城市地下环道驾驶人生理行为特征与稳驾代偿效率评价

doi:10.16097/j.cnki.1009-6744.2026.05.032

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (5): 374-385.DOI: 10.16097/j.cnki.1009-6744.2026.05.032

城市地下环道驾驶人生理行为特征与稳驾代偿效率评价

尚婷^*1a,1b，李欢^1a，曾佳佳^1a，高彩桦^1a，张宇²

1. 重庆交通大学，a.交通运输学院；b.智能综合立体交通重庆市重点实验室，重庆400074； 2. 重庆交大交通安全科技研究院有限公司，重庆400074

收稿日期:2026-05-17 修回日期:2026-06-20 接受日期:2026-07-01 出版日期:2026-10-25 发布日期:2026-10-22
作者简介:尚婷（1983—），女，重庆人，副教授，博士。
基金资助:
教育部青年人文社会科学研究青年基金(22YJCZH143)；重庆交通大学研究生科研创新项目(2025S0037)。

Evaluation of Drivers' Physiological-Behavioral Characteristics and Stable Driving Compensation Efficiency in Urban Underground Ring Roads

SHANG Ting^*1a,1b, LI Huan^1a, ZENG Jiajia^1a, GAO Caihua^1a, ZHANG Yu²

1a. School of Traffic & Transportation, 1b. Chongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation System, Chongqing Jiaotong University, Chongqing 400074, China; 2. Chongqing Jiaotong University Traffic Safety Technology Research Institute Co Ltd, Chongqing 400074, China

Received:2026-05-17 Revised:2026-06-20 Accepted:2026-07-01 Online:2026-10-25 Published:2026-10-22
Supported by:
Youth Foundation for Humanities and Social Science Research of Ministry of Education(22YJCZH143)；hongqing Jiaotong University Postgraduate Research Innovation Project(2025S0037)。

摘要/Abstract

摘要： 为明确城市地下环道曲线场景下驾驶人生理行为响应特征及稳驾代偿效率，选取重庆市解放碑地下环道开展实车试验，采集38名驾驶人在入口段、单曲线段、连续曲线段和出口段的车辆运行与心电数据。采用因子分析、差异性检验和投入导向DEA（Data Envelopment Analysis）模型，识别不同场景下驾驶行为、心电响应、生理代偿投入与行为稳定输出的匹配效率。结果表明：不同场景下驾驶行为和心电响应均存在显著差异，行为指标的场景分化特征更明显。入口转换段表现为速度恢复、平均心率升高和心率波动增强，出口转换段表现为提前减速控制；单曲线及接入口叠加场景更容易引发速度修正和心电波动，连续曲线场景下驾驶状态相对稳定。驾驶人层面DEA结果显示，各场景平均效率集中在0.898~0.920之间，但单曲线L2场景和连续曲线L5强有效数量较少，分别为10个和12个。场景层面DEA结果显示，连续曲线及部分接入口场景达到DEA强有效，而入口转换段和车库接入口叠加单曲线场景未达到DEA有效，其中，入口转换段综合效率最低，为0.446，车库接入口叠加单曲线场景综合效率为0.896，主要表现为心电投入冗余和速度稳定输出不足。结果说明，地下环道稳驾代偿效率受曲线类型、曲线半径和接入口条件共同影响，入口转换段及车库接入口叠加单曲线场景是效率损失的主要区域。

关键词: 交通工程, 稳驾代偿效率, DEA包络分析, 地下环路

Abstract: To clarify the drivers' physiological-behavioral response characteristics and stable-driving compensation efficiency in curved scenarios of urban underground ring roads, an on-road driving experiment was conducted in the Jiefangbei Underground Ring Road in Chongqing. Vehicle operation and electrocardiographic data were collected from 38 drivers in the entrance section, single-curve sections, continuous-curve sections, and exit section. Factor analysis, difference testing, and an input-oriented DEA (Data Envelopment Analysis) model were used to identify the driving behavior, electrocardiographic responses, and the matching efficiency between physiological compensation input and behavioral stability output across different scenarios. The results show that driving behavior and electrocardiographic responses differed significantly across scenarios, and the scenario-related variations of behavioral indicators show more distinct. The entrance transition section was characterized by speed recovery, increased mean heart rate, and enhanced heart rate fluctuation, whereas the exit transition section shows anticipatory deceleration control. Single curve scenarios combined with access points were more likely to induce speed correction and electrocardiographic fluctuation, while driving states were relatively stable in continuous-curve scenarios. At the driver-level DEA evaluation, the average efficiency across scenarios ranged from 0.898 to 0.920; however, the numbers of DEA strongly efficient drivers were relatively small in the single-curve L2 scenario and the continuous-curve L5 scenario, with 10 and 12 drivers, respectively. At the scenario-level DEA evaluation, continuous- curve scenarios and some access-point scenarios reached DEA strong efficiency, whereas the entrance transition section and the single- curve scenario combined with a garage access point were not achieved DEA efficient. The entrance transition section had the lowest comprehensive efficiency, at 0.446, and the comprehensive efficiency of single-curve scenario combined with a garage access point was 0.896. These two scenarios were mainly characterized by electrocardiographic input redundancy and insufficient speed-stability output. The results indicate that stable-driving compensation efficiency in underground ring roads is jointly affected by curve type, curve radius, and access-point conditions. The entrance transition section and single-curve scenario combined with a garage access point are the main areas of efficiency loss.

Key words: traffic engineering, stable-driving compensation efficiency, DEA envelopment analysis, underground ring road

中图分类号:

U491.5

尚婷, 李欢, 曾佳佳, 高彩桦, 张宇. 城市地下环道驾驶人生理行为特征与稳驾代偿效率评价[J]. 交通运输系统工程与信息, 2026, 26(5): 374-385.

SHANG Ting, LI Huan, ZENG Jiajia, GAO Caihua, ZHANG Yu. Evaluation of Drivers' Physiological-Behavioral Characteristics and Stable Driving Compensation Efficiency in Urban Underground Ring Roads[J]. Journal of Transportation Systems Engineering and Information Technology, 2026, 26(5): 374-385.

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参考文献

[1]徐进,潘存书,符经厚,等.典型道路场景以及场景切换时的速度行为特性[J]. 吉林大学学报(工学版), 2021, 51(4): 1331-1341. [XU J, PAN C S, FU J H, et al. Speed behavior characteristic on typical driving scenarios and along switched scenarios[J]. Journal of Jilin University (Engineering and Technology Edition), 2021, 51(4): 1331-1341.]

[2]赵晓华,董文慧,李佳,等.基于驾驶行为的隧道交通标志影响特征及作用机理[J].华南理工大学学报(自然科学版), 2023, 51(4): 88-100. [ZHAO X H, DONG W H, LI J, et al. Influence characteristics and mechanism of tunnel traffic signs based on driving behavior[J]. Journal of South China University of Technology (Natural Science Edition), 2023, 51(4): 88-100.]

[3]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 L, DU Z G, HE S M, 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.]

[4]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.]

[5] RAHMAN H, AHMED M U, BARUA S, et al. Non contact-based driver's cognitive load classification using physiological and vehicular parameters[J]. Biomedical Signal Processing and Control, 2020, 55: 101634.

[6]LEE C, SHIN M, ENIYANDUNMO D, et al. Predicting driver's mental workload using physiological signals: A functional data analysis approach[J]. Applied Ergonomics, 2024, 117: 104274.

[7]罗霜, 陈宽,李善兴,等.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(5): 341-349. [LUO S, CHEN K, LI S X, et al. Quantitative analysis of mental workload in closely spaced tunnel-interchange sections based on on road driving tests[J]. Journal of Transportation Systems Engineering and Information, 2025, 25(5): 341-349.]

[8]尚婷,易爱强,何军,等.自然驾驶状态下城市地下环道驾驶人心理负荷研究[J].交通运输系统工程与信息, 2024, 24(4): 274-282. [SHANG T, YI A Q, HE J, et al. Mental workload of drivers in urban underground ring roads under naturalistic driving conditions[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(4): 274-282.]

[9] FENG Z, YANG M, KUMFER W, et al. Effect of longitudinal slope of urban underpass tunnels on drivers' heart rate and speed: A study based on a real vehicle experiment[J]. Tunnelling and Underground Space Technology incorporating Trenchless Technology Research, 2018, 81: 525-533.

[10] 刘硕, 王俊骅,张兰芳,等.城市地下道路车速特征及运行车速模型[J]. 同济大学学报(自然科学版),2015, 43(11): 1677-1683. [LIU S, WANG J H, ZHANG L F, et al. Characteristic and prediction model for operating speed model in urban underground road[J]. Journal of Tongji University (Natural Science), 2015, 43(11): 1677 1683.]

[11] 方守恩, 揭磊,刘硕,等.地下道路匝道入口段车辆运行特征[J]. 系统仿真技术,2017, 13(2): 83-89. [FANG S E, JIE L, LIU S, et al. Vehicle operation characteristics of ramp entrance in underground road[J]. System Simulation Technology, 2017, 13(2): 83-89.]

[12] 徐进, 崔强, 林伟,等.螺旋匝道和螺旋桥的小客车行驶速度特征[J]. 中国公路学报,2019, 32(7): 158-171. [XU J, CUI Q, LIN W, et al. Speed behavior of passenger cars on helical ramps and helical bridges[J]. China Journal of Highway and Transport, 2019, 32(7): 158 171.]

[13] 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.]

[14] FULLER R. Towards a general theory of driver behaviour [J]. Accident Analysis and Prevention, 2004, 37(3): 461 472.

[15] 郑展骥, 吴程宇,王振科,等.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 Z J, WU C Y, WANG Z K, et al. 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.]

城市地下环道驾驶人生理行为特征与稳驾代偿效率评价

Evaluation of Drivers' Physiological-Behavioral Characteristics and Stable Driving Compensation Efficiency in Urban Underground Ring Roads

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