Review of Intelligent Traffic Signal Control Strategies Driven by Deep Reinforcement Learning
With the rapid growth of urban populations,the number of private cars has grown exponentially,which makes overwhelming traffic congestion problem become more and more acute.The traditional traffic signal control technology is difficult to adapt to the complex and changeable traffic conditions,and th...
Main Author: | YU Ze, NING Nianwen, ZHENG Yanliu, LYU Yining, LIU Fuqiang, ZHOU Yi |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial office of Computer Science
2023-04-01
|
Series: | Jisuanji kexue |
Subjects: | |
Online Access: | https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2023-50-4-159.pdf |
Similar Items
-
An Intelligent IoT Based Traffic Light Management System: Deep Reinforcement Learning
by: Shima Damadam, et al.
Published: (2022-09-01) -
Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Control
by: Rohit Bokade, et al.
Published: (2023-01-01) -
Biased Pressure: Cyclic Reinforcement Learning Model for Intelligent Traffic Signal Control
by: Bunyodbek Ibrokhimov, et al.
Published: (2022-04-01) -
Optimization Control of Adaptive Traffic Signal with Deep Reinforcement Learning
by: Kerang Cao, et al.
Published: (2024-01-01) -
Traffic Signal Control System Based on Intelligent Transportation System and Reinforcement Learning
by: Julián Hurtado-Gómez, et al.
Published: (2021-09-01)