RFI for AI-Enabled Incident Response System
Overview
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SUMMARY
KEY REQUIREMENTS
BUDGET
VerifiedCONTRACT DURATION
TIMELINE
October 15th, 2026: Response due date.
18 months: Period of performance from the effective date of award.
CONTACTS
Primary procurement contact — name, title, email, and phone
Additional decision-makers and their departments
Issuing Agency
Federal Highway Administration
DESCRIPTION
The issuing organization is seeking information from vendors regarding an AI-enabled incident response system for traffic incident scenarios. The effort will examine autonomous and semi-autonomous navigation capabilities, including navigation algorithms, path planning, obstacle avoidance, and control methodologies validated in real-world or field-test environments.
The RFI will also evaluate artificial intelligence applications for real-time data processing and automated decision-making, with particular emphasis on vision-language models. It will consider human-AI collaboration, including systems that operate alongside human copilots or responders through collaborative workflows and task-sharing.
The anticipated solution should address computing architecture, battery usage, and thermal management; support AI-aided autonomous or automated navigation toward incident sites based on real-time observations and updated instructions; and integrate vision-language models with edge and cloud pipelines for real-time incident data collection, processing, and first response. Vendors are expected to provide recommendations and insights to support this effort.
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Frequently asked questions
- When is the submission deadline?
- This RFP closed on October 15, 2026 and is no longer accepting submissions.
- What is the budget for this RFP?
- The published budget is $321,000.
- Who issued this RFP?
- It was issued by Federal Highway Administration. The work is located in Washington, District of Columbia, United States.
- Who is a good fit for this opportunity?
- AI and autonomous navigation technology provider
- Experience with traffic incident response or public safety applications
- Expertise in vision-language models and real-time computer vision
- Capability to integrate edge computing, cloud platforms, and field systems
- Experience with human-AI collaboration and autonomous robotics
- Demonstrated real-world or field-test validation of navigation solutions
Analysis generated by Settle AI from the source RFP.
RFP Hunter shows what is open. Settle shows what is forming.
Settle pieces together buyer signals, budgets, contract activity, and the sources your team already monitors. See why an opportunity fits and what to do before the RFP posts.