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Cooperative Cruise Control for Intelligent Connected Vehicles: A Bargaining Game Approach

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  • Miguel F. Arevalo-Castiblanco

    (Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
    Department of Electrical and Electronics Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia)

  • Jaime Pachon

    (Department of Electrical and Electronics Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia)

  • Duvan Tellez-Castro

    (Department of Electrical and Electronics Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia)

  • Eduardo Mojica-Nava

    (Department of Electrical and Electronics Engineering, Universidad Nacional de Colombia, Bogota 111321, Colombia)

Abstract

Intelligent transportation systems (ITSs) are at the forefront of advancements in transportation, offering enhanced efficiency, safety, and environmental friendliness. To enable ITSs, autonomous systems play a pivotal role, contributing to the development of autonomous driving, data-driven modeling, and multiagent control strategies to establish sustainable and coordinated traffic management. The integration of networked and automated vehicles has garnered significant attention as a potential solution for alleviating traffic congestion and improving fuel economy, achieved through global route optimization and cooperative driving. This study focuses on a predictive control perspective to address the cooperative cruise control problem. Online decision making is employed during the driving process, utilizing information gathered from the network. By employing bargaining games to establish an operating agreement among vehicles, we formalize a synchronization approach based on predictive control theory. Ultimately, these findings are put to the test in an emulation environment within a hardware-in-the-loop system. The results revealed that the proposed cruise control successfully achieved convergence toward the desired reference signal. These results demonstrate the effectiveness of our approach in achieving synchronized platoon behavior and correct bargaining outcomes. These findings underscore the effectiveness and potential of DMPC with bargaining games in coordinating and optimizing vehicular networks. This paves the way for future research and development in this promising area.

Suggested Citation

  • Miguel F. Arevalo-Castiblanco & Jaime Pachon & Duvan Tellez-Castro & Eduardo Mojica-Nava, 2023. "Cooperative Cruise Control for Intelligent Connected Vehicles: A Bargaining Game Approach," Sustainability, MDPI, vol. 15(15), pages 1-21, August.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11898-:d:1209183
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    References listed on IDEAS

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