data science | National Institute for Transportation and Communities

Peak Pedaling: Has Portland Bicycling reached the Top of the Logistic Curve?

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Other presentation materials: Handout (PDF)

Summary: The recent City Club report on bicycling provided an opportunity to collect and analyze a number of data sets including the new Hawthorne Bridge data. One question is where Portland bicycling on the logistic curve -- a common tool for judging the maturity of a developing product or activity. Logistic curves are used for marketing, for epidemiology, and even for visits to Indian owned casinos. The preliminary evidence is that we are reaching the horizontal area of the curve. Additional evidence Our further research into future policies indicates a shift to bicycle boulevards in order to attract more risk averse riders.

Bio: Robert McCullough is an energy economist (and an adjunct at PSU) who has written, talked, and testified on energy issues across the U.S. and Canada. He was instrumental in the identification and prosecution of Enron's energy traders. He also works with aboriginal groups in Quebec and Oregon, activists in California and Ohio, as well as many others. His most recent project is the economic review of the WNP-2 nuclear station for Physicians for Social...

Crowdsourcing Cycling Safety and Route Data with the “ORcycle” Smartphone App

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ORcycle is a new smartphone application (for both Android and iOS) developed by Transportation, Technology, and People (TTP) lab researchers at Portland State University as part of an Oregon Department of Transportation (ODOT) research project. ORcycle collects user, route, infrastructure, crash, and safety data. ORcycle was successfully launched in early November 2014 and presents many improvements over existing or similar apps. Initial data findings and insights will be presented. Lessons learned as well as opportunities and challenges associated with smartphone data collection methods will be discussed. More information about the app can be found here: http://www.pdx.edu/transportation-lab/orcycle

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Travel Decisions & Their Implications for Urban Transportation: From Campus Transportation to Statewide Modeling

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Where: Room 204 of the Distance Learning Center Wing of the Urban Center at PSU

The ability to forecast future transportation patterns under a particular land-use scenario or urban form is key to making informed decisions at the local and regional levels.

Although several researchers have explored the links between the built environment, socio-demographics and travel behavior, a consensus is not reached.

This talk highlights two recent projects. The first project focuses on individuals’ attitudes towards transportation, neighborhood characteristics and their effects on campus commuters’ transit use, and addresses the question whether attitudes, the built environment or a combination of both explains the resulting transit use better.

The second part presents the Regional Land Use Allocation Decision Analysis Tool developed for The Ohio Department of Transportation, which enables decision makers to quantify the impacts of population and employment distribution in terms of the resulting VMT (Vehicle Miles Traveled). This tool forecasts the impacts of future land-use policies in Ohio, based on alternative assumptions of highway and mass transit corridor development, zoning and environmental constraints, regional growth or decline...

Webinar: Visual Exploration of Trajectory Data

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OVERVIEW

This webinar will demonstrate the tremendous value of GPS trajectory data in understanding statewide travel patterns and measuring performance. First, Dr. Markovic (U of Utah) will conduct visual exploration of GPS trajectories that capture about 3% of all the trips in Utah. He will briefly discuss the problem of scaling GPS trajectories to the population, and then focus on the use of scaled trajectories in computing origin-destination matrices, vehicle-hours delays, vehicle-miles traveled, and trip-based performance measures. Second, Dr. Franz (CATT Lab) will demonstrate a suite of visual analytics that enables transportation agencies to easily explore terabytes of GPS trajectory data. He will demonstrate different tools and share the experience of 5 state DOTs that are currently using CATT Lab's trajectory data suite.

KEY LEARNING OUTCOMES

Trajectory data represents the most complete vehicle-probe data and provides unprecedented opportunity for transportation system analysis.
Transportation agencies can easily leverage visual analytics to obtain insights in statewide traffic patterns and...

Using "big data" for transportation analysis: A case study of the LA Metro Expo Line

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Topic: Using "big data" for transportation analysis: A case study of the LA Metro Expo Line

Summary: Access to a comprehensive historical archive of real-time, multi-modal multi-agency transportation system data has provided a unique opportunity to demonstrate how “big data” can be used for policy analysis, and to offer new insights for planning scholarship and practice. We illustrate with a case study of a new rail transit line. We use transit, freeway, and arterial data of high spatial and temporal resolution to examine transportation system performance impacts of the Exposition (Expo) light rail line (Phase 1) in Los Angeles. Using a quasi-experimental research design, we explore whether the Expo Line has had a significant impact on transit ridership, freeway traffic, and arterial traffic within the corridor it serves. Our results suggest a net increase in transit ridership, but few effects on traffic system performance. Given the latent travel demand in this heavily congested corridor, results are consistent with expectations. The benefits of rail transit investments are in increasing transit accessibility and person throughput within high-demand corridors; effects on roadway traffic are small and localized.

Bio: Mohja Rhoads...

Determinants of VMT in Urban Areas: A Panel Study of 87 US Urban Areas 1982-2009

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This paper uses econometric techniques to examine the determinants of vehicle miles traveled (VMT) in a panel study using data from a cross section of 87 U.S. urban areas over the period 1982-2009. We use standard OLS regression as well as two-stage least squares techniques to examine the impact of factors such as population density, lane-miles per capita, per capita income, real fuel cost, transit mileage, and various industry mix variables on VMT. We use a distributed lag model to estimate the long run elasticity of various factors on VMT driven.

Preliminary empirical results show the demand for VMT in urban areas is positively and significantly impacted by lane miles, personal income, and the percent of employment in the construction. Fuel price, transit use and population density are all found to be negatively related to VMT per capita. Consistent with results from earlier studies, we find the long run price elasticity of demand for VMT per capita is approximately five times larger than the short run elasticity.

Holding all factors constant, per capita VMT is found to differ significantly by region with VMT being higher the more western and the larger the population size of an urban area. Finally, we find that the industry mix or the urban area also has a significant impact on driving.

Lighten Everyone's Load: LIDAR Applications to Support Engineers, Planners, Scientists and More

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Light detection and ranging (LIDAR) technology is reshaping the civil engineering profession and offers many unique advantages. National efforts such as the 3D Elevation Plan (3DEP) are helping increase the availability of LIDAR data. LIDAR is one of the crucial technologies that is transitioning the world of civil and construction engineering from 2D paper-based design to 3D digital design. The high spatial resolution and accuracy capabilities of LIDAR have led to increased efficiencies, improved analyses, and more informed decision making.

A further advantage of this dataset is that multiple people can use the same dataset for a variety of purposes across multiple disciplines. The visual nature of the dataset also is more intuitive than traditional data acquisition and analysis techniques. This presentation will provide a brief background of LIDAR , its capabilities, limitations and platforms, and discuss its current and future role in civil engineering. Examples of a wide range of transportation, geotechnical, coastal, and structural engineering, science, and planning applications will be presented including development of mobile LIDAR guidelines for...

Development of the Idaho Statewide Travel Demand Model Trip Matrices Using Cell Phone OD Data and Origin Destination Matrix Estimation

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Topic: Airsage cell phone data and its application in travel modeling
Summary: As part of the initial phase of development for the Idaho Statewide Travel Demand Model, Parsons Brinckerhoff developed a base year auto and truck trip matrix using AirSage cell phone OD data, a statewide network in Cube, traffic counts, and origin-destination matrix estimation (ODME) procedures. To begin, the 4000+ statewide zone system was aggregated into a 700 super zone system for collecting the cell phone OD data. Next, the cell phone data was collected for the month of September 2013 for the following market segments: Average weekday resident HBW, HBO, NHB, and visitor NHB trips. The cell phone trips were then disaggregated to zones using each zone’s share of super zone population and employment. These initial trip matrices were assigned to the daily statewide network using free flow travel time for route impedance and iteratively adjusted to minimize the difference between the estimated link volumes and traffic counts by user class.

This iterative trip matrix balancing procedure, also known as ODME, converged nicely by user class and facility type and produced reasonable flows. The resulting trip matrix trip length frequencies matched fairly well with the...

Transit Scheduling/Routing Data Applications

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Abstract: TriMet collects detailed ridership data from automatic passenger counters on buses and trains. In addition, an automatic vehicle location system provides specific information on how well buses and trains adhere to preset schedules. This presentation is an overview of how TriMet uses these data in designing and managing the transit network, ranging from developing regional service policies to making minor schedule adjustments on a bus line.

Speaker Bio: Ken Zatarain is TriMet Director of Service Planning and Scheduling. He has had several other positions at TriMet. Prior to joining TriMet, he worked at the federal and local government levels. Ken has a degree in Regional and City Planning from the University of North Carolina.

Combining Climate, Crash, and Highway Data for Improved Ranking of Speed and Winter-Weather Related Crash Locations in Oregon

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KEY LEARNING OUTCOMES

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