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Reinforcement-Learning-for-Adaptive-Traffic-Light-Control

SUMO need to be installed beforehand

This undergraduate project focuses on the development and application of a reinforcement learning algorithm to manage a simulated single-intersection traffic control system. The primary goal is to create an adaptive traffic light control system that responds in real-time to varying traffic conditions, effectively reducing congestion and improving overall traffic flow. The reinforcement learning algorithm will be trained to optimize traffic light timings based on the observed traffic conditions.

File named 'Cartpole' is the code for controlling cartpole in Gymnasium, it is the tutorial at the early stage of this project

'ControlSystemCode' is the main code for Adaptive Traffic Light, contains different environment setup and different algorithms code. Tests for TraCI library and environment also here.

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This is the project of Warwick Uni, CS350

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