Intent to Sole Source
Closed Special Notice Posted
- Solicitation number
- FR20RPD31000000046
- Agency
-
Federal Railroad Administration
Department of Transportation
- Responses due
- Set-aside
- No set-aside
Opportunity facts
- NAICS code
- 541715 Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
- Place of performance
- USA
Notice details come from SAM.gov. Updated .
About this opportunity
This Special Notice announces the Federal Railroad Administration's intent to award a sole source contract to the University of Illinois. The contract concerns continuing research using laser triangulation and deep neural networks for railroad track safety inspections. The first phase of this research developed methods applying artificial intelligence to laser-based data to detect track changes impacting safety.
The second phase aims to leverage prior phase products to establish relationships between track change and inspection data to produce reports for inspectors aiding safety and maintenance decisions. It will also establish metrics and reports supporting resource prioritization. Interested parties were to submit capability statements by September 10, 2020 to Moyah Wilson for consideration solely to determine whether to conduct this opportunity competitively. The continuation directly builds on prior research uniquely combining 3D laser data and deep learning for automated track defect detection transforming inspections.
Notice text
Use of Laser Triangulation and Deep Neural Networks (DNNs) for Railway Safety Inspections Phase 2, Synopses (Sole Source Intent Notice)
The Federal Railroad Administration (FRA), Washington, DC, intends to award a Sole Source, Cost-No Fee Contract to The University of Illinois for a a continuation of research begun under FRA Contract 693JJ619C000004 and is intended to develop and demonstrate the application of artificial intelligence to laser-based range and intensity data for railroad track safety inspection. This development effort is a unique combination of 3-dimensional laser data coupled with deep neural networks (DNN) to detect and report changes in railroad track that may impact operational safety and is a logical extension of successful research conducted by this team in the Phase 1 project. This Phase 2 effort is inexorably linked to the prior work, and will leverage the products produced during the Phase 1 effort to establish the relationships between track change data and traditional inspection methods, i.e. track geometry, to produce products for rail inspectors and maintainers that are directly consumable. This new work will also establish clear metrics and reports to aid decision makers during resource prioritization activities. Automated track change detection technologies are the next generation of inspection tools to ensure track safety. This project combines the unique talents and experience of a proven team and systems to create systems and products that will effectively transform the track inspection activity. This work is directly supported by rail industry partners to help ensure project success. The results of this development effort will be widely disseminated through the rail industry, via FRA publications, industry conference reports and presentations.
.
This synopsis is not a request for competitive proposals; however interested parties may identify their interest and capability to respond to the requirement. Respondents must provide a capability statement for a “Use of Laser Triangulation and Deep Neural Networks (DNNs) for Railway Safety Inspections Phase 2”. Oral communications are not acceptable in response to this synopsis. Interested parties with the capability of meeting the proposed requirements are requested to provide an E-mail to the FRA point of contact, Ms. Moyah Wilson, (moyah.wilson@dot.gov) no later than 3:00 p.m. EST Thursday, September 10, 2020. Such capabilities/qualifications will be evaluated solely for the purpose of determining whether or not to conduct this procurement on a competitive basis. A determination by the Government not to compete this proposed effort on a full and open competition basis, based upon responses to this notice, is solely within the discretion of the Government.
Files
| File | Type | Posted |
|---|---|---|
| Intent Notice.pdf |
Similar open opportunities
| Opportunity | Agency | Set-aside | Responses due |
|---|---|---|---|
| FY 26 Broad Agency Announcement (BAA) - Federal Railroad Administration | Federal Railroad Administration | No set-aside |
On GovTribe
Work this opportunity
- Track it in your pipeline
- Find teaming partners
- Similar opportunities
- Ask GovTribe AI about this opportunity