Multi-objective deep reinforcement learning approach for adaptive traffic signal control system with concurrent optimization of safety, efficiency, and decarbonization at intersections-Reference-Cited by-同舟云学术

Multi-objective deep reinforcement learning approach for adaptive traffic signal control system with concurrent optimization of safety, efficiency, and decarbonization at intersections

Published:2024-05 Issue: Volume:199 Page:107451
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Zhang Gongquan,Chang Fangrong,Jin Jieling,Yang Fan,Huang Helai

Funder

Natural Science Foundation of Hunan Province

Publisher

Elsevier BV

Reference60 articles.

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4. Adaptive traffic signal control with actor-critic methods in a real-world traffic network with different traffic disruption events;Aslani;Transp. Res. Part C: Emerg. Technol.,2017

5. FECO: An Efficient Deep Reinforcement Learning-Based Fuel-Economic Traffic Signal Control Scheme;Boukerche;IEEE Trans. Sustain. Comput.,2021

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