Simulation-Based Model for Adaptive Traffic Signal Control Using Forecasting and Reinforcement Learning
This paper presents a simulation-based model for adaptive traffic signal control that integrates computer vision, LSTM-based forecasting, and reinforcement learning. The proposed approach enables proactive traffic management by incorporating predicted traffic states into the decision-making process of the RL agent. The...