Article(id=1309639519763263721, tenantId=1146029695717560320, journalId=1189645257101713411, issueId=1309639513614414014, articleNumber=null, orderNo=null, doi=10.19822/j.cnki.1671-6329.20250153, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790171993436, onlineDateStr=2026-09-23, pubDate=1785859200000, pubDateStr=2026-08-05, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790171993436, onlineIssueDateStr=2026-09-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790171993436, creator=13701087609, updateTime=1790171993436, updator=13701087609, issue=Issue{id=1309639513614414014, tenantId=1146029695717560320, journalId=1189645257101713411, year='2026', volume='', issue='8', pageStart='1', pageEnd='62', issueExtLink='null', onlineDate='null', pubDate='1785859200000', pubDateStr='2026-08-05', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790171991971, creator='13701087609', updateTime=1790233588708, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1309897869121913162, tenantId=1146029695717560320, journalId=1189645257101713411, issueId=1309639513614414014, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1309897869121913163, tenantId=1146029695717560320, journalId=1189645257101713411, issueId=1309639513614414014, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1, endPage=15, ext={EN=ArticleExt(id=1309639519956201706, articleId=1309639519763263721, tenantId=1146029695717560320, journalId=1189645257101713411, language=EN, title=A Framework for Behavioral Competency and Scenario Modeling of Automated Driving Systems for Safety Validation, columnId=1309639514595881152, journalTitle=Automotive Digest, columnName=Special Topic on Security Verification and Evaluation of Intelligent Connected Vehicles, runingTitle=null, highlight=null, articleAbstract=

To address the safety validation challenges faced during the large-scale deployment and industrial application of Automated Driving System (ADS), and to bridge the gaps in existing methods, particularly regarding the systematic behavioral competency modeling, the semantic completeness of test scenarios, the scenario coverage of the Operational Design Domain (ODD), and the validation of boundary capabilities, a framework for behavioral competencies and scenario modeling of ADS is presented. Based on investigations of international technical regulations and automated driving pilot practices, the framework follows the main line of"ODD-behavioral competencies-test scenarios-validation criteria-risk assessment", adopts a functional, abstract, logical and concrete scenario representation, and integrates knowledge-driven, data-driven, and goal-oriented modeling mechanisms to achieve structured and traceable validation paths. For behavioral competency modeling, it covers 4 scenario types: nominal, critical, failure as well as ODD-boundary, and establishes mappings among competencies, scenarios, as well as validation criteria through object-event-response analysis. At the validation level, the formulation logic of performance metrics and validation criteria is clarified to support the assessment of validation coverage and residual risks. The framework can provide methodological references for ADS safety declarations and product compliance assessment.

, authors=Juntao Chen¹, Zhen Chen², Qiang Yang³, Yuqing Liu⁴, Beibei Jia⁵, Guangyou Li⁶, authorsList=Juntao Chen, Zhen Chen, Qiang Yang, Yuqing Liu, Beibei Jia, Guangyou Li, authorCompany=null, correspAuthors=Zhen Chen, 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=1309639520207859947, articleId=1309639519763263721, tenantId=1146029695717560320, journalId=1189645257101713411, language=CN, title=面向安全验证的自动驾驶系统行为能力与场景建模框架, columnId=1309639514876899522, journalTitle=汽车文摘, columnName=智能网联汽车安全验证与评估专题, runingTitle=null, highlight=null, articleAbstract=

为应对自动驾驶系统规模化部署与产业化应用进程中的安全验证难题，弥补现有方法在行为能力建模系统性、测试场景语义完整性、设计运行范围的场景覆盖、边界能力验证等方面的短板，基于国际技术法规研究和自动驾驶试点实践，提出一种以“设计运行范围-行为能力-测试场景-验证准则-风险评估”为主线的行为能力与场景建模框架。采用功能-抽象-逻辑-具体场景表达，融合知识驱动、数据驱动与目标导向的建模机制，实现验证路径的结构化和可追溯性。在行为能力建模方面，覆盖标称、危险、失效及边界4类情境，通过目标物-事件-响应分析建立能力、场景与准则的映射关系。在验证层面，明确性能指标与验证准则设定逻辑，支持验证覆盖度与残余风险评估。该框架可为自动驾驶系统安全声明及产品合规性评估提供方法参考。

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