Analyzing Disaggregate FAF Flows

Background

The CT module creates discrete truck trips. It creates these truck trips from two sources, FAF and AA (Local) results from within SWIM. The FAF data represents Oregon in two zones; the Portland economic region (most of the valley, bigger than just Portland), and the remainder of Oregon. Given the FAF's national scale, it does a much better job at estimating the commercial flows in and out of Oregon than SWIM could do, given that SWIM does not have the national level information contained within in it. For these reasons, SWIM-CT relies on FAF for flows in and out of Oregon. SWIM-CT also uses AA to create calculate truck trips that occur within the model boundary.

Purpose

Because FAF is a trusted data set used across the country for a variety of transportation analysis questions, it is natural to want to gain information about how the FAF dataset is flowing across Oregon's road ways. The process within CT takes the FAF dataset and disaggregates it to the SWIM zones (~3000), allowing for FAF flows to be modeled and analyzed along Oregon's roadways. The process described below instructs how a SWIM user may pull out detailed FAF value and tonnage by commodity for a given link (repeat this process for as many locations you might be interested in).

Analysis Steps

Step 1 - Identify the model link(s) of interest

First, open up either the input Visum network version file at "inputs\t0" or open up a resulting Visum network, which has auto and truck volumes at - "outputs\ year of choice \ "NT_PATHS.ver". Note that t0 is 1990 for SWIM, so t20 is 2010. Also Note that "NT_PATHS.csv" is suggested as it is the final period run for the day in SWIM, and therefore the field "DAILY_VOL_TOTAL" is populated. This is the field one would typically want to use to understand what type of traffic has been modeled in SWIM across the network (volumes by period can also be reviewed). After reviewing the network, make note of the From-To node number combinations for the link(s) of interest.

Step 2 - Run the select link process in SWIM

Take the link From-To numbers from Step 1 and code them in the "selectLinks.csv" file found in "inputs\t0", example:

FROMNODE	TONODE	DIRECTION	STATIONNUMBER
29684	29469	IN	1_NB

(Note that Direction can be either IN or OUT, it doesn't matter for a single link location, and Station number can be any identifier meaningful to the analysis - I like to use a number and a direction, as shown in the example).

It is important to be aware that truck flows must be extracted one location at a time, so even though the input file "selectLinks.csv" is designed to work with multiple locations, for this analysis only one location at a time may be coded.

After the selectLinks.csv file is updated, the user needs to navigate to "model\config\tsteps.csv". Alter the file so that only select link is to be run. And update the year to the year or years of interest:

Year	SL - Generate Select Link Data	SL - Append Select Link To Trips
20	1	1

Now go back to the main SWIM directory in the scenario of interest (Example on TPAU-SWIM machines - D:\swim2\Reference), open a command window in that scenario by holding shift, right clicking and choosing "Open command window here", and then run "run_model.bat". (These instructions assume that a SWIM run to be analyzed has already been completed. If you need to start by running a full SWIM run, start back at these instructions first - https://github.com/tlumip/tlumip/wiki/running-scenarios).

Step 3 - Pull a copy of the resulting CT output

Every third year of SWIM runs the transport model (typically; 2010, 2013, 2016..., 2040). Each of these years has a full set of all of the truck trips modeled by CT, this can be found in "outputs\ year of interest \Trips_CTTruck.csv". However, this file is the full record for the whole model area, and there is no way from that file to determine which trips occurred on which links or routes. When the select link is run it creates a subset of the "Trips_CTTruck.csv" containing only CT records that used that selected link. This subset of the data is saved in the file - "outputs\ year of interest \select_link_outputs.zip". This zip file will exist after the select link process is successfully run (expect about 30 minutes for each location, note if you have multiple locations save this file between each run, as the file will be overwritten with each run). After running the select link, grab a copy of this zip file and bring it to an analysis directory. Unzip the file and save out a copy of the "Trips_CTTruck.csv" file, which is a subset of the full record for just the trips using the select link of interest. If multiple locations are going to be modeled, a user will want to file these or name these files in a way that identifies one select link location from the others.

Step 4 - Tabulating Value and Ton Data

From the "Trips_CTTruck" select link copies (should be named as followed by the select link process "Trips_CTTruck_select_link.csv", and then renamed under Step 3), the user has all of the FAF ton and value data by commodity that travels through a given link on the SWIM network. In a program like R, these OD truck trips can be quickly tabulated to total FAF tons and value for a given link with lines like the examples below:

    # summarize values and tons
    value.sctg <- tapply(ct..$value, ct..$sctg2, sum)
    tons.sctg <- tapply(ct..$tons, ct..$sctg2, sum)

Once the data has been summed by commodity, those values can either be reported by the 42~43 commodity categories, or aggregated into commodity groupings. For SWIM work, the commodity categories are currently being summarized into 7 groups as defined in the table below.

This process can be repeated for as many select link locations as desired. If more than a handful of locations, it is advised that a series of automation scripts be setup to automated this list of relatively simple steps.

Commodity	Description	Commodity Group
SCTG01	Live animals and live fish	Food or Kindred Products
SCTG02	Cereal grains	Food or Kindred Products
SCTG03	Other agricultural products	Food or Kindred Products
SCTG04	Animal feed and products of animal origin, n.e.c.	Food or Kindred Products
SCTG05	Meat, fish, seafood, and their preparations	Food or Kindred Products
SCTG06	Milled grain products and preparations, and bakery products	Food or Kindred Products
SCTG07	Other prepared foodstuffs and fats and oils	Food or Kindred Products
SCTG08	Alcoholic beverages	Food or Kindred Products
SCTG09	Tobacco products	Food or Kindred Products
SCTG10	Monumental or building stone	Clay, minerals, stone
SCTG11	Natural sands	Clay, minerals, stone
SCTG12	Gravel and crushed stone	Clay, minerals, stone
SCTG13	Nonmetallic minerals, n.e.c.	Clay, minerals, stone
SCTG14	Metallic ores and concentrates	Clay, minerals, stone
SCTG15	Coal	Petroleum, Coal, Chemicals
SCTG16	Crude Petroleum	Petroleum, Coal, Chemicals
SCTG17	Gasoline and aviation turbine fuel	Petroleum, Coal, Chemicals
SCTG18	Fuel oils	Petroleum, Coal, Chemicals
SCTG19	Coal and petroleum products, n.e.c.	Petroleum, Coal, Chemicals
SCTG20	Basic chemicals	Petroleum, Coal, Chemicals
SCTG21	Pharmaceutical products	Petroleum, Coal, Chemicals
SCTG22	Fertilizers	Petroleum, Coal, Chemicals
SCTG23	Chemical products and preparations, n.e.c.	Petroleum, Coal, Chemicals
SCTG24	Plastics and rubber	Petroleum, Coal, Chemicals
SCTG25	Logs and other wood in the rough	Forest or Wood Products
SCTG26	Wood products	Forest or Wood Products
SCTG27	Pulp, newsprint, paper, and paperboard	Pulp or Paper products
SCTG28	Paper or paperboard articles	Pulp or Paper products
SCTG29	Printed products	Pulp or Paper products
SCTG30	Textiles, leather, and articles of textiles or leather	Other/Misc
SCTG31	Nonmetallic mineral products	Clay, minerals, stone
SCTG32	Base metal in primary or semi-finished forms and in finished basic shapes	Machinery, Instrum, Transp Equip, Metals
SCTG33	Articles of base metal	Machinery, Instrum, Transp Equip, Metals
SCTG34	Machinery	Machinery, Instrum, Transp Equip, Metals
SCTG35	Electronic and other electrical equipment and components, and office equipment	Machinery, Instrum, Transp Equip, Metals
SCTG36	Motorized and other vehicles (including parts)	Machinery, Instrum, Transp Equip, Metals
SCTG37	Transportation equipment, n.e.c.	Machinery, Instrum, Transp Equip, Metals
SCTG38	Precision instruments and apparatus	Machinery, Instrum, Transp Equip, Metals
SCTG39	Furniture, mattresses and mattress supports, lamps, lighting fittings, and illuminated signs	Other/Misc
SCTG40	Miscellaneous manufactured products	Other/Misc
SCTG41	Waste and scrap	Other/Misc
SCTG43	Mixed Freight	Other/Misc