A simulation and decision-support tool for vulnerability reduction in hazardous material transportation via the U.S. IWTS
Stakeholders are faced with challenges in tracking and managing freight movement, evaluating human-infrastructure interactions (e.g., navigation, lockage), and suggesting alternative solutions in response to contingencies. On the other hand, vessel operators need to have good situational awareness to quickly and effectively avoid hazards and accidents. Among various types of products, hazard materials constitute a great portion of shipments. Such materials can be found in many forms on the U.S. inland waterway transportation system (IWTS), including petroleum products (e.g., diesel fuel, asphalt), chemicals (e.g., fertilizers, pesticides), and household and consumer products (e.g., paints, adhesives). Indeed, petroleum products make up over 75% of waterborne shipments. Compared to highways, rails and other modes of transportation for hazard materials, the waterways have the heaviest shipments. To minimize economic losses while ensuring safety and security during hazardous material transportation, it is invaluable to develop a computerized tool for sharing information and evaluating the impacts of a sequence of decisions, such as voyage planning and rerouting, on freight movement, costs and risks. With previous support from the National Science Foundation (NSF) and the Maritime Transportation Research and Education Center (MarTREC), this research team has developed an advanced NetLogo-based simulation tool that enables visualizing, evaluating and maintaining multimodal transportation infrastructure. This research project seeks to advance the simulation- and machine learning-based tool to help involved personnel understand how the IWTS currently performs, assess potential risks, and respond to various accidents and disruptions, especially those involving hazard material shipments. The goal is to provide an open-source software tool and machine learning-based decision-making approaches that assist the relevant stakeholders and operators in tracking hazardous material movement, making timely decisions, and enhancing the safety of the U.S. IWTS and beyond. The research findings to be achieved will be broadly disseminated to researchers and practitioners through research publications and presentations. The team will promote real-world applications of the tool by working with MarTREC partners and collaborators.
Language
- English
Project
- Status: Active
- Funding: $250,507.00
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Contract Numbers:
69A3552348331
- Sponsor Organizations: Washington DC, United States
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Managing Organizations:
Maritime Transportation Research and Education Center (MarTREC)
University of Arkansas
4190 Bell Engineering Center
Fayetteville, AR United States 72701 -
Performing Organizations:
University of Arkansas, Fayetteville
Department of Industrial Engineering
Fayetteville, AR United States 72701 -
Principal Investigators:
Liao, Haitao
Zhang, Shengfan
Nachtmann, Heather
- Start Date: 20250101
- Expected Completion Date: 20260630
- Actual Completion Date: 0
- USDOT Program: UTC
Subject/Index Terms
- TRT Terms: Decision support systems; Hazardous materials; Inland water transportation; Machine learning; Research projects; Simulation
- Geographic Terms: United States
- Subject Areas: Data and Information Technology; Marine Transportation; Operations and Traffic Management; Research; Safety and Human Factors; Security and Emergencies;
Filing Info
- Accession Number: 01944521
- Record Type: Research project
- Source Agency: Maritime Transportation Research and Education Center (MarTREC)
- Contract Numbers: 69A3552348331
- Files: UTC, RIP
- Created Date: Jan 29 2025 5:11PM