Urban Railway Alignment Optimization: Theory and Practice

This book falls within the field of urban transportation planning and design, with a particular focus on urban railway alignment optimization. It delves into the background, challenges, and objective functions and constraints (including cost, environmental impact, and risk) of urban railway alignment design. Furthermore, it presents system reliability modeling approaches for assessing the reliability of parallel railway lines. Additionally, the book emphasizes GIS-based methods for land use analysis and automatic demolition area calculation, as well as the Bayesian Sustainable Intelligent Framework for Enhancing Parallel Railway Reliability, which integrates system reliability analysis, the two-dimensional finite element method, and the Bayesian neural network surrogate model. Lastly, it covers the optimization of railway alignment using approximate dynamic programming, introducing a bi-objective approximate fine-grained optimization model that considers both construction cost and construction risk adjacent to existing operating railways.

This book encompasses not only the theoretical foundations of urban railway alignment optimization but also provide detailed case studies of practical applications. These methods and techniques are significant for enhancing the efficiency, sustainability, and economy of urban railway systems, making them highly valuable to professionals involved in urban transportation planning, design, and construction. Combining theoretical analysis with practical applications, it provides abundant illustrations and tables to elucidate complex concepts and methods, employs novel presentation styles, such as case studies to demonstrate the practical application of theories, and may include instructional elements like step-by-step guides or practical suggestions to help readers better understand and apply the knowledge.

By reading this book, readers can gain insights into the latest methods and techniques in urban railway alignment optimization and learn how to apply them in their work, thereby improving the overall performance and sustainability of urban railway systems. The primary target audience of this book is researchers, practitioners, and students involved in urban transportation planning, design, and construction. Whether for beginners seeking to delve into the field of urban railway alignment optimization or for professionals looking to update their knowledge base, this book is an invaluable resource.

Dr. Yan Gao is an Assistant Research in Southwest Jiaotong University. She holds a Ph.D. in Road and Railway Engineering from Southwest Jiaotong University (2020–2024), a Master’s in Architectural and Civil Engineering from Hunan University (2010–2012), and a Bachelor’s in Civil Engineering from the same institution (2006–2010). Prior to her academic career, she worked as an engineer at RoadDB Technology (2017–2020) and the Southwest Geotechnical & Design Institute of CNNC (2012–2017), focusing on transportation design and intelligent delivery systems.
Dr. Gao specializes in intelligent alignment planning for railways and highways. She has led the Sichuan Provincial Youth Science Fund project and contributed to multiple national and provincial research initiatives. Her work has been published in top-tier journals, including Sustainable Cities and Society, Automation in Construction, and Computer-Aided Civil and Infrastructure Engineering, with over 10 SCI-indexed papers. She holds 11 authorized patents and 2 software copyrights, reflecting her innovative contributions to infrastructure optimization and smart construction technologies.

Qing He (Member, IEEE) received the B.S. and M.S. degrees in electrical engineering from Southwest Jiaotong University and the Ph.D. degree in systems and industrial engineering from The University of Arizona, in 2010. From 2010 to 2012, he was a Post-Doctoral Researcher at the IBM T. J. Watson Research Center. Dr. He has been an Assistant Professor of civil engineering with the University at Buffalo and an Associate Professor of industrial engineering with The State University of New York, since 2012. Dr He is a professor, Ph.D. supervisor and deputy director of the School of Civil Engineering at Southwest Jiaotong University, and deputy director of the Key Laboratory of High-speed Railway Line Engineering of the Ministry of Education. His main research direction is “Intelligent Railway Route Selection Design and Railway Operation and Maintenance based on Big Data”. He serves as deputy editor-in-chief of “IEEE Transactions on Intelligent Transportation Systems”, deputy editor-in-chief of “ASCE Journal of Transportation Engineering”, and editor-in-chief of “Transportation Research Record”, executive deputy editor-in-Chief and editorial director of “Intelligent Transportation Infrastructure”. He has presided over a number of national projects, including the National Natural Science Foundation of China High-Speed Railway Basic Research Joint Fund Key Support Project and the Ministry of Science and Technology Key R&D Plan Project. He won the first prize of the 2022 China Railway Society Science and Technology Progress Award, the top 2% of the top scientists in the transportation discipline in 2024, and ranked 67th in the annual impact list of the transportation discipline in China. He has published more than 100 SCI papers, with more than 6,000 citations on Google Scholar.