IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v567y2021ics0378437120310189.html
   My bibliography  Save this article

DCFS-based deep learning supervisory control for modeling lane keeping of expert drivers

Author

Listed:
  • Chen, Jin
  • Sun, Dihua
  • Zhao, Min
  • Li, Yang
  • Liu, Zhongcheng

Abstract

In this paper, a novel driver model for lane keeping is proposed to replicate the steering behavior of expert drivers. Specifically, a feedforward-feedback control scheme mocking expert drivers is adopted: the feedforward controller plays a leading role, which is a data-driven model based on deep convolutional fuzzy systems (DCFS), and for the sake of human-simulation and guaranteed stability, a supervisory feedback controller is designed, which works only if the state hits the set boundary. Comparing with the previous driver models, the key novelty of the paper is to introduce the “motor intermittency” of human behavior into driver modeling, which is an important issue for biological modeling of the drivers. Simulations on the joint platform of PreScan and CarSim show that the newly presented driver model has better matching performance to the expert drivers comparing with the two different types of advanced model predictive control (MPC) controllers. The proposed driver model has the potential application for semi-automated vehicles to provide human-like qualities for automated driving, which may be one of the essential points to promote the comfort when the driver hands over the steering authority, and improve the transition smoothness in the scenario of human vehicle co-piloting.

Suggested Citation

  • Chen, Jin & Sun, Dihua & Zhao, Min & Li, Yang & Liu, Zhongcheng, 2021. "DCFS-based deep learning supervisory control for modeling lane keeping of expert drivers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    • Handle: RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120310189
    DOI: 10.1016/j.physa.2020.125720
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120310189
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2020.125720?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhao, Hongzhuan & Chen, Qiguang & Shi, Wei & Gu, Tianlong & Li, Wenyong, 2019. "Stability analysis of an improved car-following model accounting for the driver’s characteristics and automation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    2. Sun, Yuqing & Ge, Hongxia & Cheng, Rongjun, 2019. "An extended car-following model considering driver’s desire for smooth driving on the curved road," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    3. Li, Lixiang & Cheng, Rongjun & Ge, Hongxia, 2021. "New feedback control for a novel two-dimensional lattice hydrodynamic model considering driver’s memory effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    4. Zhang, Jing & Xu, Keyu & Li, Shubin & Wang, Tao, 2020. "A new two-lane lattice hydrodynamic model with the introduction of driver’s predictive effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    5. Zhu, H.B. & Zhou, Y.J. & Wu, W.J., 2020. "Modeling traffic flow mixed with automated vehicles considering drivers ’ character difference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huimin Liu & Rongjun Cheng & Tingliu Xu, 2021. "Analysis of a Novel Two-Dimensional Lattice Hydrodynamic Model Considering Predictive Effect," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
    2. Madaan, Nikita & Sharma, Sapna, 2022. "Delayed-feedback control in multi-lane traffic system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    3. Qiao, Yanfeng & Xue, Yu & Cen, Bingling & Zhang, Kun & Chen, Dong & Pan, Wei, 2024. "Study on particulate emission in two-lane mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    4. Kang, Yi-rong & Tian, Chuan, 2024. "A new curved road lattice model integrating the multiple prediction effect under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    5. Wang, Baojie & Li, Wei & Wen, Haosong & Hu, Xiaojian, 2021. "Modeling impacts of driving automation system on mixed traffic flow at off-ramp freeway facilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    6. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    7. Zhou, Jibiao & Chen, Siyuan & Ma, Changxi & Dong, Sheng, 2022. "Stability analysis of pedestrian traffic flow in horizontal channels: A numerical simulation method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    8. Li, Huamin & Zhang, Shun, 2022. "Lane change behavior with uncertainty and fuzziness for human driving vehicles and its simulation in mixed traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    9. Zhai, Cong & Li, Kening & Zhang, Ronghui & Peng, Tao & Zong, Changfu, 2024. "Phase diagram in multi-phase heterogeneous traffic flow model integrating the perceptual range difference under human-driven and connected vehicles environment," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    10. Zhai, Cong & Zhang, Ronghui & Peng, Tao & Zhong, Changfu & Xu, Hongguo, 2023. "Heterogeneous lattice hydrodynamic model and jamming transition mixed with connected vehicles and human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).
    11. Pan, Yuchen & Wu, Yu & Xu, Lu & Xia, Chengyi & Olson, David L., 2024. "The impacts of connected autonomous vehicles on mixed traffic flow: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    12. Zhang, Yicai & Zhao, Min & Sun, Dihua & Liu, Xiaoyu & Huang, Shuai & Chen, Dong, 2022. "Robust H-infinity control for connected vehicles in lattice hydrodynamic model at highway tunnel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    13. Zhang, Xiangzhou & Shi, Zhongke & Yang, Qiaoli & An, Xiaodong, 2024. "Impacts of visuo-spatial working memory on the dynamic performance and safety of car-following behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    14. Li, Xia & You, Zhijian & Ma, Xinwei & Pang, Xiaomin & Min, Xuefeng & Cui, Hongjun, 2024. "Effect of autonomous vehicles on car-following behavior of human drivers: Analysis based on structural equation models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    15. Zhang, Peng & Zhu, Huibing & Zhou, Yijiang, 2022. "Modeling cooperative driving strategies of automated vehicles considering trucks’ behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    16. Zhang, Geng & Yin, Le & Pan, Dong-Bo & Zhang, Yu & Cui, Bo-Yuan & Jiang, Shan, 2020. "Research on multiple vehicles’ continuous self-delayed velocities on traffic flow with vehicle-to-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    17. Cui, Bo-Yuan & Zhang, Geng & Ma, Qing-Lu, 2021. "A stable velocity control strategy for a discrete-time car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    18. Chen, Yingda & Kong, Dewen & Sun, Lishan & Zhang, Tong & Song, Yongchang, 2022. "Fundamental diagram and stability analysis for heterogeneous traffic flow considering human-driven vehicle driver’s acceptance of cooperative adaptive cruise control vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    19. Zhang, Xiangzhou & Shi, Zhongke & Yu, Shaowei & Ma, Lijing, 2023. "A new car-following model considering driver’s desired visual angle on sharp curves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    20. Guangyang Hou, 2023. "Evaluating Efficiency and Safety of Mixed Traffic with Connected and Autonomous Vehicles in Adverse Weather," Sustainability, MDPI, vol. 15(4), pages 1-19, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120310189. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.