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Computer Simulation in Real Time Rail Traffic Control

File Language:
English


Details

  • Creators:
    Kraft, Edwin Reese
  • Corporate Creators:
    University of Pennsylvania. School of Engineering and Applied Science
  • Subject/TRT Terms:
  • Resource Type:
    Thesis
  • Right Statement:
    Public Domain
  • Geographical Coverage:
    United States
  • Corporate Publisher:
    University of Pennsylvania
  • Abstract:
    This thesis examines the use of computer-based dispatcher assist systems for real-time rail traffic control on heavily used single-track rail lines. It focuses on the problem of planning train meets and passes so that total delay is minimized while supporting dispatcher decision-making. The study evaluates methods for predicting point-to-point train running times and analyzes operating data to measure the variability of actual train performance. The results show that train running times are highly variable, and that this uncertainty must be incorporated directly into dispatching logic. Building on this finding, the thesis develops local and global optimization procedures for meet planning, including methods that account for train priorities, running times, acceleration penalties, and uncertainty in future arrivals. A branching procedure is also presented to search alternative meet-pass strategies and identify minimum-delay solutions under uncertain conditions. The thesis concludes that computerized dispatcher assist can improve rail line efficiency when it provides accurate, flexible, and interactive support rather than rigid automatic control, and it includes FORTRAN code implementing the proposed algorithms in the appendix.
  • Content Notes:
    Public Domain, except where noted in the document. Edwin Reese Kraft. (1983). Computer simulation in real time rail traffic control [Master’s thesis, University of Pennsylvania].
  • Format:
    PDF
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:5c18b89ffafc19ba5d6329f31f683487eb1978f98a297260eba95918f2ea1caa8452a1ee14132af0d5fccf32bd280fb689b4b7c354524ed1b4dbb516bc17998d
  • Download URL:
  • File Type:
    Filetype[PDF - 1.71 MB ]
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