multi-commander/Multi-Commander
Multi & Single Agent Reinforcement Learning for Traffic Signal Control Problem
This project helps traffic engineers and urban planners optimize traffic signal timings to reduce congestion and improve traffic flow across an entire city or specific intersections. It takes in traffic flow data and road network configurations, then outputs optimized signal control plans. Urban planners, traffic engineers, and city operations managers would use this to make data-driven decisions about traffic management.
130 stars. No commits in the last 6 months.
Use this if you need to develop or evaluate advanced, AI-driven strategies for dynamic traffic signal control in a simulated environment.
Not ideal if you are looking for an out-of-the-box, plug-and-play solution to deploy directly onto physical traffic light systems without further development.
Stars
130
Forks
30
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 28, 2022
Commits (30d)
0
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