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SPG
Alex Bettinardi edited this page Jan 9, 2025
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1 revision
Location | File Name | Description |
---|---|---|
scenario_name\outputs\t* |
householdsByHHCategory.csv |
SPG1 modelwide summary of households by category |
scenario_name\outputs\t* |
spg2out_hh.csv |
SPG2 Synthetic Population Household temporary (selected location fields for all HH Ids) |
scenario_name\outputs\t* |
SynPopH.csv |
SPG2 Synthetic Population household attributes (current year study area resident households) |
scenario_name\outputs\t* |
SynPopP.csv |
SPG2 Synthetic Population person attributes (current year study area resident persons) |
scenario_name\outputs\t* |
spg1.properties |
Module-specific properties from current model run |
scenario_name\outputs\t* |
spg2.properties |
Module-specific properties from current model run |
The SPG1 module is called via the com.pb.tlumip.spg.SPGnew class’s spg1 method. This method is actually called twice, once without the person-age constraint enabled to get an estimate for the total regional population (the module requires households be forecast, but not the actual population), and then a second time with the person-age constraint using the estimated population from the first run.
The SPG2 module is called via the com.pb.tlumip.spg.SPGnew class’s spg2 method.
SPG has 3 steps:
- Balance - Multidimensional HH distribution in each TAZ usually using an IPF (Fratar-type) matrix balancing procedure
- Discretize - List of HHs with controlled variables in each TAZ
- Draw - Randomly join HHs from PUMS by controlled variables
Recent update for person age controls:
- Convert person age controls to household controls:
Hhs with 1 person age 34-45 for example
Hhs with 2 persons age 34-45 for example
…
- Run SPG without person controls to get approximate persons
- Allocate approximate persons to person controls using base year person age distributions
- Re-run SPG with person controls and weight 1 person controls * 1, 2 person controls * 2, etc to account for person weighting Discretize and draws HHs to match results
Beckman, R.J., Baggerly, K.A., and McKay, M.D., 1996. Creating synthetic baseline populations. Transportation Research Part A, 30(6), 415-429.
SWIM-TLUMIP Model User Guide, version 2.5
- SI - SWIM Inputs
- NED - New Economic Demographics
- ALD - Aggregate Land Development
- AA - Activity Allocation
- POPSIMSPG - PopulationSim Synthetic Population Generator
- PT - Person Transport
- CT - Commercial Transport
- TA - Traffic Assignment
- TR - Transit Assignment
- SL - Select Link
- SWIM VIZ - Reporting DB