Estimation • MyFirstFourStepModel

Estimating a new model requires only a few lines of code, however it does require the 2017 National Household Travel Survey (NHTS, Federal Highway Administration 2017) in CSV format and unzipped (which can be obtained here), and an OpenStreetMap PBF file for the region modeled. There are many sources for OpenStreetMap PBF files, but one easy source is https://slice.openstreetmap.us. The code to estimate a model for the Research Triangle region is below. First, it loads the relevant libraries, and then the NHTS (NHTS_PATH should be replaced with a directory containing the NHTS CSV files). I filter the NHTS to only North Carolina households with a weekday travel day ( $n=7,146$ ). The final line estimates the model. It requires the (possibly filtered) NHTS, the path to the OpenStreetMap data (written as OSM_PATH below but should be replaced with the actual path), the state and a vector of counties to define the region under study, and a year. Currently 2021 is most recent year available, as this is based on American Community Survey and Longitudinal Employer-Household Dynamics data availability.

Parsing the OpenStreetMap data uses Julia (Bezanson et al. 2017) for performance, which can be installed from https://julialang.org. Julia is only required for estimation; students do not need to install Julia.

library(MyFirstFourStepModel)
library(tidyverse)

# Load NHTS and filter to North Carolina weekday data
nhts = load_nhts(NHTS_PATH)
nhts$households = filter(
  nhts$households,
  HHSTATE == "NC" & TRAVDAY %in% c(2, 3, 4, 5, 6)
)

# Estimate the model using 2023 Census/LODES data for the Triangle
model = estimate(nhts, OSM_PATH, "NC", c("Durham", "Orange", "Wake", "Chatham"), 2023)

Lastly, the model can be saved to a file for distribution to students.

save_model(model, "chatham_park.mf4sm")

This can be loaded by the load_model function described above, either from a file or a URL. If any land-use or network scenarios are created or loaded prior to saving the model, they will be included in the saved file.

References

Bezanson, Jeff, Alan Edelman, Stefan Karpinski, and Viral B. Shah. 2017. “Julia: A Fresh Approach to Numerical Computing.” SIAM Review 59 (1): 65–98. https://doi.org/10.1137/141000671.

Federal Highway Administration. 2017. “2017 National Household Travel Survey.” https://nhts.ornl.gov/downloads.