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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Interaction of Airspace Partitions and Traffic Flow Management Delay

To ensure that air traffic demand does not exceed airport and airspace capacities, traffic management restrictions, such as delaying aircraft on the ground, assigning them different routes and metering them in the airspace, are implemented. To reduce the delays resulting from these restrictions, revising the partitioning of airspace has been proposed to distribute capacity to yield a more efficient airspace configuration. The capacity of an airspace partition, commonly referred to as a sector, is limited by the number of flights that an air traffic controller can safely manage within the sector. Where viable, re-partitioning of the airspace distributes the flights over more efficient sectors and reduces individual sector demand. This increases the overall airspace efficiency, but requires additional resources in some sectors in terms of controllers and equipment, which is undesirable. This study examines the tradeoff of the number of sectors designed for a specified amount of traffic in a clear-weather day and the delays needed for accommodating the traffic demand. Results show that most of the delays are caused by airport arrival and departure capacity constraints. Some delays caused by airspace capacity constraints can be eliminated by re-partitioning the airspace. Analyses show that about 360 high-altitude sectors, which are approximately today s operational number of sectors of 373, are adequate for delays to be driven solely by airport capacity constraints for the current daily air traffic demand. For a marginal increase of 15 seconds of average delay, the number of sectors can be reduced to 283. In addition, simulations of traffic growths of 15% and 20% with forecasted airport capacities in the years 2018 and 2025 show that delays will continue to be governed by airport capacities. In clear-weather days, for small increases in traffic demand, increasing sector capacities will have almost no effect on delays.

Palopo, Kee↗
NASA NTRS2016

Analysis of Multi-Flight Common Routes for Traffic Flow Management

This paper presents an approach for creating common weather avoidance reroutes for multiple flights and the associated benefits analysis, which is an extension of the single flight advisories generated using the Dynamic Weather Routes (DWR) concept. These multiple flight advisories are implemented in the National Airspace System (NAS) Constraint Evaluation and Notification Tool (NASCENT), a nation-wide simulation environment to generate time- and fuel-saving alternate routes for flights during severe weather events. These single flight advisories are clustered together in the same Center by considering parameters such as a common return capture fix. The clustering helps propose routes called, Multi-Flight Common Routes (MFCR), that avoid weather and other airspace constraints, and save time and fuel. It is expected that these routes would also provide lower workload for traffic managers and controllers since a common route is found for several flights, and presumably the route clearances would be easier and faster. This study was based on 30-days in 2014 and 2015 each, which had most delays attributed to convective weather. The results indicate that many opportunities exist where individual flight routes can be clustered to fly along a common route to save a significant amount of time and fuel, and potentially reducing the amount of coordination needed.

weather uncertainty↗
NASA NTRS2011

Benefits Assessment of the Interaction Between Traffic Flow Management Delay and Airspace Partitions in the Presence of Weather

The concept of re-partitioning the airspace into a new set of sectors for allocating capacity rather than delaying flights to comply with the capacity constraints of a static set of sectors is being explored. The reduction in delay, a benefit, achieved by this concept needs to be greater than the cost of controllers and equipment needed for the additional sectors. Therefore, tradeoff studies are needed for benefits assessment of this concept.

Palopo, Kee↗
NASA NTRS2012

Traffic Flow Management: Data Mining Update

This presentation provides an update on recent data mining efforts that have been designed to (1) identify like/similar days in the national airspace system, (2) cluster/aggregate national-level rerouting data and (3) apply machine learning techniques to predict when Ground Delay Programs are required at a weather-impacted airport

Grabbe, Shon R.↗
NASA NTRS2006

Characterization of Days Based On Analysis of National Airspace System Performance Metrics

Days of operations in the National Airspace System can be described in term of traffic demand, runway conditions, equipment outages, and surface and enroute weather conditions. These causes manifest themselves in terms of departure delays, arrival delays, enroute delays and traffic flow management delays, Traffic flow management initiatives such as, ground stops, ground delay programs, miles-in-trail restrictions, rerouting and airborne holding are imposed to balance the air traffic demand with respect to the available capacity, In order to maintain operational efficiency of the National Airspace System, the Federal Aviation Administration (FAA) maintains delay sad other statistics in the Air Traffic Operations Network (OPSNET) and the Aviation System Performance Metrics (ASPM) databases. OPSNET data includes reportable delays of fifteen minutes ox more experienced by Instrument Flight Rule (IFR) flights. Numbers of aircraft affected by departure delays, enroute delays, arrival delays and traffic flow delays are recorded in the OPSNET data. ASPM data consist of number of actual departures, number of canceled departures, percentage of on time departures, percentage of on time gate arrivals, taxi-out delays. taxi-in delays, gate delays, arrival delays and block delays. Surface conditions at the major U.S. airports are classified in terms of Instrument Meteorological Condition (IMC) and Visual Meteorological Condition (VMC) as a function of the time of the day in the ASPM data. The main objective of this paper is to use OPSNET and ASPM data to classify the days in the datasets into few distinct groups, where each group is separated from the other groups in terms of a distance metric. The motivations for classifying the days are two-fold, 1) to enable selection of days of traffic with particular operational characteristics for concept evaluation using system-wide simulation systems such as the National Aeronautics and Space Administration's Airspace Concepts Evaluation Tool (ACES) and 2) to enable evaluation of a given day with respect to the characteristics of the classified groups. The first part of the paper is devoted to the analysis of major trends seen in the OPSNET and ASPM data. The second part of the paper is devoted to describing features or measures derived from the OPSNET and ASPM data that are suitable for characterizing days, and the classification algorithm used for grouping the days. Finally, the method for evaluating the characteristics of a given day with respect to the properties of the groups is described.

Chatterji, Gano B.↗
NASA NTRS2018

Impact of Different Trajectory Option Set Participation Levels within an Air Traffic Management Collaborative Trajectory Option Program

This paper presents the methodology and results of a Human-In-The-Loop (HITL) simulation study conducted in the Airspace Operations Laboratory at NASA Ames Research Center. This study is a part of NASA's ongoing research into developing an Integrated Demand Management (IDM) concept, whose aim is to improve traffic flow management (TFM) by coordinating the FAA's strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The purpose of TFM is to regulate air traffic demand so that it is delivered efficiently through constrained airspace resources without exceeding their capacity limits. The IDM concept leverages a new TFMS capability called the Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for managing traffic tactically by generating precise arrival schedules. Unlike other TFM tools, CTOP gives flight operators the option of submitting a set of user-preferred alternative trajectories for each flight. CTOP can then use these trajectory option sets (or TOSs) to find user-preferred alternative routes to reduce demand on an overloaded resource. CTOP's effectiveness in redistributing demand is limited, however, by the availability of flights with alternative routes. The research presented in this paper focuses on evaluating the impact on TFM operations by varying the percentage of flights that submit a multiple-option TOS ('TOS participation levels'). Results show the impact on overall system performance and on the rerouted flights themselves. The simulation used a Newark (EWR) airport arrival scenario, with en route weather affecting traffic inbound from the west. Participants were asked to control each of the three arrival flows (north, west, and south) to meet their individual capacity constraints while simultaneously ensuring efficient utilization of the capacity at the destination airport. A large, permeable convective weather cell located southeast of Chicago severely reduced the capacity of the west flow. The study evaluated the impact of five different TOS participation levels on CTOP's ability to re-allocate traffic from the west and improve TFM performance in terms of delay assignment and traffic delivery rate to the airport. Overall, the results showed that increasing TOS submissions allowed the overall system delays to be reduced and fairly distributed among the three arrival flows, at the same time achieving the airport throughput rate. Moreover, it was found that aircraft who submitted a TOS saw a greater reduction in delay, even when they were assigned longer routes. This was particularly true when fewer aircraft submitted a TOS. The results confirm that the CTOP operations with higher TOS participation levels helped utilize the overall National Airspace System (NAS) resources as well as benefited the users who participated.

Yoo, Hyo-Sang↗
NASA NTRS2017

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗
NASA NTRS2020

Benefit Assessment of the Integrated Demand Management Concept for Multiple New York Metroplex Airports

Benefits of the Integrated Demand Management (IDM) concept were assessed utilizing a newly developed automated simulation capability called ‘Traffic Management Initiative Automated Simulation (TMIAutoSim).’ The IDM concept focuses on improving traffic flow management (TFM) by coordinating the FAA’s strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The IDM concept leverages a new TFMS capability called Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for tactically managing traffic by generating precise arrival schedules. The IDM concept was developed over a multi-year effort, focusing on solving New York metroplex airport arrival problems. TMIAutoSim closely mimics NASA’s high-fidelity simulation capabilities while enabling more data to be collected at higher speed. Using this new capability, the IDM concept was evaluated using realistic traffic across various weather scenarios. Six representative weather days were selected after clustering three months of historical data. For those selected six days, Newark Liberty International Airport (EWR) and LaGuardia Airport (LGA) arrival traffic scenarios were developed. For each selected day, the historical data were analyzed to accurately simulate actual operations and the weather impact of the day. The current day operations and the IDM concept operations were simulated for the same weather scenarios and the results were compared. The selected six days were categorized into two groups: ‘clear weather’ for days without Ground Delay Programs (GDP) and ‘convective weather’ for days with GDP and significant weather around New York metroplex airports. For the clear weather scenarios, IDM operations reduced last minute, unanticipated departure delays for short-haul flights within TBFM control boundaries with minimal to no impact on throughput and total delay. For the convective weather scenarios, IDM significantly reduced delays and increased throughput to the destination airports.

Traffic Management Initiative Automated Simulation↗
NASA NTRS2004

Development and Evaluation of an Airborne Separation Assurance System for Autonomous Aircraft Operations

NASA Langley Research Center is developing an Autonomous Operations Planner (AOP) that functions as an Airborne Separation Assurance System for autonomous flight operations. This development effort supports NASA s Distributed Air-Ground Traffic Management (DAG-TM) operational concept, designed to significantly increase capacity of the national airspace system, while maintaining safety. Autonomous aircraft pilots use the AOP to maintain traffic separation from other autonomous aircraft and managed aircraft flying under today's Instrument Flight Rules, while maintaining traffic flow management constraints assigned by Air Traffic Service Providers. AOP is designed to facilitate eventual implementation through careful modeling of its operational environment, interfaces with other aircraft systems and data links, and conformance with established flight deck conventions and human factors guidelines. AOP uses currently available or anticipated data exchanged over modeled Arinc 429 data buses and an Automatic Dependent Surveillance Broadcast 1090 MHz link. It provides pilots with conflict detection, prevention, and resolution functions and works with the Flight Management System to maintain assigned traffic flow management constraints. The AOP design has been enhanced over the course of several experiments conducted at NASA Langley and is being prepared for an upcoming Joint Air/Ground Simulation with NASA Ames Research Center.

Barhydt, Richard↗
NASA NTRS2019

ATD-3 Dynamic Routes for Arrivals in Weather (DRAW) Operational Concept, V2.0

NASA's Airspace Technology Demonstration-3 (ATD-3) is the applied traffic flow management activity, and third in the series of ATD projects. ATD-3 provides a suite of en route automation tools, both ground and flight-deck based, that focus on improving the efficiency of en route operation from initial cruise to arrival into the Terminal Radar Approach Control (TRACON). Dynamic Routes for Arrivals in Weather (DRAW) is a technology in the ATD-3 suite that is designed to provide Traffic Managers with a capability to efficiently manage arrival traffic flow and help sustain metering operations when weather is impacting arrivals into major airports. DRAW mitigates convective weather impact on arrival metering operations by providing tools to Traffic Managers that enable efficient reroutes free of convective weather conflicts, and integrated with the arrival metering schedule(s).

terminal airspace↗
NASA NTRSDate not supplied

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

Integrated Demand Management (IDM), is a NASA developed Traffic Flow Management (TFM) concept that uses Collaborative Trajectory Options Program (CTOP) to precondition traffic flows into the Time Based Flow Management (TBFM) region, helping traffic planners manage imbalances between demand and capacity in the National Airspace (NAS). A workshop held at NASA was conducted to demonstrate how individual airlines can be impacted by using Trajectory Options Sets (TOS) during IDM operations. A primary concern that was specifically addressed in a part-task Human-in-the-Loop simulation was who received the greater benefit, TOS participating or non-TOS participating airlines? The results showed that TOS participating airlines received greater benefit in terms of ground delay, number of reroute options, and additional flight time, than non-TOS participating airlines. However, this result was dependent on the number and location of flights. Therefore, it was advantageous for airlines to equip TOS. In addition, we found that non-TOS participating airlines also benefitted from other airlines participating in TOS, because the total system-wide ground delay was reduced as more TOS were introduced into the system. The evidence suggests that the benefits were distributed fairly, and there were no unfair disadvantages for airlines who did not equip TOS.

Integrated Demand Management↗
NASA NTRS2011

Flight Departure Delay and Rerouting Under Uncertainty in En Route Convective Weather

Delays caused by uncertainty in weather forecasts can be reduced by improving traffic flow management decisions. This paper presents a methodology for traffic flow management under uncertainty in convective weather forecasts. An algorithm for assigning departure delays and reroutes to aircraft is presented. Departure delay and route assignment are executed at multiple stages, during which, updated weather forecasts and flight schedules are used. At each stage, weather forecasts up to a certain look-ahead time are treated as deterministic and flight scheduling is done to mitigate the impact of weather on four-dimensional flight trajectories. Uncertainty in weather forecasts during departure scheduling results in tactical airborne holding of flights. The amount of airborne holding depends on the accuracy of forecasts as well as the look-ahead time included in the departure scheduling. The weather forecast look-ahead time is varied systematically within the experiments performed in this paper to analyze its effect on flight delays. Based on the results, longer look-ahead times cause higher departure delays and additional flying time due to reroutes. However, the amount of airborne holding necessary to prevent weather incursions reduces when the forecast look-ahead times are higher. For the chosen day of traffic and weather, setting the look-ahead time to 90 minutes yields the lowest total delay cost.

Mukherjee, Avijit↗
NASA NTRS2014

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.

traffic flow management↗
NASA NTRS2014

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↗
NASA NTRS2010

Optimizing Flight Departure Delay and Route Selection Under En Route Convective Weather

This paper presents a linear Integer Programming model for managing air traffic flow in the United States. The decision variables in the model are departure delays and predeparture reroutes of aircraft whose trajectories are predicted to cross weather-impacted regions of the National Airspace System. The model assigns delays to a set of flights while ensuring their trajectories are free of any conflicts with weather. In a deterministic setting, there is no airborne holding due to unexpected weather incursion in a flight s path. The model is applied to solve a large-scale traffic flow management problem with realistic weather data and flight schedules. Experimental results indicate that allowing rerouting can reduce departure delays by nearly 57%, but it is associated with an increase in total airborne time due to longer routes flown by aircraft. The computation times to solve this problem were significantly lower than those reported in the earlier studies.

Mukherjee, Avijit↗
NASA NTRSDate not supplied

Introduction to Air Traffic Management

The presentation introduces students and faculty to air traffic management with focus on air traffic data for data-science. Starting with the common attributes of transportation systems — highway transportation, air transportation and data transportation, the initial set of slides discuss the purpose of data-science in air traffic management, reasons why air traffic management is challenging, and the multidisciplinary nature of air traffic management research. The history of flight from 1903 — Wright Flyer — to 1987 — formation of the National Air Traffic Controllers Association — is briefly discussed. The national airspace system is described in terms of airports in the U. S., air traffic control facilities (flight service stations, terminal, enroute and system command center), airspace geometry (sectors, airways and navaids), governing regulations and directives, airspace classification (Class A through G), special use airspace, visual flight rules and instrument flight rules. The contents of a flight-plan are described. Weather briefing is discussed. The surveillance equipment used for surface, terminal area and enroute are described, and the aircraft states obtained using the surveillance data are listed. Airline operations control functions — schedule development, flight planning, resource scheduling and flight following — are noted. Next, the roles and responsibilities of air traffic controllers and traffic flow managers are discussed. Separation standards and conflict resolution techniques are outlined. Finally, traffic flow management techniques are reviewed with an illustrative example.

Air Traffic Management↗
NASA NTRSDate not supplied

Introduction to Air Traffic Management

The presentation introduces students and faculty to air traffic management with focus on air traffic data for data-science. Starting with the common attributes of transportation systems — highway transportation, air transportation and data transportation, the initial set of slides discuss the purpose of data-science in air traffic management, reasons why air traffic management is challenging, and the multidisciplinary nature of air traffic management research. The history of flight from 1903 — Wright Flyer — to 1987 — formation of the National Air Traffic Controllers Association — is briefly discussed. The national airspace system is described in terms of airports in the U. S., air traffic control facilities (flight service stations, terminal, enroute and system command center), airspace geometry (sectors, airways and navaids), governing regulations and directives, airspace classification (Class A through G), special use airspace, visual flight rules and instrument flight rules. The contents of a flight-plan are described. Weather briefing is discussed. The surveillance equipment used for surface, terminal area and enroute are described, and the aircraft states obtained using the surveillance data are listed. Airline operations control functions — schedule development, flight planning, resource scheduling and flight following — are noted. Next, the roles and responsibilities of air traffic controllers and traffic flow managers are discussed. Separation standards and conflict resolution techniques are outlined. Finally, traffic flow management techniques are reviewed with an illustrative example.

Air Traffic Management↗