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Fully Distributed Optimization-Based CAV Platooning Control Under Linear Vehicle Dynamics

Author

Listed:
  • Jinglai Shen

    (Department of Mathematics and Statistics, University of Maryland, Baltimore, Maryland 21250)

  • Eswar Kumar H. Kammara

    (Department of Mathematics and Statistics, University of Maryland, Baltimore, Maryland 21250)

  • Lili Du

    (Department of Civil and Coastal Engineering, University of Florida, Gainesville, Florida 32608)

Abstract

This paper develops distributed optimization-based, platoon-centered connected and autonomous vehicle (CAV) car-following schemes, motivated by the recent interest in CAV platooning technologies. Various distributed optimization or control schemes have been developed for CAV platooning. However, most existing distributed schemes for platoon centered CAV control require either centralized data processing or centralized computation in at least one step of their schemes, referred to as partially distributed schemes. In this paper, we develop fully distributed optimization based, platoon centered CAV platooning control under the linear vehicle dynamics via the model predictive control approach with a general prediction horizon. These fully distributed schemes do not require centralized data processing or centralized computation through the entire schemes. To develop these schemes, we propose a new formulation of an objective function and a decomposition method that decomposes a densely coupled central objective function into the sum of multiple locally coupled functions whose coupling satisfies the network topology constraint. We then exploit locally coupled optimization and operator splitting methods to develop fully distributed schemes. Control design and stability analysis is carried out to achieve desired traffic transient performance and asymptotic stability. Numerical tests demonstrate the effectiveness of the proposed fully distributed schemes and CAV platooning control.

Suggested Citation

  • Jinglai Shen & Eswar Kumar H. Kammara & Lili Du, 2022. "Fully Distributed Optimization-Based CAV Platooning Control Under Linear Vehicle Dynamics," Transportation Science, INFORMS, vol. 56(2), pages 381-403, March.
  • Handle: RePEc:inm:ortrsc:v:56:y:2022:i:2:p:381-403
    DOI: 10.1287/trsc.2021.1100
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    References listed on IDEAS

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    1. Wang, Jian & Gong, Siyuan & Peeta, Srinivas & Lu, Lili, 2019. "A real-time deployable model predictive control-based cooperative platooning approach for connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 271-301.
    2. 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 conditions," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 144-178.
    3. 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.
    4. 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.
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    Cited by:

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    2. Yan Wang & Wei Wang & Shuai Mao & Jiangliang Jin & Yunjian Xu & Rong Su, 2025. "Gradient-Based Distributed Cruise Control Under Intermittent V2V Communication for Smoothing Traffic Flow," Transportation Science, INFORMS, vol. 59(6), pages 1197-1213, November.

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