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Accident/Incident Reconstruction and Visualization

[+] Author Affiliations
Kevin J. Renze

National Transportation Safety Board, Washington, DC

Paper No. JRC2018-6265, pp. V001T02A015; 14 pages
  • 2018 Joint Rail Conference
  • 2018 Joint Rail Conference
  • Pittsburgh, Pennsylvania, USA, April 18–20, 2018
  • Conference Sponsors: Rail Transportation Division
  • ISBN: 978-0-7918-5097-8


Factual evidence from locomotive event data recorders (EDR), locomotive image data recorders, accident site surveys, witness marks, rail equipment, track structure, photographs, video cameras, AEI readers, hot wheel or hot bearing detectors, wayside signal bungalows, train consist documents, and radio communication is integrated, validated, and visualized in a three-dimensional model environment. The goal is to build a physics-based, data-driven model of train position as a function of time to enhance the documentation, investigation, understanding, and analysis of in-service train derailments. Methods to construct, validate, and interrogate time-accurate, interactive visualizations of train movements for partial and complete train consists are discussed and demonstrated. In-service freight train derailments that occurred in Hoxie, Arkansas (offset frontal collision between opposing freight trains), Casselton, North Dakota (unit grain train derailment with car fouling opposing mainline track and subsequent crude oil unit train head-on collision), and Graettinger, Iowa (unit ethanol train derailment) are used to illustrate the accident reconstruction method. Similar vehicle path reconstructions for recent highway, aviation, and marine investigations are also presented.



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