modeling | National Institute for Transportation and Communities

Trick or Treatment? Impact of Route-Level Features on Decisions to Walk or Bike

The video begins at 0:34.

Speaker: Joseph Broach, Ph.D. Candidate, Portland State University
Topic: Trick or Treatment? Impact of Route-Level Features on Decisions to Walk or Bike
Summary: Some travel routes attract people walking and cycling, while others may scare them away. What features of street environments are most important, and how do available routes affect decisions to bike or walk on a specific trip?

Research to date has focused on either large-scale areal measures like "miles of bike lane nearby" or else has considered only shortest path routes. Neither method is suited to capturing the impact of targeted route-level policies like neighborhood greenways. This session will present a new technique for measuring bike and walk accessibility along the most likely route for a given trip. The method is applied to travel data, and results provide new insight into the relationship between route quality and travel mode choice.

GreenSTEP: A Strategic Planning Model for Addressing Transportation Greenhouse Gas Mitigation

Watch video

Abstract: Climate change may be the most serious and urgent issue facing the transportation sector. Transportation is both a major producer of greenhouse gas (GHG) emissions and is also vulnerable to the consequences of climate change. Major reductions in GHG emissions from the transportation sector will be needed in order to avoid the most serious effects of climate change. Travel models can play an important role in evaluating strategies for reducing transportation sector GHG emissions, but prevailing travel models do not address a number of factors that significantly affect GHG emissions. The GreenSTEP model was developed to fill this gap. The model estimates household level vehicle travel, energy consumption, and GHG emissions. GreenSTEP is currently being used to assist the development of ODOT's Statewide Transportation Strategy for reducing GHG emissions and Metro's Climate Smart Communities scenario planning process.

Speaker Bio: Brian Gregor is a senior transportation analyst for the Oregon Department of Transportation (ODOT) where for the past 15 years he has worked on a variety of transportation and land use modeling and analysis projects. He is the principal developer of the GreenSTEP and Land Use Scenario DevelopeR (LUSDR) models. He has also worked on the development and application of Oregon's Statewide Integrated Model (SWIM), lead the automation of ODOT's modeling processes...

Re-examining the influence of work and non-work accessibility on residential location choices with a micro-analytic framework

View slides

The video begins at 2:53.

Abstract: The concept of accessibility has long been theorized as a principal determinant of household residential choice behavior. Research on this influence is extensive but the empirical results have been mixed, with some research suggesting that accessibility is becoming a relatively insignificant influence on housing choices. Further, the measurement of accessibility must contend with complications arising from the increasing prevalence of trip-chains, non-work activities, and multi-worker households, as well as reconcile person-specific travel needs with household residential decisions. This paper contributes to the literature by addressing the gap framed by these issues and presents a novel residential choice model with three main elements of innovation. First, it operationalized a time-space prism (TSP) accessibility measure, which the authors believe to be the first application of its kind in a residential choice model. Second, it represented the choice sets in a building-level framework, the lowest level of spatial disaggregation available for modeling residential choices. Third, it explicitly examined the influence of non-work accessibility at both the local- and person-level. This residential choice model was applied in the...

Travel Decisions & Their Implications for Urban Transportation: From Campus Transportation to Statewide Modeling

Watch video

View slides

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 environmental constraints, regional growth or decline...

Webinar: New Travel Demand Modeling for our Evolving Mobility Landscape

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...

Development of the Idaho Statewide Travel Demand Model Trip Matrices Using Cell Phone OD Data and Origin Destination Matrix Estimation

Watch video

View slides

Topic: Airsage cell phone data and its application in travel modeling
Summary: As part of the initial phase of development for the Idaho Statewide Travel Demand Model, Parsons Brinckerhoff developed a base year auto and truck trip matrix using AirSage cell phone OD data, a statewide network in Cube, traffic counts, and origin-destination matrix estimation (ODME) procedures. To begin, the 4000+ statewide zone system was aggregated into a 700 super zone system for collecting the cell phone OD data. Next, the cell phone data was collected for the month of September 2013 for the following market segments: Average weekday resident HBW, HBO, NHB, and visitor NHB trips. The cell phone trips were then disaggregated to zones using each zone’s share of super zone population and employment. These initial trip matrices were assigned to the daily statewide network using free flow travel time for route impedance and iteratively adjusted to minimize the difference between the estimated link volumes and traffic counts by user class.

This iterative trip matrix balancing procedure, also known as ODME, converged nicely by user class and facility type and produced reasonable flows. The resulting trip matrix trip length frequencies matched fairly well with the...

Risk and Uncertainty: All Models Are Wrong But Some Are Useful

The video begins at 1:18.

Abstract: Models are used for many different purposes. Some seek to impart understanding of the system under study, while others seeks to understand dynamics. Most of the models considered in this course are also used for forecasting likely future levels of demand and its impact upon the built and natural environment. Unlike models of purely physical systems these models attempt to capture the interactions between people and institutions. Social systems are considerably more complex and chaotic. They are shaped by disruptive technologies, changing markets, economic cycles, and cultural influences that a difficult to predict, much less their subtle (and sometimes not so subtle) interaction effects. Uncertainty creeps into forecasting as a result, creating risk that a policy or investment may have unintended consequences, under-perform, or be short-lived. Transportation and land use modelers have typically only weakly accommodated such realities in their forecasts. Policy-makers and investors are increasingly demanding a more explicit accounting of risk and uncertainty in forecasting. This discussion will focus on how this will affect the practice of modeling in the future.

Speaker Bio: Rick Donnelly has over 25 years of experience in the modeling and simulation of transportation systems, from the urban to national level. His current interests include agent-based modeling of...

Transport, Land Use, and Value

The video begins at 0:52.

Abstract: This presentation considers co-evolutionary process between the development of land and transport networks. Using data from the rail and Underground in London and the streetcar system in the Twin Cities, the empirical relationship is established statistically under several different contexts, and hypotheses about the positive feedback nature of the interaction are tested. Using insights from empirical observation, a numerical simulation is constructed to more formally test the relationship, and to understand the extent to which allowing networks to vary in response to land use (and land use to vary in response to network) affects the spatial organization of each. Models of network growth which fix land use, and models of land use which fix network growth, underestimate the degree of hierarchy that emerges in the system. Given transportation creates land value, and recognizing the problem of underfunding transport infrastructure, new funding sources can be used to increase transport investment, create additional land value, and improve social welfare.

Prof. David Levinson serves on the faculty of the Department of Civil, Environmental, and Geo- Engineering at the University of Minnesota and directs the Networks, Economics, and Urban Systems (NEXUS) research group. He holds the Richard P. Braun/CTS Chair in Transportation. He also serves on the graduate faculty of the...

Development of a Pedestrian Demand Estimation Tool: a Destination Choice Model

Watch video

View slides

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 destinations. This...

Walking and Biking on their Own: Modeling Children's Independent Travel to Neighborhood Parks and Schools

The video begins at 1:47.

Joseph Broach, PhD candidate in Urban Studies, will discuss the results of his research, which models the propensity of children aged 6-16 to walk or bike to parks and school without an adult chaperone, extending existing work on children’s active travel in several ways: 1) focus on travel without an adult, 2) inclusion of school and a non-school destinations, 3) separate walk and bike models, 4) consideration of both parent and child attitudes and perceived social norms, 5) explicit inclusion of household rules limiting walking or bicycling.

PRESENTATION ARCHIVE

OVERVIEW

Pages