Implementation of Advanced Track Geometry Forecasting Models [Research Results]

Baillargeon, Jay P.; Wang, Jiajun; Ghodratighalati, Mohamad

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Implementation of Advanced Track Geometry Forecasting Models [Research Results]

2026-07-01
By Baillargeon, Jay P. ; Wang, Jiajun ; Ghodratighalati, Mohamad

File Language:

English

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Creators:

Baillargeon, Jay P. ; Wang, Jiajun ; Ghodratighalati, Mohamad
Corporate Creators:

ENSCO, Inc
Corporate Contributors:

United States. Department of Transportation. Federal Railroad Administration
Subject/TRT Terms:

Autonomous Track Geometry Measurement System Data Analysis Forecasting Geometry Plan Implementation Railroad Tracks Statistical Sampling Track Geometry
Publication/ Report Number:

RR 26-02
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Research Results
Corporate Publisher:

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

In 2022, the Federal Railroad Administration (FRA) contracted ENSCO to implement previously developed forecasting models for autonomous track geometry measurement systems (ATGMS) into an operational environment. This report describes the improvements to the track geometry foot-by-foot filtering and forecasting methods originally developed under those previous, FRA-funded research efforts (Sandikcioglu, 2024).
Format:

PDF
Funding:

693JJ6-22-F-00007N
Collection(s):

Federal Railroad Administration
Main Document Checksum:

urn:sha-512:71a061d452ecc457ef5a5c215ded0fcf993b0c5f53feef9fc8ecee755f61df3b55af0e1274beb28f396ef3734fde1d1d521e4d49e64bf7748ce9430aeee52c4d
Download URL:

https://rosap.ntl.bts.gov/view/dot/92793/dot_92793_DS1.pdf
File Type:

[PDF - 411.92 KB ]

File Language:

English

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