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AI for System Engineering

Active
Federal

Contract Overview

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

AI Contract Overview

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The Federal Highway Administration within the Department of Transportation is seeking to implement a phased integration of artificial intelligence into its system engineering processes. This initiative will leverage existing ARCIT and SETIT resources alongside Model Based Systems Engineering to modernize the development of Intelligent Transportation Systems. Key objectives include the development of NLP tools to analyze project requirements for conflicts and the use of machine learning to predict project risks by analyzing historical data such as budgets and timelines. The scope of work further involves creating AI agents to assist architects in generating system architectures via SysML integration and automating the verification, validation, and testing process. Additionally, the project will focus on researching AI systems capable of monitoring operational ITS performance to recommend or implement architectural changes for improved resilience and efficiency. This forecast is categorized under NAICS code 541990.

General Info

FHWA seeks AI integration for system engineering to modernize Intelligent Transportation Systems development.

Agency

Department of Transportation → Federal Highway Administration (FHWA)

NAICS

541990 - All Other Professional, Scientific, and Technical Services

Place of Performance

USA

Set-Aside

NONE

Documents

0

No documents available

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AI Contract Breakdown

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Organization & Contact Information

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AgencyDepartment of Transportation → Federal Highway Administration (FHWA)
Contacts2 people available
OfficeN/A
Organization / AgencyDepartment of Transportation → Federal Highway Administration (FHWA)
Office AddressN/A
Contacts
Bob Sheehan
contact@example.gov
Ryan Mavis
contact@example.gov

Full Description

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Effort to support a phased approach to integrate AI into the system engineering process, leveraging existing resources ARCIT and SETIT, and emerging Model Based Systems Engineering MBSE.
Develop and pilot AI tools to assist in the analysis of ITS project requirements. This will involve using Natural Language Processing NLP to parse, categorize, and identify potential conflicts or ambiguities in text based requirements documents. Use machine learning to analyze historical ITS project data e.g., budgets, timelines, change orders, reported issues to predict potential risks and identify early warning signs of project failure. Develop AI agents that can assist systems architects in generating and evaluating system architectures. This will involve integrating AI into MBSE tools that use languages like SysML. Utilize AI to automate significant portions of the VVT process, which is often time consuming and manual. Research and develop AI systems that can monitor the performance of an operational ITS and recommend or even implement minor architectural or operational changes to improve efficiency or resilience.

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