Traffic-Alpha/LLM-Assisted-Light
This repository contains the code for the paper "LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments".
This project helps traffic managers optimize signal timings in complex urban environments, especially when dealing with congestion or sensor malfunctions. It takes real-time traffic data, such as vehicle occupancy and intersection layouts, and uses a large language model to suggest human-like signal control strategies. The output is a series of explainable traffic signal adjustments. This tool is for traffic operations engineers and urban planners responsible for city-wide traffic flow.
No commits in the last 6 months.
Use this if you need an intelligent system to manage traffic lights that can adapt to unexpected events and explain its decisions.
Not ideal if you are looking for a simple, pre-set traffic light schedule without dynamic adaptation or complex decision-making capabilities.
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99
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Language
Python
License
Apache-2.0
Category
Last pushed
Jul 10, 2025
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