A Deep Reinforcement Learning–Based Urban Traffic Control Model for Vehicle-to-Everything Ecosystem
Infrastructure-to-infrastructure (I2I) communication enables the exchange of traffic data between intersections, which brings a new challenge to urban traffic control. This paper proposes a novel deep reinforcement learning (DRL) framework for urban traffic signal control within the vehicle-to-every...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/atr/5579549 |
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