PyTSC: A Unified Platform for Multi-Agent Reinforcement Learning in Traffic Signal Control

Effective Traffic Signal Control (TSC) is fundamental to urban traffic management, responsible for guiding the movement of vehicles through intersections by controlling traffic lights. The primary goals of TSC are to minimize traffic congestion, enhance traffic flow, and improve safety for both vehicles and pedestrians. Poor TSC optimization leads to increased congestion, fuel consumption, and pollution. Longer wait times at signals lead to increased fuel consumption, which not only exacerbates environmental issues through higher emissions but also results in economic losses due to delays. Moreover, inefficient TSC negatively impacts the quality of life in urban areas, contributing to increased noise and air pollution.