Traffic signal active control method for short-distance intersections.

IF 2.9 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES PLoS ONE Pub Date : 2025-03-14 eCollection Date: 2025-01-01 DOI:10.1371/journal.pone.0319804
Yulin Tian, Shuqing Liu, Lu Wei, Zhen Li, Shaohu Tang, Yuchen Zhang, Tao Zhu
{"title":"Traffic signal active control method for short-distance intersections.","authors":"Yulin Tian, Shuqing Liu, Lu Wei, Zhen Li, Shaohu Tang, Yuchen Zhang, Tao Zhu","doi":"10.1371/journal.pone.0319804","DOIUrl":null,"url":null,"abstract":"<p><p>Aiming at the existing problems about the overflow prevention goal and the overall traffic efficiency guarantee being difficult to optimize at the same time in the signal control process of short-distance intersections scenario, this paper proposes a traffic signal active control method based on key state prediction. In order to construct the key state evolution trend of short-distance intersection scenarios, this paper proposes the concept of overflow index for short-distance road sections and designs the prediction method of overflow index. In order to perform fast computation and solution for the active control scheme, this paper builds a solution algorithm based on deep reinforcement learning and optimizes the problem of reward sparsity in the algorithm, which improves the ability of active control in terms of state space and reward function. The experimental results show that this method can not only ensure the overall traffic efficiency of short-distance intersections and reduce the travel delay but also can actively sense the change of overflow state, improve the overflow prevention and control ability of the target scenario, and reduce the overflow risk.</p>","PeriodicalId":20189,"journal":{"name":"PLoS ONE","volume":"20 3","pages":"e0319804"},"PeriodicalIF":2.9000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PLoS ONE","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1371/journal.pone.0319804","RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Aiming at the existing problems about the overflow prevention goal and the overall traffic efficiency guarantee being difficult to optimize at the same time in the signal control process of short-distance intersections scenario, this paper proposes a traffic signal active control method based on key state prediction. In order to construct the key state evolution trend of short-distance intersection scenarios, this paper proposes the concept of overflow index for short-distance road sections and designs the prediction method of overflow index. In order to perform fast computation and solution for the active control scheme, this paper builds a solution algorithm based on deep reinforcement learning and optimizes the problem of reward sparsity in the algorithm, which improves the ability of active control in terms of state space and reward function. The experimental results show that this method can not only ensure the overall traffic efficiency of short-distance intersections and reduce the travel delay but also can actively sense the change of overflow state, improve the overflow prevention and control ability of the target scenario, and reduce the overflow risk.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
期刊最新文献
Genome-wide SNPs reveal novel genetic relationships among Atlantic cod (Gadus morhua) from the south coast of Newfoundland, Canada (subdivision 3Ps), Northern cod stock complex, and Gulf of St Lawrence. Family caregivers' contributions to self-care behaviors among heart failure patients in Oman. Methods for the health technology assessment of complex interventions: A scoping review. Optimization design and experiment of key components of mountain pendulum-lever cam type hole seeders based on DEM-MBD coupling simulation. Traffic signal active control method for short-distance intersections.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1