Browsing by Author "Swingle, Howard"

Now showing 1 - 5 of 5
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    Development of an Airport Choice Model for General Aviation Operations
    Ashiabor, Senanu Y. (Virginia Tech, 2002-07-17)
    The General Aviation Airport Choice model is an attempt to model General Aviation (GA) travel patterns in the US in order to provide a means of assessing the impact of General Aviation activities on the National Air Space system. The model will also serve as part of transportation planning tool to help assess the viability of deploying NASA's Small Aircraft Transportation Systems (SATS) aircraft as a competitive mode of transportation for intercity travel. The General Aviation Airport Choice model developed estimates General Aviation (GA) person-trips and number of aircraft operations given trip demand in the form of GA person trips from counties. A pseudo-gravity model is embedded in the model to distribute the inter-county person-trips to a prescribed set of airports in the US. The airport-to-airport person-trips are split into person-trips by three aircraft modes (single, multi and jet engine) using an attractiveness factor based on average occupancy, utilization and a distance distribution factor for each aircraft type and the number of aircraft based at each airport. The person-trips by aircraft type are then converted to aircraft operations using occupancy factors for each aircraft type. The final output from the model are aircraft operations trip-tables by aircraft type between the airports in the model. The GA trips are estimated in order to provide a means of assessing the impact of GA activities on the National Airspace System. The model output may be used to assess the viability of GA aircraft serving as a competitive mode of transportation for intercity travel.
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    The Effect of Icing on the Dispatch Reliability of Small Aircraft
    Gates, Melinda M. (Virginia Tech, 2004-10-16)
    In 2000, the National Aeronautics and Space Administration (NASA) initiated a program to promote the use of small aircraft as an additional option for national public transportation. The Small Aircraft Transportation System (SATS) asserted the idea of everyday individuals piloting themselves on trips, within a specified distance range, using a small (4 person), piston powered, un-pressurized aircraft and small airports in close proximity to their origin and destination. This thesis investigates how one weather phenomenon, in-flight icing, affects the dispatch reliability of this transportation system. Specifically, this research presumes that a route is considered a "no-go" for low time pilots in a small, piston powered aircraft if any icing conditions are forecast along the route at the altitude of the flight during the time the traveler desires to make the trip. This thesis evaluates direct flights between Cleveland and Boston; Boston and Washington, D.C.; and Washington, D.C. and Cleveland during the months of November through May for the years 2001 to 2003 at maximum cruising altitudes of 6,000 feet, 8,000 feet, 10,000 feet, and 12,000 feet above mean sea level (MSL). It was found that the overall probability of a "no-go" for all three flight paths at the normal cruising altitude of 12,000 feet is 56.8%. When the cruising altitude is reduced to 10,000 feet, 8,000 feet, and 6,000 feet the probability of a "no-go" for all three flight paths reduces to 54.6%, 48.5%, and 43.7% respectively.
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    Forecasting Model for Air Taxi, Commercial Airline, and Automobile Demand in the United States
    Baik, Hojong; Trani, Antonio A.; Hinze, Nicolas; Swingle, Howard; Ashiabor, Senanu; Seshadri, Anand (Transportation Research Board of the National Academies, 2008)
    A nationwide model predicts the annual county-to-county person roundtrips for air taxi, commercial airline, and automobile at 1-year intervals through 2030. The transportation systems analysis model (TSAM) uses the four-step transportation systems modeling process to calculate trip generation, trip distribution, and mode choice for each county origin–destination pair. Network assignment is formulated for commercial airline and air taxi demand. TSAM classifies trip rates by trip purpose, household income group, and type of metropolitan statistical area from which the round-trip started. A graphical user interface with geographic information systems capability is included in the model. Potential applications of the model are nationwide impact studies of transportation policies and technologies, such as those envisioned with the introduction of extensive air taxi service using very light jets, the next-generation air transportation system, and the introduction of new aerospace technologies.
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    Integration of the Transportation Systems Analysis Model for the Small Aircraft Transportation System
    Hinze, Nicolas Karlsson (Virginia Tech, 2005-06-20)
    Standalone computer modules for county to county travel demand forecasting have been integrated. The Trip Generation, Trip Distribution and Mode Choice modules have been unified under one Graphical User Interface (GUI). The outputs are automatically mapped using Geographic Information Systems (GIS) technology to allow immediate and spatial analysis. The integrated model allows for faster running times and quicker analysis of the results. The ability to calculate travel time savings for travelers was also included to the final model. The modeling framework developed is known as the Transportation Systems Analysis Model (TSAM).
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    A Study of Commercial Aviation Demand and Revenue Responses to Changes in Ticket and Segment Tax
    Chung, Stephanie Pei-Hua (Virginia Tech, 2005-08-08)
    The Strategy Simulator project, funded by the Federal Aviation Administration (FAA), strives to find a tax structure that will support the National Airspace System (NAS) and maintain revenue neutrality, where taxes can be adjusted and the FAA can still attain the same revenue amount if taxes had not changed. Virginia Tech's role in the project is to analyze the effects of different tax structures on passenger demand. Virginia Tech focuses on ticket and segment taxes and runs different tax scenarios through the Transportation Systems Analysis Model (TSAM) and the TSAM Aggregation for the Strategy Simulator (TASS) model. TSAM provides a more microscopic analysis of demand by including spatial representation and mode choice in the model. TASS is a work in progress that aggregates the TSAM analysis in order to reduce computation time so that scenarios can be tested quickly. Based on data from literature review, TSAM results provides the smallest combined percent error for demand and revenue, followed by TASS, then the Strategy Simulator. TSAM and TASS also provide a detailed analysis of demand behavior in response to tax changes. In general, demand decreases as taxes increase, and demand increases over the years due to a fare scaling factor applied to reduce fares over the years. Revenue increases both over increasing taxes and over the years, indicating that increases in taxes does not harm revenue collection and actually increases revenues for the ticket and segment taxes tested. Revenue increases over the years because demand increases over the years, and the revenue generated from this increased demand more than makes up for decreased fares.