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Analysis of feed-forward control effect on autonomous driving car-following system

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  • Song, Tao
  • Zhu, Wen-Xing

Abstract

In this paper, the feed-forward control effect is introduced into the car-following system, which combines the proportional differentiation and velocity feedback effect to form a new compound compensation method to improve the stability and rapidity of the traffic flow system. The unit step input response in time domain analysis method is used to analyze the system and the feed-forward effect of the system. Using the small gain theorem and the Rouse criterion, we obtain the stability conditions of the improved system and obtain the neutral stability curves. Next, setting up simulation experiments discuss the influence of feed-forward effect on autonomous traffic flow system. The results show that the introduction of feed-forward effect can effectively improve the rapidity of traffic flow system responding to disturbances. Combined with appropriate proportional differentiation and velocity feedback, the system can be both stability and rapidity, which is meaningful for autonomous driving.

Suggested Citation

  • Song, Tao & Zhu, Wen-Xing, 2022. "Analysis of feed-forward control effect on autonomous driving car-following system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
  • Handle: RePEc:eee:phsmap:v:598:y:2022:i:c:s037843712200303x
    DOI: 10.1016/j.physa.2022.127401
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    References listed on IDEAS

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    Cited by:

    1. Yin, Yu-Hang & Lü, Xing & Jiang, Rui & Jia, Bin & Gao, Ziyou, 2024. "Kinetic analysis and numerical tests of an adaptive car-following model for real-time traffic in ITS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    2. Wang, Shu-Tong & Zhu, Wen-Xing & Ma, Xiao-Long, 2023. "Mixed traffic system with multiple vehicle types and autonomous vehicle platoon: Modeling, stability analysis and control strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).

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