U.S. DOT FY 2026 Phase I Pre-Solicitation Q&A
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45 results found
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Private-Sector Use Case
For Topic 26-OS2, may a private-sector freight operator, logistics provider, or transportation management environment serve as the primary Phase I use case if the solution is designed for future integration with public-sector corridor management systems?
1 vote -
Model Baseline and Delay Definition
For Topic 26-OS2, should applicants compare the predictive model against a specific baseline and use a preferred definition of “freight delay,” such as travel time increase, missed delivery window, dwell time, congestion probability, or route deviation?
1 vote -
Commercial Freight Data
For Topic 26-OS2, are aggregated, anonymized, or proprietary commercial freight datasets acceptable for Phase I model development if carrier, customer, and shipment confidentiality are protected and data limitations are documented?
2 votes -
Corridor Type and Scale
For Topic 26-OS2, does DOT have a preferred type or scale of Phase I corridor, such as urban, rural, intermodal, port-related, manufacturing, cross-border-adjacent, or nationally significant interstate freight corridors?
1 vote -
International Trade Corridor Impacts
For Topic 26-OS2, may a Phase I proof of concept account for Canada/Mexico border-adjacent congestion, customs-related dwell time, or cross-border freight disruption variables if the model remains focused on a selected U.S. freight corridor or segment?
1 vote -
Interoperability / Architecture
For Topic 26-OS2, are there preferred interoperability standards, data schemas, APIs, geospatial formats, or architecture expectations for compatibility with State DOT systems, commercial telematics platforms, freight carrier systems, and visualization tools such as ArcGIS, Power BI, or Tableau?
1 vote -
Synthetic / Simulated Data
For Topic 26-OS2, may Phase I applicants use synthetic freight datasets or simulated corridor conditions when live operational data is not yet available, provided the proposal documents assumptions, limitations, and a validation approach?
1 vote -
Would DOT consider a topic on hardware-level cargo authentication technology for trailers and rail containers?
Would DOT consider a topic on hardware-level cargo authentication technology for trailers and rail containers? Cargo theft is a multi-hundred million dollar problem in the US and the CORCA bill identified a gap in physical security at the asset level. More advanced authentication locks that operate 100% offline have no current representation in the SBIR portfolio.
1 vote -
For the Desired Outcome “Commercial and Implementation Readiness Assessment"
For the Desired Outcome “Commercial and Implementation Readiness Assessment”, what constitutes the minimum acceptable evidence of a commercialisation pathway — a Letter of Interest from a single state DOT or logistics partner, or are commitments from multiple stakeholders expected at Phase I?
1 vote -
For Technical Parameter TP-4 (federated learning)
For Technical Parameter TP-4 (federated learning): does Phase I require a live multi-party FL deployment involving distinct legal entities sharing model updates, or is a simulated federation — two data partitions on the same infrastructure representing separate jurisdictions — sufficient as a Phase I architecture demonstration?
1 vote -
Technical Parameter TP-1 requires deploying “low-power edge AI devices at strategic freight bottlenecks.
Technical Parameter TP-1 requires deploying “low-power edge AI devices at strategic freight bottlenecks.” For Phase I, is a benchtop hardware prototype or hardware-in-the-loop simulation of the edge device sufficient to demonstrate technical feasibility, or does Phase I require actual field deployment at a freight interchange?
1 vote -
For Technical Parameter TP-3 (synthetic data generation), does the DOT expect the generator to produce freight-domain-specific
For Technical Parameter TP-3 (synthetic data generation), does the DOT expect the generator to produce freight-domain-specific synthetic trajectories and delay events, or is general-purpose tabular synthetic data augmentation acceptable as a Phase I implementation of this capability?
1 vote -
For the Freight Corridor Predictive Intelligence topic, is preference given to solutions that provide dual functionality — simultaneously mo
For the Freight Corridor Predictive Intelligence topic, is preference given to solutions that provide dual functionality — simultaneously monitoring both commercial vehicle health and the structural integrity of the weigh station platform itself using the same sensor array?
1 vote -
Data integration plan — strategy document or working ingest pipelines?
Is this more of a strategy document, or do you want to see working ingest pipelines for at least some of the data sources by the end?
1 vote -
Digital twin expectation — microsimulation, generative AI, or existing platform integration?
For the digital twin piece — are you thinking more along the lines of physics-based microsimulation (Aimsun, SUMO, Vissim), or a generative AI model trained on real corridor traces? And is the program open to building on top of an existing digital-twin platform, or would you rather see something built from scratch?
1 vote -
Priority among data sources, and are licensed feeds (NPMRDS, ATRI) government-furnished?
Is there a priority order on the data sources? We're weighing NPMRDS, ATRI, state WIM, FAF, TPIMS, and connected vehicle BSMs, and it'd help to know which ones the program sees as most important. Also, for the licensed ones like NPMRDS and ATRI — are those typically furnished to awardees, or should we plan to budget for them?
1 vote -
Clarification on 80% accuracy target — spatial unit and error metric?
Quick clarification on the 80% accuracy target for 30–60 minute forecasts — is that measured at the segment level, at specific bottlenecks, or across full origin-destination pairs? And what error metric are you using? Whether it's MAPE on travel time vs. classification accuracy on a congestion label changes the modeling approach quite a bit.
1 vote -
1 vote
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1 vote
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1 vote