Intrazonal or interzonal? Improving intrazonal travel forecast in a four-step travel demand model

  • Keunhyun ParkEmail author
  • Sadegh Sabouri
  • Torrey Lyons
  • Guang Tian
  • Reid Ewing


Conventional four-step travel demand models, used by most metropolitan planning organizations (MPOs), state departments of transportation, and local planning agencies, are the basis for long-range transportation planning in the United States. Trip distribution—whether the trip is intrazonal (internal) or interzonal (external)—is one of the essential steps in travel demand forecasting. However, the current intrazonal forecasts based on a gravity model involve flawed assumptions, primarily due to a lack of considerations on differences in zone size, land use, and street network patterns. In this study, we first survey 25 MPOs about how they model intrazonal travel and find the state of the practice to be dominated by the gravity model. Using travel data from 31 diverse regions in the U.S., we develop an approach to enhance the conventional model by including more built environment D variables and by using multilevel logistic regression. The models’ predictive capability is confirmed using k-fold cross-validation. The study results provide practical implications for state and local planning and transportation agencies with better accuracy and generalizability.


Trip distribution Gravity model Intrazonal trips Built environment Multilevel modeling 



This research was funded by the National Institute for Transportation and Communities (NITC), Utah Department of Transportation, Utah Transit Authority, Wasatch Front Regional Council, and Mountainland Association of Governments. NITC is a program of the Transportation Research and Education Center at Portland State University and a U.S. Department of Transportation University Transportation Center.

Authors’ Contributions

KP: data analysis and validation, manuscript writing and editing. SS: MPO survey, literature review, manuscript writing. TL: literature search and review, manuscript writing and editing. GT: data collection and analysis, manuscript editing. RE: research design, manuscript editing.

Compliance with Ethical Standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Landscape Architecture and Environmental PlanningUtah State UniversityLoganUSA
  2. 2.Department of City and Metropolitan Planning, College of Architecture + PlanningUniversity of UtahSalt Lake CityUSA
  3. 3.Department of Planning and Urban StudiesUniversity of New OrleansNew OrleansUSA

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