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講座預告 | Bounded rationality based day-to-day traffic evolution process with s ...

來源:天津大學管理與經濟學部 | 2019-11-18 | 發布:經管之家

講座時間:2019年11月21日(周四) 10:30-12:00

講座地點:25教學樓A區3層3B教室

主講人:Meng Xu




主講人簡介:

Dr. Xu is currently a Professor of the State Key Laboratory of Rail Traffic Control and Safety and the Institute of Transportation System Science and Engineering (TSSE) at BJTU. He was educated at the Northwestern Polytechnical University of China at Xi’an, where he was awarded the MS and PhD degrees in Computation Mathematics and Traffic Engineering in 2003 and 2005 respectively.

The major portion of his research focuses on transport policy analysis, transport and land use studies, sustainable urbanization, modeling and analysis of transportation systems, network equilibrium models and solution algorithm development, and large-scale traffic data sets analysis. He was awarded the DAAD Scholarship in 2010, the program for New Century Excellent Talents in University of China in 2011 (issued by the Ministry of Education of China), the EU Marie Curie International Incoming Fellowship in 2012, and the prestigious Excellent Young Scientist Programme in 2014 (funded by the National Natural Science Foundation of China (NSFC)).

He is the associate editor of the International journal of urban sciences (IJUS) (www.tandfonline.com/rjus), the international committee of the International Symposium on Travel Demand Management (http://2017tdm.ntu.edu.tw/index.php ), and the member of the Editorial Advisory Board of the Journal of Transportation Systems Engineering and Information Technology (TSEIT) (http://www.tseit.org.cn/CN/column/column106.shtml ) and the International Journal of Transportation (IJT) ( http://www.sersc.org/journals/IJT/ ) .

講座內容:

Smart travel applications have become important parts of the daily lives of travelers because they can provide important traffic information. However, travelers may have different attitudes towards this traffic information. In particular, some travelers may not need to refer to this information because they are familiar with the traffic network, whereas others may rely entirely on this information or some may not trust the information completely. In this study, we present a discrete-time day-to-day dynamic evolution model for depicting the behavior of travelers with respect to traffic information during their daily trips. Two cases are considered in this model: a fixed proportion and time-varying proportion of sceptics. For the first case, the system performance is analyzed in detail, where we demonstrate the existence and uniqueness of the proposed day-to-day dynamic model. Importantly, we analyze the conditions required for the asymptotic stability of the proposed evolution model. For the second case, we employ a Markov chain model to describe the changing attitudes of travelers towards traffic information. Finally, we employed a numerical experiment to verify the performance of our proposed evolution models for both the cases. Empirical results are presented based on simulation experiments and their implications are discussed.

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