I. Report Title: Exploring the Non-linear Relationship between the Built Environment and Traffic Behavior using Machine Learning

II. Time: Friday, April 26, 14:30

III. Location: Room 637, School of Transportation Engineering

IV. Abstract: Traditional research often assumes a general linear relationship between variables. If this assumption does not hold, traditional parametric models may draw incorrect conclusions. This report takes the relationship between the built environment and traffic behavior as an example to introduce the advantages of machine learning and explain how machine learning can promote planning practice and academic progress.

V. Lecturer Profile: Dr. Cao Xinyu is a professor at the Hubert H. Humphrey School of Public Affairs, University of Minnesota. His research interests include the interactive relationship between land use and transportation, the impact of telecommunication technology on traffic behavior, and satisfaction analysis. He has published over 140 papers. His work has been cited more than 15,000 times on Google Scholar, with an H-index of 64, and he has been listed among the top 2% of scientists worldwide by Stanford University for several years. He serves as the editor-in-chief of Transportation Research Part D, and as an associate editor for Transportation Policy and Journal of Planning Education and Research. He is a former president of the International Association of China Planners (IACP). He studied at Tsinghua University and the University of California, Davis.