Communicate with Traffic Lights and Vehicles Based on Multi-Agent Reinforcement Learning-Reference-Cited by-同舟云学术

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Communicate with Traffic Lights and Vehicles Based on Multi-Agent Reinforcement Learning

Published:2021-05-05 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
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Author:

Wu Qiang,Zhi Peng,Wei Yongqiang,Zhang Liang,Wu Jianqing,Zhou Qingguo,Zhou Qiang,Gao Pengfei

Funder

National Natural Science Foundation of China

Program for New Century Excellent Talents in University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9437608/9437628/09437737.pdf?arnumber=9437737

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Density-Based Classification Network Control Approach for a Single Stoplight Traffic System on a Simplified Traffic Simulation using MATLAB;2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM);2022-12-01

2. Density-Based Optimization Approach for Coordinated Traffic Management on a Simplified Traffic Model using Genetic Algorithms;TENCON 2022 - 2022 IEEE Region 10 Conference (TENCON);2022-11-01

3. A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles;IEEE Access;2022

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