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Reinforcement Learning (RL) has demonstrated excellent decision-making potential in platoon coordination problems.
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T. Bai, A. Johansson, K. H. Johansson, and J. Mårtensson, “Large-scale multi-fleet platoon coordination: A dynamic programming approach,”
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2023
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F. Codevilla, M. Müller, A. López, V. Koltun, and A. Dosovitskiy, “End-to-end driving via conditional imitation learning,” in
2018
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S. V. D. Hoef, J. Mårtensson, D. V. Dimarogonas, and K. H. Johansson, “A predictive framework for dynamic heavy-duty vehicle platoon coordination,”
2019
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T. Chu, J. Wang, L. Codecà, and Z. Li, “Multi-agent deep reinforcement learning for large-scale traffic signal control,”
2019
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T. Bai, A. Johansson, K. H. Johansson, and J. Mårtensson, “Event-triggered distributed model predictive control for platoon coordination at hubs in a transport system,” in
2021
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S. D. Kumaravel, A. A. Malikopoulos, and R. Ayyagari, “Optimal coordination of platoons of connected and automated vehicles at signal-free intersections,”
2021
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2021
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2021
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2023
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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2024
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