Reinforcement Learning for Mixed Autonomy Intersections
We propose a model-free reinforcement learning method for controlling mixed autonomy traffic in simulated traffic networks with through-traffic-only two-way and four-way intersections. Our method utilizes multi-agent policy decomposition which allows decentralized control based on local observati...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023
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| Online Access: | https://hdl.handle.net/1721.1/148680 |