#psutrec

[portlandstateresearch]

Krista Nordback and Sirisha Kothuri of Portland State’s Transportation Research and Education co-wrote a paper titled, “Annual Average Nonmotorized Traffic Estimates from Manual Counts: Quantifying Error”, published by Sage Journal in October 18th, 2018.

Abstract

Across the United States, jurisdictions are investing more in bicycle and pedestrian infrastructure, which can benefit from nonmotorized traffic volume data. The design of nonmotorized counting programs varies. Whereas some agencies use automated counters to collect continuous and short duration counts, the most common type of bicycle and pedestrian counting is manual counting either in the field or from video. The objective of this research is to identify the optimal times of day to conduct manual counts for the purposes of accurately estimating annual average daily nonmotorized traffic (AADNT). This study used continuous bicycle and pedestrian counts from six U.S. cities to estimate AADNT and analyze estimation errors for multiple short duration count scenarios. Using two permanent counters per factor group reduces error substantially (> 50%); afternoon counts seem to be best for reducing error (2:00 to 6:00 p.m.). Error on Sunday is often as good as, if not better than, Saturday, contrary to what others have found. Arlington has the lowest AADNT estimation error (mean absolute percentage error), probably because of better data quality and higher nonmotorized traffic volumes, and Mount Vernon, Washington has the highest. Average AADNT estimation errors for the studied short duration count scenarios range from 30% to 50%. Error is lower for the commute factor group, bicycle-only counts, scenarios in which more peak hours are counted, and when more than one permanent counter is available to estimate adjustment factors.

[portlandstateresearch]

Portland State University recently received a $118,000 contract from Kittelson & Associates as a part of a National Academy of Sciences, Engineering, and Medicine funded project “Enhancing Pedestiran Volume Estimations and Developing HCM Pedestrian Methodologies for Safe and Sustainable Solutions.”

The project, which will be lead by civil and environmental engineering research associate and TREC researcher Sirisha Kothuri and civil and environmental engineering professor Christopher Monsere, will lead to the development of scalable guidance for jurisdictions to identify techniques for efficient and accurate estimation of pedestrian volume and exposure to traffic and determine how pedestrian safety improvements on roadways and signal timing designs should be reflected in the Highway Capacity Manual.

[portlandstateresearch]

Investigating the precarity of affordable rental housing and the potential for displacement along planned transit lines. Speaker: Lisa Bates, Associate Professor, Urban Studies

[portlandstateresearch]

Kelly Clifton, civil and environmental engineering faculty member, coauthored “Spatial transferability assessment of a composite walkability index: The Pedestrian Index of the Environment (PIE),” published in Transportation Research Part D: Transport and Environment.

Abstract

This paper analyzes the transferability of a composite walkability index, the Pedestrian Index of the Environment (PIE), to the Greater Montréal Area (GMA). The PIE was developed in Portland, Oregon, and is based on proprietary data. It combines six urban form variables into a score ranging from 20 to 100. The measure introduces several methodological refinements which have not been applied concurrently in previous efforts: a wide coverage of the different dimensions of the urban form, together with the use of a distance-based decay function and modelling-based weighing of the variables.

This measure is applied to the GMA using local data in order to evaluate the feasibility of its transfer (the possibility of locally replicating the measure). It is then included in a series of mode choice models to assess its transferability (the capacity of the measure to describe walkability and predict mode choice in another urban area). The models, segmented by trip distance or trip purpose, are estimated and validated against observed trip data from the 2013 Origin-Destination survey.

Significant positive correlation is found between the PIE and the choice of walking for short trips, for all purposes as well as for four specific trip purposes. The inclusion of the PIE also improves the accuracy of the modelling process as well as the prediction of the choice of walking for short trips. The PIE can therefore be used in the GMA, and potentially in other metropolitan areas, to improve the modelling of travel behavior for short trips.

[portlandstateresearch]

New research on minority perceptions of bike sharing programs from  Nathan McNeil, Transportation Research & Education Center/Toulan School of Urban Studies and Planning, was recently featured in an article by Benjamin Schnider in CityLab. Read the story here.

[portlandstateresearch]

PSU study: Bike share improvements could boost minority and low-income ridership

People of color and low-income residents of major cities are far less likely to use municipal bike sharing systems than their white and higher-income counterparts. But researchers at Portland State University say that situation could change if cities addressed areas of safety, ridership cost and other factors that keep those groups from using bike sharing.

Those findings by the PSU’s Transportation Research and Education Center (TREC) were prepared for the National Institute for Transportation and Communities in a report titled Breaking Barriers to Bike Share: Insights from Residents of Traditionally Underserved Neighborhoods.

The research team, led by PSU’s Nathan McNeil and Jennifer Dill, surveyed residents of Philadelphia, Chicago and Brooklyn. One reason persons of color and low-income residents in those cities said they did not use bike share programs was because of fear of traffic and concerns for their personal safety, including fear of harassment or becoming a victim of a crime.

The report makes several suggestions for improving ridership among minorities and low-income residents, including discounts and other cost-saving measures. It also suggest greater public relations efforts to let those populations know how to use bike share and how to access available discounts.

Bike share customers typically use a credit card at a bicycle docking station, although cash options are sometimes available. The process allows riders to check out a bike for 30- to 60-minute intervals before returning it there or to another station. Customers can also use smartphones to locate docking stations and see if bikes are available.

But the report found that lower income people of color were far less likely to own a credit card, a debit card, a smartphone or have reliable internet access than higher income residents.

Cost was also a big factor among lower income respondents, as was the fear that they would have to pay for the bike if they damaged it. Although reduced-cost membership for low-income residents -- such as Portland’s BIKETOWN for All program -- is available in some cities, about a third of the respondents didn’t know about them. Eighty percent said they would be more likely to use bike share if those options were in place.

Bike sharing systems have grown rapidly over the last decade, going from a few select European cities to expanding in North America at a pace of nearly two dozen cities per year. There are more than 150 bike share programs in the United States.

The report states that less than half of low-income people of color have a driver’s license and only 17 percent own a bicycle, and that bike sharing could go a long way in filling their transportation needs.

By John Kirkland, University Communications