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Evaluating the performance of vehicular platoon control under different network topologies of initial states

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  • Li, Yongfu
  • Li, Kezhi
  • Zheng, Taixiong
  • Hu, Xiangdong
  • Feng, Huizong
  • Li, Yinguo

Abstract

This study proposes a feedback-based platoon control protocol for connected autonomous vehicles (CAVs) under different network topologies of initial states. In particularly, algebraic graph theory is used to describe the network topology. Then, the leader–follower approach is used to model the interactions between CAVs. In addition, feedback-based protocol is designed to control the platoon considering the longitudinal and lateral gaps simultaneously as well as different network topologies. The stability and consensus of the vehicular platoon is analyzed using the Lyapunov technique. Effects of different network topologies of initial states on convergence time and robustness of platoon control are investigated. Results from numerical experiments demonstrate the effectiveness of the proposed protocol with respect to the position and velocity consensus in terms of the convergence time and robustness. Also, the findings of this study illustrate the convergence time of the control protocol is associated with the initial states, while the robustness is not affected by the initial states significantly.

Suggested Citation

  • Li, Yongfu & Li, Kezhi & Zheng, Taixiong & Hu, Xiangdong & Feng, Huizong & Li, Yinguo, 2016. "Evaluating the performance of vehicular platoon control under different network topologies of initial states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 359-368.
    • Handle: RePEc:eee:phsmap:v:450:y:2016:i:c:p:359-368
    DOI: 10.1016/j.physa.2016.01.006
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    References listed on IDEAS

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    1. Jin, Sheng & Wang, Dianhai & Tao, Pengfei & Li, Pingfan, 2010. "Non-lane-based full velocity difference car following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4654-4662.
    2. Nagatani, Takashi, 1998. "Modified KdV equation for jamming transition in the continuum models of traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 261(3), pages 599-607.
    3. Tang, Tie-Qiao & He, Jia & Yang, Shi-Chun & Shang, Hua-Yan, 2014. "A car-following model accounting for the driver’s attribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 583-591.
    4. X. Zhao & Z. Gao, 2005. "A new car-following model: full velocity and acceleration difference model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 47(1), pages 145-150, September.
    5. Nagatani, Takashi, 1999. "TDGL and MKdV equations for jamming transition in the lattice models of traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 264(3), pages 581-592.
    6. Peng, Ke & Yang, Yupu, 2009. "Leader-following consensus problem with a varying-velocity leader and time-varying delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(2), pages 193-208.
    7. Tang, Tie-Qiao & Chen, Liang & Yang, Shi-Chun & Shang, Hua-Yan, 2015. "An extended car-following model with consideration of the electric vehicle’s driving range," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 148-155.
    8. Ge, H.X. & Cheng, R.J. & Lei, L., 2010. "The theoretical analysis of the lattice hydrodynamic models for traffic flow theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2825-2834.
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    Cited by:

    1. Kosun, Caglar & Ozdemir, Serhan, 2017. "Determining the complexity of multi-component conformal systems: A platoon-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 688-695.
    2. Hu, Xiaojian & Lin, Chenxi & Hao, Xiatong & Lu, RuiYing & Liu, TengHui, 2021. "Influence of tidal lane on traffic breakdown and spatiotemporal congested patterns at moving bottleneck in the framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    3. Li, Yongfu & Kang, Yuhao & Yang, Bin & Peeta, Srinivas & Zhang, Li & Zheng, Taixong & Li, Yinguo, 2016. "A sliding mode controller for vehicular traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 38-47.
    4. Zhu, Liling & Tang, Yandong & Yang, Da, 2021. "Cellular automata-based modeling and simulation of the mixed traffic flow of vehicle platoon and normal vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).

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