Conference Proceedings on the Web 22: Transforming the Marine Transportation System Through Multimodal Freight Analytics (2018) / Chapter Skim
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26 Breakout Session Summaries Introduction Kathleen Hancock, rapporteur he goal of this conference was to bring together public- and private-sector experts in marine transportation and freight analytics to share ideas and to open a dialogue toward a national high-fidelity freight flow model. Breakout sessions were grouped generally by research area and category.
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27 North Carolina has the most managed state roads, next to Texas, in the United States, and considers ramifications beyond the state line as demonstrated by its investment in rail facilities outside its borders to improve freight flows within the state. The North Carolina DOT and the analytic software company SAS began a project to generate data-driven solutions that would assist the North Carolina DOT with freight planning and help inform planners on the importance of freight.
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28 • Commodity flow survey freight production (lb/year) , • Freight shipments (shipments sent/day)
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29 Breakout Session 1B Data Analytics: Inland Waterways Joe Crabtree, Kentucky Transportation Center, presiding Jim Kruse, Texas A&M Transportation Institute, recording Presentations Inland Marine Transportation Data Integration: Extracting Additional Value from Publicly Available Data James Dobbins, FACTOR, Inc. Measuring the Network Impacts of Local Disruptions: An Inland Waterways Case Study Craig Philip, Vanderbilt University Modeling Dynamic Behavior of Navigable Inland Waterways Heather Nachtmann, University of Arkansas Quantifying the Impacts of Disruptions to the Inland Marine Transportation System Patricia DiJoseph, U.S.
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30 unusual spikes in activity or activity in unexpected locations that may indicate a business opportunity. Craig Philip noted that more frequent disruptions have occurred on the Ohio River over the past year or two and that environmental conditions have exacerbated already existing problems.
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31 were acquired from the USACE Lock Operations Management Application and the USCG Nationwide Automatic Identification System. The research developed and used the AIS Analysis Package.
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32 Breakout Session 1C Decision Support: Resilience Josh Murphy, National Oceanic and Atmospheric Administration, presiding Sandra Knight, WaterWonks, LLC, recording Presentations 2017 Hurricanes: A Resilient Path Forward for Marine Transportation System Federal Agencies Katherine Touzinsky, U.S. Army Corps of Engineers A GIS Inventory and Exposure Assessment for Critical Coastal Transport Infrastructure Land Use in the Caribbean Small Island Developing States Gerald Bove, University of Rhode Island Barriers to Climate and Extreme Weather Adaptations for Seaports: A Cultural Consensus Model for North Atlantic Medium and High-Use Port Decision Makers Elizabeth Mclean, University of Rhode Island Using Geographic Information Science to Evaluate Legal Restrictions on Freight Transportation Routing in Disruptive Scenarios Steven Peterson, Oak Ridge National Laboratory his session demonstrated the interdependencies of sectors and organizations when decisions are being made about recovery and responding to disasters.
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33 Several barriers and issues were identified by the presenters. These included • Poor communication and missing information during disasters, • Short-term investments over long-term solutions and misaligned time horizons, • Lack of ownership and leadership, • Decentralized requests and access to information and data, • Classified data complicating the use of remote sensing data, • Lack of data resolution at the local scale, and • Lack of funding and awareness keeping ports from implementing resilience measures.
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34 Breakout Session 2A Data Analytics: Maritime and Freight 2 Heather Nachtmann, University of Arkansas, presiding Matthew Chambers, Bureau of Transportation Statistics, recording Presentations Container Ship Routing and Scheduling with Multiple Time Windows Anastasios Charisis, Florida Atlantic University Modeling Agricultural Commodity Flows on the U.S. Railroads and Inland Waterways System Using Waybill and Waterborne Commerce Statistics Data Steven Peterson, Oak Ridge National Laboratory Short Sea Shipping Versus Trucking: A Cost–Benefit Analysis Using Mathematical Modeling Evangelos Kaisar, Florida Atlantic University ll modes of transportation are key for moving passengers and freight around the world.
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35 highway, rail, and waterways)
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36 to bridge the gap between the way the public- and private-sectors use data and how to chip away at the challenges of proprietary data by demonstrating how anonymized and aggregated freight data use by the public sector would benefit the private sector through improved public-sector decision-making and investment. Mark Berndt presented an optimization model focused on demonstrating how Quetica, a freight network planning company, has been able to integrate different data flows and use granular data to estimate supply chain flows.
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37 shutdowns or storms to determine impacts on ship movements, routing, dwell, and other issues that impact ship flows. Additionally, the AIS data can help in forensic analysis, for example, in pinpointing vessel locations and movement data when a near miss or accident occurs and in tracing the corresponding vessel movements.
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38 • Standards and methods are important because the information will be different depending on the methods used. The methodology used can provide different results.
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39 research also used bay time (the amount of time to discharge and load a fully loaded cargo bay of a container ship) and berth time (the amount of time between vessel docking and undocking, which is also a function of discharging and loading)
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40 becoming increasingly complex and costly to implement. TOSs also face development challenges, including • Central control instead of central intelligence; • Prevention of collisions; • Direct handshakes, which requires synchronization; and • Finding the optimal sequence of working orders [operations research (OR)
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41 • AIS data are shedding new light on port operations. • AIS data can be used to evaluate port mobility.
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42 as the most consistent predictor of more serious events. From this first broad analysis, the research concluded that near misses currently identified in MISLE may provide warning signs of future serious events and that the number of near misses from a previous year correlates with serious events in the following year.
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43 regulations. Questions from attendees centered on whether machine learning and algorithms could be introduced to automate some of this process.
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44 Transport Analysis Framework of the King Abdullah Petroleum Studies and Research Center: Building a Global Freight Network Model with Satellite and Automatic Identification System Data Hector Guillermo Lopez-Ruiz, King Abdullah Petroleum Studies and Research Center his was the third session related to the use and the promulgation of data analytics in the maritime and freight industries that focused on applications of analytics to improve decision makers' understanding of maritime and freight mobility needs. Amirhassan Kermanshah described his work for the Tennessee DOT.
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45 with computer-aided image identification, enabling the locating of commercial activity areas and urban-level freight origins and destinations. KEY TAKEAWAYS Three key themes emerged from this session: • Various emerging technologies can be harnessed to describe and understand freight and maritime activity and improve operations and decision-making.
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46 preprocesses, and understands heterogeneous data sources to answer a query. This type of artificial intelligence (AI)
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47 capabilities. To be a useful tool, it must be highly scalable, resilient, elastic, and capable for ingesting, organizing, and analyzing large volumes of freight-related data from multiple data streams.
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48 KEY TAKEAWAYS • Blockchain and machine learning applications may be leveraged to improve logistics and research of the maritime domain, but this action will require access to multiple, accurate, and complete data streams. • One speaker suggested that a natural-language use interface might be one solution to allowing better access to and analysis of transportation data.
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49 modeling was achieved. This improved modeling included vessel type classification with more specific vessel type/engine combinations, actual engine loads versus defaults, highly detailed spatial and temporal resolution, exclusion of state waters activities, and no spatial allocation or assumptions as activity is calculated in place.
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50 • Explore using data and analytic analysis to identify where modal shifts for cargo and freight are beneficial and cost-effective and make sense for system users.
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