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Optimal Trajectory Planning and Train Scheduling for Urban Rail Transit Systems

  • Yihui Wang
  • Bin Ning
  • Ton van den Boom
  • Bart De Schutter

Part of the Advances in Industrial Control book series (AIC)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 1-5
  3. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 7-21
  4. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 23-51
  5. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 53-80
  6. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 81-108
  7. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 109-134
  8. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 135-160
  9. Yihui Wang, Bin Ning, Ton van den Boom, Bart De Schutter
    Pages 161-162
  10. Back Matter
    Pages 163-180

About this book

Introduction

This book contributes to making urban rail transport fast, punctual and energy-efficient –significant factors in the importance of public transportation systems to economic, environmental and social requirements at both municipal and national levels.  It proposes new methods for shortening passenger travel times and for reducing energy consumption, addressing two major topics: (1) train trajectory planning: the authors derive a nonlinear model for the operation of trains and present several approaches for calculating optimal and energy-efficient trajectories within a given schedule; and (2) train scheduling: the authors develop a train scheduling model for urban rail systems and optimization approaches with which to balance total passenger travel time with energy efficiency and other costs to the operator.

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.

Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

Keywords

Urban Rail Systems Train Scheduling Trajectory Planning for Trains Model Predictive Control Optimization of Travel Time vs Operational Cost

Authors and affiliations

  • Yihui Wang
    • 1
  • Bin Ning
    • 2
  • Ton van den Boom
    • 3
  • Bart De Schutter
    • 4
  1. 1.Lab of Rail Traffic Control and SafetyBeijing Jiaotong University, State KeyBeijingChina
  2. 2.State Key Laboratory for Rail TrafficBeijing Jiaotong UniversityBeijingChina
  3. 3.Delft Center for Systems and ControlDelft University of TechnologyDelftThe Netherlands
  4. 4.Delft Center for Systems and ControlDelft University of TechnologyDelftThe Netherlands

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-30889-0
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-30888-3
  • Online ISBN 978-3-319-30889-0
  • Series Print ISSN 1430-9491
  • Series Online ISSN 2193-1577
  • Buy this book on publisher's site