Revolutionising Traffic: Intelligent Reinforcement Learning Systems

Created using ChatSlide

This project delves into the complexities of urban traffic management, highlighting the inefficiencies of fixed-time traffic signals amidst growing urbanisation. By leveraging Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL), the research proposes adaptive traffic control systems that can address congestion, pollution, and inefficiencies. A detailed literature review contrasts traditional methods with RL-based approaches in traffic signal management, focusing on scalability...