I-ETMS™ Positive Train Control Passenger Braking Algorithm Enhancement – Phase II

Details

• Creators:
  Dasher, Jeremy ; Anaya, Rachel ; Morrison, Kenny
• Corporate Creators:
  Transportation Technology Center, Inc.
• Corporate Publisher:
  United States. Department of Transportation. Federal Railroad Administration
• Corporate Contributors:
  United States. Department of Transportation. Federal Railroad Administration. Office of Railroad Policy and Development ; United States. Department of Transportation. Federal Railroad Administration. Office of Research, Development and Technology
• Subject/TRT Terms:
  • Positive train control
  • Automatic train control
  • Braking
  • Braking performance
  • Field tests
  • Calibration
  • Algorithms
• Publication/ Report Number:
  DOT/FRA/ORD-23/36
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  May 24, 2018–November 22, 2021
• Contracting Officer:
  Jacobini, Francesco Bedini
• Description:
  The Federal Railroad Administration (FRA) funded Transportation Technology Center, Inc. (TTCI) to examine the performance benefits of four potential modifications to the current methodology used for passenger braking enforcement algorithms (EA) in the Interoperable Electronic Train Management System (I-ETMS™) Positive Train Control (PTC). Additionally, researchers developed a methodology for simulating PTC braking algorithm performance for Electric Multiple Unit/Diesel Multiple Unit consists. This process does not rely on brake pipe pressure changes and requires different information to be provided to the EA and simulation program. Finally, the project included field testing to demonstrate the modifications to the EA reflected operational data. Due to the global pandemic, equipment was limited and testing was conducted using available cars and locomotives. The testing was conducted using the baseline, Total Approach Management, tuned train type, and specified consist algorithms. An analysis of the test results showed that the enhancements could be used to improve the EA performance for certain scenarios.
• Format:
  PDF
• Funding:
  DTFR5311D00008L
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/71920/dot_71920_DS1.pdf
• File Type:
  [PDF - 3.81 MB]
• Collection(s):
  Federal Railroad Administration
• Main Document Checksum:
  urn:sha-512:5a1526f63118bb5b2c5db960adf1eb926174cfe97f01290c3a81bdf155f90de358cead3e7182324a689093244b4d40dc71cf10692e26e0cafadd5d3995a6eaa1