mahmoudtaouti/RL_Highway_Merge
applying multi-agent reinforcement learning for highway-merging autonomous vehicles
This project helps engineers and researchers design and test autonomous vehicle systems for safer and more efficient highway merging. It takes simulated traffic data and vehicle behaviors as input and outputs optimized control policies for individual autonomous vehicles to navigate complex merging scenarios. The primary users are autonomous driving engineers, traffic simulation specialists, and intelligent transportation system researchers.
No commits in the last 6 months.
Use this if you are developing or evaluating multi-agent reinforcement learning strategies for autonomous vehicles, particularly for challenging highway merge scenarios.
Not ideal if you are looking for a complete, production-ready autonomous driving stack or a system to directly control real-world vehicles.
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67
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Language
Python
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Last pushed
Dec 09, 2023
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