Ask the Experts – Commodity Flow Databases in MPO Travel Demand Models

How can subarea extraction methods be used to convert national commodity flows into travel demand models for MPOs?

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The travel demand models used for Metropolitan Planning Organizations (MPOs) often depend on subarea extraction methods in order to conduct more focused studies within a defined geographic area. Subarea extraction is one of the typical processes employed to develop the tools to support such studies. To develop a subarea model from a larger (typically regional) model involves defining the spatial limits of the subarea and then extracting a subarea network and its corresponding trip table. This method was used in a study by The Port Authority of New York and New Jersey (PANYNJ) to improve freight flow along the bridges of the Hudson River. This same method has also been used for a project reporting flows for: the PANYNJ Regional Gods Movement Plan; the New Jersey Department of Transportation (DOT) Freight Plan; the Houston Galveston Association of Governments (HGAC) Freight Plan; and is currently being used for the MetroPlan Orlando Regional Freight Plan.

In an effort to seek project alternatives designed to improve freight movement to, from, and through New York City and the northern New Jersey region, PANYNJ undertook the Cross Harbor Freight Movement Program. The program includes the completion of an ongoing Environmental Impact Statement. To analyze the impacts of these alternatives, the PANYNJ needed an estimation of the diversion of goods movement among modes based on their performance. To analyze the benefits, the diversion was estimated by modifying a national commodity flow matrix and applying the diversions to the travel demand networks maintained by the affected MPOs: the North Jersey Transportation Planning Authority (NJTPA) and the New York Metropolitan Transportation Council (NYMTC). Though both MPOs have travel demand forecasting models suitable for analyzing the impacts on the highway system, their detailed highway and zone system covers only their areas of jurisdiction, rather than all of North America. The national commodity flow database must therefore be converted into a matrix of weekday truck trips consistent with the geographies of the MPO models. This conversion comprised a five-step process that uses subarea extraction methods to convert national commodity flows to the smaller geographies associated with travel demand models. It depends on standard software routines and network files that exist publicly.

  1. Trip Table Development – The information from the national commodity database must be converted to daily truck trip tables that can be applied to the subarea model. These tables can then be translated to be compatible with the MPO model software.

    The PANYNJ purchased the TRANSEARCH Commodity Flow database to use as the national commodity flow model. This database can be converted into a weekday truck Origin-Destination table. TRANSEARCH reports annual tons and annual truck flows in Standard Transportation Commodity Classification (STCC) 4 codes that were aggregated to STCC 2 codes. The annual truck unit flows were used in this analysis that explicitly used the payload, tons to truck, conversion by STCC included in TRANSEARCH. A comparison of average mid-weekday to annual truck flows from continuous classification count stations (located in Northern New Jersey) was used to determine the share that week day truck flows are to annual flows. A query of the flow table was developed to report the information as a comma separated value (CSV) file containing: origin zone number, destination zone number, STCC2, aggregated weekday trucks for that O/D/STCC2.
  2. Develop the National Highway Network – The truck trip table, developed in step 1, can be assigned to a national highway network. Helpful Hint: The FHWA website provides hyperlinks to a downloadable version of the FAF2 network available as a TransCAD network that can be used as a national network. This will consider congestion for both commodity and non commodity highway traffic and the infrastructure of the highway links. The flow units in the table have already been converted from annual to weekday trucks and the zones used in the national network were associated with the appropriate zones of the commodity table.

    The selected areas of the national network are known as county centroids and are denoted by FIPS codes. Certain centroids were chosen based on professional judgment to allow for the direct use of the national highway system. After incorporating the FAF3 county centroid connectors to the FAF3 network, the FAF3 network can be used to calculate link impedances, including truck restrictions and non-freight truck congestion, assigning the FAF3 daily highway trucks. These procedures can then be coded into the TransCAD network.
  3. Window to MPO Network Boundaries – The zonal layers of the respective MPO models were obtained in the same GIS projection as the loaded national highway network. These shapefiles were overlaid on the national highway network and GIS was used to define a selection set of national network highway links that cross the MPO boundaries. The Subarea Focusing procedure in TransCAD was used to create an O-D commodity truck trip table for the subareas defined by the MPOs.
  4. Associate FAF2 Subarea External Highway Links With MPO External Stations – The conversion of the subarea trip table to a geographic format consistent with the MPO trip tables is a two step process:
    • National highway links selected as subarea external stations are associated with the external stations of the respective MPO models.
    • The internal county zones in the subarea network need to be disaggregated to the Traffic Analysis Zones (TAZ) and MPO models. For the PANYNJ project, this was done based on the share that TAZ total heavy truck trips ends were to county total heavy truck trips ends.
  5. Assign the Converted TS Trip Table to the MPO Networks – The commodity database has been converted to a weekday truck trip table, so it is necessary to allocate the weekday trucks to the time periods used in the MPO model in order to use the highway assignment routines of the MPO models. This process may vary depending on the MPO model. For example, for the NYMTC model, the allocation was based on the share that the time period total heavy trucks are to daily total heavy trucks while for the NJTPA model, the allocation is included in scripts in the software which were modified to include similar factors. The resulting commodity truck tables were assigned to the MPO highway networks using the congested highway time in each period as the impedance. Once validated, the commodity trucks were subtracted from all other heavy trucks, allowing them to be assigned as part of a multiclass assignment with other vehicles. This assignment allows the MPO to properly calculate and attribute user benefits.

Daniel Beagan, is a Principal of Cambridge Systematics with more than 27 years of experience in transportation, traffic analysis, and planning in the public and private sectors. His experience also includes transportation forecasting, analysis, and development of mitigation for environmental impact reports in the office, retail, residential, university, industrial, and recreational industries and developed this method for use in all of the projects cited.

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