New Travel Demand Models
Dec 18, 2019

PRESENTATION ARCHIVE

OVERVIEW

Conventional four-step travel demand models are used by nearly all metropolitan planning organizations (MPOs), state departments of transportation, and local planning agencies, as the basis for long-range transportation planning in the United States. A flaw of the four-step model is its relative insensitivity to the so-called D variables. The D variables are characteristics of the built environment that are known to affect travel behavior. The Ds are development density, land use diversity, street network design, destination accessibility, and distance to transit. In this seminar, we will explain how we developed a vehicle ownership model (car shedding model), an intrazonal travel model (internal capture model), and mode choice model that consider all of the D variables based on household travel surveys and built environmental data for 32, 31, and 29 regions, respectively, validates the models, and demonstrates that the models have far better predictive accuracy than Wasatch Front Regional Council (WFRC)/Mountailand Association of Governments’ (MAG) current models.

In this webinar, researchers Reid Ewing and Sadegh Sabouri will demonstrate the effectiveness of the new...

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A bus in Utah
Dec 04, 2019
Photo by KuntalSaha/iStock
Reid Ewing, University of Utah

Conventional four-step travel demand modeling is overdue for a major update. The latest NITC report from the University of Utah offers planners better predictive accuracy through an improved model, allowing for much greater sensitivity to new variables that affect travel behavior. Specifically, it accounts for varying rates of vehicle ownership, intrazonal travel, and multimodal mode...

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Apr 13, 2015

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There is growing support for improvements to the quality of the walking environment, including more investments to promote pedestrian travel. Planners, engineers, and others seek improved tools to estimate pedestrian demand that are sensitive to environmental and demographic factors at the appropriate scale in order to aid policy-relevant issues like air quality, public health, and smart allocation of infrastructure and other resources. Further, in the travel demand forecasting realm, tools of this kind are difficult to implement due to the use of spatial scales of analysis that are oriented towards motorized modes, vast data requirements, and computer processing limitations.

To address these issues, a two-phase project between Portland State University and Oregon Metro is underway to develop a robust pedestrian planning method for use in regional travel demand models. The first phase, completed in 2013, utilizes a tool that predicts the number of walking trips generated with spatial acuity, based on a new measure of the pedestrian environment and a micro-level unit of analysis. Currently, phase two is building upon this tool to predict the distribution of walking trips, connecting the origins predicted in phase one to...

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Apr 13, 2015

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Where: Room 204 of the Distance Learning Center Wing of the Urban Center at PSU

The ability to forecast future transportation patterns under a particular land-use scenario or urban form is key to making informed decisions at the local and regional levels.

Although several researchers have explored the links between the built environment, socio-demographics and travel behavior, a consensus is not reached.

This talk highlights two recent projects. The first project focuses on individuals’ attitudes towards transportation, neighborhood characteristics and their effects on campus commuters’ transit use, and addresses the question whether attitudes, the built environment or a combination of both explains the resulting transit use better.

The second part presents the Regional Land Use Allocation Decision Analysis Tool developed for The Ohio Department of Transportation, which enables decision makers to quantify the impacts of population and employment distribution in terms of the resulting VMT (Vehicle Miles Traveled). This tool forecasts the impacts of future land-use policies in Ohio, based on alternative assumptions of highway and mass transit corridor development, zoning and...

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Oct 23, 2012

When policymakers look to meet cycling goals by investing in new bicycle routes, they have little research to help them determine whether cyclists will actually use them. As a result, bicycle facilities aren’t considered equally with motor vehicle infrastructure.

That’s changing, thanks in part to OTREC research. An OTREC-funded study, the first to gather large-scale data that reveal cyclists’ actual route preference, is being published in a scientific journal (Transportation Research Part A). The findings have already been incorporated into the regional travel demand model used to make transportation investment decisions across the Portland region.

In the study, Portland State University researchers Joseph Broach, Jennifer Dill and John Gliebe (Gliebe is now with RSG Inc.) outfitted cyclists with GPS units to record which routes they chose and model the choices to reveal preferences. Previous studies have relied on stated preference surveys or less reliable methods of determining cyclists’ actual routes. The data gathering was supported by a grant from the Robert Wood Johnson Foundation through its national program Active...

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