Article(id=1281608090256651037, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608054340829934, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.04.0144, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1762012800000, receivedDateStr=2025-11-02, revisedDate=1767974400000, revisedDateStr=2026-01-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1783488779844, onlineDateStr=2026-07-08, pubDate=1777305600000, pubDateStr=2026-04-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783488779844, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783488779844, creator=13701087609, updateTime=1783488779844, updator=13701087609, issue=Issue{id=1281608054340829934, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='4', pageStart='1', pageEnd='286', issueExtLink='null', onlineDate='null', pubDate='1777305600000', pubDateStr='2026-04-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783488771281, creator='13701087609', updateTime=1783588648031, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282026967885124001, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608054340829934, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282026967885124002, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281608054340829934, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=142, endPage=151, ext={EN=ArticleExt(id=1281608090470560542, articleId=1281608090256651037, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Aircraft swarm improved velocity obstacle methods considering low carbon and deviation, columnId=1277328337617941059, journalTitle=China Safety Science Journal, columnName=Safety Technology and Engineering, runingTitle=null, highlight=null, articleAbstract=

In order to address the requirements of low-carbon operation and safety in aircraft conflict resolution, an IVO method based on adaptive elliptical protected zones was proposed, taking into account aircraft carbon emissions and speed adjustment deviations. First, adaptive elliptical protected zones were constructed according to the velocity differences among aircraft. Second, aircraft flying on the same route with similar velocity vectors and close spatial proximity were grouped into clusters, and key characteristics such as cluster centroids, velocity vectors, and safety regions were defined. Then, a cluster control algorithm was applied to reasonably adjust the velocity vectors of aircraft within each cluster, ensuring the maintenance of safe separation during conflict resolution. Subsequently, velocity obstacle cones were established between clusters. By incorporating constraints on the maximum allowable adjustment per unit time and combining planar geometric analysis with a mathematical optimization model, conflict-free velocities and headings with minimal deviation were determined under low-carbon objectives. Finally, dynamic behaviour analysis was conducted through numerical simulations implemented in Python. The results show that, compared with the traditional velocity obstacle method, the proposed approach improves conflict resolution efficiency by 87.5%, reduces the average adjustment magnitude by 86.67%, and achieves fuel savings of up to 37.36%, demonstrating its effectiveness for aircraft conflict resolution and operational optimization in complex air traffic environments.

, authors=Qingwei Zhong^{1, 2}, Yingxue Yu^{1, 3}, Su Liu^{**, 1}, Rui Wang¹, Jingwei Guo⁴, Weijun Pan², authorsList=Qingwei Zhong, Yingxue Yu, Su Liu, Rui Wang, Jingwei Guo, Weijun Pan, authorCompany=null, correspAuthors=Su Liu, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281608091137454881, articleId=1281608090256651037, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=考虑低碳及速度调整偏差的航空器集群改进速度障碍法, columnId=1277328337940902469, journalTitle=中国安全科学学报, columnName=安全技术与工程, runingTitle=null, highlight=null, articleAbstract=

为满足民航运行中低碳减排与冲突解脱安全性并重的需求，在考虑航空器碳排放及速度调整偏差的基础上，提出基于自适应椭圆保护区的改进速度障碍法（IVO）。首先，根据航空器速度差异构造自适应椭圆保护区；其次，将同一航路、矢量速度相似、距离接近的航空器划分为集群，并刻画集群的质点、速度矢量和安全范围等特征；再次，针对已划分的集群，采用集群控制算法合理调整集群内航空器的速度矢量，确保冲突解脱期间保持安全间隔；然后，在集群间建立速度障碍锥，结合单位时间最大改变量限制，通过平面几何分析与数学优化模型求解低碳目标下偏差最小的解脱速度和航向；最后，通过Python基于数值模拟实现动态行为分析。研究结果表明：与传统速度障碍法相比，改进方法使航空器解脱效率提高87.5%，平均调整幅度优化86.67%，燃油节省最高达37.36%，为复杂空中交通环境下冲突解脱与运行优化问题提供了一种可行的技术方案。

, authors=钟庆伟副教授^{1, 2}, 庾映雪^{1, 3}, 刘苏讲师^{**, 1}, 王睿讲师¹, 郭经纬副教授⁴, 潘卫军教授², authorsList=钟庆伟副教授, 庾映雪, 刘苏讲师, 王睿讲师, 郭经纬副教授, 潘卫军教授, authorCompany=null, correspAuthors=刘苏讲师, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=mglfJ57MWBsC4/r44cnK1A==, magXml=JZzE7iknsJNEh9anqckh0w==, pdfUrl=null, pdf=qCDc8kqYIgNW5tGpM7FK6w==, pdfFileSize=6234082, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=8Tf5gv//ZF0EZXA6VM9FRg==, mapNumber=null, fund=null)}, authors=[Author(id=1281608091649159983, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281608090256651037, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=qingweizhong@cafuc.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281608091728851762, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281608090256651037, authorId=1281608091649159983, language=EN, stringName=Qingwei Zhong, firstName=Qingwei, middleName=null, lastName=Zhong, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹School of Air Traffic Management, Civil Aviation Flight University of China, Guanghan Sichuan 618307, China
²Key Laboratory of Flight Techniques and Flight Safety, Civil Aviation Flight University of China, Guanghan Sichuan, 618307, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281608091804349235, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281608090256651037, authorId=1281608091649159983, language=CN, stringName=钟庆伟副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹中国民用航空飞行学院 空中交通管理学院，四川 广汉 618307
²中国民用航空飞行学院 民航飞行技术与飞行安全重点实验室，四川 广汉 618307, bio={"content":"

钟庆伟（1991—），男，四川什邡人，博士，副教授，主要从事交通运输组织优化方面的研究。E-mail: qingweizhong@cafuc.edu.cn。

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钟庆伟（1991—），男，四川什邡人，博士，副教授，主要从事交通运输组织优化方面的研究。E-mail: qingweizhong@cafuc.edu.cn。

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