A robust control strategy for mixed traffic systems with time-varying delays and uncertainties
Abstract In mixed traffic environments, connected and automated vehicles (CAVs) are subject to time-varying delays arising from wireless communication, data processing, and driving tasks. Additionally, the complexity of human driving behavior makes it difficult to accurately determine the parameters...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44443-025-00204-1 |
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| Summary: | Abstract In mixed traffic environments, connected and automated vehicles (CAVs) are subject to time-varying delays arising from wireless communication, data processing, and driving tasks. Additionally, the complexity of human driving behavior makes it difficult to accurately determine the parameters of the human-driven vehicles (HDVs) model, meaning that the parameters of the HDV dynamic model are often uncertain. To address these challenges, this paper proposes a robust control strategy for mixed traffic systems with time-varying delays and uncertainties. First, a mathematical model of a mixed traffic system with time-varying delays and HDV model parameter uncertainties is developed. The mixed traffic system includes multiple HDVs and a CAV, and treats the received state information from neighboring HDVs as the system output to design an output-feedback controller. Then, a robust performance analysis is conducted to ensure the asymptotic stability of the closed-loop mixed traffic system under the robustness criterion. Next, we propose a robust output feedback control strategy to address the challenges of time-varying delays and parameter uncertainties and stabilize the traffic flow. Finally, the effectiveness of this control strategy is validated through numerical simulations to demonstrate its capability to maintain overall traffic stability. |
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| ISSN: | 1319-1578 2213-1248 |