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AI & Machine Learning for Rail Safety

Active
Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The AI and Machine Learning for Rail Safety subcontract focuses on developing advanced predictive analyses and computer learning models to support prime contractors on Federal Railroad Administration projects. The scope of work includes creating predictive models for PTC system performance and fault detection, as well as implementing computer vision models designed to identify risky trespasser behavior near railroad tracks and crossings. The selected provider will be responsible for delivering AI algorithms, predictive models, and comprehensive validation reports. This effort falls under NAICS code 541511 and is managed under the Department of Transportation. The response deadline for this opportunity is September 30, 2027.

General Info

AI and ML subcontract for FRA rail safety, predictive models, and computer vision.

Agency

Department Of Transportation → Federal Railroad AdministrationView Agency

NAICS

541511 - Custom Computer Programming ServicesView NAICS

Place of Performance

USA

Set-Aside

NONE

Documents

This scope was carved out of 693JJ626R000001.

The full solicitation package (11 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

FY 26 Broad Agency Announcement (BAA) - Federal Railroad Administration

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Timeline

Posted

subcontract

Response Deadline

Submission deadline

Response Deadline

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Organization & Contact Information

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AgencyDepartment Of Transportation → Federal Railroad Administration
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of Transportation → Federal Railroad Administration
View Agency Profile
Office AddressN/A
ContactsNo contact information available

Full Description

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Develops AI and Computer Learning (CL) predictive analyses for prime contractors on Federal Railroad Administration projects. Creates predictive models for PTC system performance, fault detection, and computer vision models to identify risky trespasser behavior around railroad tracks and crossings. Delivers AI algorithms, predictive models, and validation reports.

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