Energy-saving metro train timetable rescheduling model considering ATO profiles and dynamic passenger flow

Zhuopu Hou, Hairong Dong, Shigen Gao, Gemma Nicholson, Lei Chen, Clive Roberts

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
534 Downloads (Pure)

Abstract

For metro systems in over-crowded conditions, when an unexpected disturbance occurs, the operation of trains might be disturbed due to the high frequency and density of the metro traffic. A large number of passengers might be stranded on platforms due to service gaps and the limited free capacity of trains. In this paper, by introducing binary variables as selection indicators for ATO profiles which were preset in on-board ATO systems by metro signal suppliers, we develop a mixed integer programming (MIP) model for a metro train timetable rescheduling problem in order to jointly optimize the total train delay, the number of stranded passengers, and the energy consumption of trains. We formulate the total energy consumption as the difference between the tractive energy consumption and the regenerated energy by considering the mass of in-vehicle passengers. Then, we adopt commercial optimization software CPLEX to solve the proposed model, which can obtain tradeoff solutions in a short time. Finally, three numerical experiments based on real-world operational data are carried out to verify the effectiveness of the proposed method.
Original languageEnglish
Article number8684279
Pages (from-to)2774-2785
Number of pages12
JournalIEEE Transactions on Intelligent Transportation Systems
Volume20
Issue number7
Early online date9 Apr 2019
DOIs
Publication statusPublished - Jul 2019

Keywords

  • Metro train timetable rescheduling
  • mixed integer programming
  • ATO profile

Fingerprint

Dive into the research topics of 'Energy-saving metro train timetable rescheduling model considering ATO profiles and dynamic passenger flow'. Together they form a unique fingerprint.

Cite this