Engineering Commons^™

Countywide Bluetooth System: Use Cases & Performance Measures, Shaun Quayle

PSU Transportation Seminars

Washington County has 124 permanent roadside Bluetooth readers, which passively and in an anonymous fashion collect travel time, speed, and origin-destination information across the major arterials in the urban County. This presentation gives an overview of the program purpose, history, some interesting use cases, and the formation of comparative performance metrics to gauge the magnitude and duration of congestion across the County. These metrics and information will help planners improve travel demand models, consultants improve traffic analyses, operations staff prioritize timing, detection, and maintenance functions, agencies inform traveler information data, and leaders better communicate the story of traffic demand, delay, …

Narratives Of Marginalized Cyclists: Understanding Obstacles To Utilitarian Cycling Among Women And Minorities In Portland, Or, Amy Lubitow

TREC Final Reports

Research has demonstrated that everyday or utilitarian forms of cycling are most likely to generate positive population-level health impacts (Garrard et al., 2012), yet significant deterrents to routine cycling remain, particularly for women and minorities. The primary aim of this project was to conduct a qualitative interview study that generated rich, narrative data regarding obstacles to routine or utilitarian cycling for women and minorities who already see biking as a viable form of transit, but who make relatively few bike trips. A secondary aim of the project was to develop a set of specific interventions that have the potential to …

Big Data And The Future Of Travel Modeling, Greg Macfarlane

PSU Transportation Seminars

New technologies such as smart phones and web applications constantly collect data on individuals' trip-making and travel patterns. Efforts at using these "Big data" products, to date, have focused on using them to expand or inform traditional travel demand modeling frameworks; however, it is worth considering if a new framework built to maximize the strengths of big data would be more useful to policy makers and planners.

In this presentation Greg Macfarlane will present a discussion on elements of travel models that could quickly benefit from big data and concurrent machine learning techniques, and results from a preliminary application of …

Exploring The Positive Utility Of Travel And Mode Choice, Patrick Allen Singleton

PSU Transportation Seminars

Why do people travel? We traditionally assume traveling is a means to an end, travel demand is derived (from the demand for activities), and travel time is to be minimized. Recently, scholars have questioned these axioms, noting that some people may like to travel, use travel time productively, enjoy the experience of traveling, or travel for non-utilitarian reasons. The idea that travel can provide benefits and may be motivated by factors beyond reaching activity destinations is known as “the positive utility of travel” or PUT.

This study presents a conceptual and empirical look at the positive utility of travel and …