  Integrating land use, travel demand, and traffic models represents a gold
standard for regional planning, but is rarely achieved in a meaningful way,
especially at the scale of disaggregate data. In this report, we present a new
pipeline architecture for integrated modeling of urban land use, travel demand,
and traffic assignment. Our land use model, UrbanSim, is an open-source
microsimulation platform used by metropolitan planning organizations worldwide
for modeling the growth and development of cities over long (~30 year) time
horizons. UrbanSim is particularly powerful as a scenario analysis tool,
enabling planners to compare and contrast the impacts of different policy
decisions on long term land use forecasts in a statistically rigorous way. Our
travel demand model, ActivitySim, is an agent-based modeling platform that
produces synthetic origin--destination travel demand data. Finally, we use a
static user equilibrium traffic assignment model based on the Frank-Wolfe
algorithm to assign vehicles to specific network paths to make trips between
origins and destinations. This traffic assignment model runs in a
high-performance computing environment. The resulting congested travel time
data can then be fed back into UrbanSim and ActivitySim for the next model run.
This technical report introduces this research area, describes this project's
achievements so far in developing this integrated pipeline, and presents an
upcoming research agenda.
