Automated Track Change Detection Technology for Enhanced Railroad Safety Assessment

Harrington, Ryan; de Oliveira Lima, Arthur; Edwards, J. Riley; Dersch, Marcus S.; Fox-Ivey, Richard; Laurent, John; Nguyen, Thanh

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Automated Track Change Detection Technology for Enhanced Railroad Safety Assessment

2023-04-01
By Harrington, Ryan ; de Oliveira Lima, Arthur ; Edwards, J. Riley

File Language:

English

Details

Creators:

Harrington, Ryan ; de Oliveira Lima, Arthur ; Edwards, J. Riley ; Dersch, Marcus S. ; Fox-Ivey, Richard ; Laurent, John ; Nguyen, Thanh
Corporate Creators:

University of Illinois at Urbana-Champaign ; Pavemetrics Systems, Inc.
Corporate Contributors:

United States. Department of Transportation. Federal Railroad Administration. Office of Railroad Policy and Development ; United States. Federal Railroad Administration. Office of Research, Development, and Technology
Subject/TRT Terms:
Publication/ Report Number:

DOT/FRA/ORD-23/13
Resource Type:

Tech Report
Geographical Coverage:

United States
Contracting Officer:

Stuart, Cameron
Corporate Publisher:

United States. Department of Transportation. Federal Railroad Administration
Abstract:

The Rail Transportation and Engineering Center at the University of Illinois at Urbana-Champaign and Railmetrics, Inc. evaluated the use of 3D laser scanning, Deep Convolutional Neural Networks (DCNNs), and change detection technology for railway track safety inspections. Researchers evaluated the potential use of these combined technologies to provide value-added inspection data to traditional track inspection methods. The project was conducted between April 2019 and October 2020. Field testing was completed on the High Tonnage Loop at the Transportation Technology Center in Pueblo, Colorado.
Format:

PDF
Funding:

693JJ619C000004
Download URL:

https://rosap.ntl.bts.gov/view/dot/67233/dot_67233_DS1.pdf
File Type:

[PDF - 9.80 MB]
Collection(s):

Artificial Intelligence Deployment Center of Excellence (AI COE) ; Federal Railroad Administration
Main Document Checksum:

urn:sha-512:93ba91662ae0b6a1fb9386b6f0923e6d7f310c5b28a71ecd9be520f60725016facf767d3af846b201b3c0dfe976fac41292ef9c1b789f70fd0abb0fa4b518b8d

File Language:

English

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