Article(id=1282030069090587306, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282030021623657005, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.08.0813, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1741968000000, receivedDateStr=2025-03-15, revisedDate=1748102400000, revisedDateStr=2025-05-25, acceptedDate=null, acceptedDateStr=null, onlineDate=1783589387437, onlineDateStr=2026-07-09, pubDate=1756310400000, pubDateStr=2025-08-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783589387437, onlineIssueDateStr=2026-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783589387437, creator=13701087609, updateTime=1783589387437, updator=13701087609, issue=Issue{id=1282030021623657005, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='8', pageStart='1', pageEnd='276', issueExtLink='null', onlineDate='null', pubDate='1756310400000', pubDateStr='2025-08-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783589376121, creator='13701087609', updateTime=1783589731222, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282031511155228698, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282030021623657005, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282031511155228699, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282030021623657005, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=70, endPage=83, ext={EN=ArticleExt(id=1282030069308691115, articleId=1282030069090587306, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Research on collision risk of parallel air routes under autonomous aircraft operation, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

In the scenario of air-ground collaborative autonomous operations, the collision risk of aircraft was assessed to ensure operational safety. The collision risk of parallel routes under autonomous flight was studied based on human factors and the performance of CNS systems. Firstly, an in-depth analysis of the characteristics of autonomous operation scenarios was performed. The Cognitive Reliability and Error Analysis Method (CREAM) model was improved by incorporating cognitive behavior and interactions between pilots and air traffic controllers to assess human reliability in autonomous operations. Subsequently, combined with the CNS performance and human factors, a collision risk model for autonomous operation aircraft was established. The lateral, longitudinal, vertical, and overall collision risks of the aircraft were evaluated separately. The feasibility of this method was validated through a parallel route example, and the impact patterns of human reliability and CNS performance on the collision risk of parallel routes were analyzed. The results indicate that the collision risk values in all three directions and the overall risk remain below the target safety level (5×10^-9). Furthermore, it is demonstrated that improving human cognitive reliability and CNS performance contributes to reducing the spacing between parallel routes, thereby enhancing the safety of autonomous operations.

, authors=Honghai ZHANG¹, Sijia TANG¹, Junqiang WAN^{**, 2}, authorsList=Honghai ZHANG, Sijia TANG, Junqiang WAN, authorCompany=null, correspAuthors=Junqiang WAN, 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=1282030071414231726, articleId=1282030069090587306, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=航空器自主运行下的平行航路碰撞风险研究, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为有效评估航空器在空地协同的自主运行场景下的碰撞风险并保障运行安全，基于人为因素和通信、导航、监视（CNS）性能，开展航空器自主运行下的平行航路碰撞风险研究。首先，深入分析航空器自主运行场景特征，基于飞行员和管制员认知行为及其交互作用改进认知可靠性与失误分析方法（CREAM），评估自主运行过程中的人因可靠性；然后，结合CNS性能，构建基于人为因素和CNS性能的自主运行航空器碰撞风险模型，分别评估航空器在侧向、纵向、竖直方向和综合碰撞风险；其次，通过平行航路算例验证该方法的可行性，分析人因可靠性和CNS性能对平行航路碰撞风险的影响。结果表明：自主运行航空器在3个方向及综合碰撞风险值均低于目标安全水平（5×10^-9），且提高人的认知可靠性和CNS性能均有利于减小平行航路间距，从而提升自主运行的安全性。

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张洪海（1979—），男，山东菏泽人，博士，教授，主要从事航空航天科学与工程、计算机软件及计算机应用、自动化技术、空中交通管理、航空运输等方面的研究。E-mail: honghaizhang@nuaa.edu.cn。

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张洪海（1979—），男，山东菏泽人，博士，教授，主要从事航空航天科学与工程、计算机软件及计算机应用、自动化技术、空中交通管理、航空运输等方面的研究。E-mail: honghaizhang@nuaa.edu.cn。

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