基于实车试验的小净距“隧道-互通”心理负荷量化分析

doi:10.16097/j.cnki.1009-6744.2025.06.031

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (6): 341-349.DOI: 10.16097/j.cnki.1009-6744.2025.06.031

基于实车试验的小净距“隧道-互通”心理负荷量化分析

罗霜^*a,b，陈宽^b，李善兴^b，徐进^a,b

重庆交通大学，a.智能综合立体交通重庆市重点实验室，b.交通运输学院，重庆400074

收稿日期:2025-06-10 修回日期:2025-08-17 接受日期:2025-09-29 出版日期:2025-12-25 发布日期:2025-12-24
作者简介:罗霜(1990—)，男，重庆北碚人，副教授，博士。
基金资助:
国家自然科学基金 (52302431)；重庆交通大学研究生科研创新项目 (CYS25526)。

Quantitative Analysis of Mental Workload in Closely Spaced Tunnel-Interchange Sections Based on on-road Driving Tests

LUO Shuang^*a,b, CHEN Kuan^b, LI Shanxing^b, XU Jin^a,b

a. Chongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation System; b. College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China

Received:2025-06-10 Revised:2025-08-17 Accepted:2025-09-29 Online:2025-12-25 Published:2025-12-24
Supported by:
NationalNaturalScienceFoundation of China (52302431)；Research and Innovation Program for Graduate Students in Chongqing Jiaotong University (CYS25526)。

摘要/Abstract

摘要： 为明确高速公路小净距“隧道-互通”路段下匝道驾驶人心理负荷水平，通过实车驾驶试验采集33名被试者在渝湘高速黄草互通至保家互通的心电数据，分析驾驶人心率增长率均值、心率增长率最大值、R-R间期（心电图相邻R波之间的时间间隔）标准差和连续R-R间期均方根的分布特征，以此为观测变量构建基于因子分析法的心理负荷综合量化模型，揭示小净距“隧道-互通”心理负荷水平，以及其与常规隧道、常规互通的差异，探讨隧道与互通之间的净距及驾驶人因素的影响。结果表明：4处小净距“隧道-互通”的驾驶人心理负荷分别分布在0.23~1.00、0.00~0.87、0.15~0.76和0.03~0.65，显著高于常规隧道( p<0.05)；净距在410 m及以下的3处小净距“隧道-互通”的心理负荷显著高于常规互通出口(p<0.05)；随着净距的减小，心理负荷逐渐增大，且心理负荷在两两小净距“隧道-互通”路段之间均存在显著性差异(p<0.05)；不同类型驾驶人之间心理负荷差异显著(p<0.05)，女性驾驶人心理负荷比男性高41.0%，不熟悉路线的驾驶人比熟悉型心理负荷高37.8%，非经验型驾驶人心理负荷比经验型增加59.0%。

关键词: 交通工程, 心理负荷, 实车试验, 小净距“隧道-互通”, 因子分析法

Abstract: To quantify the mental workload of drivers in closely spaced tunnel-interchange sections on diverging freeways, electrocardiogram data of 33 participants were collected through on-road driving tests along the Huangcao to Baojia Interchange section of Chongqing-Hunan Expressway. The distribution characteristics of the mean heart rate increasing rate, maximum increasing rate of heart rate, standard deviation of R-R intervals (the time intervals between adjacent R waves on the electrocardiogram) and root mean square of continuous R-R intervals of drivers were analyzed. A comprehensive quantitative model of mental workload based on factor analysis method was constructed through using these indicators as observation valuables. The mental workload level of the closely spaced tunnel-interchange section and its differences between general tunnel and interchange were revealed. The influences of clearance distance and driver factors on the mental workload were discussed. The results show that the mental workload of the four closely spaced tunnel-interchange sections ranges between 0.23~1.00, 0.00~0.87, 0.15~0.76, and 0.03~0.65 respectively, which is significantly higher than that of the general tunnel ( p<0.05). The mental workload of the closely spaced tunnel-interchange sections with clearance distance of 410 meter or less is significantly higher than that of the general interchange ( p<0.05). As the clearance distance decreases, the mental workload gradually increases. There are significant differences in mental workload between each pair of the closely spaced tunnel-interchange sections ( p<0.05). There are also significant differences in mental workload among different types of drivers ( p<0.05). The mental workload of female drivers is 41.0% higher than that of male drivers. The drivers who are not familiar with the route have a 37.8% higher mental workload than those who are familiar with it, and non-experienced drivers have a 59.0% higher mental workload than experienced drivers.

Key words: traffic engineering, mental workload, on-road driving test, closely spaced tunnel-interchange section, factor analysis

中图分类号:

U491.255

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.

LUO Shuang, CHEN Kuan, LI Shanxing, XU Jin. 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 Technology, 2025, 25(6): 341-349.

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http://www.tseit.org.cn/CN/Y2025/V25/I6/341

参考文献

[1] 罗霜,杨书群,徐进.小净距“隧道-互通”路段车辆行驶轨迹特征研究[J].交通运输系统工程与信息,2024, 24(6): 326-338. [LUO S, YANG S Q, XU J. Vehicle trajectory characteristics on tunnel-interchange section with short connection[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(6): 326-338.]

[2]CHEN Y, DU Z, XU J, et al. Driving characteristics of static obstacle avoidance by drivers in mountain highway tunnels: A lateral safety distance judgement[J]. Accident Analysis & Prevention, 2025, 210: 107845.

[3]JU Y, CHEN F, LI J, et al. Supporting driver performance in closely spaced tunnel-interchange structure: Traffic control devices and effects on driving behavior[J]. Traffic Injury Prevention, 2025, 26(2): 207-214.

[4]宋瑞华,马朝晖,佘明星,等.高速公路隧道出口至互通入口最小净距研究[J]. 深圳大学学报(理工版), 2024, 41(4): 444-452. [SONG R H, MA Z H, SHE M X, et al. Minimum clearance from highway tunnel exits to interchange entrances[J]. Journal of Shenzhen University (Science and Engineering), 2024, 41(4): 444-452.]

[5]葛洪成,郭忠印,宋灿灿,等.半地下枢纽互通匝道隧道出口与二次分流点间安全距离[J].吉林大学学报(工学版), 2025, 55(7): 2223-2232. [GE H C, GUO Z Y, SONG C C, et al. Safety distance between semi underground hub interchange ramp tunnel exit and ramp secondary diversion points[J]. Journal of Jilin University (Engineering and Technology Edition), 2025, 55(7): 2223-2232.]

[6]SHANG T, LIAN G, ZHAO Y, et al. Off-ramp vehicle mandatory lane-changing duration in small spacing section of tunnel-interchange section based on survival analysis[J]. Journal of Advanced Transportation, 2022, 2022: 9427052.

[7]陈荔,张驰,王博,等.隧道与互通出口小净距路段换道可靠性研究[J]. 中国公路学报,2022, 35(9): 51-65. [CHEN L, ZHANG C, WANG B, et al. Research of lane changing reliability on short distance section between tunnel and interchange exit[J]. China Journal of Highway and Transport, 2022, 35(9): 51-65.]

[8] 张驰,高艳阳,杨榕玮,等.基于航拍数据的互通隧道小净距路段运行速度模型[J].长安大学学报(自然科学版), 2024, 44 (2): 136-150. [ZHANG C, GAO Y Y, YANG R W, et al. Operating speed model of tunnel exit and interchange exit in short distance sections based on aerial photography data[J]. Journal of Chang'an University (Natural Science Edition), 2024, 44(2): 136 150.]

[9] 张驰,王博,杨坤,等.高速公路隧道与互通出入口小净距路段行车风险评价方法[J].安全与环境学报, 2023, 23(6): 1739-1751. [ZHANG C, WANG B, YANG K, et al. Driving risk evaluation method on the short distance section between the tunnel and interchange on freeways[J]. Journal of Safety and Environment, 2023, 23 (6): 1739-1751.]

[10] 马兆有, 方守恩,刘硕,等.毗邻互通立交特长隧道交通组织方法[J].哈尔滨工业大学学报,2021,53(3):51 57. [MA Z Y, FANG S E, LIU S, et al. Traffic organization method for super-long tunnels adjacent to interchanges[J]. Journal of Harbin Institute of Technology, 2021, 53(3): 51-57.]

[11] 白婧荣, 唐伯明,孙宗元,等.毗邻互通立交特长隧道驾驶负荷研究[J].交通运输系统工程与信息,2022,22 (1): 301-310. [BAI J R, TANG B M, SUN Z Y, et al. On driving load of super-long tunnel adjacent to interchanges [J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(1): 301-310.]

[12] 中交第一公路勘察设计研究院有限公司. JTGD202017公路路线设计规范[S].北京:人民交通出版社股份有限公司, 2017. [CCCC First Highway Consultants Co Ltd. JTG D20-2017, Design specification for highway alignment[S]. Beijing: China Communication Press, 2017.]

[13] 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.]

[14] 白婧荣,齐宏娇,毕辉云.特长隧道群出入口段驾驶员瞳孔大小变化规律[J].科学技术与工程,2022,22(4): 1601-1609. [BAI J R, QI H J, BI H Y. Variation law of pupil size of drivers at entrances and exits of extra-long tunnel groups[J]. Science Technology and Engineering, 2022, 22 (4): 1601-1609.]

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基于实车试验的小净距“隧道-互通”心理负荷量化分析

Quantitative Analysis of Mental Workload in Closely Spaced Tunnel-Interchange Sections Based on on-road Driving Tests

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