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Summary: The transportation system is the backbone of the United States' economy, and transportation is an essential part of everyday life for American citizens. It is essential that the transportation system continue to provide accessibility and connectivity to an ever-evolving global economy. A key way to do so is to embrace, develop and implement new technologies. One of the newest and most promising facets of transportation-related technology is in the field of connected mobility. The vision behind connected mobility is of a transportation system where vehicles, travelers, and infrastructure are all wirelessly connected with one another and able to transmit real-time data about things like weather, location, and vehicle and infrastructure status. Such a degree of connectivity could have substantial benefits for the safety, mobility, and sustainability of the domestic transportation system, including accident prevention and congestion reduction. In recent years, major strides have been made into the research and development of connected mobility technology and some field-testing has commenced, but there is a need for more attention and investment from stakeholders throughout the transportation community and beyond. 

Bio: Robert Bertini is a...

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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.

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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...

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OVERVIEW

Every day transit riders ask the same question: when’s the next one coming? To answer this question, transit agencies are transitioning to providing real-time transit information through smartphones or displayed at transit stops. 

The proliferation of transit planning and real time arrival tools that have hit the market over the past decade is staggering. Yet with transit ridership on the decline, agencies can’t afford to ignore the importance of providing accurate, real time information to their customers. Real-time transit information improves the reliability and efficiency of passenger travel, but barriers have prevented some transit agencies from adopting the GTFSrealtime v1.0 technology. A new NITC-funded study in May led by Sean Barbeau of the University of South Florida seeks to...

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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...

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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...

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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...

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