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Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach

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  • Zhou, Yang
  • Ahn, Soyoung
  • Wang, Meng
  • Hoogendoorn, Serge

Abstract

This paper presents a car-following control strategy of connected automated vehicles (CAVs) to stabilize a mixed vehicular platoon consisting of CAVs and human-driven vehicles. This study first establishes a string stability criterion for a mixed vehicular platoon. Specifically, a mixed vehicular platoon is decomposed into “subsystems” that are all possible sequential subsets of the platoon. String stability is then defined as the “head-to-tail” string stability for all subsystems: the magnitude of a disturbance is not amplified from the first vehicle to the last vehicle of each subsystem. Based on this definition, distributed frequency-domain-based CAV control is proposed to increase the number of head-to-tail string stable subsystems and consequently dampen stop-and-go disturbances drastically. Specifically, an H-infinity control problem is formulated, where the maximum disturbance “damping ratios” in each subsystem is minimized within the predominant acceleration frequency boundaries of human-driven vehicles. Simulation experiments, embedded with real human-driven vehicle trajectories, were conducted, and results show that the proposed control can effectively dampen stop-and-go disturbances.

Suggested Citation

  • Zhou, Yang & Ahn, Soyoung & Wang, Meng & Hoogendoorn, Serge, 2020. "Stabilizing mixed vehicular platoons with connected automated vehicles: An H-infinity approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 152-170.
    • Handle: RePEc:eee:transb:v:132:y:2020:i:c:p:152-170
    DOI: 10.1016/j.trb.2019.06.005
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    3. Yang, Da & Jia, Bingmei & Dai, Liyuan & Jin, Jing Peter & Xu, Lihua & Chen, Fei & Zheng, Shiyu & Ran, Bin, 2022. "Optimization model for the freeway-exiting position decision problem of automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 24-48.
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    6. Zhou, Yang & Zhong, Xinzhi & Chen, Qian & Ahn, Soyoung & Jiang, Jiwan & Jafarsalehi, Ghazaleh, 2023. "Data-driven analysis for disturbance amplification in car-following behavior of automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    7. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    8. Liu, Zhongcheng & Sun, Dihua & Zhao, Min & Jin, Shuang & Zhang, Yicai, 2022. "Pinning control strategy and stability analysis of mixed platoon: A cyber–physical perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    9. Dong, Shuoxuan & Zhou, Yang & Chen, Tianyi & Li, Shen & Gao, Qiantong & Ran, Bin, 2021. "An integrated Empirical Mode Decomposition and Butterworth filter based vehicle trajectory reconstruction method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
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