A Simple Framework Towards Vision-based Traffic Signal Control with Microscopic Simulation

Understand

Traffic signal control (TSC) is crucial for reducing traffic congestion leading to smoother traffic flow, reduced idle time, and mitigated CO2 emissions.

• In this paper, we explore the computer vision approach for TSC that modulates on-road traffic flows through visual observation.
• Unlike traditional feature-based approaches, vision-based methods depend much less on heuristics and predefined features, bringing promising potentials for end-to-end learning and optimization of traffic signals.
• Thus, we introduce a simple traffic simulation framework called TrafficDojo towards vision-based TSC and its benchmark by integrating the microscopic traffic flow provided in SUMO into the 3D driving simulator MetaDrive.