Overview
- Takes forward efforts to reduce the energy and financial costs of public transportation at the same time as increasing speed and reliability
- Provides the reader with modeling techniques that can cope with single trains in detail or with more general multi-train systems
- Shows how variable scheduling can accommodate variable passenger demand
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Industrial Control (AIC)
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Table of contents (8 chapters)
Keywords
About this book
Mixed-integer linear programming and pseudospectral methods are among the new methods proposed for single- and multi-train systems for the solution of the nonlinear trajectory planning problem which involves constraints such as varying speed restrictions and maximum traction/braking force. Signaling systems and their effects are also accounted for in the trajectory planning model.
Origin–destination passenger demand is included in the model formulation for train scheduling. Iterative convex programming and efficient bi-level approaches are utilized in the solution of the train-scheduling problem. In addition, the splitting rates and route choices of passengers are also optimized from the system point of view.
The problems and solutions described in Optimal Trajectory Planning and Train Scheduling for Urban Rail Transit Systems will interest researchers studying public transport systems and logistics whether from an academic or practitioner background as well as providing a real application for anybody studying optimization theory and predictive control.Authors and Affiliations
About the authors
Yihui Wang received the B.Sc in control engineering from the School of Electronic and Information Engineering, Beijing Jiaotong University in 2007. She became a Ph.D. student at Delft Center for Systems and Control, Delft University of Technology in September 2010 and obtained the Ph.D. degree in November, 2014. She is currently an assistant professor at the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University. Her main research interests include train scheduling, energy-efficient train control, hybrid systems, and model predictive control.
Bart De Schutter received the M.Sc. degree in electrotechnical and mechanical engineering and the Ph.D. degree in applied sciences (summa cum laude with congratulations of the examination jury) from the K.U.Leuven, Leuven, Belgium, in 1991 and 1996, respectively. He is currently a Full Professor with the Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands. His current research interests include the control of intelligent transportation systems, hybrid system control, and multiagent systems. Prof. De Schutter is an Associate Editor for Automatica and for the IEEE Transactions on Intelligent Transportation Systems.
Bin Ning received the B.S. degrees from Northern Jiaotong University (now Beijing Jiaotong University), Beijing, China, in 1982, where he received both the M.S. and Ph.D. degrees afterwards. He is currently a full professor with the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, as well as the President of Beijing Jiaotong University. His research interests include intelligent transportation systems, communication-based train control, rail transport systems, system fault-tolerant design, fault diagnosis, system reliability, and safety studies. Prof. Ning is a Fellow of the Institution of Railway Signal Engineers and IET, a Senior Member of the China Railway Society, and a member of theWestern Returned Scholars Association. He is the Chair of the Technical Committee on Railroad Systems and Applications of the IEEE Intelligent Transportation Systems Society.
Ton van den Boom received the MSc and PhD degrees in Electrical Engineering from Eindhoven University of Technology, Eindhoven, The Netherlands, in 1988 and 1993, respectively. Currently he is an Associate Professor at Delft University of Technology, The Netherlands. His research interests are in the areas of linear and nonlinear model predictive control, control and identification of discrete event systems and hybrid systems with applications in railway, robotics, and printers.
Bibliographic Information
Book Title: Optimal Trajectory Planning and Train Scheduling for Urban Rail Transit Systems
Authors: Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
Series Title: Advances in Industrial Control
DOI: https://doi.org/10.1007/978-3-319-30889-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-30888-3Published: 03 May 2016
Softcover ISBN: 978-3-319-80909-0Published: 27 May 2018
eBook ISBN: 978-3-319-30889-0Published: 21 April 2016
Series ISSN: 1430-9491
Series E-ISSN: 2193-1577
Edition Number: 1
Number of Pages: XXI, 180
Number of Illustrations: 57 b/w illustrations, 2 illustrations in colour
Topics: Control and Systems Theory, Transportation Technology and Traffic Engineering, Landscape/Regional and Urban Planning, Transportation