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    Distributed Control of a Vehicular Platoon Using Event-Triggered Communication Strategy Based on State Estimation

    Source: Journal of Transportation Engineering, Part A: Systems:;2023:;Volume ( 149 ):;issue: 009::page 04023092-1
    Author:
    Hongyu Hu
    ,
    Zixuan Wang
    ,
    Ming Cheng
    ,
    Zhengyi Li
    ,
    Bin Liu
    ,
    Guoying Chen
    DOI: 10.1061/JTEPBS.TEENG-7756
    Publisher: ASCE
    Abstract: Forming a platoon of connected and automated vehicles (CAVs) can contribute to alleviating traffic jams, easing traffic congestion, and improving traffic safety. To address the problem of frequent communication possibly causing network congestion when there are many CAVs, we propose the distributed control of a vehicular platoon using an event-triggered communication strategy based on state estimation. First, a hierarchical control structure comprising a linear quadratic regulator (LQR) and fuzzy proportional–integral–derivative (fuzzy PID) controller was established to realize vehicle-following behavior in a platoon. To handle the frequent communication that would waste resources, an event-triggered communication strategy based on state estimation (ETCS-SE) was adopted. The event-triggered communication strategy determines whether to communicate by comparing the transmission error and the dynamic trigger threshold. The distributed Kalman filter reduces the noise of the signal, which further contributes to the reduction of false triggering. The simulation shows that the proposed platoon control algorithm exhibits excellent performance: communication resources are saved by 69.77% and the maximum of the following error is reduced by 14.16%.
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      Distributed Control of a Vehicular Platoon Using Event-Triggered Communication Strategy Based on State Estimation

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4293158
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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorHongyu Hu
    contributor authorZixuan Wang
    contributor authorMing Cheng
    contributor authorZhengyi Li
    contributor authorBin Liu
    contributor authorGuoying Chen
    date accessioned2023-11-27T22:56:10Z
    date available2023-11-27T22:56:10Z
    date issued7/4/2023 12:00:00 AM
    date issued2023-07-04
    identifier otherJTEPBS.TEENG-7756.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4293158
    description abstractForming a platoon of connected and automated vehicles (CAVs) can contribute to alleviating traffic jams, easing traffic congestion, and improving traffic safety. To address the problem of frequent communication possibly causing network congestion when there are many CAVs, we propose the distributed control of a vehicular platoon using an event-triggered communication strategy based on state estimation. First, a hierarchical control structure comprising a linear quadratic regulator (LQR) and fuzzy proportional–integral–derivative (fuzzy PID) controller was established to realize vehicle-following behavior in a platoon. To handle the frequent communication that would waste resources, an event-triggered communication strategy based on state estimation (ETCS-SE) was adopted. The event-triggered communication strategy determines whether to communicate by comparing the transmission error and the dynamic trigger threshold. The distributed Kalman filter reduces the noise of the signal, which further contributes to the reduction of false triggering. The simulation shows that the proposed platoon control algorithm exhibits excellent performance: communication resources are saved by 69.77% and the maximum of the following error is reduced by 14.16%.
    publisherASCE
    titleDistributed Control of a Vehicular Platoon Using Event-Triggered Communication Strategy Based on State Estimation
    typeJournal Article
    journal volume149
    journal issue9
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/JTEPBS.TEENG-7756
    journal fristpage04023092-1
    journal lastpage04023092-10
    page10
    treeJournal of Transportation Engineering, Part A: Systems:;2023:;Volume ( 149 ):;issue: 009
    contenttypeFulltext
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