In this paper, we propose a novel approach using MARL, where the traffic junction becomes the agent. Each traffic junction is composed of four Micro Junction ...
The design employs an ARR-CRL-based agent controller for each signalized junction that collaborates with neighbouring agents in order to learn appropriate phase ...
Feb 5, 2022 · In this paper, we propose a novel approach using MARL, where the traffic junction becomes the agent. Each traffic junction is composed of four ...
Micro Junction Agent: A Scalable Multi-agent Reinforcement Learning Method for Traffic Control. BK Choi, JSB Choe, J Kim. International Conference on Agents ...
PDF | This paper describes using multi-agent reinforcement learning (RL) algorithms for learning traffic light controllers to minimize the overall.
An alternative way is multi-agent reinforcement learning. (MARL) in which each signalized intersection is regarded as an agent. A challenge of a MARL approach ...
Duration: 59:08
Posted: Oct 1, 2024
Posted: Oct 1, 2024
Missing: Micro Scalable
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Cooperative traffic optimization with multi-agent reinforcement learning and evolutionary strategy: Bridging the gap between micro and macro traffic control.
Missing: Junction | Show results with:Junction
The implementation of intelligent traffic signal control (TSC) presents a practical approach to mitigating traffic congestion. This strategy is a ...
Missing: Micro | Show results with:Micro
Apr 1, 2020 · This study develops an architecture that allows for communication among agents and tailors the system's reward for each individual agent, ...