Article(id=1281685532879074035, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281685530169545672, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.06.0530, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736870400000, receivedDateStr=2025-01-15, revisedDate=1742745600000, revisedDateStr=2025-03-24, acceptedDate=null, acceptedDateStr=null, onlineDate=1783507243603, onlineDateStr=2026-07-08, pubDate=1751040000000, pubDateStr=2025-06-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783507243603, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783507243603, creator=13701087609, updateTime=1783507243603, updator=13701087609, issue=Issue{id=1281685530169545672, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='6', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='1751040000000', pubDateStr='2025-06-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783507242958, creator='13701087609', updateTime=1783589309504, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282029742274622413, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281685530169545672, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282029742274622414, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281685530169545672, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=27, endPage=36, ext={EN=ArticleExt(id=1281685533113955060, articleId=1281685532879074035, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Causal inference of effect of motor-vehicle driver's avoidance action on cyclists' injury, columnId=1149733271128420907, journalTitle=China Safety Science Journal, columnName=Safety social science and safety management, runingTitle=null, highlight=null, articleAbstract=

To verify the impact of drivers' evasive actions on injuries of two-wheeler riders and to identify the conditions under which evasive maneuvers fail or even exacerbate the injuries, based on data from China In-Depth Accident Study (CIDAS), NSGA-II was first used to simulate and optimize the reconstruction of accident scenes. Vehicle speed and two-wheeler speed data at the moment of collision were extracted. A research dataset consisting of independent variables, dependent variables, and 11 covariates was constructed. Simulation-derived variables and investigation-based data fields were integrated to serve as the foundational data for modeling. Secondly, two causal inference methods were adopted, namely the propensity score (PS) weighting - regression analysis combination method considering positive hypotheses and covariate adjustment (inverse probability weighting (IPW) and overlap probability weighting (OW)), to infer the causality between evasive actions and injury severity, and to compare the inter-group balance after processing by IPW, OW and unweighted regression methods. Finally, the causal effect of drivers' evasive actions on the injury severity of two-wheeler riders under different conditions was quantitatively analyzed. The results show that, in general, the evasive actions currently adopted by drivers cannot effectively reduce the injury severity of riders. When the vehicle types are commercial vehicles and the motor vehicle traveling at medium to high speeds, taking evasive driving actions tends to aggravates the injuries of riders. Among these actions, steering maneuvers is more likely to increase the severity of rider injuries.

, authors=Tong ZHU¹, Wei LI¹, Yunfei ZHAO¹, Xiaohu LI², Peng WANG³, authorsList=Tong ZHU, Wei LI, Yunfei ZHAO, Xiaohu LI, Peng WANG, 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=1281685535047529207, articleId=1281685532879074035, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=机动车驾驶人避险动作对骑行者损伤影响的因果推断, columnId=1149733271296193071, journalTitle=中国安全科学学报, columnName=安全社会科学与安全管理, runingTitle=null, highlight=null, articleAbstract=

为验证驾驶人避险动作对两轮车骑行者损伤的影响，识别出避险失效乃至加重损伤的条件。首先，在中国交通事故深度调查（CIDAS）数据的基础上，采用非支配排序遗传算法II（NSGA-II）仿真优化重建事故场景，提取碰撞时刻机动车速度、两轮车速度数据，构建由自变量、因变量和11项协变量构成的数据集，将仿真获取的字段与调查所得的数据字段融合作为建模的基础数据；其次，采用2种因果推断方法，即考虑正性假设与协变量调整的倾向性评分（PS）加权-回归分析结合方法（逆概率权重（IPW）和重叠概率权重（OW）），推断避险动作与损伤程度之间的因果性，并比较IPW、OW及无加权回归方法处理后的组间均衡性；最后，定量分析不同条件下驾驶人避险动作与两轮车骑行者损伤程度的因果效应。结果表明：总体上看，驾驶人目前采用的避险动作不能有效地减轻骑行者的损伤程度；当车辆类型为商用车、机动车并以中高速行驶时，采取避险驾驶动作会加剧骑行者损伤，其中，打方向盘更容易造成骑行者损伤加剧。

, authors=朱彤副教授¹, 李微¹, 赵云飞¹, 李晓虎², 王鹏³, authorsList=朱彤副教授, 李微, 赵云飞, 李晓虎, 王鹏, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=c/p3zK6srZolvLY97Zq53w==, magXml=zcYC9p9E7l50nCzavJ5k0g==, pdfUrl=null, pdf=9gSQAL41wV1M3RGQkXJeaQ==, pdfFileSize=8574706, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=rv17NG31updF1isl6QPWwg==, mapNumber=null, fund=null)}, authors=[Author(id=1281685535508902658, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281685532879074035, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=zhutong@chd.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281685535588594436, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281685532879074035, authorId=1281685535508902658, language=EN, stringName=Tong ZHU, firstName=Tong, middleName=null, lastName=ZHU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹College of Transportation Engineering, Chang 'an University, Xi'an Shaanxi 710064, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281685535680869125, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281685532879074035, authorId=1281685535508902658, language=CN, stringName=朱彤副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹长安大学 运输工程学院，陕西 西安，710064, bio={"content":"

朱彤（1977—），男，浙江诸暨人，博士，副教授，主要从事交通规划、交通安全与智能交通等方面的研究。E-mail: zhutong@chd.edu.cn。

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朱彤（1977—），男，浙江诸暨人，博士，副教授，主要从事交通规划、交通安全与智能交通等方面的研究。E-mail: zhutong@chd.edu.cn。

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