Browsing Transportation, Logistics, and Finance by Author "Dhingra, Neeraj"
Now showing items 1-5 of 5
-
Detecting Sources of Ride Roughness by Ensemble Connected Vehicle Signals
Bridgelall, Raj; Bhardwaj, Bhavana; Lu, Pan; Tolliver, Denver D.; Dhingra, Neeraj (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. ... -
Enhancement of Signals from Connected Vehicles to Detect Roadway and Railway Anomalies
Bridgelall, Raj; Chia, Leonard; Bhardwaj, Bhavana; Lu, Pan; Tolliver, Denver D.; Dhingra, Neeraj (2019)Frequent network-wide monitoring of the condition of roadways and railways prevent fatalities, injuries, and financial losses. Even so, agencies cannot afford to inspect vast transportation networks using present methods. ... -
Ranking Risk Factors in Financial Losses From Railroad Incidents: A Machine Learning Approach
Dhingra, Neeraj; Bridgelall, Raj; Lu, Pan; Szmerekovsky, Joseph; Bhardwaj, Bhavana (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 ... -
Signal Feature Extraction and Combination to Enhance the Detection and Localization of Railroad Track Irregularities
Bhardwaj, Bhavana; Bridgelall, Raj; Lu, Pan; Dhingra, Neeraj (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 ... -
Signal Filter Cut-off Frequency Determination to Enhance the Accuracy of Rail Track Irregularity Detection and Localization
Bhardwaj, Bhavana; Bridgelall, Raj; Chia, Leonard; Lu, Pan; Dhingra, Neeraj (2019)A continuous condition monitoring system to detect and localize railroad track irregularities is achievable with inertial sensors onboard revenue service trains. However, the inaccurate geospatial position estimates of GPS ...