y, MA Y F, CHEN S Y, et al. The effects of radius and longitudinal slope of extra-long freeway spiral tunnels on driving behavior: A practical engineering design case [J]. Tunnelling and Underground Space Technology, 2024, 152: 105967.
[13] 刘贤鹏,闫尉深,刘畅,等.基于交叉熵权可拓模型的公路螺旋隧道运营风险评估研究[J].公路,2022,67(7):280-288. LlU Xian-peng, YAN Wei-shen, LIU Chang, et al. Research on operation risk assessment of highway spiral tunnel based on cross-entropy extension model [J]. Highway, 2022, 67 (7): 280-288.
[14] 王鼎媛,乔梅梅,盛刚.面向驾驶员视觉的公路螺旋形隧道LED照明光源指标研究[J].公路交通科技,2022,39(9):125-131. WANG Ding-yuan, QIAO Mei-mei, SHENG Gang. Study on LED lighting source indicators of road spiral tunnels for driver's vision [J]. Journal of Highway and Transportation Research and Development, 2022, 39 (9): 125-131.
[15] 李峰伟.山区高速公路螺旋展线隧道圆曲线半径分析[J].交通科技, 2017,(6):75-78. LI Feng-wei. Study on minimum tunnel radius of helix line development in mountain highway [J]. Transportation Science & Technology, 2017 (6): 75-78.
[16] 赵帅.双螺旋隧道驾驶负荷研究[D].石家庄:石家庄铁道大学,2023. ZHAO Shuai. Research on the driving load of spiral tunnels [D]. Shijiazhuang: Shijiazhuang Tiedao University, 2023.
[17] 赖金星,张鹏,周慧,等.高速公路隧道交通事故规律研究[J].隧道建设(中英文),2017,37(1):37-42. LAI Jin-xing, ZHANG Peng, ZHOU Hui, et al. Study of rules of traffic accidents in expressway tunnels [J]. Tunnel Construction, 2017, 37 (1): 37-42.
[18] 赵华祥,杜飞翔,付开华,等.山区公路小半径弯道路段事故严重度影响因素及其异质性比较分析[J].交通信息与安全,2022,40(3):42-50. ZHAO Hua-xiang, DU Fei-xiang, FU Kai-hua, et al. A comparative analysis of heterogeneous effects of various factors on accident severity at sharp curve sections of mountainous highway [J]. Journal of Transport Information and Safety, 2022, 40 (3): 42-50.
[19] 郑号染,杜志刚,王首硕,等.基于线性诱导的高速公路隧道交通安全优化设计[J].中国安全科学学报,2023,33(8):134-141. ZHENG Hao-ran, DU Zhi-gang, WANG Shou-shuo, et al. Design of traffic safety optimization for expressway tunnel based on linear guidance [J]. China Safety Science Journal, 2023, 33 (8): 134-141.
[20] 杜志刚,梅家林,倪玉丹,等.城市水下道路隧道驾驶安全影响因素分析和改善思路[J].隧道建设(中英文),2020,40(11):1558-1569. DU Zhi-gang, MEI Jia-lin, NI Yu-dan, et al. Analysis of influencing factors and improve ideas for driving safety in urban road underwater road tunnels [J]. Tunnel Construction, 2020, 40 (11): 1558-1569.
[21] 薛继国.基于眼动和脑电的心理旋转认知机制研究[D].北京:中国人民解放军军事医学科学院,2017. XUE Ji-guo. The cognitive mechanism of mental rotation: An eye movement and EEG study [D]. Beijing: The PLA Academy of Military Medical Sciences, 2017.
[22] PAVLOVIC N J, KEILLOR J, HOLLANDS J G, et al. Reference frame congruency in search-and-rescue tasks [J]. Human Factors, 2009, 51 (2): 240-250.
[23] WICKENS C D, KELLER J W, SMALL R L. Left. No, Right! Development of the frame of reference transformation tool (FORT) [C] //SAGE. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. Los Angeles: SAGE Publications, 2010, 54 (13): 1022-1026.
[24] 陈鑫,杜志刚,王首硕,等.五路环形交叉口导向系统改善方法研究[J].武汉理工大学学报(交通科学与工程版),2018,42(4):554-558，563. CHEN Xin, DU Zhi-gang, WANG Shou-shuo, et al. Study on improvement method of guidance system for five-way roundabout [J]. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2018, 42 (4): 554-558, 563.
[25] 郭孜政,刘仙,陈瑞雅,等.疲劳影响驾驶员心理旋转能力的ERP试验研究[J].中国安全科学学报,2017,27(10):7-12. GUO Zi-zheng, LIU Xian, CHEN Rui-ya, et al. ERP-based study on influence of fatigue on drivers' mental rotation ability [J]. China Safety Science Journal, 2017, 27 (10): 7-12.
[26] 杜志刚,柳青云,朱新建,等.基于心理旋转效应的双向立交环形交叉口导向系统[J].武汉理工大学学报(交通科学与工程版),2017,41(3):411-414. DU Zhi-gang, LIU Qing-yun, ZHU Xin-jian, et al. A bi-directional roundabout guidance system based on psychological rotation effect [J]. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2017, 41 (3): 411-414.
[27] 杜志刚,韩磊,梅家林,等.基于心理旋转效应的小半径公路长隧道视觉环境优化研究框架[J].同济大学学报(自然科学版),2023,51(9):1372-1382. DU Zhi-gang, HAN Lei, MEI Jia-lin, et al. Research framework for visual environment optimization of small radius highway long tunnels based on psychological rotation effect [J]. Journal of Tongji University (Natural Science), 2023, 51 (9): 1372-1382.
[28] 马勇,付锐.驾驶人视觉特性与行车安全研究进展[J].中国公路学报,2015,28(6):82-94. MA Yong, FU Rui. Research and development of drivers visual behavior and driving safety [J]. China Journal of Highway and Transport, 2015, 28 (6): 82-94.
[29] 韩磊,杜志刚,贺世明,等.基于因子分析和数据包络分析的公路隧道入口区域吸睛效应评价[J].交通运输工程学报,2024,24(6):286-298. HAN Lei, DU Zhi-gang, HE Shi-ming, et al. Evaluation of eye-catching effect of highway tunnel entrance zones based on factor analysis and data envelopment analysis [J]. Journal of Traffic and Transportation Engineering, 2024, 24 (6): 286-298.
[30] MANE A, DJORDJEVIC B, GHOSH B. A data-driven framework for incentivising fuel-efficient driving behaviour in heavy-duty vehicles [J]. Transportation Research Part D: Transport and Environment, 2021, 95: 102845.
[31] EZZATI AMINI R, AL HADDAD C, BATABYAL D, et al. Driver distraction and in-vehicle interventions: A driving simulator study on visual attention and driving performance [J]. Accident Analysis & Prevention, 2023, 191: 107195.
[32] KERAUTRET L, DABIC S, NAVARRO J. Exploration of driver stress when resuming control from highly automated driving in an emergency situation [J]. Transportation Research Part F: Traffic Psychology and behaviour, 2023, 93: 222-234.
[33] LU K, SJÖRS DAHLMAN A, KARLSSON J, et al. Detecting driver fatigue using heart rate variability: A systematic review [J]. Accident Analysis & Prevention, 2022, 178: 106830.
[34] MILLER E E, BOYLE L N. Driver behavior in road tunnels: Association with driver stress and performance [J]. Transportation Research Record, 2015, 2518 (1): 60-67.
[35] 陶达,黄玉勇,吴玉卓,等.长时驾驶任务中脑力负荷多维特征变化趋势研究[J].中国公路学报,2023,36(11):456-464. TAO Da, HUANG Yu-yong, WU Yu-zhuo, et al. Changing mechanism of mental workload multidimensional characteristics during long-term driving tasks [J]. China Journal of Highway and Transport, 2023, 36 (11): 456-464.
[36] LI G, CHUNG W Y. Detection of driver drowsiness using wavelet analysis of heart rate variability and a support vector machine classifier [J]. Sensors, 2013, 13 (12): 16494-16511.
[37] WANG F W, WANG H, FU R R. Real-time ECG-based detection of fatigue driving using sample entropy [J]. Entropy, 2018, 20 (3): 196.
[38] ZHANG T, CHEN J C, HE E Q, et al. Sample-entropy-based method for real driving fatigue detection with multichannel electroencephalogram [J]. Applied Sciences, 2021, 11 (21): 10279.

基金

国家自然科学基金项目(52072291)

National Natural Science Foundation of China (52072291)

PDF全文下载(7769 KB)

Accesses

Citation

Detail

段落导航

摘要
Abstract
关键词
Key words
引用本文
参考文献
基金

收稿日期	出版日期
2024-08-15	2025-03-31
发布日期
2025-03-31

选择文件类型/文献管理软件名称

选择包含的内容

摘要

Abstract

关键词

Key words

引用本文

{{custom_sec.title}}

{{custom_sec.title}}

参考文献

{{custom_fnGroup.title_cn}}

脚注

基金

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

摘要

Abstract

关键词

Key words

引用本文

{{custom_sec.title}}

{{custom_sec.title}}

参考文献

{{custom_fnGroup.title_cn}}

脚注

基金