IDEAS home Printed from https://ideas.repec.org/a/spr/joheur/v28y2022i1d10.1007_s10732-021-09488-8.html
   My bibliography  Save this article

Intersections management for autonomous vehicles: a heuristic approach

Author

Listed:
  • Victor Silva

    (Universidade Federal da Paraíba)

  • Clauirton Siebra

    (Universidade Federal da Paraíba)

  • Anand Subramanian

    (Universidade Federal da Paraíba)

Abstract

Roads intersections are one of the main causes of traffic jams since vehicles need to stop and wait for their time to go. Scenarios that only consider autonomous vehicles can minimize this problem using intelligent systems that manage the time when each vehicle will pass across the intersection. This paper proposes a mathematical model and a heuristic that optimize this management. The efficiency of this approach is demonstrated using traffic simulations, with scenarios of different complexities, and metrics representing the arrival time, $$\hbox {CO}_{{2}}$$ CO 2 emission and fuel consumption. The results show that the present approach is scalable, maintaining its performance even in complex real scenarios. Moreover, its execution time is maintained in milliseconds, what suggests this approach as a candidate for dealing with real-time and dynamic scenarios.

Suggested Citation

  • Victor Silva & Clauirton Siebra & Anand Subramanian, 2022. "Intersections management for autonomous vehicles: a heuristic approach," Journal of Heuristics, Springer, vol. 28(1), pages 1-21, February.
    • Handle: RePEc:spr:joheur:v:28:y:2022:i:1:d:10.1007_s10732-021-09488-8
    DOI: 10.1007/s10732-021-09488-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10732-021-09488-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10732-021-09488-8?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. Gong, Siyuan & Shen, Jinglai & Du, Lili, 2016. "Constrained optimization and distributed computation based car following control of a connected and autonomous vehicle platoon," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 314-334.
    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. Gong, Siyuan & Du, Lili, 2018. "Cooperative platoon control for a mixed traffic flow including human drive vehicles and connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 25-61.
    2. Zhou, Yang & Ahn, Soyoung, 2019. "Robust local and string stability for a decentralized car following control strategy for connected automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 175-196.
    3. Zhang, Hanyu & Du, Lili & Shen, Jinglai, 2022. "Hybrid MPC System for Platoon based Cooperative Lane change Control Using Machine Learning Aided Distributed Optimization," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 104-142.
    4. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part I: Modeling and solution algorithm design," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 174-198.
    5. 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.
    6. Lu, Gongyuan & Nie, Yu(Marco) & Liu, Xiaobo & Li, Denghui, 2019. "Trajectory-based traffic management inside an autonomous vehicle zone," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 76-98.
    7. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part II: Theoretical analysis," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 199-216.
    8. Zhou, Linjie & Ruan, Tiancheng & Ma, Ke & Dong, Changyin & Wang, Hao, 2021. "Impact of CAV platoon management on traffic flow considering degradation of control mode," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    9. Qin, Yanyan & Xiao, Tengfei & Wang, Hua, 2024. "Optimization strategy for connected automated vehicles to reduce energy consumption on freeway in rainy weather," Energy, Elsevier, vol. 296(C).
    10. Yu Lin & Hongfei Jia & Bo Zou & Hongzhi Miao & Ruiyi Wu & Jingjing Tian & Guanfeng Wang, 2021. "Multiobjective Environmentally Sustainable Optimal Design of Dedicated Connected Autonomous Vehicle Lanes," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    11. Wang, Jian & Lu, Lili & Peeta, Srinivas, 2022. "Real-time deployable and robust cooperative control strategy for a platoon of connected and autonomous vehicles by factoring uncertain vehicle dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 88-118.
    12. Qiu, Jiahua & Du, Lili, 2023. "Cooperative trajectory control for synchronizing the movement of two connected and autonomous vehicles separated in a mixed traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    13. Wei, Yuguang & Avcı, Cafer & Liu, Jiangtao & Belezamo, Baloka & Aydın, Nizamettin & Li, Pengfei(Taylor) & Zhou, Xuesong, 2017. "Dynamic programming-based multi-vehicle longitudinal trajectory optimization with simplified car following models," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 102-129.
    14. Qingyu Luo & Rui Du & Hongfei Jia & Lili Yang, 2022. "Research on the Deployment of Joint Dedicated Lanes for CAVs and Buses," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    15. Gu, Yewen & Goez, Julio C. & Mario, Guajardo & Wallace, Stein W., 2019. "Autonomous vessels: State of the art and potential opportunities in logistics," Discussion Papers 2019/6, Norwegian School of Economics, Department of Business and Management Science.
    16. Zhou, Yang & Zhong, Xinzhi & Chen, Qian & Ahn, Soyoung & Jiang, Jiwan & Jafarsalehi, Ghazaleh, 2023. "Data-driven analysis for disturbance amplification in car-following behavior of automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    17. Liu, Zhongcheng & Sun, Dihua & Zhao, Min & Jin, Shuang & Zhang, Yicai, 2022. "Pinning control strategy and stability analysis of mixed platoon: A cyber–physical perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    18. Liu, Chunyu & Sheng, Zihao & Chen, Sikai & Shi, Haotian & Ran, Bin, 2023. "Longitudinal control of connected and automated vehicles among signalized intersections in mixed traffic flow with deep reinforcement learning approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    19. Zhou, Yang & Wang, Meng & Ahn, Soyoung, 2019. "Distributed model predictive control approach for cooperative car-following with guaranteed local and string stability," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 69-86.
    20. Zhao, Shuaidong & Zhang, Kuilin, 2020. "A distributionally robust stochastic optimization-based model predictive control with distributionally robust chance constraints for cooperative adaptive cruise control under uncertain traffic conditi," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 144-178.

    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:spr:joheur:v:28:y:2022:i:1:d:10.1007_s10732-021-09488-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.