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Master of Science Theses

• Simulation-Based Study to Quantify Data-Communication Benefits in Congested Airport Terminal Area (2008)
  
  Author: Gabriele Enea
  
  T he scope of this study was to evaluate the impact of the air traffic controller-to-pilot communication standard known as CPDLC or Data-Communication on the future air traffic operations. The impact was evaluated from the double viewpoint of airport delays and air traffic controllers’ workload. RAMS simulation software is used to perform all the runs and from its output data the values of terminal area delays and controllers workload are obtained. The New York Metroplex terminal area was used as a case study. Because of its complexity, where three major airports (i.e. JFK, Newark, and La Guardia) interact and constraint each other, this area was particularly interesting to be studied and the data analyzed gave a valuable insight on the possible future impact of Data-Communication in congested terminal areas. The results of the study, based on some previous man-in-the-loop simulations performed by the FAA in the nineties, showed that significant potential benefits could be obtained with the complete implementation of such technologies in the workload experienced by air traffic controllers. Moreover some small but not negligible benefits were obtained in the total delays accrued by each airport studied. On the other hand, the simulations of the future demand predicted by the FAA demonstrated that without a significant increment in capacity or limitation on the traffic growth intolerable delays would be recorded across the NAS in the future. For the complexity of the simulation model calibration and for the very time-consuming run time not all the scenarios described in the methodology were tested, demonstrating the weakness of RAMS as a ground simulation model.
  
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• A Modeling Framework to Estimate Airport Runway Capacity in the National Airspace System (2007)
  
  Author: Yueh-Ting Chen
  

  The objective of this study is to estimate the airport capacity in the National Airspace System (NAS). Previous studies have focused on the airport capacity of large commercial airports. This research study estimates the runway capacity for more than two thousand airports in the NAS in order to understand future tradeoffs between air transportation demand and supply. The study presented in this report includes capacity estimates for general aviation and commercial airports. To estimate airport runway capacity, the Federal Aviation Administration (FAA) Airfield Capacity Model (ACM) is used to assess the capacity at all candidate airports in a target airport set. This set includes all airports with potential Very Light Jet (VLJ) operations. The result of the study provides a broad view about the airport capacity in the future air transportation system, and could help decision makers with a modeling framework to identify congestion patterns in the system. Moreover, airport capacity is an important limiting factor in the growth of air transportation demand. The main motivation in our analyis is to include airport capacity constraints in forecasts of air transportation demand. The framework described in this report has been integrated into the Transportation Systems Analysis Model (TSAM). TSAM is a comprehensive intercity and multimode transportation planning tool to predict future air transportation demand.
  
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• Prediction of International Flight Operations at U.S. Airports (2006)
  
  Author: Ni Shen
  

  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.
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• Modeling of United States Airline Fares Using the Official Airline Guide (OAG) and Airline Origin and Destination Survey (DB1B) (2006)
  
  Author: Krishna Rama-Murthy
  

  Prediction of airline fares within the United States including Alaska & Hawaii is required for transportation mode choice modeling in impact analysis of new modes such as NASA's Small Airplane Transportation System (SATS). Developing an aggregate cost model i.e. a 'generic fare model' of the disaggregated airline fares is required to measure the cost of air travel. In this thesis, the ratio of average fare to distance i.e. fare per mile and average fare is used as a measure of this cost model. The thesis initially determines the Fare Class categories to be used for Coach and Business class for the analysis .The thesis then develops a series of 'generic fare models' using round trip distance traveled as an independent variable. The thesis also develops a set of models to estimate average fare for any origin and destination pair in the US. The factors considered by these models are: the round trip distance traveled between the origin (o) and destination (d), the type of fare class chosen by the traveler (first, business class and unrestricted coach class and restricted coach class), the type of airport (large hub, medium hub, small hub, or non hub), whether or not the route is served by a low cost airline and the airline market concentration between the o-d pair. The models suggest that competition at the destination airport is more critical than the competition at origin airport for coach class fares and vice a versa for business class fares. Models suggested in this thesis predict air fares with R-square values of 0.3 to 0.75.
  
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• Development of a Decision Support Tool for Planning Rail Systems: An Implementation in TSAM (2005)
  
  Author: Chetan Joshi
  

  A Decision Support model for planning Intercity Railways is presented in this research. The main aim of the model is to generate inputs for the logit model existing in the Virginia Tech Transportation Systems Analysis Model (TSAM). The inputs required by the TSAM logit model are travel time, travel cost and schedule delay. Travel times and travel costs for different rail technologies are calculated using a rail network and actual or proposed rail schedules. The concept of relational databases is used in the development of the network topology. Further, an event graph approach is used for analysis of the generated network. Shortest travel times and their corresponding travel costs between origin-destination pairs are found using Floyd’s algorithm. Complete itineraries including transfers (if involved) are intrinsically held in the precedence matrix generated after running the algorithm. A standard mapping technique is used to obtain the actual routes. The algorithms developed, have been implemented in MATLAB. Schedules from the North American Passenger rail system AMTRAK are used to generate the sample network for this study. The model developed allows the user to evaluate what-if scenarios for various route frequencies and rail technologies such as Accelerail, High Speed Rail and Maglev. The user also has the option of modifying route information. Comparison of travel time values for the mentioned technology types in different corridors revealed that frequency of service has a greater impact on the total travel time in shorter distance corridors, whereas technology/line-haul speed has a greater influence on the total travel time in the longer distance corridors. This tool could be useful to make preliminary assessments of future rail systems. The network topology generated by the algorithm can further be used for network flow assignment, especially time-dependent assignment if used with dynamic graph algorithms.
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• Cost-Benefit Analysis Model for Advanced Weather Forecasting Installations in Airport Terminal Areas (2005)
  
  Author: Aniruddha V. Kane
  

  Better utilization of the airport system capacities can significantly decrease delays, as well as number of cancelled lights. An efficient Air Traffic Control system equipped with advanced technology installations in the terminal area can help reduce flight delays and cancellations. The same technology could also help reduce accidents in the terminal area, thereby increasing the safety of the system. Due to the expense of fielding advanced technology in the terminal area, it is important to conduct realistic cost-benefit analysis to predict the life-cycle cost of the system. A computer simulation and optimization model to estimate the costs and benefits of fielding advanced technologies at airport terminal areas is introduced in this paper. The model developed is called the Cost-Benefit Analysis Terminal Investment Model (COTIM). This model considers costs and benefits to both service providers (Federal Aviation Administration and airport authorities) and users (Airlines). The model combines a simulation-optimization based approach to predict benefits and costs accrued in one day or throughout the life-cycle of the facility. We present an example to demonstrate the functionality of the model using Chicago O’Hare International Airport (ORD) equipped with the Integrated Terminal Weather System (ITWS). The Integrated Terminal Weather System (ITWS) is a relatively new technology that forecasts convective weather movements thus allowing Air Traffic Control (ATC) personnel to re-direct flights inside the terminal area efficiently. COTIM estimates flight delays and cancellations at an airport, when the airport is equipped with advanced technologies such as ITWS. The model performs cost-benefit analysis by comparing a baseline scenario without terminal area technologies against a scenario with technology. The difference between the two scenarios help decision makers justify whether technology investments are warranted of not.
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• A Study of Commercial Aviation Demand and Revenue Responses to Changes in Ticket and Segment Tax (2005)
  
  Author: Stephanie Pei-Hua Chung
  

  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.
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• Integration of the Transportation Systems Analysis Model for the Small Aircraft Transportation System (2005)
  
  Author Nicolas Karlsson Hinze
  

  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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• Measuring and Ranking Efficiency of Major Airports in the United States Using Data Envelopment Analysis (2004)
  
  Author: Myunghyun Lee
  

  An airport is an important piece of infrastructure in air transportation system. This project focuses on measuring and ranking the efficiency of airports in the United States using the basic DEA, Ranking DEA, Goal programming and DEA and TOPSIS. In general, airport authorities of relatively inefficient airports are trying to benchmark the operational strategies of efficient airports. This project focuses on evaluating hub airports in the United States. ATL, LAX, and MEM airports are relatively efficient among forty four hub airports in the United States based on the performances and airport facilities of the 2000 year when the results of all applied methods in this project, the basic DEA ranking, the Cross Efficiency ranking, the Andersen-Petersen ranking and TOPSIS ranking method, are compared. The implication of this project is that airport authorities in the United States would benchmark these three airports to maximize operation and management efficiency for their airports. In general, most of the airports are handling passengers and freight. Therefore, ATL and LAX would be the most efficient hub airports in the United States. The capacities of airport facilities and more appropriate input data like financial data should be considered in the follow up research.
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• A Model to Assess the Mobility of the National Airspace System (NAS) (2003)
  
  Author: Anand Seshadri
  

  One of the ways to define mobility in a transportation system is total travel time for all travelers using the transportation network. A good assessment of the mobility is essential for knowing the points of congestion in the network and the factors responsible for the congestion. Also the change in mobility from the baseline to the horizon year would give the modeler an idea of the effectiveness of the various transportation systems. One of the applications of the mobility measurement is the evaluation of aviation technologies proposed by FAA to ease the congestion. This paper addresses a method to estimate the mobility of the air transportation network in the baseline year (2000). Also presented is a method to estimate the mobility to the horizon year by considering congestion on the roadway.
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• A Bi-Level System Dynamics Modeling Framework to Evaluate Costs and Benefits of Implementing Controller Pilot Data Link Communications and Decision Support Tools in a Non-Integrated and Integrated Scenario (2003)
  
  Author: Debayan Sen
  

  A modeling framework to evaluate the costs and benefits of implementation of Controller Pilot Data Link Communication (CPDLC), and Air Traffic Management (ATM) decision support tools is proposed in this paper. The benefit/cost evaluation is carried out for four key alternatives namely alternative A: Do nothing scenario (only voice channel), alternative B: Voice channel supplemented with CPDLC, alternative C: Alternative B with ATM tools in a non-integrated scenario and finally alternative D: Alternative B with ATM tools in an integrated scenario. It is a bi-level model that cap-tures the linkages between various technologies at a lower microscopic level using a daily microscopic model (DATSIM) and transfers the measures of effectives to a higher macroscopic level. DATSIM stands for Data Link and Air Traffic Technologies SIMulation and it simulates air traffic in the enroute sector and terminal airspace for a single day and captures the measures of effectiveness at a microscopic level and feeds its output to the macroscopic annual model which then runs over the entire life cycle of the system. Airspace dwell time benefit data from the microscopic model is regressed into three dimensional benefit surfaces as a function of the equipage level of aircraft and aircraft density and embedded into the macroscopic model. The main function of the annual model is to ascertain economic viability of any deployment schedule or alternative over the entire life cycle of the system. The life cycle cost model is com-posed of four modules namely: Operational benefits module, Safety benefit module,Technology cost module and Training cost module. Analysis using the model showed that an enroute sector gets congested at aircraft den-sities greater 630 per day. This is mainly because the controller workload gets satu-rated at that traffic volume per day. Benefits realized in alternatives B, C and D as compared to alternative A increased exponentially at traffic densities greater than 630 i.e. when controller workload for alternative A becomes saturated.
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• Development of an Airport Choice Model for General Aviation Operations (2002)
  
  Author: Senanu Y. Ashiabor
  

  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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• Development of a Computer Based Airspace Sector Occupancy Model (1998)
  
  Author: Shrinivas M. Sale
  

  This thesis deals with the development of an Airspace Sector Occupancy Model (ASOM). The model determines the occupancy of Air Traffic Control Center (ARTCC) sectors for a given geometry of sectors and flight schedules, and can be used to study the impact of alternative flight schedules on the workload imposed on the sectors. Along with complimentary airspace analysis models, this can serve as an advisory tool to approve flight plans in the Free Flight Scenario, or to reschedule flights around a Special Use Airspace (SUA). ASOM is developed using Matlab 5.2, and can be run on an IBM compatible PC, Macintosh, or Unix Workstation. The computerized model incorporates the powerful features of graphics and hierarchical modeling inherent in Matlab, to design an effective tool for analyzing air traffic scenarios and their respective sector occupancies.
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• Investigation Into Free Flight Impact On Air Traffic Control (1998)
  
  Author: Alexander B. Suchkov
  

  This thesis deals with innovative concept of air traffic operations such as Free Flight. First, a baseline is established to determine how controllers operate under the current operation guidelines. Then flight trajectories are developed for different alternatives to the Free Flight operational concept. Finally, a comparison of these Free Flight alternatives with current operational concept is conducted to investigate an impact of Free Flight on Air Traffic Control. With the powerful features of optimization, graphics, and hierarchical modeling, the MATLAB toolboxes proved to be effective in the modeling process involved in this research.
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• Neural Network Aided Aviation Fuel Consumption Modeling (1997)
  
  Author: Wing Ho Cheung
  
  This thesis deals with the potential application of neural network technology to aviation fuel consumption estimation. This is achieved by developing neural networks representative jet aircraft. Fuel consumption information obtained directly from the pilot’s flight manual was trained by the neural network. The trained network was able to accurately and efficiently estimate fuel consumption of an aircraft for a given mission. Statistical analysis was conducted to test the reliability of this model for all segments of flight. Since the neural network model does not require any wind tunnel testing nor extensive aircraft analysis, compared to existing models used in aviation simulation programs, this model shows good potential. The design of the model is described in depth, and the MATLAB source code are included in appendices.
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• AQM Shell Development - Creating a Framework for Airspace and Airfield Operations and Air Quality Visualization Software (1997)
  
  Author: Todd Alan Peterson
  

  It is believed that the analysis of air traffic impacts on air quality will benefit from attention to the three-dimensional nature of the air traffic network as well as the actions of individual aircraft during the study period. With the existence of air traffic simulation models, the actions of individual aircraft may already be defined in a simulated environment. SIMMOD, the Federal Aviation Administration's airport and airspace modeling software, performs such models of scheduled air traffic. The results of such models may be used to determine the impacts of scheduled air traffic on air quality as well as other parameters. This report addresses the interpretation of output from SIMMOD models for use in air quality analysis and visualization of the air traffic network, and the application of these techniques in a stand-alone computer program. This program, named AQM for its purpose in assisting development of Air Quality Models, provides a working framework for future development of software for detailed air quality analysis and visualization.
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• Modeling Aircraft Fuel Consumption with a Neural Network (1997)
  
  Author: Glenn D. D. Schilling
  

  This research involves the development of an aircraft fuel consumption model to simplify Bela Collins of the MITRE Corporation aircraft fuelburn model in terms of level of computation and level of capability. MATLAB and its accompanying Neural Network Toolbox, has been applied to data from the base model to predict fuel consumption. The approach to the base model and neural network is detailed in this paper. It derives from the basic concepts of energy balance. Multivariate curve fitting techniques used in conjunction with aircraft performance data derive the aircraft specific constants. Aircraft performance limits are represented by empirical relationships that also utilize aircraft specific constants. It is based on generally known assumptions and approximations for commercial jet operations. It will simulate fuel consumption by adaptation of a specific aircraft using constants that represent the relationship of lift-to-drag and thrust-to-fuel flow. The neural network model invokes the output from MITRE1s algorithm and provides: (1) a comparison to the polynomial fuelburn function in the fuelburn post- processor of the FAA Airport and Airspace Simulation Model (SIMMOD), (2) an established sensitivity of system performance for a range of variables that effect fuel consumption, (3) a comparison of post fuel burn (fuel consumption algorithms) techniques to new techniques, and (4) the development of a trained demo neural network. With the powerful features of optimization, graphics, and hierarchical modeling, the MATLAB toolboxes proved to be effective in this modeling process.
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• Routing Algorithms for Dynamic, Intelligent Transportation Networks (1997)
  
  Author: Shivaram Subramanian
  

  Traffic congestion has been cited as the most conspicuous problem in traffic management. It has far-reaching economic,social and political effects. Intelligent Transportation Systems (ITS) research and development programs have been assigned the task of developing sophisticated techniques and counter-measures to reduce traffic congestion to manageable levels, and also achieve these objectives using area-wide traffic management methods. During times of traffic congestion, the traffic network in a transient, time-dynamic state, and resembles a dynamic network. In addition, in the context of ITS, the network can accurately detect such transient behavior using traffic sensors, and several other information gathering devices. In conjunction with Operations Research techniques, the time-varying traffic flows can be routed through the network in an optimal manner, based on the feedback from these information sources. Dynamic Traffic Assignment (DTA) methods have been proposed to perform this task. An important step in DTA is the calculation of user-optimal, system-optimal, and multiple optimal routes for assigning traffic. One would also require the calculation of user-optimal paths for vehicle scheduling and dispatching problems.

  The main objective of this research study is to analyze the effectiveness of time-dependent shortest path (TDSP) algorithms and k-shortest path (k-SP) algorithms as a practical routing tool in such intelligent transportation networks. Similar algorithms have been used to solve routing problems in computer networks. The similarities and differences between computer and ITS road networks are studied. An exhaustive review of TDSP and k-SP algorithms was conducted to classify and determine the best algorithms and implementation procedures available in the literature. A new (heuristic) algorithm (TD-kSP) that calculates multiple optimal paths for dynamic networks is proposed and developed. A complete object-oriented computer program in C++ was written using specialized network representations, node-renumbering schemes and efficient path processing data structures (classes) to implement this algorithm. A software environment where such optimization algorithms can be applied in practice was then developed using object-oriented design methodology. Extensive statistical and regression analysis tests for various random network sizes, densities and other parameters were conducted to determine the computational efficiency of the algorithm. Finally, the algorithm was incorporated within the GIS-based Wide-Area Incident Management Software System (WAIMSS) developed at the Center for Transportation Research, Virginia Tech. The results of these tests are used to obtain the empirical time-complexity of the algorithm. Results indicate that the performance of this algorithm is comparable to the best TDSP algorithms available in the literature, and strongly encourages its possible application in real-time applications.

  Complete testing of the algorithm requires the use of real-time link flow data. While the use of randomly generated data and delay functions in this study may not significantly affect its computational performance, other measures of effectiveness as a routing tool remains untested. This can be verified only if the algorithm itself becomes a part of the user-behavior feedback loop. A closed loop traffic simulation/ system-dynamics study would be required to perform this task. On the other hand, an open-loop simulation would suffice for vehicle scheduling/dispatching problems.
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• A Computer Simulation Model to Assess Attack Aircraft Survivability and Lethality Tradeoffs (1986)
  
  Author: Antonio Trani