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PRESENTATION ARCHIVE
OVERVIEW
The National Street Improvements Study, conducted by PSU in conjunction with PeopleForBikes and consulting firm Bennett Midland, researched the economic effects of bicycle infrastructure on 14 corridors across six cities — Portland, Seattle, San Francisco, Memphis, Minneapolis and Indianapolis. The study found that improvements such as bicycle and pedestrian infrastructure had either positive or non-significant impacts on the local economy as measured through sales and employment. In this webinar, lead researcher Jenny Liu will share the results of the investigation and the unique methodology for investigating these economic outcomes.
THE RESEARCH
This webinar is based on a study funded by the National Institute for Transportation and Communities (NITC) and the Summit Foundation, and conducted at Portland State University. Read more about the research: ...
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For a number of reasons—congestion, public health, greenhouse gas emissions, energy use, demographic shifts, and community livability to name a few—the importance of walking and bicycling as transportation options will only continue to increase. Currently, policy interest and infrastructure funding for nonmotorized modes far outstrip our ability to successfully model bike and walk travel. In the past five years, we have learned a lot about where people prefer to bike and walk, but what can that tell us about whether people will bike or walk in the...
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Dr. Kelly Clifton, associate professor of Civil and Environmental Engineering at PSU, will present results from Clifton's recent study that aims to make connections between our travel choices and our consumer behavior. Based upon a survey administered in the Portland metro area in the summer 2011, the analysis examines the various influences on mode choices to local restaurants. Similarly, patron spending and frequency of visits are also analyzed with respect to mode to better understand these complex relationships. In this talk, there will be an emphasis on comparing patrons that choose non-automobile modes to those who take a private vehicle. These findings are useful as communities around the country try to educate the business community about the potential impacts of investments in cycling, pedestrians and transit.
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Abstract: Existing regional travel forecasting systems are not typically set up to forecast usage of bicycle infrastructure and are insensitive to bicyclists' route preferences in general. We collected revealed preference, GPS data on 162 bicyclists over the course of several days and coded the resulting trips to a highly detailed bicycle network model. We then use these data to estimate bicyclist route choice models. As part of this research, we developed a sophisticated choice set generation algorithm based on multiple permutations of labeled path attributes, which seems to out-perform comparable implementations of other route choice set generation algorithms. The model was formulated as a Path-Size Logit model to account for overlapping route alternatives. The estimation results show compelling intuitive elasticities for route choice attributes, including the effects of distance and delay; avoiding high-volumes of vehicular traffic, stops and turns, and elevation gain; and preferences for certain bike infrastructure types, particularly at bridge crossings and off-street paths. Estimation results also support segmentation by commute versus non-commute trip types, but are less clear when it comes to gender. The final model will be implemented as part of the regional travel forecasting system for Portland, Oregon, U.S.A.