Development of an Adaptive Predictive Braking Enforcement Algorithm [Research Results]

Details

• Creators:
  Tse, Terry
• Corporate Creators:
  Transportation Technology Center, Inc.
• Corporate Contributors:
  United States. Department of Transportation. Federal Railroad Administration
• Subject/TRT Terms:
  • Algorithms
  • Automatic train control
  • Braking
  • Interoperability
  • Railroad safety
  • Positive train control
  • Adaptive control
  • Railroads
  • Safety and Human Factors
  • I85: Safety Devices used in Transport Infrastructure
• Publication/ Report Number:
  RR09-14
• Resource Type:
  Brief
• Geographical Coverage:
  Colorado ; United States
• TRIS Online Accession Number:
  01142468
• Edition:
  Research Results
• Corporate Publisher:
  United States. Department of Transportation. Federal Railroad Administration
• Abstract:
  Predictive enforcement braking is one of the key concepts behind positive train control (PTC) systems. If a train is on the verge of overrunning a target stopping location, such as an authority limit, the system enforces a brake application to stop the train safely short of the limit. The concept depends on an algorithm that can predict the stopping distance of the train. Errors in stopping distance prediction can result in target overruns, target underruns, or unnecessary enforcements, which can negatively impact railroad safety or operations. Due to the uncertainty of many parameters that affect stopping distance, PTC enforcement algorithms have traditionally used a target offset to ensure that no trains overshoot the target. But this can force the algorithm to be overly conservative, resulting in unnecessary or early warnings and enforcements. Federal Railroad Administration (FRA) contracted Transportation Technology Center, Inc.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/40520/dot_40520_DS1.pdf
• File Type:
  [PDF - 136.66 KB]
• Collection(s):
  US Transportation Collection ; Federal Railroad Administration
• Main Document Checksum:
  urn:sha256:4e6409f252e06eb65a57b074c7a465a162517da54f81eef38cb9099b6f443817