Optimal Coordination of Platoons of Connected and Automated Vehicles at Signal-Free Intersections
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Abstract (arXiv)
In this paper, we address the problem of coordinating platoons of connected and automated vehicles at signal-free intersections. We present a decentralized, two-level optimal framework to coordinate the platoons with the objective to minimize travel delay and fuel consumption of every platoon crossing the intersection. In the upper-level, each platoon derives an optimal schedule to enter the intersection. In the low-level, the platoons derive their optimal control input (acceleration/deceleration) for the optimal schedule derived in the upper-level. We validate the effectiveness of the proposed framework in simulation and show significant improvements both in travel delay and fuel consumption compared to the baseline scenario with fixed time traffic signals at the intersection.
Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). First posted on arXiv 14 Jan 2020.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 1.
3 papers.
- 2022COOR-PLT: A hierarchical control model for coordinating adaptive platoons of connected and autonomous vehicles at signal-free intersections based on deep reinforcement learningcited by 2
- 2022Modeling Adaptive Platoon and Reservation Based Autonomous Intersection Control: A Deep Reinforcement Learning Approachcited by 1
- 2025An Automated Reinforcement Learning Reward Design Framework with Large Language Model for Cooperative Platoon Coordinationcited by 1
- 2025An Automated Reinforcement Learning Reward Design Framework with Large Language Model for Cooperative Platoon Coordination28 Apr 2025
- 2022COOR-PLT: A hierarchical control model for coordinating adaptive platoons of connected and autonomous vehicles at signal-free intersections based on deep reinforcement learning1 Jul 2022
- 2022Modeling Adaptive Platoon and Reservation Based Autonomous Intersection Control: A Deep Reinforcement Learning Approach24 Jun 2022