Estimating Freight Activity on Major Highways with the Freight Analysis Framework (FAF)

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Bureau of Transportation Statistics Estimating Freight Activity on Major Highways with the Freight Analysis Framework (FAF) Geospatial Interest Group of the Federal Committee on Statistical Methodology October 16th, 2015 Michael Sprung Total Domestic Exports 1 Imports 1 Total 20,063 17,950 914 1,199 Truck 13,955 13,732 120 103 Rail 1,858 1,681 82 94 Water 808 410 89 309 Air, air & truck 15 3 5 7 Multiple modes & mail 1,554 459 559 536 Pipeline 1,539 1,391 11 137 Other & unknown 333 274 47 13

Understanding Freight Transportation How much & what freight moves from place to place? Weight Value Type of commodity Where & how is freight moving? Origin & destination Route used Mode of transport When is freight being carried? Season Time of day

What FAF Does Estimate current and future volumes of freight moving within and between regions by mode and commodity Assigns truck flows on highway corridors Identify baseline conditions for a better understanding where there are freight-related challenges Forecast the pressure future freight flows would place on the existing highway network

What FAF Does Not Do Estimate flows precisely within local regions and on individual routes Estimate temporal variations in freight flows Include effects of capacity limitations on forecasts of future demand Forecast future capacity expansion Adjust for changes in costs of transportation

FAF Data Products A tabular database of regional O-D freight flows by tons and value for all modes, including annual provisional updates, and long-range forecasts 2013 Total Domestic Exports 1 Imports 1 Total 20,063 17,950 914 1,199 Truck 13,955 13,732 120 103 Rail 1,858 1,681 82 94 Water 808 410 89 309 Air, air & truck 15 3 5 7 Multiple modes & mail 1,554 459 559 536 Pipeline 1,539 1,391 11 137 Other & unknown 333 274 47 13 An assignment of the average number of freight-hauling trucks to individual highway segments on the national network 5

FAF Data Product Details Regional O-D Database Tons & value Origin/destination All modes Commodity detail Base year, most recent year, & forecast years Accessed with tabular data software or create subsets using the online data tabulation tool Network Database Avg. Daily traffic counts on highway segments Highway only No origin/destination No commodity detail Base year and 30 year forecast Accessed with GIS software 6

Origin-Destination Database Details Value & weight for all domestic, export, & import shipments 8 Domestic modes (truck, rail, water, air, multiple modes & mail, pipeline, other & unknown, and no domestic mode) 7 Foreign modes 131 Domestic regions 8 International regions (Canada, Mexico, & 6 groupings of all other countries) 43 Commodity classes (2-digit SCTG codes)

FAF Regions

Network Database Details Approximately 450,000 miles of the nation s highways where trucks are permitted to operate Route type FAF trucks (freight hauling trucks) All trucks All highway vehicles Capacity measures Volume to capacity ratios Base and forecast year

FAF Network Coverage All interstate highways Non-interstate NHS routes NN routes not part of NHS Other rural and urban principal arterials Intermodal connectors Rural minor arterials for those counties that are not served by either NN or NHS routes Urban bypass and streets as needed for network connectivity

Routable FAF Network

Network Assignment Components O-D matrix Routable highway network Truck payload factors (VIUS & VTRIS) Empty trucks estimate (VIUS) Calibrated O-D disaggregation Assignment model Traffic counts (HPMS) Network capacity/restrictions Impedance factors

O-D Disaggregation More than 4600 O-D centroids created based on several factors: County Business Patterns Truck based distribution centers Warehouse clusters Rail/Truck intermodal facilities Secondary disaggregation at international freight gateways: Land border crossings Water ports Calibrated trip distribution model applied to account for the spatial interaction of freight movements

Trucks on the Network

Major Truck Freight Flows by State

Diversion Analysis Example May 2011 - a section of I-40 in Arkansas was closed due to flooding from the White River Major non-interstate routes in the surrounding area were also flooded or closed because of the possibility for flooding Of the ~31,000 vehicles that cross the I-40 White River Bridge on an average day, an estimated 60% are large commercial vehicles

Pre-Scenario FAF Truck Flow (Local)

orrilton Post-Scenario FAF Truck Flow (Local) M anila Jonesboro Batesv ille O sceola Trumann N ew port 55 M arked T ree Greers Ferry Lake H eber S prings Bald Knob E arle S earcy Mississippi River Wy nne 240 40 40 40 C onw ay Memphis 55 Beebe Ward F orrest C ity Lake Maumelle 430 Little Rock 440 40 Brinkley 40 M aumelle H ernando Lonoke M arianna Tunica 30 S enatobia E ngland West H elena 55 S tuttgart S ardis 530 S heridan FAF Truck Volume/Day Batesv ille D e Witt 50,000 25,000 12,500

Pre-Scenario FAF Truck Flow (Regional)

Post-Scenario FAF Truck Flow (Regional)

Change in FAF Truck Flow (Regional) 18% Increase 28% Increase

Freight Flows by Highway, Railroad and Waterway

Accessing FAF Data U.S. DOT Freight Page: http://freight.dot.gov/ FHWA Website: http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/index.htm BTS Website www.bts.gov Fall 2015

Moving Forward BTS 2012 benchmark O-D data by commodity and mode Provisional annual updates FHWA Long range forecasts of O-D Network assignment of truck flows

Upcoming Releases FAF4 O-D data benchmarked to 2012 CFS October 2015 Long-range forecasts through 2045 January 2016 Network assignment, and highway flow maps March 2016 Historical data for 1997, 2002, and 2007 May 2016 Domestic ton-miles and distance bands Summer 2016 26

Thank You For additional information on BTS programs and products visit: www.bts.gov For additional information on USDOT freight data programs and products visit: www.freight.dot.gov Michael Sprung michael.sprung@dot.gov (202) 366-9047 Without Data It s Just An Opinion.