Prescribed-Time Cooperative Control of Connected and Autonomous Vehicles on Rough Roads

This paper addresses a prescribed-time lateral and longitudinal cooperative formation control problem of connected and autonomous vehicles on rough roads with limited communication range. To deal with the impact of road disturbance in a prescribed time, a sliding mode observer with nested adaptation laws is designed based on relaxed assumptions of the road disturbance. Then, by introducing model transformation and backstepping control, a distributed prescribed-time cooperative formation control method is developed, which can achieve multiple driving maneuvers like lane changing and platooning with communication connectivity preservation. Numerical simulations verify the effectiveness of the presented control method.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2024-09-05
DOI
https://doi.org/10.1109/tvt.2024.3454969
Citations
8
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
2.63
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article

Prescribed-Time Cooperative Control of Connected and Autonomous Vehicles on Rough Roads

Ge Guo, Qian Zhang
8 citations
IEEE Transactions on Vehicular Technology
Traffic control and management
2.63
article

Prescribed-Time Cooperative Control of Connected and Autonomous Vehicles on Rough Roads

Ge Guo, Qian Zhang
article en
8 citations

Abstract

This paper addresses a prescribed-time lateral and longitudinal cooperative formation control problem of connected and autonomous vehicles on rough roads with limited communication range. To deal with the impact of road disturbance in a prescribed time, a sliding mode observer with nested adaptation laws is designed based on relaxed assumptions of the road disturbance. Then, by introducing model transformation and backstepping control, a distributed prescribed-time cooperative formation control method is developed, which can achieve multiple driving maneuvers like lane changing and platooning with communication connectivity preservation. Numerical simulations verify the effectiveness of the presented control method.

IEEE Transactions on Vehicular TechnologyVol. 74(1)
Northeastern University (CN)
Openalex Percentile: Top 10%
Traffic control and management
2.63
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