城市地下道路接入口驾驶人眼动特征影响机制研究

doi:10.16097/j.cnki.1009-6744.2026.01.030

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (1): 329-339.DOI: 10.16097/j.cnki.1009-6744.2026.01.030

城市地下道路接入口驾驶人眼动特征影响机制研究

郑展骥¹，吴程宇¹，王振科¹，饶嘉强¹，凃强^*1,2，徐进¹

1. 重庆交通大学，交通运输学院，重庆400074；2.重庆市城投金卡信息产业（集团）股份有限公司，博士后科研工作站，重庆400074

收稿日期:2025-08-10 修回日期:2025-09-09 接受日期:2025-09-18 出版日期:2026-02-25 发布日期:2026-02-17
作者简介:郑展骥（1990—），男，浙江瑞安人，副教授，博士。
基金资助:
国家自然科学基金(52202407)；中国博士后科学基金面上项目(2022M710547)。

Influence Mechanism of Drivers' Eye Movement Characteristics at Access Points of Urban Underground Roads

ZHENG Zhanji¹, WU Chengyu¹, WANG Zhenke¹, RAO Jiaqiang¹, TU Qiang^*1,2, XU Jin¹

1. School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China; 2. Postdoctoral Research Station, Chongqing City Investment & Golden Card Information Industry (Group) Co Ltd, Chongqing 400074, China

Received:2025-08-10 Revised:2025-09-09 Accepted:2025-09-18 Online:2026-02-25 Published:2026-02-17
Supported by:
National Natural Science Foundation of China(52202407)；China Postdoctoral Science Foundation (2022M710547)。

摘要/Abstract

摘要： 为明确驾驶人通过城市地下道路接入口时的眼动特性，选取重庆市渝中区解放碑地下环道，利用Tobii-Glasses-2可穿戴式眼动仪，采集40名驾驶人通过8类接入口时的眼动特征，统计驾驶人瞳孔面积、眨眼频率和扫视幅度等指标，并按接入口功能与方位分类，进行DEA（DataEnvelopmentAnalysis）评价，明确影响地下道路接入口布局对驾驶行为影响的重要指标。研究结果表明：弯道接入口驾驶人瞳孔直径均值达4.401 mm，显著高于直线段（4.183mm）和相邻接入口（4.123mm）；联络道接入口视觉效率最佳，其综合效率为DEA强有效，水平扫视速度均值为261.698pixel∙s^-1，高于其他类型接入口；直线段左侧接入口瞳孔直径均值（4.213mm）高于右侧（4.078mm），且综合效率小于1；组合型接入口综合效率为DEA强有效，其眨眼频率为0.607次∙s^-1，高于接入口S（0.587次∙s^-1）和接入口C（0.591次∙s^-1），且瞳孔直径为4.123mm低于接入口C（4.401 mm）和接入口S（4.183mm）。研究结果揭示了地下道路接入口布局对驾驶行为的影响机制，可为优化城市地下道路接入口布局及提升行车安全提供更全面的理论支持。

关键词: 交通工程, 驾驶人视觉负荷, 数据包络分析, 城市地下道路接入口, 眼动指标

Abstract: To clarify the eye movement characteristics of drivers when passing through the accesses of urban underground roads, the Jiefangbei Underground Ring Road in Yuzhong District, Chongqing was selected as the research site. Tobii Glasses 2 wearable eye tracker was used to collect the eye movement data from 40 drivers when passing through 8 types of accesses. The indicators, such as the pupil area drivers', blink frequency, and saccade amplitude, were statistically analyzed, and further classified according to the function and orientation of accesses and DEA (Data Envelopment Analysis) evaluation. It identifies the key indicators which influence the layout of underground road access on driving behavior. The research results show that: the average pupil diameter of drivers at curved accesses reaches 4.401 mm, which is significantly higher than that at straight segments (4.183 mm) and adjacent accesses (4.123 mm); the visual efficiency of the connecting road accesses is the best while their comprehensive efficiency is strongly effective by DEA, and the average horizontal saccade speed is 261.698 pixel · s-¹, higher than that of other types of accesses; The average pupil diameter at left accesses of straight segments (4.213 mm) is larger than that at right accesses (4.078 mm), and the comprehensive efficiency is less than 1; the comprehensive efficiency of combined accesses is strongly effective by DEA, with a blink frequency of 0.607 blinks·s-¹, which is higher than that of Access S (0.587 blinks·s-¹) and Access C (0.591 blinks · s-¹), while the pupil diameter is 4.123 mm, which is smaller than that of Access C (4.401 mm) and Access S (4.183 mm). These results reveal the mechanism by which the layout of underground road accesses affects driving behavior, and can provide more comprehensive theoretical support for optimizing the layout of urban underground road accesses and improving driving safety.

Key words: traffic engineering, visual load of drivers', data envelopment analysis, urban underground road access, eye movement indicators

中图分类号:

U491.25

郑展骥, 吴程宇, 王振科, 饶嘉强, 凃强, 徐进. 城市地下道路接入口驾驶人眼动特征影响机制研究[J]. 交通运输系统工程与信息, 2026, 26(1): 329-339.

ZHENG Zhanji, WU Chengyu, WANG Zhenke, RAO Jiaqiang, TU Qiang, XU Jin. Influence Mechanism of Drivers' Eye Movement Characteristics at Access Points of Urban Underground Roads[J]. Journal of Transportation Systems Engineering and Information Technology, 2026, 26(1): 329-339.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: http://www.tseit.org.cn/CN/10.16097/j.cnki.1009-6744.2026.01.030

http://www.tseit.org.cn/CN/Y2026/V26/I1/329

参考文献

[1] MOGARKAR O A, GHODMARE S D. Improvement of access point on NH passing through industrial area[C]// International Conference on Recent Trends in Infrastructural Development and Sustainable Materials, Cham: Springer Nature Switzerland, 2023: 177-190.

[2]郑展骥,郑礼伟,许宇轩,等.基于实车数据的城市地下螺旋匝道小客车运行特性研究[J].中国公路学报, 2024, 37(9): 273-288. [ZHENG Z J, ZHENG L W, XU Y X, et al. Operating characteristics of urban underground helical ramp passenger cars based on field driving data [J]. China Journal of Highway and Transport, 2024, 37 (9): 273-288.]

[3]中华人民共和国住房和城乡建设部.城市地下道路工程设计规范:CJJ221-2015[S]. 北京: 中国建筑工业出版社, 2015. [Ministry of Housing and Urban-Rural Development of the People's Republic of China. Code for design of urban underground road engineering: CJJ 221-2015[S]. Beijing: China Architecture & Building Press, 2015.]

[4]尚婷,郭明洋,唐伯明,等.基于动态贝叶斯网络的地下道路行车风险评估[J].交通运输系统工程与信息,2025, 25(3): 232-245. [SHANG T, GUO M Y, TANG B M, et al. Risk assessment of underground road driving based on dynamic Bayesian networks[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(3): 232-245.]

[5]LEE Y C, LEE J D, BOYLE L N. Visual attention in driving: The effects of cognitive load and visual disruption[J]. Human Factors, 2007, 49(4): 721-733.

[6]HAN L, DU Z G, WANG S S. Assessment of drivers' visual search patterns and cognitive load during driving in curved tunnels[J]. Traffic Injury Prevention, 2025, 26(5): 524-534.

[7]孟云伟,王磊,李智鹏,等.基于因子分析与熵权法的山区双车道公路驾驶视觉负荷研究[J].交通运输系统工程与信息, 2025, 25(4): 361-372. [MENG Y W, WANG L, LI Z P, et al. Driver's visual load based on factor analysis and entropy weight methods for mountainous two-lane road[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(4): 361-372.]

[8]尚婷,胥浩,梁叶,等.基于博弈论云物元的地下环道出入口视觉负荷研究[J].交通运输系统工程与信息, 2025, 25(1): 345-354. [SHANG T, XU H, LIANG Y, et al. Visual load analysis of underground ring road junctions using game theoretic cloud object elements[J]. Journal of Transportation Systems Engineering and Information Technology, 2025, 25(1): 345-354.]

[9]NOBLE A M, MILES M, PEREZ M A, et al. Evaluating driver eye glance behavior and secondary task engagement while using driving automation systems[J]. Accident Analysis & Prevention, 2021, 151: 105959.

[10] WANG Y, BAO S, DU W, et al. Examining drivers' eye glance patterns during distracted driving: Insights from scanning randomness and glance transition matrix[J]. Journal of Safety Research, 2017, 63: 149-155.

[11] STERN J A, WALRATH L C, GOLDSTEIN R. The endogenous eyeblink[J]. Psychophysiology, 1984, 21(1): 22-33.

[12] 韩磊, 杜志刚,杨永正,等.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. [HAN L, DU Z G, YANG Y Z, et al. 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.

[13] 姜鲁青,杜志刚,麦晶.公路隧道入口区域交通标志信息量对驾驶人视觉行为影响的实证研究[J].交通信息与安全,2025, 43(2): 19-27. [JIANG L Q, DU Z G, MAI J. An empirical study on the impact of traffic sign information volume at the entrance area of highway tunnels on drivers' visual behavior[J]. Journal of Transport Information and Safety, 2025, 43(2): 19-27.]

[14] LEE Y C, LEE J D, BOYLE L N. Visual attention in driving: The effects of cognitive load and visual disruption[J]. Human Factors, 2007, 49(4): 721-733.

[15] RECARTE M A, NUNES L M. Effects of verbal and spatial-imagery tasks on eye fixations while driving[J]. Journal of Experimental Psychology: Applied, 2000, 6(1): 31.

[16] 韩磊, 杜志刚,马傲君,等.公路隧道入口区域驾驶人吸睛效应综合评价[J]. 交通运输系统工程与信息, 2024, 24(2): 313-322. [HAN L, DU Z G, MA A J, et al. Evaluation of driver's eye-catching effect in highway tunnel entrance zone[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(2): 313-322.]

[17] 朱秋晨, 吴付威,白骅,等.城市快速路中央分隔带线性空间布局形式的视觉刺激对驾驶行为的影响[J].中国公路学报,2022, 35(11): 239-251. [ZHU Q C, WU F W, BAI H, et al. Influence of visual stimuli on driving behavior in the form of linear spatial layout of urban expressway median strip[J]. China Journal of Highway and Transport, 2022, 35(11): 239-251.]

[18] RAYNER K. Eye movements and attention in reading, scene perception, and visual search[J]. The Quarterly Journal of Experimental Psychology, 2009, 62(8): 1457- 1506. [19] LOUREIRO A L D, OLIVEIRA R, MIGUÉIS V L, et al. Efficiency assessment of taxi operations using data envelopment analysis[J]. European Transport Research Review, 2025, 17(1): 9

城市地下道路接入口驾驶人眼动特征影响机制研究

Influence Mechanism of Drivers' Eye Movement Characteristics at Access Points of Urban Underground Roads

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	王福建, 马佳豪, 李廷浩, 马东方. 混合交通环境下基于动态决策间隔的强化学习信号控制方法[J]. 交通运输系统工程与信息, 2026, 26(1): 45-54.
[2]	杜太升, 彭正鍾, 张源凯, 田琼, 蒋晓桐. 考虑乘客偏好的需求响应定制公交线路优化[J]. 交通运输系统工程与信息, 2026, 26(1): 217-227.
[3]	杨洋, 陈冠华, 王明涛, 黄海博. 考虑数据平衡影响的道路交通事故建模与致因分析[J]. 交通运输系统工程与信息, 2026, 26(1): 261-269.
[4]	罗霜, 陈宽, 李善兴, 徐进. 基于实车试验的小净距“隧道-互通”心理负荷量化分析[J]. 交通运输系统工程与信息, 2025, 25(6): 341-349.
[5]	韩宝睿, 纪宇轩, 李根, 杨政, 颜荣添, 徐圣睿. 基于粘滞性车辆组团识别的道路偶发拥堵预警研究[J]. 交通运输系统工程与信息, 2025, 25(5): 91-102.
[6]	张文会, 乔梓凡, 陈德启. 出租车轨迹数据驱动的充电站选址定容方法[J]. 交通运输系统工程与信息, 2025, 25(5): 291-301.
[7]	郑立勇, 孙剑, 饶红玉, 邵健轩, 赵威, 郝勇刚. 基于物理信息深度学习的交叉口车辆轨迹补全方法[J]. 交通运输系统工程与信息, 2025, 25(4): 116-125.
[8]	荣建, 吴培佳, 高亚聪, 王益, 窦灏. 融合仿真与机器学习的交织区通行能力协同估计方法[J]. 交通运输系统工程与信息, 2025, 25(4): 206-218.
[9]	许左前, 陈海龙, 李连进, 张顶, 陈红. 道路养护作业区车辆冲突预测及关键因素判别[J]. 交通运输系统工程与信息, 2025, 25(4): 230-240.
[10]	戢晓峰, 李金, 普永明, 卢梦媛, 韩春阳. 穿村镇公路车辆跟驰冲突暴露时间生存分析[J]. 交通运输系统工程与信息, 2025, 25(4): 349-360.
[11]	孟云伟, 王磊, 李智鹏, 李斌斌, 青光焱, 刘中帅. 基于因子分析与熵权法的山区双车道公路驾驶视觉负荷研究[J]. 交通运输系统工程与信息, 2025, 25(4): 361-372.
[12]	覃文文, 彭栋梁, 戢晓峰, 徐迎豪, 李冰, 李武, 曾浩. 山区双车道公路借道超车轨迹预测模型[J]. 交通运输系统工程与信息, 2025, 25(3): 96-106.
[13]	龙科军, 寇诗雨, 邢璐, 高志波, 唐幼仪, 费怡. 考虑货车影响的匝道合流区车辆微观换道行为建模[J]. 交通运输系统工程与信息, 2025, 25(3): 117-131.
[14]	程国柱, 陈永胜, 孟凤威, 徐亮. 客货混行异质交通流下高速公路专用道车流管理方法[J]. 交通运输系统工程与信息, 2025, 25(3): 178-189.
[15]	时玉琦, 杨晓光, 马成元. 随机需求下机非车道分配与复用优化研究[J]. 交通运输系统工程与信息, 2025, 25(3): 204-214.