How Sprawl is Lengthening our Commutes and Why Misleading Mobility Measures are Making Things Worse

The video begins at 2:26.

Abstract: This report offers a new view of urban transportation performance. It explores the key role that land use and variations in travel distances play in determining how long Americans spend in peak hour travel. It shows how the key tool contained in the Urban Mobility Report – the Travel Time Index – actually penalizes cities that have shorter travel distances and conceals the additional burden caused by longer trips in sprawling metropolitan areas. Finally, it critically examines the reliability and usefulness of the methodology used in the Urban Mobility Report, finding it does not accurately estimate travel speeds, it exaggerates travel delays, and it overestimates the fuel consumption associated with urban travel. How we measure transportation systems matters, and the nation needs a better set of measures than it has today.

Extending the Value of Automatic Data Collection Systems in Transit

The video begins at 3:10.

Student presentations from TRB, week 2

Watch video

View Nicholas Stoll's presentation slides

View Nicholas Kobel's presentation slides

Nicholas Stoll, Graduate Research Assistant, Portland State University

Topic: Utilizing High Resolution Bus GPS Data to Visualize and Identify Congestion Hot-spots in Urban Arterials

The research uses high resolution bus data to examine sources of delay on urban arterials. A set of tools were created to help visualize trends in bus behavior and movement, which allowed for larger traffic trends to be visualized along urban corridors and urban streets. By using buses as probes and examining aggregated bus behavior, contoured speed plots were used to understand the behavior of roadways outside the zone of influence of bus stops. These speed plots can be utilized to discover trends and travel patterns with only a few days’ worth of data. Congestion and speed variation can be viewed by time of day and plots can help indicate delays caused by intersections, crosswalks, or bus stops.

This type of information is important to transit authorities looking to improve bus running times and reliability. Congested areas can be detected and ranked. Speed plots...

Read more

TRB Highlights: 3 PSU Student Presentations

Watch video

View slides: Bell Presentation (PDF)

Moore Presentation (PDF)

Ma Presentation (PDF)

Summaries: 
Identification and Characterization of PM2.5 and VOC Hot Spots on Arterial Corridor by Integrating Probe Vehicle, Traffic, and Land Use Data: The purpose of this study is to explore the use of integrated probe vehicle, traffic and land use data to identify and characterize fine particulate matter (PM2.5) and volatile organic compound (VOC) hot spot locations on urban arterial corridors. An emission hot spot is defined as a fixed location along a corridor in which the mean pollutant concentrations are consistently above the 85th percentile of pollutant concentrations when considering all other locations along the corridor during the same time period. In order to collect data for this study, an electric vehicle was equipped with instruments designed to measure PM2.5 and VOC concentrations. Second-by-second measurements were performed for each pollutant from both the right and left sides of the vehicle. Detailed meteorological, traffic and land use data is also...

Read more

Portal 2.0: A Next-Generation Archived Data User Service

Video begins at 3:33.

Evaluating Travel Survey Data Collection Methods in Oregon

The video begins at 0:29.

Student presentations from TRB, week 3

View Andy Kading's slides

View Patrick Singleton's slides

Watch video

Andy Kading, Graduate Student Researcher, Portland State University

Topic: Managing User Delay with a Focus on Pedestrian Operations

Across the U.S, walking trips are increasing. However, pedestrians still face significantly higher delays than motor vehicles at signalized intersections due to traditional signal timing practices of prioritizing vehicular movements. This study explores pedestrian delay reduction methods via development of a pedestrian priority algorithm that selects an operational plan favorable to pedestrian service, provided a user defined volume threshold has been met for the major street. This algorithm, along with several operational scenarios, were analyzed with VISSIM using Software-In-The-Loop (SITL) simulation to determine the impact these strategies have on user delays. One of the operational scenarios examined was that of actuating a portion of the coordinated phase, or actuated-coordinated operation. Following a discussion on platoon dispersion and the application of it in the design of actuated-coordinated signal...

Read more

Modeling Injury Outcomes of Crashes involving Heavy Vehicles on Texas Highways

Watch video

View slides

Summary: A growing concern related to large-truck crashes has increased in the State of Texas in recent years due to the potential economic impacts and level of injury severity that can be sustained. Yet, studies on large truck involved crashes highlighting the contributing factors leading to injury severity have not been conducted in detail in the State of Texas especially for its interstate system.  In this study, we analyze the contributing factors related to injury severity by utilizing Texas crash data based on a discrete outcome based model which accounts for possible unobserved heterogeneity related to human, vehicle and road-environment. We estimate a random parameter logit model (i.e., mixed logit) to predict the likelihood of five standard injury severity scales commonly used in Crash Records Information System (CRIS) in Texas – fatal, incapacitating, non-incapacitating, possible, and no injury (property damage only). Estimation findings indicate that the level of injury severity outcomes is highly influenced by a number of complex interactions between factors and the effects of the some factors can vary across observations. The contributing factors include drivers’ demographics, traffic flow condition, roadway geometrics, land use and temporal...

Read more

Residential Choice Locations - A Search in the Mirror of the Past

View slides

Abstract: We propose to decompose residential self-selection by understanding its formation process. We take a life course perspective and postulate that locations experienced early in life have a lasting effect on our locational preferences in life. In other words, what was experienced spatially is a key factor contributing to our residential self-selection and our preferences in residential locations are formed long before our own self-selection begins.  We further hypothesize that prior locational influence interacts with period effect such that the same location experienced in different periods may have distinct effects.  Using an empirically collected dataset in the New York Metropolitan Region, we estimated a series of models to test these hypotheses. The results demonstrate that prior locational influence precedes residential self-selection. Furthermore, we show a variety-seeking behavioral pattern resulted from locations experienced during adolescence.

Data R Us: Personal Travel Data Sources for Planning

The video begins at 2:12.

Pages