Carbon Emission Reduction in Traffic Control: A Signal Timing Optimization Method Based on Rainbow DQN

Carbon Emission Reduction in Traffic Control: A Signal Timing Optimization Method Based on Rainbow DQN

To improve intersection traffic flow and reduce vehicle energy consumption and emissions at intersections, a signal optimization method based on deep reinforcement learning (DRL) is proposed. The algorithm uses Rainbow DQN as the core framework, incorporating vehicle position, speed, and acceleratio...

Bibliográfalaš dieđut
Váldodahkkit:	Juan Lv, Zhaowei Wang, Jianxiao Ma
Materiálatiipa:	Artihkal
Giella:	English
Almmustuhtton:	MDPI AG 2025-01-01
Ráidu:	Applied Sciences
Fáttát:	traffic management signal timing optimization multi-objective optimization deep reinforcement learning (DRL) CO<sub>2</sub> reduction
Liŋkkat:	https://www.mdpi.com/2076-3417/15/3/1101

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