Harnessing Multi-Source Heterogeneous Data for Public Transit
Description
This book focuses on the innovative use of multi-source heterogeneous data to address key issues in public transit systems. Readers will explore advanced methodologies for data mining, problem diagnosis, mechanism analysis, and stochastic optimization tailored to the public transit context.
This book stands out by integrating the latest in data processing techniques, pattern recognition, and mechanism analysis, providing a comprehensive framework for systematic diagnosis and optimization of transit systems. By examining both microscopic and macroscopic perspectives, it offers insights into passenger behavior, system reliability, and personalized transit solutions.
The unique approach of this book lies in its holistic perspective, emphasizing the study of patterns, problem diagnosis, mechanism analysis, and model construction through the use of multi-source heterogeneous public transit data. It bridges the gap between multi-source data analysis, Bayesian network technology, and synergistic optimization models, serving as a crucial resource for researchers, practitioners, and policymakers who aim to enhance the efficiency, reliability, and passenger satisfaction of public transit systems.
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Persons
Dr. Shaopeng Zhong is a professor in Department of Transportation and Logistics at Dalian University of Technology, the Deputy Director of Department of Transportation and Logistics, and the Vice President of Smart Transportation Research Institure. In 2005, he received his bachelor's degree in transportation engineering from Harbin Institute of Technology, China. In 2010, he obtained his doctorate from Southeast University, China. He is a visiting scholar in urban and regional planning at University of North Carolina at Chapel Hill (2008-2010). He is a guest professor at Technical University of Denmark (2017-2018). He has more than 20 years of professional experience in the field of urban transportation network analysis,sustainable urban planning and transportation planning, land use and transportation integration modeling, transportation network reliability, road congestion pricing, logic-driven transport big data analysis, and shared autonomous mobility. He has written and published three books and more than forty scientific papers in the top journals in the field of transportation planning, such as npj Urban Sustainability, Transportation Research Part A, Transportation Research Part C, Transportation Research Part E, European Journal of Operational Research, Computer-Aided Civil and Infrastructure Engineering, Cities, IEEE Transactions on ITS, Journal of Transport Geography, Computers, Environment and Urban Systems, Journal of Transport & Health, Journal of Transport and Land Use, Journal of Transportation Engineering-ASCE, IET Intelligent Transport Systems, and Journal of Advanced Transportation. He is a member of China Intelligent Transportation Systems Association Youth Expert Committee, a member of the board of directors of the Transportation Intelligent Construction Branch of the China Highway and Transportation Society, a senior member of the China Computer Society (CCF), first executive member/standing committee member of the CCF Smart Transportation Branch, and a member of Intelligent Transportation Professional Committee of Chinese Association for Artificial Intelligence. He is the lead guest editor of the Journal of Transport and Land Use (SSCI index) and Journal of Advanced Transportation (SCI index), editorial board member of Transportation Letters: The International Journal of Transportation Research (SCI/SSCI index), Transportation Management, Journal of Civil Engineering Inter Disciplinaries, and Frontiers in Future Transportation (Transportation Emissions). He is the chairman of the urban planning and travel behavior technical committee of the World Transport Convention. He is the organizing committee and scientific committee of several international conferences, such as International Workshop on Integrated Land Use and Transport Modeling (ILUTM), 6th International Symposium on Travel Demand Management (TDM), Transportation Research Congress (WRC), The 2017 International Conference on Economic Development and Management Engineering (EDME).
Dr. Jiang is an Associate Professor (Tenured) at Lancaster University Management School (LUMS), UK, and Transport DTU, Denmark. Prior to this, he worked in the Oxford University. He received his Ph.D. from the University of Hong Kong and specializes in applying operations research techniques to analysis, modelling, and optimising transportation systems. He is world top author in Transit Assignment on Web of Science and has published more than 50 papers in the leading international journals.His work has been funded by European Union, Independent Research Fund Denmark, Otto Mønsted Foundation, Tecnneical University of Denmark, EuroTech Alliance, the Royal Society of the United Kingdom, National Natural Science Foundation and Ministry of Education of China. Notably, he is the recipient of the DFF-Research Project 1 from Independent Research Fund Denmark (11% success rate, 2.87 million DKK).
Content
Introduction .- Chapter 1 Harnessing multi-source data for public transit: An introduction (Zhong).- Chapter 2 Reliability-based stochastic transit assignment: Formulations and capacity paradox (Jiang).- Chapter 3 Incorporating personalization and bounded rationality into stochastic transit assignment model (Jiang) .- Chapter 4 Preprocessing of multi-source heterogeneous transportation data (Zhong).- Chapter 5 Mining and analysis of multi-source heterogeneous transportation data (Zhong) .- Chapter 6 Systematic diagnosis and analysis of microscopic public transit problems (Zhong).- Chapter 7 Systematic diagnosis and analysis of macroscopic public transit problems(Zhong) .- Chapter 8 Passenger transfer mechanism analysis based on Bayesian network technology (Zhong).- Chapter 9 Synergistic optimization model incorporating latent passenger flow (Zhong).- Chapter 10 Reliability-based equitable transit frequency design (Jiang).-Chapter 11 Integrated optimization of transit networks with schedule-and frequency-based services subject to the bounded stochastic user equilibrium (Jiang).