Government agencies are seeking a better understanding of changing transportation needs and impacts as the U.S. expands domestic fuel production of petroleum, natural gas, and alternative fuels in order to use federal policies and regulations to foster a supply chain that minimizes environmental and safety impacts.
To analyze potential fuel options, the Federal Aviation Administration (FAA), the Department of Energy (DOE), and the U.S. Navy’s Office of Naval Research have turned to U.S. DOT's Volpe Center to develop a national model for evaluating optimal freight and fuel transport patterns, costs, and impacts.
Volpe has developed the Freight and fuel Transportation Optimization Tool (FTOT) in support of FAA, DOE, and the Navy’s Office of Naval Research.
This tool is designed to analyze the transportation needs and constraints associated with fuel and raw material collection, processing, and distribution in the continental United States.
How it Works
FTOT is a flexible scenario-testing tool designed to analyze a variety of commodities, datasets, and assumptions, and is customizable to the particular needs of a user. The tool analyzes local, regional, and national scenarios based on raw material origins, destinations, transportation cost estimates, weightings, and parameters for converting or refining materials (see illustration below).
Optimal routing and flows are evaluated through an optimization module and a geographic information system (GIS) module that enable powerful mapping and display capabilities.
The tool uses a unique intermodal network constructed at Volpe from private and public data sources on truck, rail, water, and pipeline links.
With the GIS component, Volpe logistics experts can look at how commodities and materials flow over the transportation enterprise—using either actual or hypothetical infrastructure, like anticipated network links or potential refineries. A network template then knits together parameters on costs and other factors into the nation’s multimodal network, and then generates route options among origins and destinations.
Outputs of optimized scenarios for transporting material include material/commodity flows, costs, CO2 emissions, fuel burn, number of vehicle trips, and distance by mode for each link in the network, which can then be aggregated in various ways. The model also takes into account temporal schedules for facilities to assess how variations in demand, production, or processing operations influence the overall scenario results.
FTOT helps government agencies analyze freight and fuel transport options and hone in on multimodal transportation flow patterns and emissions associated with future freight and energy scenarios.
Volpe experts use FTOT to help FAA understand how much alternative jet fuel can be produced in the near term. Analyses focus on the availability of commodities like residues from timber harvesting, tallow from slaughterhouses, and municipal solid waste. With FTOT, Volpe experts can use projected availability of those materials out to 2030 and anticipated demand to analyze how they would flow optimally over the transportation network.
For DOE’s Energy Policy and Systems Analysis group, Volpe experts examine crude oil and coal scenarios. Working with Oak Ridge National Lab data, these analyses drill down to county-to-county flows of crude oil and coal. Volpe experts use FTOT to map these data and identify the best paths for these materials—optimizing routes according to transportation costs, routing preferences, and other factors related to processing capacity and cost.
Volpe experts are working to enhance FTOT’s suite of capabilities in several areas. One enhancement is to introduce capacity constraints, such as the maximum number of vehicles that could travel on a particular road over current levels, after which additional flows would need to be re-routed. The team also anticipates delving into more detailed regional analyses with sponsors and partners.
 A scenario-testing tool does not predict future conditions but is used to test effects of potential future scenarios.