This report presents a top-down methodology to forecast annual international flight operations at sixty-six U.S. airports, whose combined operations accounted for 99.8% of the total international passenger flight operations in National Airspace System (NAS) in 2004. The forecast of international flight operations at each airport is derived from the combination of passenger flight operations at the airport to ten World Regions. The regions include: Europe, Asia, Africa, South America, Mexico, Canada, Caribbean and Central America, Middle East, Oceania and U.S. International. In the forecast, a "top-down" methodology is applied in three steps. In the fist step, individual linear regression models are developed to forecast the total annual international passenger enplanements from the U.S. to each of nine World Regions. The resulting regression models are statistically valid and have parameters that are credible in terms of signs and magnitude. In the second step, the forecasted passenger enplanements are distributed among international airports in the U.S. using individual airport market share factors. The airport market share analysis conducted in this step concludes that the airline business is the critical factor explaining the changes associated with airport market share. In the third and final step, the international passenger enplanements at each airport are converted to flight operations required for transporting the passengers. In this process, average load factor and average seats per aircraft are used. The model has been integrated into the Transportation Systems Analysis Model (TSAM), a comprehensive intercity transportation planning tool. Through a simple graphic user interface implemented in the TSAM model, the user can test different future scenarios by defining a series of scaling factors for GDP, load factor and average seats per aircraft. The default values for the latter two variables are predefined in the model using 2004 historical data derived from Department of Transportation T100 international segment data. / Master of Science

This dissertation is a collection of several models to understand airline and passenger dynamics in the National Airspace System (NAS). Agent-based modeling is one of the most widely used modeling simulation-analysis approaches to understanding the dynamic behavior of complex systems. The usefulness of agent-based modeling has been demonstrated by simulating the complex interactions between airlines, travelers, and airports of a small-scale transportation system. Three airlines, one low cost and two network airlines are simulated to examine how each airline behaves over time to maximize their profit margins for a given passenger demand and operation cost structure. Passenger mode choice and itinerary choice sub modules are embedded in the framework to characterize traveler agent's response to the evolved airline schedule. An airport delay model was implemented to estimate the average delay at each airport. The estimated delay fed into the mode choice and itinerary choice models to update the travel time related variables. International passenger demand is a very important component of the air transportation system in the United States. The proportion of international enplanements relative to total enplanements increased from 8% in 1990 to 11% in 2008. Nine linear regression models are developed to forecast the enplanements from the United States to each of nine international regions. The international enplanements from the CONUS to each world region are modeled as a function of GDP and GDP per capita of both the United States and the specific region. A dummy variable is also used to account for the effects of September 11, 2001. The total number of international enplanements is forecast to increase from 74.7 million in 2008 to 184.4 million in 2028. The average annual growth rate is expected to be 4.7%. The European Union – United States Open Skies Agreement, which became effective March 30, 2008. Mathematical models are developed to forecast the effect of EU-US Open Skies Agreement on commercial airline passenger traffic over the North Atlantic Ocean. Nine econometric models were developed to forecast passenger traffic between the United States and nine selected European countries between 2008 through 2020. 68 new nonstop flights between the United States airports and the European airports are predicted by the model in 2020 using the airport pair passenger demand forecast. London, Heathrow is demonstrated as an example for rerouting the excess air travel passengers from one airport to other airports when the airport operational capacity is exceeded. The proportion of international enplanements relative to total enplanements within CONUS increased from 8% in 1990 to 11% in 2008. 51% of the sampled international and U.S. territories passengers served by U.S. carriers had at least one domestic coupon in 2007. The number of DOI passengers through airport-pairs in each of the historical years (1990-2007) is estimated based on the adjusted 100% international itineraries including pure international itineraries plus the non-CONUS itineraries. The total number of DOI enplanements is estimated to grow from 37.3 million in 1990 to 79.4 million in 2007. 193 CONUS airports are estimated to have at least 10,000 DOI enplanements in 2007. The number of DOI enplanements is forecast to grow from 79.4 million in 2007 to 206.2 million in 2030 with average growth rate of 4.2% per year. In recent years, there has been an increasing use of secondary airports both in Europe and the U.S. Regional airports have long been considered as a possible source of relief to reduce airport congestion at the hub airport and to efficiently accommodate future air travel demand. The conditions under which the secondary airports develop in a metropolitan area are examined. Fifteen multi-airport systems including 19 Operational Evolution Plan airports and 25 active secondary airports are identified in the National Airspace System. Diverse trends of traffic distribution among airports in the same metropolitan area are observed. We observed that the number of markets served at the secondary airports is less than that at the primary airport in the same metropolitan area. Most of the secondary airports are currently dominated by the low-cost carriers. The share of seats supplied by the low-cost carriers at the secondary airports has increased during the period 1990-2008. Full service carriers concentrate their service mainly on the primary airport in all the multi-airport systems analyzed. The average seat capacity per aircraft at the secondary airports is higher than that of primary airports in most of the multi-airport systems. The secondary airports mainly serve the domestic O&D passengers. / Ph. D.

The Portfolio Analysis Management Office (PAMO) for the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters tasked the Systems Analysis and Concepts Directorate at NASA Langley to combine efforts with Virginia Tech to develop a global demand model with the capability to predict future demand in the air transportation field. A previous study (Alsalous, 2015) started the development of the Global Demand Mode (GDM) to predict air travel demand based on Gross Domestic Product (GDP) and population trends for 3,974 airports worldwide. The study was done from year 2016 to year 2040. This research project intends to enhance the GDM capabilities. A Fratar model is implemented for the distribution of the forecast demand during each year. The Fratar model uses a 3,974 by 3,974 origin-destination matrix to distribute the demand among 55,612 unique routes in the network. Moreover, the GDM is capable to estimate the aircraft fleet mix per route and the number of flights per aircraft that are needed to satisfy the forecast demand. The model adopts the aircraft fleet mix from the Official Airline Guide data for the year 2015. Once the aircraft types are distributed and flights are assigned, the GDM runs an aircraft retirement and replacement analysis to remove older generation aircraft from the network and replace them with existing or newer aircraft. The GDM continues to evolve worldwide aircraft fleet by introducing 14 new generation aircraft from Airbus, Boeing, Bombardier, and Embraer and 5 Advanced Technology Aircraft from NASA. / Master of Science / The Portfolio Analysis Management Office (PAMO) for the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters tasked the Systems Analysis and Concepts Directorate at NASA Langley to combine efforts with Virginia Tech to develop a global demand model with the capability to predict future demand in the air transportation field. A previous study (Alsalous, 2015) started the development of the Global Demand Mode (GDM) to predict air travel demand based on Gross Domestic Product (GDP) and population trends for 3,974 airports worldwide. The study was done from year 2016 to year 2040. The previous study done by Alsaous, predicts how many seats will be departing out of the 3,974 airports worldwide. This project intends to use the outputs of the GDM and distribute the seats predicted among the airports. The objective is to predict how many seats will be offered that will be departing from airport “A” and arriving at airport “B”. For this, a Fratar model was implemented. The second objective of this project is to estimate what will the aircraft fleet be in the future and how many flights will be needed to satisfy the predicted air travel demand. If the number of seats going from airport A to airport B is known, then, by analyzing real data it can be estimated what type of aircraft will be flying from airport “A” to airport “B” and how many flights each aircraft will have to perform in order to satisfy the forecasted demand. Besides of estimating the type of aircraft that will be used in the future, the modeled created is capable of introducing new aircraft that are not part of the network yet. Fourteen new generation aircraft from Airbus, Boeing, Bombardier, and Embraer and 5 Advanced Technology Aircraft from NASA.

Is GDP per capita one of the main drivers affecting demand for passenger air travelling? Based on the time series analysis conducted for North American and Middle Eastern region, we have not rejected hypothesis about positive impact of GDP per capita on demand for air travelling. The thesis also analyzes whether the effects observed are weaker for more developed and more saturated markets. The second hypothesis was rejected, as we have found that the effect of the GDP per capita was on average 10% stronger for the North American region than for the Middle Eastern region. Moreover, we have found that for both regions oil prices are the important driver of the passenger air travel demand.