A new transportation comic, "Moving From Cars To People (PDF)," offers a succinct and fun introduction to a complicated topic: namely, how the built environment in the United States came to be designed for cars and what we can do about it.
Want a physical copy? Here are a few ways to get one:
NITC research led by Reid Ewing of the University of Utah, examining impacts that the built environment and development patterns have on transportation, has produced a number of journal articles in the past year. Three 2021 articles highlighted below each focus on different aspects of the body of work, which revolves around polycentric development and trip generation.
A May 2021 article in the Journal of Transport Geography estimated a vehicle ownership model that contributes to our understanding of vehicle ownership and improves the accuracy of travel demand forecasts. "The built environment and vehicle ownership modeling: Evidence from 32 diverse regions in the U.S.," authored by Sadegh Sabouri, Guang Tian, Reid Ewing, Keunhyun Park and William Greene, draws on findings from the NITC project Key Enhancements to the WFRC/MAG Four-Step Travel Demand Model.
Two main outcomes of this paper are:
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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Many cities are reconsidering their reliance on ITE's Trip Generation Manual, now in its 10th edition.
Kelly Clifton, TREC researcher and associate dean for research of Portland State University's Maseeh College of Engineering & Computer Science, is one of the people leading the charge to identify better, more nuanced ways to anticipate transportation demand; especially person (non-car) trips. In an extended series of TREC projects, Clifton and...
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In recent decades, cities have become increasingly motivated to invest in infrastructure that supports multimodal options like walking, biking and public transit. Trip generation, the first step in conventional four-step forecasting models, is a central figure in determining how those investments are made.
However, when considering pedestrian and bicycling travel, the current practice is usually to either leave those trips out of the model altogether, or to simply present them as a mode choice option that is not analyzed further. In short, they’re car-centric.
Without reliable trip generation rates for anyone but drivers, an accurate transportation impact is difficult to predict. Certain land uses will draw far more walkers, cyclists and transit riders than drivers. Cities...
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The city of Portland is using research and expertise from TREC researchers to change how it calculates fees for new development. Developers pay the fees, called transportation system development charges, to offset some of the costs of providing transportation infrastructure.
The foundation for those fees has been cars: that is, how many car trips a development will generate. In December, the Portland City Council voted to instead use “person trips” as the basis for those fees.
Researchers Kelly Clifton and Kristina Currans have assembled an impressive portfolio of research projects on trip generation. Their research caught the attention of city officials, who brought Clifton and Currans in as consultants to help them rethink the way they assess new fees for development.
Their work found a receptive audience of practitioners at TREC’s flagship conference, the Transportation and Communities Summit, last fall. Clifton and Currans held a workshop on improving trip generation methods to better represent the mix of modes found in livable communities. That led to a collaboration with transportation consultants...
A new NITC report offers a multimodal framework for transportation impact analysis – a welcome tool for professionals in many cities seeking more detailed data about non-drivers.
Improving Trip Generation Methods for Livable Communities, a research project headed by Kelly Clifton of Portland State University and Nico Larco of the University of Oregon, is the latest effort in an ongoing collaboration to create more open sourced, widely available data about non-motorized road users.
Over the last decades, cities have become more invested in fostering the conditions to support walking, biking and public transit.
The land development process presents a unique challenge.
Prior to a zoning change or new development, someone has to determine what its impact on the transportation system will be, and whether upgrades will be necessary to accommodate travelers to the new destination. Trip generation is the first step in the conventional transportation forecasting process.
Current trip generation methods used by engineers across the country tend to focus on motorized modes.
Without reliable trip generation rates for anyone but drivers, the transportation impact is difficult to predict. Certain land uses will draw far more walkers,...
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Planners looking to develop an dense mix of urban land uses often face a dilemma: they’re using trip-generation models that undercount the very trips on bicycle and foot that the planners encourage while paving the way for more driving.
Portland State University Associate Professor Kelly Clifton dove into the topic Monday, presenting a paper at the Transportation Research Board annual meeting in Washington D.C. Kristina Currans of PSU, April Cutter of Metro, and Robert Schneider of the University of California Berkeley are coauthors.
Clifton and other panelists agreed that the Institute of Transportation Engineers’ trip generation rates don’t adequately reflect actual trips in an urban area with multiple land uses and transportation modes. They differed on the remedy, however.
Presenting another paper, Associate Professor Kevan Shafizadeh of California State University Sacramento, evaluated and tested several complex methods, finding that none truly suits smart-growth development projects. However, Shafizadeh and his team found that every method tested does a better job at predicting the number of trips generated than the ITE rates.
We need to predict trips better, Clifton said, but perhaps a simpler solution exists. She acknowledged Shafizadeh’s conclusions that each alternative also had deficiencies in certain applications, and suggested that the ITE rates could be tweaked instead of scrapped entirely.
“It’s a Band-Aid to temporarily adjust...
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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...
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