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Path Planning for Autonomous Platoon Formation

Author

Listed:
  • Ouafae El Ganaoui-Mourlan

    (IFP Energies Nouvelles, 1 et 4 Avenue de Bois-Préau, 92852 Rueil-Malmaison, France)

  • Stephane Camp

    (IFP School, 228-232, Avenue Napoléon Bonaparte, CEDEX, 92852 Rueil-Malmaison, France)

  • Thomas Hannagan

    (STELLANTIS, Centre Technique Vélizy, 78140 Vélizy-Villacoublay, France)

  • Vaibhav Arora

    (IFP School, 228-232, Avenue Napoléon Bonaparte, CEDEX, 92852 Rueil-Malmaison, France)

  • Martin De Neuville

    (IFP School, 228-232, Avenue Napoléon Bonaparte, CEDEX, 92852 Rueil-Malmaison, France)

  • Vaios Andreas Kousournas

    (IFP School, 228-232, Avenue Napoléon Bonaparte, CEDEX, 92852 Rueil-Malmaison, France)

Abstract

In the context of automated highway systems (AHS), this work proposes an approach that enables a vehicle to autonomously join a platoon with optimized trajectory in the presence of dynamical traffic obstacles. A notable aspect is the use of Model Predictive Control (MPC) optimization of the planned path, in conjunction with a variant of the Rapidly-exploring Random Trees (RRT*) algorithm for the purpose of platoon formation. This combination efficiently explores the space of possible trajectories, returning trajectories that are smoothened out with respect to the dynamic constraints of the vehicle, while at the same time allowing for real-time implementation. The implementation we propose takes into consideration both localization and mapping through relevant sensors and V2V communication. The complete algorithm is tested over various nominal and worst-case scenarios, qualifying the merits of the proposed methodology.

Suggested Citation

  • Ouafae El Ganaoui-Mourlan & Stephane Camp & Thomas Hannagan & Vaibhav Arora & Martin De Neuville & Vaios Andreas Kousournas, 2021. "Path Planning for Autonomous Platoon Formation," Sustainability, MDPI, vol. 13(9), pages 1-13, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4668-:d:541173
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    Citations

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    Cited by:

    1. Saeed Vasebi & Yeganeh M. Hayeri, 2021. "Collective Driving to Mitigate Climate Change: Collective-Adaptive Cruise Control," Sustainability, MDPI, vol. 13(16), pages 1-30, August.
    2. Ouafae El Ganaoui-Mourlan & Stephane Camp & Charles Verhas & Nicolas Pollet & Benjamin Ortega & Baptiste Robic, 2023. "Traffic Manager Development for a Roundabout Crossed by Autonomous and Connected Vehicles Using V2I Architecture," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    3. 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).

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