Browsing by Subject "Air traffic control"

Now showing 1 - 3 of 3
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    Development of an Ability-Based Selection Instrument for the MARC-Air Traffic Controller Training Program: Final Report
    (1993-02) Ackerman, Phillip L.; Kanfer, Ruth
    This report reviews the completed task and deliverable components of the contract between the Minnesota Air Traffic Control Training Center (MATCTC) and the University of Minnesota, and describes the findings of our research concerning the implementation of a selection instrument for air traffic control (ATC) trainees. The report reviews the basic research plan, describes the results of test development and validation activities (using the University of Minnesota laboratory sample and the FAA student sample), and describes in detail the results of test development and validation for the MATCTC student samples. References are provided for previously submitted reports that detail subcomponents of the research program.
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    An intelligent optimization system for terminal traffic management
    (2013-12) Lee, Hoilun Helen
    This dissertation presents the development of a terminal traffic flow management system using an intelligent optimization method. The system is in an effort to provide advisories to efficiently assign runways to cope with the unbalanced traffic flow from and/or toward different directions and computes the optimal arrival or departure time for each flight. This is a high fidelity advisory system to assist traffic managers at airports to manage the complex terminal traffic in a more efficient fashion in order to ultimately minimize the overall flight delay in the entire airport and maintain a high level of safety at the same time. Multiple objectives pertaining to overall airport throughput, system delay, maximum individual delay, and runway balance are used. The system described in this study utilizes knowledge base intelligent optimization methods and takes advantage of the self-contained mixed integer linear program. The mixed integer linear program calculates the optimal schedule for each aircraft for each runway while the intelligent optimization method is used to produce optimal runway assignment for all flights in the entire airport. The importance of improving airport efficiency is introduced in detail in this dissertation. The system explicitly considers eliminating mid-air crossings within the terminal airspace due to irrational runway assignments. This not only improves safety but also effectively reduces controller workload. The importance and contribution of the study is addressed. This system is suitable for an airport with multiple runways. Simulations were conducted based on the real traffic mix for four of the 30 busiest airports in the United States and the results of the simulation prove the feasibility of the system. Future development of the system is also discussed.
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    A systematic study of terminal area traffic management.
    (2012-08) Chen, Heming
    This dissertation conducts a systematic study of terminal area traffic management using optimization methods. The critical role that the airport plays in national airspace system is introduced. The challenges in managing complex terminal traffic are explained. The necessity and importance of the study is addressed. To assist human air traffic controllers in managing complex terminal traffic, our solution strategy is to calculate each flight's optimal arrival/departure schedule, to minimize the overall flight delay and runway congestion in the entire airport. Three solutions are developed in the thesis, including the static solution, the dynamic solution, and the stochastic solution. The static solution uses one computation and attempts to optimize the schedules of many flights arriving/departing the airport within a wide time window. The accuracy of its solution heavily relies on the quality of the predicted traffic situation acquired right before the computation. On the contrary, the dynamic solution attempts to divide the entire traffic flow into a series of small pieces, and optimize flight schedules piece by piece. It collects the latest traffic information before each computation and experiences far less computational load. Both static and dynamic solutions assume the traffic information to be explicitly known. They are inherently deterministic solutions. The third solution proposed in this thesis is a stochastic solution. It assumes that traffic information is not known with certain due to a variety of random factors in actual flight operations. This stochastic solution is mathematically and structurally designed to handle multiple sources of uncertainties in managing terminal traffic. In the last, the conclusion is given based upon the simulation tests of the three proposed runway scheduling solutions. Future work is also suggested.