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Detecting Sources of Ride Roughness by Ensemble Connected Vehicle Signals
(2022)
It is expensive and impractical to scale existing methods of road condition monitoring for more frequent and network-wide coverage. Consequently, defects that increase ride roughness or can cause accidents will go undetected. ...
Signal Feature Extraction and Combination to Enhance the Detection and Localization of Railroad Track Irregularities
(2020)
Tracks are critical and expensive railroad asset, requiring frequent maintenance. The stress from heavy car axle loads increases the risk of deviations from uniform track geometry. Irregularities in track geometry, such ...
Ranking Risk Factors in Financial Losses From Railroad Incidents: A Machine Learning Approach
(2023)
The reported financial losses from railroad accidents since 2009 have been more than US$4.11 billion dollars. This considerable loss is a major concern for the industry, society, and the government. Therefore, identifying ...