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

Keunhyun Park (), Sadegh Sabouri, Torrey Lyons, Guang Tian and Reid Ewing
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Keunhyun Park: Utah State University
Sadegh Sabouri: University of Utah
Torrey Lyons: University of Utah
Guang Tian: University of New Orleans
Reid Ewing: University of Utah

Transportation, 2020, vol. 47, issue 5, No 2, 2087-2108

Abstract: Abstract 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.

Keywords: Trip distribution; Gravity model; Intrazonal trips; Built environment; Multilevel modeling (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11116-019-10002-0

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