主题：在内生关系下探索交通执法与违法对道路安全的影响（Exploring the impact of traffic law enforcement andviolations on road safety under the endogenous interrelations）
简介：丰明洁，滚球体育交通系统工程系讲师。博士毕业于同济大学，曾前往英国拉夫堡大学访学一年。主要研究方向为道路交通安全评估、交通事故建模与分析、交通执法分析与管理等。在Analytic Methods in Accident Research、AccidentAnalysis and Prevention、Transportation Research Board等国内外学术期刊和会议上发表论文10余篇，撰写发明专利1项。
Mingjie Feng is a Lecturer ofTransportation Engineering at the University of Shanghai for Science andTechnology. She holds her Ph.D. degree in traffic and transportationengineering from Tongji University and has visited Loughborough University as avisiting scholar for one year. Her areas of expertise include the statisticalanalysis of crash datasets, safety evaluation of roadway design, and trafficenforcement management on safety. She has published more than 10 papers injournals and international conferences including Analytic Methods in AccidentResearch, Accident Analysis and Prevention, and Transportation Research Board.She has also published 1 invention patent.
Safer roads and police enforcement are closelyassociated since the latter directly encourages road users to improve theirbehavior by complying with traffic rules and laws. Understanding therelationships between police enforcement, driving behavior, and traffic safetyis a prerequisite for optimizing enforcement strategies. However, there is adearth of research on the contemporaneous relationships between these three variables.To this end, the multivariate time series modeling technique was utilized in thisstudy to conduct an in-depth analysis of the contemporaneous relationships,dynamic interactions and potential effects among police enforcement, trafficviolations, and traffic crashes. The results indicated that police patrol time hada negative impact on traffic crashes, but crashes were the Granger cause ofpolice patrol. The significant bidirectional interactions in conditionalvariances of police enforcement, traffic violations, and traffic crashesfurther confirm the necessity to analyze the three simultaneously.