DEMAND-RESPONSIVE AIRSPACE SECTORIZATION AND AIR TRAFFIC CONTROLLER STAFFING

This dissertation optimizes the problem of designing sector boundaries and assigning air traffic controllers to sectors while considering demand variation over time. For long-term planning purposes, an optimization problem of clean-sheet sectorization is defined to generate a set of sector boundaries that accommodates traffic variation across the planning horizon while minimizing staffing. The resulting boundaries should best accommodate traffic over space and time and be the most efficient in terms of controller shifts. Two integer program formulations are proposed to address the defined problem, and their equivalency is proven. The performance of both formulations is examined with randomly generated numerical examples. Then, a real-world application confirms that the proposed model can save 10%-16% controller-hours, depending on the degree of demand variation over time, in comparison with the sectorization model with a strategy that does not take demand variation into account. Due to the size of realistic sectorization problems, a heuristic based on mathematical programming is developed for a large-scale neighborhood search and implemented in a parallel computing framework in order to obtain quality solutions within time limits. The impact of neighborhood definition and initial solution on heuristic performance has been examined. Numerical results show that the heuristic and the proposed neighborhood selection schemes can find significant improvements beyond the best solutions that are found exclusively from the Mixed Integer Program solver's global search. For operational purposes, under given sector boundaries, an optimization model is proposed to create an operational plan for dynamically combining or splitting sectors and determining controller staffing. In particular, the relation between traffic condition and the staffing decisions is no longer treated as a deterministic, step-wise function but a probabilistic, nonlinear one. Ordinal regression analysis is applied to estimate a set of sector-specific models for predicting sector staffing decisions. The statistical results are then incorporated into the proposed sector combination model. With realistic traffic and staffing data, the proposed model demonstrates the potential saving in controller staffing achievable by optimizing the combination schemes, depending on how freely sectors can combine and split. To address concerns about workload increases resulting from frequent changes of sector combinations, the proposed model is then expanded to a time-dependent one by including a minimum duration of a sector combination scheme. Numerical examples suggest there is a strong tradeoff between combination stability and controller staffing

Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes

Controller time and delay costs - a trade-off analysis

Air traffic controller shortages remain a significant challenge in European ATM. Comparing different rules, we quantify the cost effectiveness of adding controller hours to Area Control Centre regulations to avert the delay cost impact on airlines. Typically, adding controller hours results in a net benefit. Distributions of delay duration and aircraft weight play an important role in determining the total cost of a regulation. Errors are likely to be incurred when analysing performance based on average delay values, particularly at the disaggregate level

Relations among Enroute Traffic, Controller Staffing and System Performance

Relations are estimated among enroute air traffic, controller staffing and performance of controllers and ATC system. Controller staffing is found to increase at least linearly with air traffic in the US National Airspace System. Findings in literature review, FAA controller staffing models, FAA standards, and results of analyses support this finding. Measures of controller performance, controller workload and models are developed to estimate relations between controller performance and air traffic in sectors and centers of the NAS. It is found that controller performance is not affected by air traffic congestion within sectors and centers. The estimated relations may be biased by factors such as spatial and temporal propagation of delays in the NAS, ATC procedures used to delay flights away from the source of airspace congestion, strategic and tactical planning performed by ATC system and different traffic management processes and programs implemented for traffic flow management in the NAS. There is a need to evaluate the performance of ATC system in managing air traffic and minimizing delays in the entire NAS. It is found that a hyperbolic function is applicable for relating delays and enroute traffic volumes in the NAS. Monthly models estimated using monthly measures of delays and enroute traffic volumes perform better than daily models. Monthly models estimated for same calendar month of successive years show the best statistical fit. It appears that the enroute operational capacity of NAS can differ considerably for different months. Ground delays, taxi out delays, gate departure delays and airport departure delays used to reduce air delays due to enroute congestion are identified using the monthly and month-specific models

The Decline in U.S. Air Traffic Controllers: A Qualitative Exploration of Current African American Air Traffic Controller Perspectives on Diversity Recruitment in Air Traffic Collegiate Training Initiative Schools

The Federal Aviation Administration’s (FAA) Air Traffic Control Specialists (ATCS) workforce has been in steady decline since 2012. The declining number of federal ATCS threatens a $1.5 trillion aviation economy in the United States. The results of fewer controllers are increased delays and cancelled flights (National Air Traffic Controllers Association [NATCA], 2018). Additionally, the controller workforce is predominantly White male (Carey, 2014). Diversity amongst ATCS is another troubling trend for the FAA (McCartin, 2011). According to Outtz and Hanges (2013), an underrepresentation of minorities, including women, exists among the candidates who were hired successfully in the FAA ATCS centralized hiring process. The purpose of this qualitative methods study was to examine the experiences of African American ATCS who studied air traffic control at the collegiate level. Lent and Brown (1996) suggest that an individual’s career pursuit is determined by their self-efficacy (SE) and outcome expectation (OE). This study explored the SE and OE of African American ATCS hired through the FAA’s Air Traffic Collegiate Training Initiative (AT-CTI) program. Several outcomes were the result of eight semi-structured interviews including high SE and OE that drove the personal goals of obtaining a college degree and becoming an FAA ATCS. This study produced several recommendations including practices the FAA could implement using its Aviation & Space Education Outreach Program (AVSED) to target young African Americans interested in STEM fields to pursue a career in air traffic control (ATC)

Federal Aviation Administration: Efforts to Hire, Staff, and Train Air Traffic Controllers Are Generally on Track, but Challenges Remain

Testimony issued by the Government Accountability Office with an abstract that begins "Each day, the Federal Aviation Administration (FAA) controls the take-offs, landings, and flights of over 50,000 aircraft. To accomplish this mission safely and efficiently, FAA must have a sufficient number of adequately trained air traffic controllers working at its air traffic control facilities. Over the next decade, FAA will need to hire and train nearly 17,000 controllers to replace over 15,000 current controllers, most of whom will be retiring. This massive hiring effort will occur as FAA begins to implement the next generation air transportation system (NextGen), which will integrate new technologies and procedures into air traffic operations and fundamentally change the role of air traffic controllers from controlling individual aircraft to managing air traffic flow. Hence, FAA will need to train experienced controllers to use the new technologies at the same time that it hires and trains new controllers to operate both the current and the new technologies. This testimony addresses FAA's progress and challenges in hiring, staffing, and training air traffic controllers in the current air traffic control system and in preparing them for NextGen. It is based on prior GAO work, updated with reviews of FAA documents and interviews with FAA officials, controller union representatives, and other stakeholders.

En-route air traffic optimization under nominal and perturbed conditions, on a 3D data-based network flow model

Air Traffic Management (ATM) aims at ensuring safe and efficient movement of aircraft in the airspace. The National Airspace System is currently undergoing a comprehensive overhaul known as NextGen. With the predicted growth of air transportation, providing traffic flow managers with the tools to support decision making is essential. These tools should aid in accommodating the air traffic throughput increase, while limiting controller workload and ensuring high safety levels. In the National Airspace System (NAS), the goal of en-route Traffic Flow Management (TFM) is to balance air traffic demand against available airspace capacity, in order to ensure a safe and expeditious flow of aircraft, both under nominal and perturbed conditions. The objective of this thesis is to develop a better understanding of how to analyze, model and simulate air traffic in a given airspace, under both nominal and degraded conditions. First, a new framework for en-route Traffic Flow Management and Airspace Health Monitoring is developed. It is based on a data-driven approach for air traffic flow modeling using historical data. This large-scale 3D flow network of the Cleveland center airspace provides valuable insight on airspace complexity. A linear formulation for optimizing en-route Air Traffic is proposed. It takes into account a controller taskload model based on flow geometry, in order to estimate airspace capacity. The simulations run demonstrate the importance of sector constraints and traffic demand patterns in estimating the throughput of an airspace. To analyze airspace degradation, weather blockage maps based on vertically integrated liquid (VIL) are incorporated in the model, representing weather perturbations on the same data set used to compute the flows. Comparing the weather blockages and the network model of the airspace provides means of quantifying airspace degradation. Simulations under perturbed conditions are then run according to different objectives. The results of the simulations are compared with the data from these specific days, to identify the advantages and drawbacks of the present model.MSCommittee Chair: Feron, Eric; Committee Member: Clarke, John-Paul; Committee Member: Gariel, Maxime; Committee Member: Pritchett, Am

A Performance-Based Framework for Guiding Enroute Air Traffic Control Sector Design

Sectors are small regions of airspace through which aircraft fly and air traffic controllers are required to manage while considering notions like safety, efficiency, and effectiveness. Interestingly, we do not know how to design, i.e. make considerations surrounding airspace, air traffic, controller, and technology factors, such that sectors generate specific levels of performance. Rather, sectors have always been designed in an artistic fashion where the focus is on human operator workload, which is fairly subjective. This research leverages the fact that many aspects of performance are objective and so are many aspects of design. A framework is proposed such that the sector design problem is abstracted in a generalizable way where performance is the focus. The framework consists of a series of natural questions which aim to set up a decision variable representative of all aspects of underlying performance we choose to care about. The decision variable is a normalized-weighted-summed-modeled-performance-loss function. A specific instance of the performance-based sector design problem was successfully demonstrated in the context of the framework. Results showed that the derived composite performance score was useful for inferring design heuristics and optimally selecting among competing design configurations. Simulation and modeling was key to this work