Intelligent Automation, Inc. — Department of Defense SBIR Phase II: NGA192-004
Intelligent Automation, Inc. — SBIR Phase II award from Department of Defense.
Phase II SBIR prototype / development signal
- Phase II is where Department of Defense funds deeper R&D after feasibility. Incumbents with Phase II history are serious competitors on adjacent topics.
- Use this award as past-performance context and to map customer organizations for STRATFI/TACFI-style transition planning.
- Obligated amount $999,992 is consistent with substantial Phase II-scale effort; compare to related awards from the same agency.
- Topic code NGA192-004 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $999,992
- Agency
- Department of Defense · National Geospatial-Intelligence Agency
- Program / Phase
- SBIR · Phase II
- Topic
- NGA192-004
- Solicitation
- 19.2
- NAICS
- —
- Place of performance
- MD
- Period
- 2021-08-27 → 2023-08-31
Description
NGA seeks to incorporate Artificial Intelligence (AI) and Machine Learning (ML) into Intelligence, Surveillance, and Reconnaissance (ISR) missions to capture fleeting targets. As such, a large number of dynamic scenes with accurate target motions and behaviors will be needed for training and performance evaluation. The traditional microscopic model-based approach for vehicle activity simulation is unable to produce enough fidelity for the training and the evaluation of ISR tracking, analytics, or collection strategies. Intelligent Automation Inc. (IAI) proposes to develop a high-fidelity Vehicle Motion Simulation (VMS) system that includes a framework for SUMO (Simulation of Urban Mobility) based traffic simulation and validation with real-world roadway sensor data coupled with a deep reinforcement learning (DRL) model for activity simulation of target moving vehicles. In Phase I, we successfully demonstrated the feasibility of our proposed VMS framework and we have made significant progress towards the ultimate goals of this project. In Phase II, we plan to extend the scope of our simulation and reinforcement learning framework and build a full-fledged prototype software tool that addresses NGA’s needs.