CoLLMLight introduces a cooperative framework where Large Language Models act as intelligent traffic signal controllers that communicate and coordinate with each other across an entire traffic network.

• Leverages LLMs' problem-solving capabilities for optimized traffic flow management
• Implements effective inter-agent coordination protocols missing in previous approaches
• Enables network-wide traffic optimization rather than isolated intersections
• Demonstrates how AI agents can collaborate to solve complex urban infrastructure challenges

This engineering breakthrough offers cities a path to reduce congestion, decrease travel times, and improve fuel efficiency across entire transportation networks without expensive infrastructure upgrades.

CoLLMLight: Cooperative Large Language Model Agents for Network-Wide Traffic Signal Control