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Clustering Days with Similar Airport Weather Conditions

On any given day, traffic flow managers must often rely on past experience and intuition when developing traffic flow management initiatives that mitigate imbalances between the aircraft demand and the weather impacted airport capacity. The goal of this study was to build on recent efforts to apply data mining classification and clustering algorithms to vast archives of historical weather and air traffic data to identify patterns and past decisions that can ultimately inform day-of-operations decision-making. More specifically, this study identified similar weather impacted days at select U.S. airports, and analyzed the traffic management initiatives implemented on these representative days. The identification of the similar days was accomplished by applying a decision tree algorithm to the hourly Localized Aviation Model Output Statistics Program observations and the arrival delays for Newark Liberty International Airport. The branches from the trained decision tree were subsequently pruned to identify four weather conditions that resulted in medium to high delays for the arrivals scheduled to Newark in 2012. Using these weather conditions, four, daily airport-level Weather Impacted Traffic Index values were calculated using the Localized Aviation Model Output Statistics Program observations and the 2012 scheduled arrival counts from the FAAs Aviation System Performance Metric system. The four, daily Weather Impacted Traffic Index values for 2012 were subsequently clustered using an Expectation Maximization clustering algorithm, and nine unique types of weather days at Newark were identified. By far the most prominent type of day at Newark was a day associated with relatively good weather conditions, where there was little convective activity, winds were low, ceilings and visibility were high and there was little precipitation. Moderate levels of convective activity characterized the next most prominent type of day. Days with persistently high winds or low ceiling and visibility levels were relatively rare in 2012. Lastly, the frequency at which Ground Delay Programs, Ground Stops and Miles-in-Trail restrictions were implemented on each of the typical types of days at Newark were analyzed. Based on the results, it does appear as if the usage of Miles-in-Trail, Ground Delay Program and Ground Stop restrictions correlates well with the severity of the weather associated with each unique type of weather impacted day at Newark. Furthermore, the results demonstrate that it is feasible to use historical weather and air traffic archives to provide guidance on the types of traffic management restrictions to implement in response to the weather conditions impacting an airport.

weather↗

The employment of a spoken language computer applied to an air traffic control task.

Assessment of the merits of a limited spoken language (56 words) computer in a simulated air traffic control (ATC) task. An airport zone approximately 60 miles in diameter with a traffic flow simulation ranging from single-engine to commercial jet aircraft provided the workload for the controllers. This research determined that, under the circumstances of the experiments carried out, the use of a spoken-language computer would not improve the controller performance.

Laveson, J. I.↗

NASA Ames ATM Research

The NASA Ames research Center, in cooperation with the FAA and the industry, has a series of major research efforts underway that are aimed at : 1) improving the flow of traffic in the national airspace system; and 2) helping to define the future air traffic management system. The purpose of this presentation will be to provide a brief summary of some of these activities.

Denery, Dallas G.↗

Demonstrating Early-Adopter Benefits of Submitting Multiple Trajectory Options for Airlines

A workshop at NASA Ames Research Center was held with airline industry stakeholders to demonstrate the impact of using Trajectory Options Sets (TOSs) during a Collaborative Trajectory Options Program (CTOP) for severe weather operations. The demonstration was conducted using apart-task Human-in-the-Loop (HITL) simulation of the Integrated Demand Management (IDM) concept, which is an air traffic management method that uses CTOP to deliver preconditioned traffic to the Time-Based Flow Management (TBFM) region. The demonstration addressed the following research objectives: first, determine who receives a greater benefit, TOS-participating or TOS-excluded airlines? Second, determine which method of trajectory selection yields a better solution, human/manual selection or automation? Finally, obtain feedback from stakeholders on their impression of the concept and recommendations for future work. The results showed that TOS-participating airlines received greater benefit in terms of total ground delay, ground delay savings, number of reroute options, and additional flight time, compared to TOS-excluded airlines. However, this result was dependent on the situational context, such as the number and location of flights. We found that all airlines benefitted when just a subset of airlines submitted TOS, but the greatest benefit went to the TOS-participating airlines. These benefits to the TOS-participating airlines were diminished as the number of TOS-participants in the system increased. Therefore, there was an “early-adopter” effect that suggested airlines could benefit by becoming the first to equip TOS without causing unfair disadvantages to those who do not equip TOS. In addition, we found that manual selection of trajectory options performed similarly to CTOP, but the CTOP solution was more efficient in terms of number of reroutes, additional flight time, and average ground delay for rerouted flights. Feedback from the stakeholders was solicited, and their overall impressions of the demonstrations were positive. They remarked that CTOP could do a better job than current day solutions, and they thought airlines could benefit from continuing to develop TOS capabilities.

Integrated Demand Management↗

Design and Operational Evaluation of the Traffic Management Advisor at the Ft. Worth Air Route Traffic Control Center

NASA and the FAA have designed and developed and an automation tool known as the Traffic Management Advisor (TMA). The system was operationally evaluated at the Ft. Worth Air Route Traffic Control Center (ARTCC). The TMA is a time-based strategic planning tool that provides Traffic Management Coordinators and En Route Air Traffic Controllers the ability to efficiently optimize the capacity of a demand impacted airport. The TMA consists of trajectory prediction, constraint-based runway scheduling, traffic flow visualization and controllers advisories. The TMA was used and operationally evaluated for forty-one rush traffic periods during a one month period in the Summer of 1996. The evaluations included all shifts of air traffic operations as well as periods of inclement weather. Performance data was collected for engineering and human factor analysis and compared with similar operations without the TMA. The engineering data indicates that the operations with the TMA show a one to two minute per aircraft delay reduction during rush periods. The human factor data indicate a perceived reduction in en route controller workload as well as an increase in job satisfaction. Upon completion of the evaluation, the TMA has become part of the normal operations at the Ft. Worth ARTCC.

Swenson, Harry N.↗

Future of Fuel Savings

Using automation to free up controllers for more strategic management of air traffic is one approach being studied by NASA as it seeks to boost airspace system capacity and efficiency, thereby saving fuel. Heinz Erzberger, a NASA Ames Research Center senior scientist, says the Advanced Airspace Concept (AAC) has been studied for several years. It could increase efficiency 15% by providing optimal routes that cut airlines direct operating costs. A 25% increase in landings on existing runways could follow an important benefit. AAC is one of the efforts to be reviewed by the Joint Planning and Development Organization, an FAA-led initiative by six federal agencies to redesign the U.S. air transportation system by 2025. The main goal is to triple air traffic capacity within 20 years to avert the sort of gridlock that would make fuel consumption only one of many travel nightmares. The automated system approach would allow aircraft to fly optimal trajectories. A trajectory would be defined in the standard three dimensions and eventually include the fourth, time. The management of air traffic by the data-linked exchange of trajectories would start at high altitude and eventually move down to lower altitudes. The automated concept is an outgrowth of the type of tools developed by NASA for use by FAA controllers in managing traffic flows over the years, including ones that optimize routings for the best fuel burn. But AAC would push automation further to reduce workload so controllers can focus on "solving strategic control problems, managing traffic flow during changing weather and ... other unusal events." One key component, the automated trajectory server (ATS), is a ground systems that would rely on software to manage flight path requests from aircrews and controllers. But, Erzberger acknowledges, "The FAA's current plan for upgrades to air traffic services does not include [allowing] the future ground system to issue separation-critical clearances of trajectory changes autonomously to aircraft via data link without explicit approval of a controller," as the AAC proposes. The AAC enables pilots or controllers to data link requests for a trajectory change to the ATS for approval after they are deconflicted with the paths of other aircraft. To divert around storms, for example, pilots could data link their trajectory preference to the ATS. Since several aircraft might request similar routes, the computer would then have to suggest alternatives. This could be accomplished without pilot-controller radio calls, a big bottleneck now. The ATS would have a built-in conflict monitor to call for a resolution (turn, climb or descend), when loss of separation is likely in 1-20 min. The AAC system would reduce controller errors by 90%, according to NASA Ames estimates. The AAC would have a back-up program to assure separation-Tactical Separation Assurance (TSAFE). It s designed to detect short-term traffic conflicts within 3-4 min. of loss of separation. The last line of defense would still be provided by traffic alert & collision avoidance systems (TCAS).

Hughes, David↗

The Mission Oriented Terminal Area Simulation (MOTAS)

A new simulation facility is described in which flight management and flight operations research studies can be conducted in a highly realistic terminal area environment. The historical evolution and justification of the facility is discussed, along with the design configuration of the system hardware and software. Details are provided on the traffic management features of the terminal area model as well as the human controller and multicockpit interface capabilities. The facility is currently operational with two cockpit simulators, two air traffic control (ATC) stations, four pseudo pilot stations (PPS), a metering and spacing system of traffic flow control management, and terminal area models providing two route structure environments: area navigation (RNAV) for advanced-equipped aircraft and vectoring for conventionally-equipped aircraft. Plans for future experiments utilizing the facility are discussed.

Naftel, P. B.↗

Convective Weather Avoidance with Uncertain Weather Forecasts

Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

Karahan, Sinan↗

CATS-based Air Traffic Controller Agents

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.

Callantine, Todd J.↗

An Evaluation and Redesign of the Conflict Prediction and Trial Planning Planview Graphical User Interface

The Planview Graphical User Interface (PGUI) is the primary display of air traffic for the Conflict Prediction and Trial Planning, function of the Center TRACON Automation System. The PGUI displays air traffic information that assists the user in making decisions related to conflict detection, conflict resolution, and traffic flow management. The intent of this document is to outline the human factors issues related to the design of the conflict prediction and trial planning portions of the PGUI, document all human factors related design changes made to the PGUI from December 1996 to September 1997, and outline future plans for the ongoing PGUI design.

Laudeman, Irene V.↗

Airspace Automation Flight Tabletop Exercise

Interconnections of new systems are needed for airspace automation capabilities required in Urban Air Mobility (UAM). FAA Concept of Operations (CONOPS) V1.0 shows Provider of Services for UAM (PSU) at the center of the notional architecture; however, the functional role of the PSU in data exchange and the path to get there is unclear. In partnership with Wisk Aero, Avision, ANRA, Collins Aerospace, OneSky, SkyGrid, and AURA, the NASA National Campaign held discussions and tabletop exercises to test the functional allocations and work flows between an aircraft operator, airspace providers, Command and Control Communication Service Providers (C2CSP), and FAA air traffic in a real-world scenario. The exercise included preplanning and execution of a passenger mission with nominal, contingency, and conflict management scenarios for initial UAM operations. This working paper describes initial conditions for the flight tabletop exercise, exercise summaries, lessons learned, and recommendations for future work.

National Campaign↗

How do Air Traffic Controllers Use Automation and Tools Differently During High Demand Situations?

In a human-in-the-loop simulation, two air traffic controllers managed identical airspace while burdened with higher than average workload, and while using advanced tools and automation designed to assist with scheduling aircraft on multiple arrival flows to a single meter fix. This paper compares the strategies employed by each controller, and investigates how the controllers' strategies change while managing their airspace under more normal workload conditions and a higher workload condition. Each controller engaged in different methods of maneuvering aircraft to arrive on schedule, and adapted their strategies to cope with the increased workload in different ways. Based on the conclusions three suggestions are made: that quickly providing air traffic controllers with recommendations and information to assist with maneuvering and scheduling aircraft when burdened with increased workload will improve the air traffic controller's effectiveness, that the tools should adapt to the strategy currently employed by a controller, and that training should emphasize which traffic management strategies are most effective given specific airspace demands.

ATC↗

Laminar flow control leading edge systems in simulated airline service

The feasibility of two candidate leading-edge flow laminarization systems applicable to airline service was tested using representative airline operational conditions with respect to air traffic, weather, and airport insect infestation. One of the systems involved a perforated Ti alloy suction surface with about 1 million 0.0025-in. diameter holes drilled by electron beam, as well as a Krueger-type flap that offered protective shielding against insect impingement; the other supplied surface suction through a slotted Ti alloy skin with 27 spanwise slots on the upper and lower surface.

Wagner, R. D.↗

Airborne Conflict Management within Confined Airspace in a Piloted Simulation of DAG-TM Autonomous Aircraft Operations

A human-in-the-loop experiment was performed at the NASA Langley Research Center to study the feasibility of Distributed Air/Ground Traffic Management (DAG-TM) autonomous aircraft operations in highly constrained airspace. The airspace was constrained by a pair of special use airspace (SUA) regions on either side of the pilot s planned route. The available airspace was further varied by changing the separation standard for lateral separation between 3 nm and 5 nm. The pilot had to maneuver through the corridor between the SUA s, avoid other traffic and meet flow management constraints. Traffic flow management (TFM) constraints were imposed as a required time of arrival and crossing altitude at an en route fix. This is a follow-up study to work presented at the 4th USA/Europe Air Traffic Management R&D Seminar in December 2001. Nearly all of the pilots were able to meet their TFM constraints while maintaining adequate separation from other traffic. In only 3 out of 59 runs were the pilots unable to meet their required time of arrival. Two loss of separation cases are studied and it is found that the pilots need conflict prevention information presented in a clearer manner. No degradation of performance or safety was seen between the wide and narrow corridors. Although this was not a thorough study of the consequences of reducing the en route lateral separation, nothing was found that would refute the feasibility of reducing the separation requirement from 5 nm to 3 nm. The creation of additional, second-generation conflicts is also investigated. Two resolution methods were offered to the pilots: strategic and tactical. The strategic method is a closed-loop alteration to the Flight Management System (FMS) active route that considers other traffic as well as TFM constraints. The tactical resolutions are short-term resolutions that leave avoiding other traffic conflicts and meeting the TFM constraints to the pilot. Those that made use of the strategic tools avoided additional conflicts, whereas, those making tactical maneuvers often caused additional conflicts. Many of these second-generation conflicts could be avoided by improved conflict prevention tools that clearly present to the pilot which maneuver choices will result in a conflict-free path. These results, together with previously reported studies, continue to support the feasibility of autonomous aircraft operations.

Barmore, Bryan↗

Future Air Traffic Growth and Schedule Model User's Guide

The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

Kimmel, William M.↗

Future Air Traffic Growth and Schedule Model, Supplement

The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

Kimmel, William M.↗

Airspace Technology Demonstration 2 (ATD-2) Phase 1 Concept of Use (ConUse)

This document presents an operational Concept of Use (ConUse) for the Phase 1 Baseline Integrated Arrival, Departure, and Surface (IADS) prototype system of NASA's Airspace Technology Demonstration 2 (ATD-2) sub-project, which began demonstration in 2017 at Charlotte Douglas International Airport (CLT). NASA is developing the IADS system under the ATD-2 sub-project in coordination with the Federal Aviation Administration (FAA) and aviation industry partners. The primary goal of ATD-2 sub-project is to improve the predictability and the operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 effort is a five-year research activity through 2020. The initial phase of the ATD-2 sub-project, which is the focus of this document, will demonstrate the Phase 1 Baseline IADS capability at CLT in 2017. The Phase 1 Baseline IADS capabilities of the ATD-2 sub-project consists of: (a) Strategic and tactical surface scheduling to improve efficiency and predictability of airport surface operations, (b) Tactical departure scheduling to enhance merging of departures into overhead traffic streams via accurate predictions of takeoff times and automated coordination between the Airport Traffic Control Tower (ATCT, or Tower) and the Air Route Traffic Control Center (ARTCC, or Center), (c) Improvements in departure surface demand predictions in Time Based Flow Management (TBFM), (d) A prototype Electronic Flight Data (EFD) system provided by the FAA via the Terminal Flight Data Manager (TFDM) early implementation effort, and (e) Improved situational awareness and demand predictions through integration with the Traffic Flow Management System (TFMS), TBFM, and TFDM (3Ts) for electronic data integration and exchange, and an on-screen dashboard displaying pertinent analytics in real-time. The surface scheduling and metering element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 Upon successful demonstration of the Phase 1 Baseline IADS capability, follow-on demonstrations of the matured IADS traffic management capabilities will be conducted in the 2018-2020 timeframe. At the end of each phase of the demonstrations, NASA will transfer the ATD-2 sub-project technology to the FAA and industry partners.

integrated arrival↗

NY TBO Research: Integrated Demand Management (IDM): IDM Concept, Tools, and Training Package

A series of human-in-the-loop simulation sessions were conducted in the Airspace Operations Laboratory (AOL) to evaluate a new traffic management concept called Integrated Demand Management (IDM). The simulation explored how to address chronic equity, throughput and delay issues associated with New Yorks high-volume airports by operationally integrating three current and NextGen capabilities the Collaborative Trajectory Options Program (CTOP), Time-Based Flow Management (TBFM) and Required Time of Arrival (RTA) in order to better manage traffic demand within the National Air Traffic System. A package of presentation slides was developed to describe the concept, tools, and training materials used in the simulation sessions. The package will be used to outbrief our stakeholders by both presenting orally and disseminating of the materials via email.

trajectory-based operations↗