Article(id=1322594163447677908, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1322594153020641347, articleNumber=null, orderNo=null, doi=10.20104/j.cnki.1674-6546.20260288, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=1789488000000, revisedDateStr=2026-09-16, acceptedDate=null, acceptedDateStr=null, onlineDate=1793260621177, onlineDateStr=2026-10-29, pubDate=1791993600000, pubDateStr=2026-10-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793260621177, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793260621177, creator=13701087609, updateTime=1793260621177, updator=13701087609, issue=Issue{id=1322594153020641347, tenantId=1146029695717560320, journalId=1189918454225211397, year='2026', volume='', issue='10', pageStart='1', pageEnd='48', issueExtLink='null', onlineDate='null', pubDate='1791993600000', pubDateStr='2026-10-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1793260618691, creator='13701087609', updateTime=1793261887162, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322599473793060887, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1322594153020641347, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322599473793060888, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1322594153020641347, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=11, endPage=18, ext={EN=ArticleExt(id=1322594163678364629, articleId=1322594163447677908, tenantId=1146029695717560320, journalId=1189918454225211397, language=EN, title=Trigger Condition Superposition Assessment and Simulation Validation for the Safety of the Intended Functionality of Automatic Emergency Braking, columnId=1322594154186657860, journalTitle=Automotive Engineer, columnName=Selected Papers of SAECCE 2026, runingTitle=null, highlight=null, articleAbstract=

To address the identification and prioritization of Safety of the Intended Functionality (SOTIF)-related risks for Automatic Emergency Braking (AEB) systems in complex road environments, a triggering-condition superposition assessment method integrating Bayesian networks and multi-index scoring is proposed. 4 triggering conditions (weather condition, road surface condition, traffic interaction behavior and camera frame rate) are selected. A probabilistic propagation model is constructed from triggering conditions to perception degradation, braking-margin reduction and hazardous events. A scenario-importance scoring system is established by incorporating severity, exposure, controllability, perception degradation and coupling complexity. 3 types of straight road environments are considered, including clear–dry, moderate rain–wet/slippery as well as heavy rain with ponding and low adhesion coefficient. Under each road surface category, 3 types of interaction behaviors(pedestrian crossing, lead vehicle emergency braking and vehicle cut-in) are designed. 3 camera frame rates (30 fps, 15 fps, and 10 fps) are set, forming 27 combined simulation scenarios. The simulation results show that deteriorating weather and reduced road adhesion significantly weaken the braking capability of the AEB system, while a lower camera frame rate increases target-confirmation delay and further compresses the system safety margin. Among the scenarios, heavy rain with ponding and low adhesion coefficient road – pedestrian crossing has the highest risk level, and the lead vehicle emergency braking and pedestrian crossing scenarios under moderate rain – wet/slippery road conditions also exhibit borderline risk. The results demonstrate that the proposed method can effectively identify high-risk superposed scenarios of AEB from the SOTIF perspective and can provide a reference for scenario-library construction, virtual-test prioritization, and safety argumentation.

, authors=Sumin Zhang¹, Rui Wang¹, Haixia Li², Lei He¹, authorsList=Sumin Zhang, Rui Wang, Haixia Li, Lei He, authorCompany=null, correspAuthors=null, 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=1322594164320093142, articleId=1322594163447677908, tenantId=1146029695717560320, journalId=1189918454225211397, language=CN, title=面向自动紧急制动系统预期功能安全的触发条件叠加评估与仿真验证, columnId=1322594154534785094, journalTitle=汽车工程师, columnName=2026中国汽车工程学会年会优秀论文（选登）, runingTitle=null, highlight=null, articleAbstract=

针对自动紧急制动（AEB）系统在复杂道路环境下的预期功能安全（SOTIF）风险识别与场景优先级排序问题，提出一种基于贝叶斯网络与多指标评分融合的触发条件叠加评估方法。选取天气状况、路面条件、交通交互行为和摄像头帧率4类触发条件，构建由触发条件到感知退化、制动裕度下降及危险事件发生的风险传播模型，并结合严重度、暴露度、可控性、感知退化度和耦合复杂度建立场景重要性评分体系。在晴天-干燥、中雨-湿滑、大雨-积水低附着系数3类平直路面下分别设计行人横穿、前车紧急制动和车辆切入3类交互行为，同时设置30帧/s、15帧/s和10帧/s 3种摄像头帧率，形成27组组合仿真场景。仿真结果显示，天气恶化与路面附着系数降低会显著削弱AEB系统的制动能力，摄像头帧率下降会增加目标确认延迟并压缩系统安全裕度。其中，大雨-积水低附着系数路面-行人横穿场景危险度最高，中雨-湿滑路面下的前车紧急制动和行人横穿场景亦表现出明显的边界风险。结果表明，所提出的方法能够有效识别AEB系统在SOTIF视角下的高风险叠加场景，可为场景库构建、虚拟仿真测试排序和安全论证提供参考。

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