Near-Real-time Health Monitoring and Assessment of a Railway Track system

Transportation plays a crucial role in shaping societal equity, and addressing disparities in accessibility and mobility is a pressing challenge faced by government and private agencies. Ensuring the safety and efficiency of railway track systems is of paramount importance in the dynamic landscape of modern transportation. The extensive rail network in the United States serves as a lifeline for the mobility of people and goods, underscoring the critical need for robust methods to evaluate, monitor, and predict the health of rail infrastructure. The primary aim of this research is to create an evaluation framework that enables the rigorous analysis of the equity implications of various transportation policies, especially within the context of the Washington DC area. By using advanced machine learning techniques to enable near-real-time assessment and early warning of railway track conditions, this research will seek to bridge the existing gap by developing an innovative evaluation framework that quantifies and assesses the equity impact of diverse transportation policy initiatives prior to implementation. This study focuses on the intersection of "equity" and "transformation" and as a result, aligns with the United States Department of Transportation's plan of ensuring transportation equity through assessment, investment, enhancement, and coordination.


  • English


Subject/Index Terms

Filing Info

  • Accession Number: 01919545
  • Record Type: Research project
  • Source Agency: Sustainable Mobility and Accessibility Regional Transportation Equity Research Center
  • Contract Numbers: 69A3552348303
  • Files: UTC, RIP
  • Created Date: May 23 2024 4:42PM