IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v526y2019ics0378437119305217.html
   My bibliography  Save this article

Delayed-feedback control in a car-following model with the combination of V2V communication

Author

Listed:
  • Peng, Guanghan
  • Yang, Shuhong
  • Xia, Dongxue
  • Li, Xiaoqin

Abstract

In this paper, the delayed-feedback control method for car-following model is proposed with the combination of V2V communication. The stability condition is obtained with the consideration of the control signals by applying control method. Numerical simulation indicates that the control signals can alleviate traffic jam successfully, which is in accordance with analytical results. In a conclusion, the performance of traffic flow is improved with delayed-feedback control method under V2V communication situation for car-following theory.

Suggested Citation

  • Peng, Guanghan & Yang, Shuhong & Xia, Dongxue & Li, Xiaoqin, 2019. "Delayed-feedback control in a car-following model with the combination of V2V communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119305217
    DOI: 10.1016/j.physa.2019.04.148
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119305217
    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.2019.04.148?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Madaan, Nikita & Sharma, Sapna, 2022. "Delayed-feedback control in multi-lane traffic system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    2. Yadav, Sunita & Redhu, Poonam, 2024. "Impact of driving prediction on headway and velocity in car-following model under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    3. Jiang, Nan & Yu, Bin & Cao, Feng & Dang, Pengfei & Cui, Shaohua, 2021. "An extended visual angle car-following model considering the vehicle types in the adjacent lane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    4. Peng, Guanghan & Jia, Teti & Kuang, Hua & Tan, Huili, 2022. "Energy consumption in a new lattice hydrodynamic model based on the delayed effect of collaborative information transmission under V2X environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    5. 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).
    6. Shuaiyang Jiao & Shengrui Zhang & Bei Zhou & Zixuan Zhang & Liyuan Xue, 2020. "An Extended Car-Following Model Considering the Drivers’ Characteristics under a V2V Communication Environment," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    7. 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).
    8. Jafaripournimchahi, Ammar & Cai, Yingfeng & Wang, Hai & Sun, Lu & Yang, Biao, 2022. "Stability analysis of delayed-feedback control effect in the continuum traffic flow of autonomous vehicles without V2I communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    9. Song, Tao & Zhu, Wen-Xing, 2022. "Analysis of feed-forward control effect on autonomous driving car-following system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    10. Ammar Jafaripournimchahi & Yingfeng Cai & Hai Wang & Lu Sun, 2022. "Environmental Analyses of Delayed-Feedback Control Effects in Continuum-Traffic Flow of Autonomous Vehicles," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    11. Xin, Qi & Fu, Rui & Ukkusuri, Satish V. & Yu, Shaowei & Jiang, Rui, 2021. "Modeling and impact analysis of connected vehicle merging accounting for mainline random length tight-platoon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).

    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:526:y:2019:i:c:s0378437119305217. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.