SBIR/STTR Research Award

Predictive Analytics-Based US Inland Waterways Voyage Planning Analysis Tool (VSAT)

Award identifier 9361d08363e201c839f9b9bedb1d4010c509e045483aaf59e0e9a9fad58f3398Awarding agency Department of Energy

Award amount

$150,000

Program and phase

STTR · Phase I

Award year

2018

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
TRABUS
Proposal award date
2018-04-09
Contract end date
2018-10-08
UEI
GUVDFLFNAB87
Solicitation number
DE-FOA-0001770
Topic code
01a

Research abstract

Trabus Technologies (TRABUS), working with Louisiana State University (LSU), will develop a predictive analytics-based US Inland Waterways Voyage Planning Analysis tool to help vessel traffic managers, tow boat pilots, and river lock operators maximize transport logistic resources. This tool will use current and forecasted hydrographic, meteorological, lock status, and Marine Safety Information to help commercial cargo operators and the Marine Industry determine optimal barge loading and tow configuration for any specified commodity/cargo movement. When planning any journey using US Inland Waterways, commercial cargo operators must manually consider a vast range of complex factors to determine optimal load for every vessel to ensure efficient and safe passage for its entire journey, which often includes rapidly-changing environmental conditions. For example, a 4-inch change in river level (from rain a week after departure) correlates to a 72-ton variance in a large barge’s capacity; operators must predict this change or risk hundreds of thousands of dollars of revenue per journey. A machine learning based predictive tool to rapidly process current and forecasted conditions would provide the Marine Industry with greater voyage planning and efficient transport management. Developed by TRABUS for the US Army Corps of Engineers (USACE), the River Information Services Enterprise (RISE) provides the technical framework enabling collection, integration, and exchange of navigation and vessel logistics information for safe, efficient, reliable, and environmentally responsible navigation between the Marine Industry and Government. Develop predictive algorithms and data-driven analytics for a commercial cloud-based Voyage/Transport Planning Service to maximize transport commodities and minimize intermodal transfers. Leverage ongoing RISE BigData efforts to analyze data from US Geological Survey (USGS), USACE Lock Performance Monitoring System, US Coast Guard’s Notice to Mariners, and Marine Industry’s barge, vessel, commodity, and supply chain data. LSU will leverage its ongoing BigData expertise with NOAA, National Weather Service, and USGS data to develop the methodology.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

5 SBIR/STTR records share this UEI (2018–2025). Reported award amounts total $1,573,993. Reported amounts are not federal obligations.

Phases: Phase I, Phase II – Direct to Phase II

Agencies: Department of Defense, Department of Energy

Agency intelligence

Department of Energy

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