Workload-Based Capacity for Air Traffic Management

Air Traffic Management helps to ensure all National Airspace System (NAS) operators have the opportunity to safely accomplish their operational goals while maintaining NAS efficiency. Advancements in technology and a robust global demand for access to space are leading to new space flight participants and increasing numbers of space launch and reentry operations, adding complexity to NAS management coordination and decision-making processes. Diversity of launch and reentry profiles and locations, coupled with increased activity [1, 2], will impact airspace management planning by requiring increased coordination among the Federal Aviation Administration (FAA) and other federal agencies, civilian facilities, and commercial operators. Current processes will not scale as space activity in the NAS increases. The MITRE Corporation is working with the FAA to improve launch and reentry operations efficiency and repeatability. The approach includes analyzing current processes and identifying how more standardized communication mechanisms, integrated information flows, and consistent analysis capabilities can be applied. This paper describes a concept for sharing information and integrating it as part of a standardized, repeatable process that can help the FAA meet future space activity needs in the NAS. A key feature is to integrate information related to NAS effects assessment into the process to facilitate rapid analysis and feedback.

Today’s National Airspace System (NAS) is approaching its limit to efficiently cope with the increasing air traffic demand. Next Generation Air Transportation System (NextGen) with its ambitious goals aims to make the air travel more predictable with fewer delays, less time sitting on the ground and holding in the air to improve the performance of the NAS. However, currently the performance of the NAS is mostly measured using delaybased metrics which do not capture a whole range of important factors that determine the quality and level of utilization of the NAS. The factors affecting the performance of the NAS are themselves not well defined to begin with. To address these issues, motivated by the use of throughput-based metrics in many areas such as ground transportation, wireless communication and manufacturing, this paper identifies the different factors which majorly affect the performance of the NAS as demand (split into flight cancellation and flight rerouting), safe separation (split into conflict and metering) and weather (studied as convective weather) through careful comparison with other applications and performing empirical sensitivity analysis. Additionally, the effects of different factors on the NAS’s performance are quantitatively studied using real traffic data with the Future ATM Concepts Evaluation Tool (FACET) for various sectors and centers of the NAS on different days. In this paper we propose a diagnostic tool which can analyze the factors that have greater responsibility for regions of poor and better performances of the NAS, thus providing vital information which can be used for suitable economic and environmental advantages.

The focus of this paper is on the problem of airline schedule recovery when airspace capacity is limited by convective weather. The problem is represented in a simulation, the Boeing National Flow Model (NFM), and an analysis is conducted to measure the benefits of increased automation and improved weather forecasting. In particular, an analysis is undertaken based upon all scheduled traffic and the actual convective weather experienced on specific good and bad weather days for the U.S. National Airspace System (NAS) in the year 2007. The analysis quantifies the benefits associated with a collaborative flow management concept involving distributed airline schedule recovery. The concept permits airline users to optimize or re-plan their own schedules given an assigned and equitable share of forecast system capacities. The methodology can be used to evaluate alternative convective weather forecasting products, including both polygonal forecasts (such as the CCFP), along with gridded probabilistic forecasts. The methodology can also utilize the actual weather, typically available in snapshots every 5-6 minutes, as a gridded 0/1 “perfect” forecast. The analysis was conducted and is reported on in two major phases. In both phases of the study we allowed the use of strategies for ground delay and flight cancellation but did not allo w for re-routing. The first phase of the analysis was an initial attempt to study the relative value of alternative forecasts and levels of planner automation and utilized multiple forecasting products in their original form. In this phase, we discovered a systematic difference (i.e., bias) in overall coverage between the forecast and actual weather. The forecasts contained much higher levels of weather coverage, leading to re-planning responses that were considerably over-reactive. These findings led to a forecast calibration effort at NOAA that served to adjust both the forecast and actual weather coverage to greatly reduce or eliminate the bias. In the second phase of the study we undertook to compare multiple calibrated forecasting products as well as alternative levels of planner automation.

In this paper, we present a new method for quantifying the impact of forecast convective weather on the National Airspace System (NAS). Data generated by a convective forecast product (broad areas, percentage coverage and confidence level) is converted to a format similar to the actual convective weather data (detailed reports on a NAS-wide fine grid). From this, we build a NAS weather impact index showing how the forecast and actual weather might have impacted the air traffic. The aim of the project is to better understand how the accuracy of the weather impact forecast (not just the weather forecast in itself) affects NAS operational response strategies. The results are compared for several convective seasons and typical cases are discussed.

By the year 2025, the number of aircraft operations in the U.S. will significantly increase [1]. In order to address the safety, capacity, and environmental needs that this situation will generate, the Next Generation Air Transportation System (NextGen) is transforming the National Airspace System (NAS) by including 21st Century technology [1, 2]. NASA's NextGen Systems Analysis, Integration, and Evaluation (SAIE) project, under the Airspace System Program (ASP), assesses the cost and NAS performance benefits of these technologies. One of these new near-term technologies is Dynamic Weather Rerouting (DWR), which is being developed by NASA. DWR has the capability to provide rerouting information for flights to efficiently avoid severe convective weather situations. The objective of the research documented in this paper was to design and implement a sampling process for the selection of representative days that best reflect the yearly patterns of convective weather impact to the NAS, which will be used for testing the DWR technology.

The Federal Aviation Administration (FAA) is accelerating the transformation of aviation operations through an automation evolution strategy refining capabilities and processes in the National Airspace System (NAS), including Traffic Flow Management (TFM). To chart the execution of the NAS's next TFM operational evolution phase leading up to 2030, the FAA established a joint collaborative effort, with representation across multiple lines of business and NAS users. This effort to develop the FAA Air Traffic Organization's (ATO) Corporate Plan for TFM, termed Future Flow Management (FFM), is charged with understanding current and future TFM stakeholder needs and perspectives and prioritizing and integrating among them while innovatively addressing diverse strategic initiatives as they pertain to TFM.The MITRE Corporation's Center for Advanced Aviation System Development (MITRE CAASD) has been capturing and validating with FAA Subject Matter Experts (SMEs) a robust ATO FFM Corporate Plan. This is a set of four documents: Corporate Plan Overview, Vision, Strategy, and Action Plan. To provide a comprehensive mechanism to share, review, and analyze this volume of information in a more effective manner, MITRE CAASD developed a database with the material and various visualizations of this corporate plan. This paper will discuss the development of visualizations and user stories for stakeholder interaction and use.

We present a fully-dynamic multi-commodity Network Flow Model (NetFM) representation of the National Airspace System (NAS). NetFM is a high-level aggregate model incorporating time-varying demand and capacity profiles to define the optimal routing and scheduling of all NAS traffic within a matter of minutes. NetFM routing solutions are not limited to a set of user-inputted route options. Rather, spatial-temporal flight paths are computed through a hexagonal network of nodes and arcs over successive time steps. We present the NetFM formulation. NetFM results include a set of diagnostics which show predicted capacity, traffic flow patterns, and regions where additional capacity would be most beneficial. These diagnostic results may offer improved situational awareness and decision support to Traffic Flow Management (TFM) planners. NetFM capabilities also enable a laboratory in which TFM researchers can study advanced TFM concepts such as integrated airspace flow and ground delay programs.

The current demand in the National Airspace System (NAS) is rapidly approaching the system capacity. This capacity limit causes significant congestion and delay in off-nominal conditions, such as inclement weather. It will also constrain future growth in the aviation sector. Transformation of the current system can relieve this constraint. Examples of such transformation include (i) flight schedule shifting to periods of low demand or alternate airports, (ii) air traffic control (ATC) productivity enhancements, (iii) new procedures and airspace redesigns, and (iv) improvements in weather nowcasting and forecasting. Planners are now investigating such NAS architecture strategies. This paper describes research and plans regarding our investigation of future NAS performance in inclement weather days. Our NAS simulation allows researchers and decision makers to hypothesize strategies in various weather conditions and traffic demand levels to quantify the combined impact on the NAS. The results of the simulation will guide decisions regarding the value of investments in weather forecasting technology and NAS procedures. Our simulation approach is to use (i) archived weather and traffic schedule data with (ii) weather and traffic forecasting models and (iii) tactical weather vectoring and stochastic traffic flow management capabilities.

Integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) is currently a major problem for government and industry. The detection of unauthorized UAS activity is a concern. There is a need for effective low-cost sensor technology to detect and track unauthorized UAS operations. Acoustic sensor systems have potential to improve counter UAS (C-UAS) sensing capabilities at greatly reduced cost relative to traditional sensors such as radar and optical systems, but the commercially available acoustic sensing technology is still lacking. The MITRE Corporation has been a leader in advising the United States’ Federal Government on the issues around integration of UAS into the NAS and C-UAS technologies. Research done by MITRE on acoustic sensing of UAS will be presented. The current state of commercially available acoustic sensor systems will be briefly reviewed. Recommendations that MITRE has developed on how to design acoustic sensor systems for C-UAS will be discussed. Future research directions in topics such as acoustic beamforming, array design, and outdoor sound propagation will be recommended. Approved for Public Release; Distribution Unlimited 18-4035

The capability to properly assess the risks associated with the integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) is critical to ensuring UAS operations are introduced in a safe and responsible manner. Key to this capability is the accurate determination of the likelihood of collision between UAS and other aircraft. Likelihood of such collisions are not well understood and, in many cases, are assessed in a subjective and qualitative manner, resulting in potentially inaccurate assumptions and evaluation of risk and/or allocation of limiting mitigations that decrease the efficiency and effectiveness of UAS operations. Quantification of the likelihood of these collision risk elements will transform the way UAS integration is evaluated and approvedThis paper focuses on a methodology to quantify and analyze the likelihood of unmitigated aircraft collisions within defined airspace volumes. This methodology, developed by The MITRE Corporation (MITRE), will enable a more objective, standardized, and comprehensive assessment of the collision risk posed by the integration of UAS into the NAS with the ability to statistically assess the differences between distributions of risk across multiple airspace volumes. Leveraging this methodology will speed the determination of airspace risk associated with integration and will specifically assist in the identification of mitigations to reduce identified risk to an acceptable level.

Wake turbulence encounters are a significant concern to pilots flying in the National Airspace System (NAS). The MITRE Corporation's Center for Advanced Aviation System Development (CAASD) has worked with the Federal Aviation Administration (FAA) to increase efficiency and capacity in the NAS that will come with the FAA's Next Generation Air Transportation System (NextGen). By increasing efficiency and capacity, there will be a corresponding reduction in required separations that exist in operations today. As operations are optimized and these separations are reduced, it is important that there is not an increase in wake encounter rates that would tend to limit the acceptance of NextGen. NextGen technology, however, may enable the community to provide better tools to pilots and controllers for avoiding wake, thereby bounding the wake encounter rate at no more than today's operationally acceptable level. In this paper, arrival and departure procedures that take advantage of Automatic Dependent Surveillance-Broadcast (ADS-B) and Cockpit Display of Traffic Information (CDTI) technology in the cockpit are reviewed and their performance during a human-in-the-loop evaluation discussed.

A number of Federal Aviation Administration (FAA) automation systems and developmental programs interoperate to support the day-to-day operations of the National Airspace System (NAS). The integration of New Entrants (NEs), such as Remotely Piloted Aircraft (RPA) 1 and Space Vehicle (SV) operations, into the NAS will require modification to the current state of automation. Examining the relevant operational, technical, and procedural implications of integrated NE operations, in addition to exploring the potential impacts of accelerated RPA usage on NAS dynamics, are critically important efforts necessary to understanding operational impacts to NAS systems and users. Our paper presents the potential impacts of RPA integration on two of these systems: En Route Automation Modernization (ERAM) and Traffic Flow Management System (TFMS). A significant component of the impact on NAS systems comes from flight plan and related data processing since all SVs and many RPAs will fly non-standard flight patterns (e.g., RPA loitering and grid search). The processes and details of the non-traditional flight routes, as well different RPA performance specifications, need to be considered as missions are overlaid on the national jet route structure. Of particular concern and interest are the changes in air traffic control (ATC) and air traffic management (ATM) systems and sub-systems needed to address air traffic controller workload and workload complexity concerns associated with NE activities. One potential accommodation approach, presented in this paper, is the use of Dynamic Airspace Configuration both for RPA routine operations and contingency events. Additionally, we present an RPA 1 In this paper, UAS and RPA are used interchangeably without intending any difference per se. It is noted that the U.S. DoD and ICAO use RPA while NASA and the FAA use UAS. demand forecast tool developed under a National Aeronautics and Space Administration (NASA) project. This tool will assist the FAA in meeting its objectives for accommodation of RPA by providing accurate demand forecast information.

The National Airspace System (NAS) is a large and complex system encompassing a wide-range of resources to enable safe and efficient air transportation. To effectively manage the NAS, it is very important to be able to reliably assess current and future demand for communications, navigation, and surveillance (CNS) resources as they are triggered by air traffic control (ATC) events. The authors present an integrated model that is capable of relating NAS ATC events to NAS CNS demand. Model validation with a subset of recorded ETMS CNS statistics will be presented. Combining such a model with NAS future demand predictors such as Terminal Area Forecasts (TAF) and Future Aviation Timetable Estimator (FATE), it becomes possible to estimate the increase in CNS demand and future requirements for CNS capacity, for resource planning purposes. The model presented in this paper includes tracking of radar-related messages and sector workload.

For a system to be managed, it must be measured. The National Airspace System (NAS), the collection of airspace and airport resources in and under the control of the United States (U.S.), is a very complex system which presents great challenges of measurement and management. One key measure of en route airspace efficiency is flying time, i.e., the amount of time it takes for an aircraft to travel through en route airspace on its flight from origin to destination airport. A number of factors influence flying time, the most obvious being the winds. Other important factors are: traffic congestion, air traffic management (ATM) interventions, route structure, industry strategies, and weather. In this paper, we calculate en route flying time in the aggregate and compare a subset of data for the years 2001 and 2002. We account for aircraft equipment type and adjusted flying time for wind effects. In addition, we have selected for analysis a sample of only good weather days (15 in each of the 2 years). The results show that 2002 has slightly shorter flying times than 2001, on the order of 20–25 seconds shorter. Although we did not investigate the causes for the change, we conjecture that the lower levels of traffic after the Fall of 2001 are causing less congestion and less delay. New automation and procedural initiatives may also be contributing to the improvement. Introduction The Federal Aviation Administration (FAA) is charged with the safe, efficient movement of air traffic in U.S. airspace. In recent years, the FAA has begun initiatives to measure efficiency of airspace usage. The measurements are useful for determining the impact of automation and procedural enhancements. Such measurements are also useful for identifying problem areas in the NAS, which can be targeted for remediation. Changes in efficiency may be examined as a function of time. This study assessed system efficiency using en route flying times, comparing 2001 versus 2002. Although several studies have been performed in the past calculating changes in en route flying distance, the authors are familiar with one time-based analysis in the open literature. Bolczak, et al. used Estimated Time of Arrival (ETA) data to analyze a trend in flying time, and discover some year-to-year changes. Other studies of flight times are in the literature, though they have not compared actual or modeled values across years. An early simulation of Free Flight, Ball, et al. analyzed flying times for flights without the constraints of route structuring. Efficiency may be defined as the level of utilization of a resource, with consideration of the cost or effort undertaken to achieve that level. † Free Flight is an industry/government initiative which provides greater freedom for pilots and airlines to select planned and flown routes and take-off times. Free Flight supports collaboration between airspace managers and airspace users. 1 American Institute of Aeronautics and Astronautics Willemain examined sources of variability in flying times for certain city pairs. The Bureau of Transportation Statistics has collected flight time statistics and hosts a web site which allows the public to access this information. In this study, results are presented in aggregated form, with some detail with respect to city pairs. Differences were found in the flying time metrics: 2002 has slightly lower flying times than 2001. The causes for this difference are not discussed.

This paper discusses the results of modeling and simulation performed by FAA’s Performance Analysis and Strategy office to forecast delays at thirty major US airports six months ahead of time. In order to have reliable delay forecasts, it is important that the simulation model validates well with historic actual data. As part of the validation efforts, we recognize that an aircraft’s movement in the US National Airspace System (NAS) involves its interaction with various resources along the flight path, such as airport runways, arrival and departure fixes, airspace sectors, and terminal gates. When multiple aircraft compete for access to these resources, their movements are impeded due to operational and safety considerations, resulting in flight delays. The objective of this study is to understand how various resources contribute to total flight delays, and how sensitive the delays are to changes in resource capacities. The results to date indicate that reduced airport runway capacities play a significant role in overall delays, but arrival and departure fixes and airspace sector constraints do not. Our use of historical airport AARs and ADRs for runway capacities, which may inherently account for fix constraints, yields delays that agree very well with actual values reported in ASPM. However, care has to be taken to use and interpret these rates when there are runway additions or closures. One area in which all NAS-wide models fail to replicate the behavior of the NAS is gate-out delay. Our simulation includes modeled distributions to capture gate-out delays, but they were found to capture only a fraction of actual gate-out delays. Terminal gate constraints were added to verify if they yielded large gate-in delays that would result in additional gate-out delays. No significant additional gate-out delays were obtained, although we gained better insight into how gate-in delays may occur. We are continuing to research potential NAS interactions that would account for the gap in predicting gate-out delays. Additional simulation model enhancements are planned to account for traffic flow initiatives such as GDP, as well as itinerary adjustments due to flight cancellation and substitutions.