A dynamic model for quantifying rail–highway grade crossing roughness

Teng Wang, Reginald R. Souleyrette, Ahmed K. Aboubakr, Daniel Lau

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Annually, more than 2,000 rail–highway crossing crashes in the United States result in nearly 300 fatalities. Crossing roughness is a concern for the motoring public from a comfort and vehicle maintenance perspective, and to highway authorities from a maintenance perspective. Roughness may even increase the risk of crossing crashes. However, with 216,000 rail–highway grade crossings in the United States, maintenance management is a large undertaking. Crossings deteriorate over time, sometimes rapidly, and life-cycle costs increase without preventive maintenance. However, though methods are available to quantify highway roughness, no method exists to quantitatively assess the condition of rail crossings. Because conventional inspection relies on qualitative judgment based on an inspector's perception of the crossing, effect on different vehicles and perception by other drivers are unknown. Further, roughness may be due to as-built geometry, deterioration, or a combination of both. A quantifiable and extensible procedure is thus desired. The article details the use of 3D surface models and a customized vehicle dynamic model to predict accelerations experienced by highway vehicles using the crossing. The model is validated with field-measured accelerations. Results indicate good agreement between modeled and measured accelerations for a test vehicle at several speed ranges at two different locations.

Original languageEnglish
Pages (from-to)70-82
Number of pages13
JournalJournal of Transportation Safety and Security
StatePublished - Jun 30 2016

Bibliographical note

Publisher Copyright:
© 2016 Taylor & Francis Group, LLC and The University of Tennessee.


  • field research
  • highway
  • infrastructure design
  • railway
  • simulation

ASJC Scopus subject areas

  • Transportation
  • Safety Research


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