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Summary: Dr. Lovell will talk about three projects funded by NASA and the FAA, addressing congestion in the National Airspace System. Dr. Lovell's team developed diffusion-based queuing models of individual airports that could support better building blocks for network-wide congestion models. The advantage of the new models is their flexibility with respect to input distributions. In a study for the FAA, Dr. Lovell's team developed day-of-operations collaboration "languages" suitable for the FAA and individual carriers in order to collectively manage expected airspace disruptions. Finally, he will discuss a study on predictability in the airspace, with a focus on scheduled block times.

Dr. Lovell is an Associate Professor with joint appointments in the Department of Civil and Environmental Engineering and the Institute for Systems Research. He is a member of the faculty of the Applied Mathematics, Statistics, and Scientific Computation Program. He is director of the University of Maryland chapter of Engineers Without Borders - USA, and serves that organization on its board and as a leader of one of its Technical Advisory Councils. Dr. Lovell received his B.A. in Mathematics from Portland State University in 1990, and M.S. and Ph.D....

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The video begins at 1:11.

Abstract: Metro's Transportation Research and Modeling Services Program's (TRMS) is responsible for the development, maintenance, and application of travel demand models for application in long-range planning efforts in the Portland metropolitan region. Representation of traffic -- both vehicular and transit -- plays an integral role in the travel demand modeling process. Complex software is required to assign vehicles and transit users to transportation networks to determine viable options available to travelers, costs associated with those options, and sets of routes by which travelers might navigate their trips. TRMS's current static assignment model has traditionally sufficed for use with Metro's four-step travel demand model. However, static assignments have well documented limitations that preclude the ability of the analyst to answer complex policy questions, especially those related to green house gas emissions, congestion, and transportation network reliability. In addition, static assignments cannot fulfill a need for small duration travel time increments required by the next generation activity-based models. The shortcomings of the static assignment necessitates TRMS's development of regional dynamic traffic assignment (DTA) models. The resolution of these models allows for continuous modeling of traffic over an analysis period, which allows the analyst to capture...

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Steven Gehrke, Ph.D. Candidate, Portland State University

Topic: An Activity-related Land Use Mix Construct and Its Connection to Pedestrian Travel

Land use mix is a central smart growth principle connected to active transportation. This presentation describes the indicators of local land use mixing and their association with pedestrian travel in Oregon’s Willamette River Valley. It argues that land use mix is a multidimensional construct reflected by the complementarity, composition, and configuration of land use types, which is positively linked to walk mode choice and home-based trip frequency. Findings from this study underline the conceptual and empirical benefit of analyzing this transportation-land use interaction with a landscape pattern measure of activity-related composition and spatial configuration.

Steven Gehrke is a Ph.D. candidate in Civil and Environmental Engineering at Portland State University. His research examines the transportation-land use interaction,...

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The video begins at 0:47.

Topic: Schedule-based Public Transportation Planning Model and Integration with Other Transportation Planning Models

Speaker Hyunsoo Noh, a PhD Candidate from the University of Arizona, will discuss the integration of schedule-based public transportation and other transporation planning models.

The video begins at 1:47.

Abstract: In transportation planning and engineering, market segments or groups of individuals with varying attitudes and travel behavior are often identified in order to define a set of policies and strategies targeted at each segment. Examples include residential location choice studies, electric vehicle adoption and the marketing of public transit options. Defining market segments is common in the marketing literature, typically based on observed socioeconomic characteristics, such as gender and income. However, in addition to these characteristics, travelers may also be segmented based on variations in their observed travel and activity patterns. The activity-based approach to travel demand analysis acknowledges the need to analyze the travel patterns of individuals, conceptualized as a trip chain or tour, as opposed to individual trip segments. This has implications for identifying markets segments based on travel patterns which needs to distinguish between the sequencing and timing of travel choices and activities, in addition to the actual travel choices and activities. One approach that holds promise is pattern recognition theory which has wide applications in image analysis, speech recognition and physiological signal processing. In this study, pattern recognition methods are applied to observed daily travel and activity patterns from Oregon to identify travel market...

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The video begins at 5:40.

Current research at the Institute of Transport and Logistics Analysis of the University of Sydney, under Professor Peter Stopher, has been concentrating on using personal GPS devices to collect travel behaviour data of individuals. In this seminar, Professor Stopher will outline the several projects that have been conducted and are currently underway that are using GPS. He will describe the survey procedures, and then provide an overview of some of the results emerging from collection of such data. Of particular interest is that the GPS surveys are being conducted in most cases by using a panel, with at least two waves of data collection, and that panel members carry the GPS devices for anywhere from one week to one month. Initial studies of the variability in daily travel, where there are no fatigue effects from recording multiple days in a diary, are showing some interesting patterns and leading to some important conclusions.

Peter Stopher is Professor of Transport Planning at the Institute of Transport and Logistics Studies of the University of Sydney, a position he has held since the beginning of 2001. Previously he held academic positions and also worked as a full-time consultant in the USA since 1968. He obtained his B.Sc. (Eng) and Ph.D. from University College London in the 1960s. He has more than 40 years of experience as an educator and consultant in transport...

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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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