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Robust local and string stability for a decentralized car following control strategy for connected automated vehicles

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  • Zhou, Yang
  • Ahn, Soyoung

Abstract

This paper presents a robust car-following control strategy under uncertainty for connected and automated vehicles (CAVs). The proposed control is designed as a decentralized linear feedback and feedforward controller with a focus on robust local and string stability under (i) time-varying uncertain vehicle dynamics and (ii) time-varying uncertain communication delay. The former uncertainty is incorporated into the general longitudinal vehicle dynamics (GLVD) equation that regulates the difference between the desired acceleration (prescribed by the control model) and the actual acceleration by compensating for nonlinear vehicle dynamics (e.g., due to aerodynamic drag force). The latter uncertainty is incorporated into acceleration information received from the vehicle immediately ahead. As a primary contribution, this study derives and proves (i) a sufficient and necessary condition for local stability and (ii) sufficient conditions for robust string stability in the frequency domain using the Laplacian transformation. Simulation experiments verify the correctness of the mathematical proofs and demonstrate that the proposed control is effective for ensuring stability against uncertainties.

Suggested Citation

  • Zhou, Yang & Ahn, Soyoung, 2019. "Robust local and string stability for a decentralized car following control strategy for connected automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 175-196.
    • Handle: RePEc:eee:transb:v:125:y:2019:i:c:p:175-196
    DOI: 10.1016/j.trb.2019.05.003
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    References listed on IDEAS

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    Cited by:

    1. Wang, Jian & Zhou, Anye & Liu, Zhiyuan & Peeta, Srinivas, 2024. "Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).
    2. Wang, Yong & Wu, Yuankai & Tang, Yingjuan & Li, Qin & He, Hongwen, 2023. "Cooperative energy management and eco-driving of plug-in hybrid electric vehicle via multi-agent reinforcement learning," Applied Energy, Elsevier, vol. 332(C).
    3. Zhou, Yang & Wang, Meng & Ahn, Soyoung, 2019. "Distributed model predictive control approach for cooperative car-following with guaranteed local and string stability," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 69-86.
    4. Biyao Wang & Yi Han & Siyu Wang & Di Tian & Mengjiao Cai & Ming Liu & Lujia Wang, 2022. "A Review of Intelligent Connected Vehicle Cooperative Driving Development," Mathematics, MDPI, vol. 10(19), pages 1-31, October.
    5. Li, Tienan & Chen, Danjue & Zhou, Hao & Laval, Jorge & Xie, Yuanchang, 2021. "Car-following behavior characteristics of adaptive cruise control vehicles based on empirical experiments," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 67-91.
    6. 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.
    7. Zhang, Jing & Xu, Keyu & Li, Guangyao & Li, Shubin & Wang, Tao, 2021. "Dynamics of traffic flow affected by the future motion of multiple preceding vehicles under vehicle-connected environment: Modeling and stabilization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    8. Liu, Huaqing & Jiang, Rui, 2021. "Improving comfort level in traffic flow of CACC vehicles at lane drop on two-lane highways," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 575(C).
    9. Dai, Yulu & Yang, Yuwei & Wang, Zhiyuan & Luo, YinJie, 2022. "Exploring the impact of damping on Connected and Autonomous Vehicle platoon safety with CACC," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. 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).
    11. 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.
    12. Wang, Jian & Lu, Lili & Peeta, Srinivas, 2022. "Real-time deployable and robust cooperative control strategy for a platoon of connected and autonomous vehicles by factoring uncertain vehicle dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 88-118.
    13. Chandle Chae & Youngho Kim, 2023. "Investigation of Following Vehicles’ Driving Patterns Using Spectral Analysis Techniques," Sustainability, MDPI, vol. 15(13), pages 1-15, July.

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