IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i16p2987-d891986.html
   My bibliography  Save this article

Developing a Variable Speed Limit Control Strategy for Mixed Traffic Flow Based on Car-Following Collision Avoidance Theory

Author

Listed:
  • Chen Yuan

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China)

  • Yuntao Shi

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Bin Pan

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Ye Li

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

Abstract

Variable speed limit (VSL) control is an effective technology to improve safety near freeway bottlenecks. This study aims to develop a control strategy for mixed traffic flow consisting of both human-driven vehicles (HDVs) and connected and automated vehicles (CAVs) based on collision avoidance theory. A microscopic simulation platform is first established, and four vehicle longitudinal dynamic models including Cruising model, Intelligent Driver Model (IDM), Adaptive Cruise Control model (ACC), Cooperative Cruise Control model (CACC) and one vehicle lateral dynamic model Minimizing Overall Braking Induced by Lane Changes model (MOBIL) are incorporated into the simulation platform. Then, a new VSL control strategy derived from collision avoidance theory is proposed for mixed traffic flow at the initial stage of CAVs’ popularization. Extensive simulation experiments are conducted, and surrogate safety measures and total travel time indicators are utilized to evaluate the safety and efficiency performances of the proposed VSL control. Results indicate that the proposed VSL control strategy can effectively improve the safety performance near freeway bottlenecks with an acceptable efficiency level.

Suggested Citation

  • Chen Yuan & Yuntao Shi & Bin Pan & Ye Li, 2022. "Developing a Variable Speed Limit Control Strategy for Mixed Traffic Flow Based on Car-Following Collision Avoidance Theory," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:2987-:d:891986
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/16/2987/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/16/2987/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Martínez, Irene & Jin, Wen-Long, 2020. "Optimal location problem for variable speed limit application areas," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 221-246.
    2. Han, Youngjun & Chen, Danjue & Ahn, Soyoung, 2017. "Variable speed limit control at fixed freeway bottlenecks using connected vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 113-134.
    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. Lu, Ruicheng & Ma, Minghui & Wang, Yansong & Lu, Jiaxuan & Liang, Shidong, 2023. "Dynamic areas strategy design for variable speed limiting at fixed freeway bottlenecks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    2. Bouadi, Marouane & Jia, Bin & Jiang, Rui & Li, Xingang & Gao, Zi-You, 2022. "Stability analysis of stochastic second-order macroscopic continuum models and numerical simulations," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 193-209.
    3. Nishi, Ryosuke & Watanabe, Takashi, 2022. "System-size dependence of a jam-absorption driving strategy to remove traffic jam caused by a sag under the presence of traffic instability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    4. Yuan, Tianchen & Ioannou, Petros A., 2023. "Coordinated Traffic Flow Control in a Connected Environment," Institute of Transportation Studies, Working Paper Series qt6q67f9z4, Institute of Transportation Studies, UC Davis.
    5. Nishi, Ryosuke, 2020. "Theoretical conditions for restricting secondary jams in jam-absorption driving scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    6. Zhou, Yang & Ahn, Soyoung & Wang, Meng & Hoogendoorn, Serge, 2020. "Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 152-170.
    7. Zeng, Junwei & Qian, Yongsheng & Mi, Pengfei & Zhang, Chaoyang & Yin, Fan & Zhu, Leipeng & Xu, Dejie, 2021. "Freeway traffic flow cellular automata model based on mean velocity feedback," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    8. Han, Youngjun & Ahn, Soyoung, 2018. "Stochastic modeling of breakdown at freeway merge bottleneck and traffic control method using connected automated vehicle," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 146-166.
    9. Gao, Hang & Chen, Shenyang & Zhang, Michael, 2020. "Get More Out of Variable Speed Limit (VSL) Control: An Integrated Approach to Manage Traffic Corridors with Multiple Bottlenecks," Institute of Transportation Studies, Working Paper Series qt6th037wz, Institute of Transportation Studies, UC Davis.
    10. Krešimir Kušić & Edouard Ivanjko & Filip Vrbanić & Martin Gregurić & Ivana Dusparic, 2021. "Spatial-Temporal Traffic Flow Control on Motorways Using Distributed Multi-Agent Reinforcement Learning," Mathematics, MDPI, vol. 9(23), pages 1-28, November.

    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:gam:jmathe:v:10:y:2022:i:16:p:2987-:d:891986. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.