Design of reinforcement learning for perimeter control using network transmission model based macroscopic traffic simulation-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Design of reinforcement learning for perimeter control using network transmission model based macroscopic traffic simulation

Published:2020-07-30 Issue:7 Volume:15 Page:e0236655
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Yoon Jinwon,Kim Sunghoon^ORCID,Byon Young-Ji^ORCID,Yeo Hwasoo^ORCID

Funder

National Research Foundation of Korea

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference44 articles.

1. Sydney Co-ordinated Adaptive Traffic (Scat) System;A. Sims;Publ Aust Road Res Board,1979

2. A multivariable regulator approach to traffic-responsive network- Wide signal control;C Diakaki;Control Eng Pract,2002

3. New signal control optimization policy for oversaturated arterial systems;J Chang;Transportation Research Board,2010

4. Urban gridlock: Macroscopic modeling and mitigation approaches;CF Daganzo;Transp Res Part B Methodol,2007

5. Macroscopic modeling of traffic in cities;N. Geroliminis;Transportation Research Board,2007

Cited by 6 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. Optimizing gate control coordination signal for urban traffic network boundaries using multi-agent deep reinforcement learning;Expert Systems with Applications;2024-12

2. Demonstration-guided deep reinforcement learning for coordinated ramp metering and perimeter control in large scale networks;Transportation Research Part C: Emerging Technologies;2024-02

3. A bibliometric analysis and review on reinforcement learning for transportation applications;Transportmetrica B: Transport Dynamics;2023-03-02

4. Transformer-based map-matching model with limited labeled data using transfer-learning approach;Transportation Research Part C: Emerging Technologies;2022-07

5. Switched Perimeter Control for Two-Region Urban Traffic Networks with Dynamic Macroscopic Fundamental Diagrams;2021 China Automation Congress (CAC);2021-10-22

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3