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Stability enhancement for traffic flow via self–stabilizing control strategy in the presence of packet loss

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  • Yang, Yichen
  • Li, Zuxing
  • Li, Yabin
  • Cao, Tianyu
  • Li, Zhipeng

Abstract

Connected and automated vehicles (CAVs) with vehicle–to–vehicle (V2V) wireless communication have the potential to significantly improve traffic stability, resulting in increased traffic capacity and safety. However, the performance and effectiveness are heavily dependent on the quality of communication, and packet loss during V2V communication can negatively impact traffic stability. To address this issue, this paper proposes a self–stabilizing control strategy that exploits the historical velocity information stored locally in each vehicle. Specifically, we integrate V2V communication topology (CT) (i.e. multi predecessors–following communication topology, MPF–CT), a packet transmission model, and a car–following model to represent the cyber–physical system. Other than theoretical stability analysis, we also conduct a series of numerical simulations and verify the performance of our proposed self–stabilizing control strategy versus the number of predecessors, the probability of successful packet transmission, and packet transmission interval, respectively. The results show that the proposed self–stabilizing control strategy can significantly improve traffic stability in various packet loss scenarios. Therefore, this work provides insight into addressing the communication unreliability problems of CAVs in practice.

Suggested Citation

  • Yang, Yichen & Li, Zuxing & Li, Yabin & Cao, Tianyu & Li, Zhipeng, 2023. "Stability enhancement for traffic flow via self–stabilizing control strategy in the presence of packet loss," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    • Handle: RePEc:eee:phsmap:v:622:y:2023:i:c:s0378437123003564
    DOI: 10.1016/j.physa.2023.128801
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    References listed on IDEAS

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    1. Yao, Zhihong & Wang, Yi & Liu, Bo & Zhao, Bin & Jiang, Yangsheng, 2021. "Fuel consumption and transportation emissions evaluation of mixed traffic flow with connected automated vehicles and human-driven vehicles on expressway," Energy, Elsevier, vol. 230(C).
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