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, …

China's Motorization Wave And The Place Of Emerging Technologies, Christopher Cherry

PSU Transportation Seminars

E-bikes, E-Cars, Carshare, Bikeshare, and Micro-EVs in China have shaken up the traditional motorization pathways that have occurred in developing countries in the past. The combination of emerging vehicle technologies, urban and environmental constraints, and heavy-handed policy make China's motorization processes unique in the world—but how China motorizes has far-reaching impacts based on sheer volume of vehicles and population.

This seminar discusses the results of a six-year NSF CAREER project to explore China's motorization processes, combining behavioral and environmental modeling approaches to assess the impacts of emerging vehicle technologies on motorization and ultimately environmental sustainability. The focus is mostly on …

Network Congestion Effect Of E-Hailing Transportation Services, Xuegang Ban

PSU Transportation Seminars

E-hailing plays a key role in emerging transportation services such as ridesourcing, ridesharing and taxis, among others. This seminar will present a general economic model to analyze the congestion effect of e-hailing services in a transportation network.

The model can help analyze customers’ choices of different modes, based on their value of time and the charging schemes of different services, as well as the overall impact of the services to network level congestion.

Getting To Know The Data: Understanding Assumptions, Sensitivities, Uncertainty, And Being "Conservative" While Using Ite's Trip Generation Data In The Land Development Process, Kristina Marie Currans

PSU Transportation Seminars

Many agencies rely on trip generation estimates to evaluate the transportation impacts of land development in urban and suburban areas alike. Over the past decade, substantial attention has been paid to one national set of guidelines—the Institute of Transportation Engineers (ITE) Trip Generation Handbook (2014) and corresponding Manual (2012)—focusing in particular to improve the use of these data and supplementary methods for urban contexts.

The purpose of this study is to explore the typical data provided in the Handbook, within the context of these new improved state-of-the-art methods. As ITE’s describes, “an example of poor professional judgment is to rely …

Addressing Data Challenges For Bicycle Crash Analysis, Eleni Christofa

PSU Transportation Seminars

Although an increasing number of separated bicycle facilities have been appearing across the US over the last few years, the majority of bicyclists are still traveling on roadways shared with motorized vehicles.

As a result, bicycles are essentially double exposed to safety risk, due to their interactions with both motorized vehicles and other bicycles. In addition to this double exposure, data challenges–such as a lack of continuous counts and bicycle crash data—complicate the assessment of bicycle safety further.

This research presents a bicycle crash analysis framework for estimating bicycle crash rates accounting for both bicycle and motorized vehicle exposure as …

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 …

Webinar: Integrating Explicit And Implicit Methods In Travel Behavior Research: A Study Of Driver Attitudes And Bias, Tara Goddard

TREC Webinar Series

Car crashes are still a leading cause of death in the United States, with vulnerable road users like bicyclists and pedestrians being injured or killed at rates that outpace their mode share.

Planners, engineers, and advocates are increasingly adopting Vision Zero and Tactical Urbanism approaches and trying to better understand the underlying causes of dangerous roadway interactions. However, existing research into crash causation has focused on instrumental factors (e.g. intersection type, vehicle speed) while little research has probed the role of attitudes or socio-cognitive mechanisms in interactions between roadway users.

Social psychology suggests that attitudes and social cognitions can play …

Using Fuzzy Cognitive Maps To Model Policy Issues In The Face Of Uncertainty And Limited Data, Brian Gregor

PSU Transportation Seminars

Planners and policymakers are often faced with the need to make decisions about issues for which there is uncertainty and limited data. For example, transportation planners are now faced with the prospect that new transportation technologies such as autonomous vehicles could greatly alter future transportation system needs. Decisions about these types of issues are difficult to reason about and consequently are likely to be ignored or made on the basis of simplistic logic. Although modeling could be helpful, especially for issues involving complex systems, it is rarely used because models usually require large amounts of data and and handle uncertainty …

Estimating Reliability Indices And Confidence Intervals For Transit And Traffic At The Corridor Level, Travis B. Glick

PSU Transportation Seminars

As congestion worsens, the importance of rigorous methodologies to estimate travel-time reliability increases. Exploiting fine-granularity transit GPS data, this research proposes a novel method to estimate travel-time percentiles and confidence intervals. Novel transit reliability measures based on travel-time percentiles are proposed to identify and rank low-performance hotspots; the proposed reliability measures can be utilized to distinguish peak-hour low performance from whole-day low performance. As a case study, the methodology is applied to a bus transit corridor in Portland, Oregon. Time-space speed profiles, heatmaps, and visualizations are employed to highlight sections and intersections with high travel-time variability and transit low performance. …

Avoiding Bus Bunching: From Theory To Practice, Ricardo Giesen

PSU Transportation Seminars

The problem of bus bunching in a high frequency service has been largely studied in the literature.

This phenomenon is produced by three main factors

(i) the variability in travel time between stops; (ii) variations in passenger demand; and (iii) drivers’ heterogeneity.

In order to tackle this phenomenon a wide range of control strategies have been proposed, however, none of them had been successfully implemented on a large transit network with high frequency services.

In this talk, we present a control scheme based on a rolling horizon optimization problem that has been successfully implemented for real-time control of two high …