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.
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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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Adam Moore: Bus Stop Air Quality: An Empirical Analysis of Exposure to Particulate Matter at Bus Stop Shelters
Congested traffic corridors in dense urban areas are key contributors to the degradation of urban air quality. While waiting at bus stops, transit patrons may be exposed to greater amounts of vehicle-based pollution, including particulate matter, due to their proximity to the roadway. Current guidelines for the location and design of bus stops do not take into account air quality or exposure considerations. This study compares the exposure of transit riders waiting at three-sided bus stop shelters that either: 1) face the roadway traffic or 2) face away from the roadway traffic. Shelters were instrumented with air quality monitoring equipment, sonic anemometers, and vehicle counters. Data were collected for two days at three shelters during both the morning and afternoon peak periods. Bus shelter orientation is found to significantly affect concentration of four sizes of particulate matter: ultrafine particles, PM1, PM2.5, and PM10. Shelters with an opening oriented towards the roadway were consistently observed to have higher concentrations inside the shelter than outside the shelter. In contrast, shelters oriented away from the roadway were observed to have lower concentrations inside the shelter than outside the shelter. The differences in particulate matter...Read more
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Abstract: Urban arterials often represent complex venues of transportation operations, co-mingling non-motorized users with transit services and a wide variety of land uses and traffic patterns. This presentation presents results related to the evaluation of a new Adaptive Traffic Control System (SCATS) on Powell Boulevard in southeast Portland. The presentation will discuss challenges and opportunities associated with the evaluation of new technologies and the development of comprehensive urban arterial performance measures.
Speaker Bio: Miguel Figliozzi is an Associate Professor of Civil and Environmental Engineering at Portland State University. His diverse research interests include transit and traffic operations, bicycle and pedestrian modes, emissions and air quality modeling, and freight and logistics. He holds a MS from the University of Texas at Austin and a PhD from the University of Maryland College Park. Figliozzi is a member of the Transportation Research Board Network Modeling Committee, Freight and Logistics, and Intermodal Terminal Design Committees. Papers, reports, and more detailed information available at Figliozzi's webpage: http://web.cecs.pdx.edu/~...Read more
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Abstract: Traffic counts are an important piece of information used by transportation planners; however, while count programs are common for motor vehicles most efforts at counting non-motorized traffic – cyclists and pedestrians – are minimal. Long-term, continuous counts of non-motorized traffic can be used to estimate month of year and day of week adjustment factors that can be used to scale short-duration counts to estimates of annual average daily traffic. Here we present results from continuous counts of non-motorized traffic at 6 locations on off-street trails in Minneapolis, MN using two types of automated counters (active infrared and inductive loop detectors). We found that traffic volumes varied significantly by location, but the month of year and day of week patterns were mostly consistent across locations and mode (i.e., cycling, walking, or mixed mode). We give examples of how this information could be used to extrapolate short-duration counts to estimates of annual average daily traffic as well as Bicycle Miles Traveled (BMT) and Pedestrian Miles Traveled (PMT) for defined lengths of off-street trails. More research is needed to determine if non-motorized traffic patterns (and subsequently our adjustment factors) for...Read more
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Abstract: TriMet has used a computer aided dispatch (CAD)/automatic vehicle location (AVL) system to manage bus and rail operations since the late 1990s. TriMet is currently in the process of updating the CAD/AVL system, and anticipates improvements in bus tracking and performance monitoring. This presentation will show how TriMet uses data from the system to support intelligent transportation systems (ITS) such as TransitTracker and automatic stop announcements in buses and trains, as well as to analyze transit operations such as on time performance and passenger loads.
Speaker Bios: Steve Callas is the Manager of Service and Performance Analysis at TriMet in Portland Oregon, where he is responsible for operations performance monitoring and analysis. This includes analyzing TriMet’s comprehensive automatic vehicle location and automatic passenger counter data archive. Additionally, Steve is involved in various transit operations research projection in conjunction with Portland State University and OTREC. Steve has been with TriMet for over 15 years.
David is an operations analyst with TriMet. He is involved in AVL data mining and analysis, safety analysis, automatic stop announcements, transit signal priority, and real-time customer information. David has been with...Read more
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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.
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.