VERPAT Inputs and Parameters
VERPAT contains 34 input files and 5 parameter files, some of which the user must change and others which typically remain unchanged. This page walks the end user through these files and specifies which files must be updated to implement VERPAT in a new region.
Built Environment
Demand
- region_trips_per_cap.csv
- employment.csv
- azone_hh_pop_by_age.csv
- azone_per_cap_inc.csv
- region_truck_bus_vmt.csv
- [
- model_tdm_transit.csv
- model_tdm_transitlevels.csv
- model_tdm_vanpooling.csv
- model_tdm_workschedule.csv
- model_tdm_workschedulelevels.csv
- region_accident_rates.csv
- region_fuel_co2.csv
- region_fuel_composition_prop.csv
- region_fuel_prop_by_veh.csv
- region_gt1_veh_prop.csv
- region_lt1_veh_prop.csv
- region_place_type_elasticities.csv
- region_place_type_relative_values.csv
- region_transportation_costs.csv
- region_veh_cumprop_by_vehage.csv
- region_veh_mpg_by_year.csv
- region_veh_mpg_dvmt_prop.csv
- region_veh_prop_by_vehage_vehtype_inc.csv
- azone_gq_pop_by_age.csv
- azone_hhsize_targets.csv
- azone_its_prop.csv
- azone_relative_employment.csv
- marea_lane_miles.csv
- marea_parking_growth.csv
- marea_rev_miles_pc.csv
- model_commute_options.csv
- model_light_vehicles.csv
- model_tdm_ridesharing.csv
- model_parameters.json
- run_parameters.json
- units.csv
- deflators.csv
- geo.csv
The user should change the input files described here. All files are *.csv
.
Population and Jobs by Place Type: This file contains the distribution of population and employment among the 13 place types for base and future year. See this explanation for more infomation regarding place types. Each column, for each year, must sum to one (1). It is acceptable to have no land use (i.e. a value of 0) in certain categories. The yearly TAZ employment and population totals were summed by the 13 place type and then scaled to total one for both employment and population. Here is a snapshot of the file:
Geo | Year | Pop | Emp |
---|---|---|---|
Rur | 2005 | 0.05 | 0.1 |
Sub_R | 2005 | 0.3 | 0 |
Sub_E | 2005 | 0 | 0.2 |
Sub_M | 2005 | 0.1 | 0.1 |
Sub_T | 2005 | 0 | 0 |
CIC_R | 2005 | 0.15 | 0 |
CIC_E | 2005 | 0 | 0.2 |
CIC_M | 2005 | 0.1 | 0.1 |
CIC_T | 2005 | 0 | 0 |
UC_R | 2005 | 0.1 | 0 |
UC_E | 2005 | 0 | 0.1 |
UC_M | 2005 | 0.1 | 0.1 |
UC_T | 2005 | 0.1 | 0.1 |
Rur | 2035 | 0.05 | 0.1 |
Sub_R | 2035 | 0.3 | 0 |
Sub_E | 2035 | 0 | 0.2 |
Sub_M | 2035 | 0.1 | 0.1 |
Sub_T | 2035 | 0 | 0 |
CIC_R | 2035 | 0.15 | 0 |
CIC_E | 2035 | 0 | 0.2 |
CIC_M | 2035 | 0.1 | 0.1 |
CIC_T | 2035 | 0 | 0 |
UC_R | 2035 | 0.1 | 0 |
UC_E | 2035 | 0 | 0.1 |
UC_M | 2035 | 0.1 | 0.1 |
UC_T | 2035 | 0.1 | 0.1 |
Auto and transit trips per capita: This file contains regional averages for auto and transit trips per capita per day for the base year.
- Auto is the regional average of auto trips per capita, including drive alone and shared ride travel. This data can be derived from the National Household Travel Survey by region or from a local household travel survey or regional travel demand forecasting model.
- Transit is the regional average of transit trips per capita, including walk and drive access to transit. This data can be derived from the National Transit Database where the annual database contains a “service” table that has annual transit trip data for each transit operator or from a local household travel survey or regional travel demand forecasting model.
Here is a snapshot of the files:
Mode | Trips |
---|---|
Auto | 3.2 |
Transit | 0.4 |
Employment: This file contains employment data for each of the counties that make up the region. The file is derived from County Business Pattern (CBP) data by county. Industries are categorized by the North American Industrial Classification System (NAICS) 6 digit codes. Firm size categories are:
- n1_4: 1- 4 employees
- n5_9: 5-9 employees
- n10_19: 10-19 employees
- n20_99: 20-99 employees
- n100_249: 100-249 employees
- n250_499: 250-499 employees
- n500_999: 500-999 employees
- n1000: 1,000 or More Employee Size Class
- n1000_1: 1,000-1,499 employees
- n1000_2: 1,500-2,499 employees
- n1000_3: 2,500 to 4, 999 Employees
- n1000_4: Over 5,000 employees
While the county field is required to be present, the business synthesis process does not require a meaningful value and therefore users may simply enter “region”. The consistency in the naming of the "region" should be maintained across all the files that contains the label "county" or "Geo". It is also not necessary to use such detailed NAICS categories if those are not available; the current business synthesis model and subsequent models do not use this level of detail (although future versions of the model may) – at minimum, the number of establishments for all employment types can be provided by size category. Regions with significant employment in industries such as government and public administration that are not covered by the CBP may need to add records to the file that cover this type of employment to more accurately match employment totals in their region. The two additional fields contained in the file are:
- emp: Total number of employees
- est: Total number of establishments
Here is the snapshot of the file:
county | year | naics | emp | est | n1_4 | n5_9 | n10_19 | n20_49 | n50_99 | n100_249 | n250_499 | n500_999 | n1000 | n1000_1 | n1000_2 | n1000_3 | n1000_4 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Multnomah | 2005 | 113110 | 0 | 5 | 2 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 113310 | 0 | 3 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 114111 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 114112 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 115114 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 115210 | 0 | 4 | 3 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 115310 | 0 | 5 | 2 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 212319 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Multnomah | 2005 | 212321 | 0 | 4 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Household population: This file contains population estimates/forecasts by county and age cohort for each of the base and future years. The file format includes six age categories used by the population synthesis model:
- 0-14
- 15-19
- 20-29
- 30-54
- 55-64
- 65 Plus
Future year data must be developed by the user; in many regions population forecasts are available from regional or state agencies and/or local academic sources. As with the employment data inputs the future data need not be county specific. Rather, regional totals by age group can be entered into the file with a value such as “region” entered in the county field.
Here is a snapshot of the file:
Geo | Year | Age0to14 | Age15to19 | Age20to29 | Age30to54 | Age55to64 | Age65Plus |
---|---|---|---|---|---|---|---|
Multnomah | 2005 | 129869 | 41133 | 99664 | 277854 | 71658 | 72648 |
Multnomah | 2035 | 169200 | 48800 | 144050 | 327750 | 116100 | 162800 |
###azone_per_cap_inc.csv
Regional income: This file contains information on regional average per capita household and group quarters income by forecast year in year 2000 dollars. The data can be obtained from the U.S. Department of Commerce Bureau of Economic Analysis for the current year or from regional or state sources for forecast years. In order to use current year dollars just replace 2000 in column labels with current year. For example, if the data is obtained in year 2005 dollars then the column labels in the file shown below will become HHIncomePC.2005 and GQIncomePC.2005. Here is a snapshot of the file:
Geo | Year | HHIncomePC.2000 | GQIncomePC.2000 |
---|---|---|---|
Multnomah | 2005 | 32515 | 0 |
Multnomah | 2035 | 40000 | 0 |
Truck and bus vmt: This file contains the region’s proportion of VMT by truck and bus as well as the distribution of that VMT across functional classes (freeway, arterial, other). The file includes one row for bus VMT data and one row for Truck VMT data. It should be noted that it is not necessary to enter values in the PropVmt column for BusVmt as this is calculated using the values in the transportation_supply.csv #EDIT (marea_rev_miles_pc.csv?) user input file. The truck VMT proportion (PropVMT column, TruckVMT row) can be obtained from Highway Performance Monitoring System data and local sources or the regional travel demand model if one exists. The proportions of VMT by functional class can be derived from the Federal Highway Cost Allocation Study and data from transit operators. The Federal Highway Cost Allocation Study (Table II-6, 1997 Federal Highway Cost Allocation Study Final Report, Chapter II is used to calculate the average proportion of truck VMT by functional class. Data from transit authorities are used to calculate the proportions of bus VMT by urban area functional class. Here is a snapshot of the file:
Type | PropVmt | Fwy | Art | Other |
---|---|---|---|---|
BusVmt | 0 | 0.15 | 0.591854 | 0.258146 |
TruckVmt | 0.08 | 0.452028 | 0.398645 | 0.149327 |
- Getting Started
- VisionEval Primer
- Concepts Primer
- VisionEval Models
- VERPAT Tutorial
- VERSPM Tutorial
- VE-RSPM Training
- VE-State Tutorial
- Developer Orientation