Volume 21 Issue 2
Aug.  2021
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2021  >  21(2): 209-221
YAO Rong-han, QI Wen-yan, GUO Wei-wei. Structural equation model of drivers' takeover behaviors in autonomous driving environment[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 209-221. doi: 10.19818/j.cnki.1671-1637.2021.02.018
Citation: YAO Rong-han, QI Wen-yan, GUO Wei-wei. Structural equation model of drivers' takeover behaviors in autonomous driving environment[J]. Journal of Traffic and Transportation Engineering, 2021, 21(2): 209-221. doi: 10.19818/j.cnki.1671-1637.2021.02.018
shu

Structural equation model of drivers' takeover behaviors in autonomous driving environment

doi: 10.19818/j.cnki.1671-1637.2021.02.018
  • 1.

    School of Transportation and Logistics, Dalian University of Technology, Dalian 116024, Liaoning, China

  • 2.

    Beijing Key Laboratory of Urban Road Traffic Intelligent Control Technology, North China University of Technology, Beijing 100144, China

Funds:

National Natural Science Foundation of China 51578111

Fundamental Research Funds for the Central Universities DUT20JC40

More Information
  • Author Bio:

    YAO Rong-han(1979-), female, associate professor, PhD, cyanyrh@dlut.edu.cn

  • Received Date: 2020-11-30
  • Publish Date: 2021-04-01
    Abstract
  • Tests were conducted to explore the key factors that influence drivers' takeover behaviors in an autonomous driving environment using a driving simulator and an eye movement instrument. Data were collected from 11 participants who responded to 5 takeover scenarios, including vehicle and eye movement data, and the participants' personal attributes were investigated. According to the results of measured data processed by qualitative analysis and situational difference processed by quantitative analysis, a structural equation model was established using AMOS to describe drivers' takeover behaviors. The longitudinal takeover behavior, lateral takeover behavior, and eye movement behavior were the three potential variables. Nine observed variables were identified to represent the three potential variables. Based on the modification indices, the final structural equation model was obtained using multiple amendments. Thus, the relationships between all the variables and the corresponding parameters were obtained to describe the drivers' takeover behaviors. Research results show that the entire process in which a driver takes over an autonomous driving vehicle can be divided into 5 stages, including perception and reaction, deceleration and avoidance, acceleration and ascending, stable recovery, and stable movement. The drivers' takeover risk is higher when a left-front vehicle merges into the current lane. The lateral driving behavior is negatively correlated with the longitudinal driving or eye movement behavior, with correlation coefficients of -0.226 and -0.223, respectively. The longitudinal driving behavior is positively correlated with the eye movement behavior, with a correlation coefficient of 0.152. Average speed, mean of the overall yaw angle, and saccade time in a second can interpret the potential longitudinal, lateral, and eye behaviors, respectively, when drivers takeover autonomous driving vehicles. Therefore, the research can reveal drivers' overall and local behaviors when they takeover autonomous driving vehicles, and can help improve the human-computer interaction mode and takeover request hints in autonomous driving. 10 tabs, 7 figs, 30 refs.

     

    • FullText(HTML)
  • loading
    • References(30)
  • [1]
    SAE International. Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles[R]. New York: SAE International, 2018.
    [2]
    LU Zhen-ji, HAPPER R, CABRALL C D D, et al. Human factors of transitions in automated driving: a general framework and literature survey[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2016, 43: 183-198. doi: 10.1016/j.trf.2016.10.007
    [3]
    吴超仲, 吴浩然, 吕能超. 人机共驾智能汽车的控制权切换与安全性综述[J]. 交通运输工程学报, 2018, 18(6): 131-141. doi: 10.3969/j.issn.1671-1637.2018.06.014

    WU Chao-zhong, WU Hao-ran, LYU Neng-chao. Review of control switch and safety of human-computer driving intelligent vehicle[J]. Journal of Traffic and Transportation Engineering, 2018, 18(6): 131-141. (in Chinese) doi: 10.3969/j.issn.1671-1637.2018.06.014
    [4]
    ERIKSSON A, BANKS V A, STANTON N A. Transition to manual: comparing simulator with on-road control transitions[J]. Accident Analysis and Prevention, 2017, 102: 227-234. doi: 10.1016/j.aap.2017.03.011
    [5]
    GOLD C, DAMBÖCK D, LORENZ L, et al. "Take over!" How long does it take to get the driver back into the loop?[C]// HFES. Proceedings of the Human Factors and Ergonomics Society Annual Meeting. New York: SAGE Publications, 2013: 1938-1942.
    [6]
    FORSTER Y, NAUJOKS F, NEUKUM A, et al. Driver compliance to take-over requests with different auditory outputs in conditional automation[J]. Accident Analysis and Prevention, 2017, 109: 18-28. doi: 10.1016/j.aap.2017.09.019
    [7]
    张泽权. 自动驾驶接管中的触觉显示系统设计研究[D]. 广州: 华南理工大学, 2019.

    ZHANG Ze-quan. Study on the vibrotactile displays system of take-over requests for automated driving[D]. Guangzhou: South China University of Technology, 2019. (in Chinese)
    [8]
    YOON S H, KIM Y W, JI Y G. The effects of takeover request modalities on highly automated car control transitions[J]. Accident Analysis and Prevention, 2019, 123: 150-158. doi: 10.1016/j.aap.2018.11.018
    [9]
    钮建伟, 张雪梅, 孙一品, 等. 险情中驾驶人接管自动驾驶车辆的驾驶行为研究[J]. 中国公路学报, 2018, 31(6): 272-280. doi: 10.3969/j.issn.1001-7372.2018.06.014

    NIU Jian-wei, ZHANG Xue-mei, SUN Yi-pin, et al. Analysis of driving behavior during the takeover of automatic driving vehicles in dangerous traffic situations[J]. China Journal of Highway and Transport, 2018, 31(6): 272-280. (in Chinese) doi: 10.3969/j.issn.1001-7372.2018.06.014
    [10]
    WAN Jing-yan, WU Chang-xu. The effects of lead time of take-over request and nondriving tasks on taking-over control of automated vehicles[J]. IEEE Transactions on Human-Machine Systems, 2018, 48(6): 582-591. doi: 10.1109/THMS.2018.2844251
    [11]
    KIM J, KIM H S, KIM W, et al. Take-over performance analysis depending on the drivers' non-driving secondary tasks in automated vehicles[C]//IEEE. 9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence. New York: IEEE, 2018: 1364-1366.
    [12]
    WANDTNER B, SCHMIDT G, SCHOEMIG N, et al. Non-driving related tasks in highly automated driving-effects of task modalities and cognitive workload on take-over performance[C]//Automotive Meets Electronics. 9th GMM Symposium Automotive meets Electronics. New York: VDE Verlag GmbH, 2018: 1-6.
    [13]
    ERIKSSON A, PETERMEIJER S M, ZIMMERMANN M, et al. Rolling out the red (and green) carpet: supporting driver decision making in automation-to-manual transitions[J]. IEEE Transactions on Human-Machine Systems, 2018, 49(1): 20-31. http://ieeexplore.ieee.org/document/8594655/
    [14]
    WANG Jiao, SÖFFKER D. Bridging gaps among human, assisted, and automated driving with DVIs: a conceptional experimental study[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(6): 2096-2108. http://ieeexplore.ieee.org/document/8428654/
    [15]
    KÖRBER M, GOLD C, LECHNER D, et al. The influence of age on the take-over of vehicle control in highly automated driving[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2016, 39: 19-32. doi: 10.1016/j.trf.2016.03.002
    [16]
    GOLD C, KÖRBER M, HOHENBERGER C, et al. Trust in automation-before and after the experience of take-over scenarios in a highly automated vehicle[J]. Procedia Manufacturing, 2015, 3: 3025-3032. doi: 10.1016/j.promfg.2015.07.847
    [17]
    KÖRBER M, CINGEL A, ZIMMERMANN M, et al. Vigilance decrement and passive fatigue caused by monotony in automated driving[J]. Procedia Manufacturing, 2015, 3: 2403-2409. doi: 10.1016/j.promfg.2015.07.499
    [18]
    WU Yan-bin, KIHARA K, TAKEDA Y, et al. Effects of scheduled manual driving on drowsiness and response to take over request: a simulator study towards understanding drivers in automated driving[J]. Accident Analysis and Prevention, 2019, 124: 202-209. doi: 10.1016/j.aap.2019.01.013
    [19]
    徐超. 基于虚拟驾驶的切换型人机共驾行为评价[D]. 长春: 吉林大学, 2018.

    XU Chao. Evaluation of cooperative driving behavior based on the virtual driving[D]. Changchun: Jilin University, 2018. (in Chinese)
    [20]
    GOLD C, HAPPEE R, BENGLER K. Modeling take-over performance in level 3 conditionally automated vehicles[J]. Accident Analysis and Prevention, 2018, 116: 3-13. doi: 10.1016/j.aap.2017.11.009
    [21]
    XIE Guo-tao, GAO Hong-bo, HUANG Bin, et al. A driving behavior awareness model based on a dynamic Bayesian network and distributed genetic algorithm[J]. International Journal of Computational Intelligence Systems, 2018, 11(1): 469-482. doi: 10.2991/ijcis.11.1.35
    [22]
    ZHANG Li, YU Gui-zhen, ZHOU Bin, et al. Detection algorithm of takeover behavior of automatic vehicles' drivers based on deep learning[C]//IEEE. 4th International Conference on Intelligent Transportation Engineering. New York: IEEE, 2019: 126-130.
    [23]
    仲任. 基于SEM的公路货运平台溢出效应研究[D]. 南昌: 华东交通大学, 2019.

    ZHONG Ren. Research on spillover effect of highway freight platform based on SEM[D]. Nanchang: East China Jiaotong University, 2019. (in Chinese)
    [24]
    卞玉梅. 结构方程模型研究及其应用[D]. 大连: 大连海事大学, 2017.

    BIAN Yu-mei. Research and application of structural equation model[D]. Dalian: Dalian Maritime University, 2017. (in Chinese)
    [25]
    HASSAN H M. Investigation of the self-reported aberrant driving behavior of young male Saudi drivers: a survey-based study[J]. Journal of Transportation Safety and Security, 2016, 8(2): 113-128. doi: 10.1080/19439962.2015.1017782
    [26]
    刘玲莉, 田东东, 王子越. 私家车驾驶员驾驶行为与人格特质的关系研究[J]. 中国安全科学学报, 2019, 29(1): 13-18. https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201901003.htm

    LIU Ling-li, TIAN Dong-dong, WANG Zi-yue. Study on relationships between driving behavior of private car drivers and their personality traits[J]. China Safety Science Journal, 2019, 29(1): 13-18. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZAQK201901003.htm
    [27]
    杨丽平. 基于人格特质的驾驶人换道行为及决策过程研究[D]. 合肥: 合肥工业大学, 2018.

    YANG Li-ping. A study on drivers' lane-changing behavior and decision-making process based on personality traits[D]. Hefei: Hefei University of Technology, 2018. (in Chinese)
    [28]
    秦雅琴, 张静, 贾现广, 等. 基于SEM的双车道公路超车行为安全评价[J]. 安全与环境学报, 2017, 17(4): 1359-1364. https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ201704032.htm

    QIN Ya-qin, ZHANG Jing, JIA Xian-guang, et al. Safety evaluation for the overtaking behavior on the two-lane highway based on the structural equation model[J]. Journal of Safety and Environment, 2017, 17(4): 1359-1364. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ201704032.htm
    [29]
    文江辉, 郭浩, 吴超仲, 等. 基于结构方程模型的疲劳驾驶行为影响因素间量化关系研究[J]. 交通信息与安全, 2014, 32(5): 95-102. doi: 10.3963/j.issn.1674-4861.2014.05.017

    WEN Jiang-hui, GUO Hao, WU Chao-zhong, et al. Quantitative relationship between influencing factors of fatigue driving behavior based on structural equation model[J]. Journal of Transport Information and Safety, 2014, 32(5): 95-102. (in Chinese) doi: 10.3963/j.issn.1674-4861.2014.05.017
    [30]
    温忠麟, 侯杰泰, 马什赫伯特. 结构方程模型检验: 拟合指数与卡方准则[J]. 心理学报, 2004, 2(9): 186-194. https://www.cnki.com.cn/Article/CJFDTOTAL-XLXB200402009.htm

    WEN Zhong-lin, HAU Kit-tai, MARSH H W. Structural equation model testing: cutoff criteria for goodness of fit indices and chi-square test[J]. Acta Psychologica Sinica, 2004, 2(9): 186-194. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XLXB200402009.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
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (923) PDF downloads(152) Cited by()
    Proportional views
    Related

    Copyright《Journal of Traffic and Transportation Engineering》编辑部陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return