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NASA NTRS1974

Advanced Flow Control as a Management Tool in the National Airspace System

Advanced Flow Control is closely related to Air Traffic Control. Air Traffic Control is the business of the Federal Aviation Administration. To formulate an understanding of advanced flow control and its use as a management tool in the National Airspace System, it becomes necessary to speak somewhat of air traffic control, the role of FAA, and their relationship to advanced flow control. Also, this should dispell forever, any notion that advanced flow control is the inspirational master valve scheme to be used on the Alaskan Oil Pipeline.

Wugalter, S.↗

NASA NTRS2005

Analysis of Aircraft Clusters to Measure Sector-Independent Airspace Congestion

The Distributed Air/Ground Traffic Management (DAG-TM) concept of operations* permits appropriately equipped aircraft to conduct Free Maneuvering operations. These independent aircraft have the freedom to optimize their trajectories in real time according to user preferences; however, they also take on the responsibility to separate themselves from other aircraft while conforming to any local Traffic Flow Management (TFM) constraints imposed by the air traffic service provider (ATSP). Examples of local-TFM constraints include temporal constraints such as a required time of arrival (RTA), as well as spatial constraints such as regions of convective weather, special use airspace, and congested airspace. Under current operations, congested airspace typically refers to a sector(s) that cannot accept additional aircraft due to controller workload limitations; hence Dynamic Density (a metric that is indicative of controller workload) can be used to quantify airspace congestion. However, for Free Maneuvering operations under DAG-TM, an additional metric is needed to quantify the airspace congestion problem from the perspective of independent aircraft. Such a metric would enable the ATSP to prevent independent aircraft from entering any local areas of congestion in which the flight deck based systems and procedures may not be able to ensure separation. This new metric, called Gaggle Density, offers the ATSP a mode of control to regulate normal operations and to ensure safety and stability during rare-normal or off-normal situations (e.g., system failures). It may be difficult to certify Free Maneuvering systems for unrestricted operations, but it may be easier to certify systems and procedures for specified levels of Gaggle Density that could be monitored by the ATSP, and maintained through relatively minor flow-rate (RTA type) restrictions. Since flight deck based separation assurance is airspace independent, the challenge is to measure congestion independent of sector boundaries. Figure 1 , reproduced from Ref. 1, depicts an example traffic situation. When the situation is analyzed by sector boundaries (left side of figure), a Dynamic Density metric would identify excessive congestion in the central sector. When the same traffic situation is analyzed independent of sector boundaries (right side of figure), a Gaggle Density metric would identify congestion in two dynamically defined areas covering portions of several sectors. The first step towards measuring airspace-independent congestion is to identify aircraft clusters, i.e., groups of closely spaced aircraft. The objective of this work is to develop techniques to detect and classify clusters of aircraft.

Bilimoria, Karl D.↗

NASA NTRS1999

En route Spacing Tool: Efficient Conflict-free Spacing to Flow-Restricted Airspace

This paper describes the Air Traffic Management (ATM) problem within the U.S. of flow-restricted en route airspace, an assessment of its impact on airspace users, and a set of near-term tools and procedures to resolve the problem. The FAA is committed, over the next few years, to deploy the first generation of modem ATM decision support tool (DST) technology under the Free-Flight Phase-1 (FFp1) program. The associated en route tools include the User Request Evaluation Tool (URET) and the Traffic Management Advisor (TMA). URET is an initial conflict probe (ICP) capability that assists controllers with the detection and resolution of conflicts in en route airspace. TMA orchestrates arrivals transitioning into high-density terminal airspace by providing controllers with scheduled times of arrival (STA) and delay feedback advisories to assist with STA conformance. However, these FFPl capabilities do not mitigate the en route Miles-In-Trail (MIT) restrictions that are dynamically applied to mitigate airspace congestion. National statistics indicate that en route facilities (Centers) apply Miles-In-Trail (MIT) restrictions for approximately 5000 hours per month. Based on results from this study, an estimated 45,000 flights are impacted by these restrictions each month. Current-day practices for implementing these restrictions result in additional controller workload and an economic impact of which the fuel penalty alone may approach several hundred dollars per flight. To mitigate much of the impact of these restrictions on users and controller workload, a DST and procedures are presented. The DST is based on a simple derivative of FFP1 technology that is designed to introduce a set of simple tools for flow-rate (spacing) conformance and integrate them with conflict-probe capabilities. The tool and associated algorithms are described based on a concept prototype implemented within the CTAS baseline in 1995. A traffic scenario is used to illustrate the controller's use of the tool, and potential display options are presented for future controller evaluation.

Green, S.↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

NextGen↗

NASA NTRS1991

Who or what saved the day? A comparison of traditional and glass cockpits

This study examined incidents reported to NASAs Aviation Safety Reporting System from a different perspective: rather than focusing on the factors contributing to or causing incidents, this study concentrated on who and what (subsystems and information) enabled the recovery from an anomaly. Incident reports describing altitude deviations were classified as to cockpit type (glass or traditional), flight phase, agent restoring safety, and cockpit subsystems providing specific information that helped restore safety. The data revealed and quantified the agents, information, and factors that 'saved the day'. The flight crews used many sources of information to detect the altitude deviations: altimeter, outside scene, altitude alert, kinesthesia, attitude and communications monitoring. In the glass cockpits the crews also used the map display and autothrottles to detect deviations from assigned altitudes. There was an interaction between the person detecting the anomaly (controller/flight crew) and the type of cockpit. Glass cockpit flight crews detect proportionally more deviations than their counterparts in traditional cockpits, while controllers tend to detect more deviations involving traditional cockpits. There was no effect of cockpit position (captain/first officer). A model that details the flow of altitude information between air traffic control, flight crews, and cockpit subsystems, was developed and validated. This model identifies strengths and weaknesses in the flow of altitude information within the current ground/air system.

Degani, Asaf↗

NASA NTRS2017

Integrated Demand Management: Minimizing Unanticipated Excessive Departure Delay while Ensuring Fairness from a Traffic Management Initiative

This paper introduces NASA's Integrated Demand Management (IDM) concept and presents the results from an early proof-of-concept evaluation and an exploratory experiment. An initial development of the concept was focused on integrating two systems - i.e. the FAA's newly deployed Traffic Flow Management System (TFMS) tool called the Collaborative Trajectory Options Program (CTOP) and the Time-Based Flow Management (TBFM) system with Extended Metering (XM) capabilities to manage projected heavy traffic demand into a capacity-constrained airport. A human-in-the-loop (HITL) simulation experiment was conducted to demonstrate the feasibility of the initial development of the concept by adapting it to an arrival traffic problem at Newark Liberty International Airport (EWR) during clear weather conditions. In this study, the CTOP was utilized to strategically plan the arrival traffic demand by controlling take-off times of both short- and long-haul flights (long-hauls specify aircraft outside TBFM regions and short-hauls specify aircraft within TBFM regions) in a way that results in equitable delays among the groups. Such strategic planning allows less airborne delay to occur within TBFM by feeding manageable long-haul traffic demand while reserving sufficient slots in the overhead streams for the short-haul departures. The manageable traffic demand indicates the TBFM scheduler assigns no more airborne delay than its assigned airspace is capable of absorbing. TBFM then uses its time-based metering capabilities to deliver the desirable throughput by tactically rescheduling the TBFM entered long-haul flights and short-haul departures. Additional research was also performed to explore use of Required Time of Arrival (RTA) capabilities as a potential control mechanism for the airborne flights to improve arrival traffic delivery accuracy of scheduled long-haul traffic demand. The study results show that both short- and long-haul flights received similar ground delays. In addition, there was a noticeable reduction in the total amount of excessive unanticipated last-minute ground delays, i.e. delays that are frequently imposed on the short-haul flight in current day operations due to saturation in the overhead stream, commonly referred to as 'double penalty'. Furthermore, the concept achieved the target throughput while minimizing the expected cost associated with overall delays in arrival traffic. Assessment of the RTA capabilities showed that there was indeed improvement of the scheduled entry times into TBFM regions by using RTA capabilities. However, with respect to reduction in delays incurred within TBFM, there was no observable benefit of improving the precision of long-haul flights entry times.

Collaborative Trajectory Options Program (CTOP)↗

DOE OSTI2025

Hestia-SWIFL: hourly anthropogenic fossil fuel CO2 and heat on the 2km WRF grid, version 1.1

The Hestia-SWIFL version 1.1 anthropogenic heat (AH) and fossil fuel CO2 (FFCO2) emissions data product represent emissions due to the combustion of fossil fuel and cement production within the state of Arizona from 2019 to 2022. This product was developed as part of the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL) project, which aims to provide new knowledge and tools that address extreme heat, air quality, climate change and related urban environmental issues by integrating high-resolution observations, modeling, and civic engagement. The emissions are generated using a bottom-up/engineering approach and are tied to results generated by the Vulcan Project version 4, an effort to quantify space/time-resolved FFCO2 & AH emissions for the entire United States landscape. A large number of data sources are combined to best estimate the emissions at fine scales such as air quality emissions data, traffic flow data, building information, sociodemographic information, and fuel statistics. The AH product provides emissions for two emissions sources (transportation and point source emissions) in units of Watts per hour per square meter (W/m2) per year (annual files) or per hour (hourly files). The FFCO2 product provides emissions from nine individual emission sectors as well as the total, and in units of tons of carbon (tC) per grid cell per year or per hour. The output made available here places the native spatial resolution of the Hestia FFCO2 & AH emissions data product (points, lines, and polygons) into a regularized 2km x 2km grid at hourly and annual temporal resolutions, and stored in netCDF files. The exact spatial extent is defined by the ASU Weather Research Forecast (WRF) simulation grid. All data are processed using R/Python pm high-performance computing system. 2-27-2026 updates: Bugs in airport hourly profile (both AH and FFCO2) and building spatial patterns (FFCO2 only) were fixed. Hourly emissions are reprocessed for all years to reflect those changes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1982

The outlook for advanced transport aircraft

The technological advances most likely to contribute to advanced aircraft designs and the efficiency, performance, and financial considerations driving the development directions for new aircraft are reviewed. Fuel-efficiency is perceived as the most critical factor for any new aircraft or component design, with most gains expected to come in areas of propulsion, aerodynamics, configurations, structural designs and materials, active controls, digital avionics, laminar flow control, and air-traffic control improvements. Any component area offers an efficiency improvement of 3-12%, with a maximum of 50% possible with a 4000 m range aircraft. Advanced turboprops have potential applications in short and medium haul subsonic aircraft, while a fuel efficient SST may be possible by the year 2000. Further discussion is devoted to the pivoted oblique wing aircraft, lightweight structures, and the necessity for short payback times.

Leavens, J. M., Jr.↗

NASA NTRS1989

Descent strategy comparisons for TNAV-equipped aircraft under airplane-preferred operating conditions

Three 4-D descent strategies were evaluated which were employed by TNAV-equipped aircraft in an advanced metering air traffic control environment. The Flow Management Evaluation Model (FMEM) was used to assess performance using three criteria when traffic enters the simulation under preferred cruise operating conditions (altitude and speed): throughput, fuel usage, and conflict probability. In comparison to an evaluation previously performed under NASA contract, the current analysis indicates that the optimal descent strategy is preferred over the clean-idle and constant descent angle (CFPA) strategies when all three criteria are considered.

Izumi, K. H.↗

NASA NTRS1998

A Fast-Time Study of Aircraft Reordering in Arrival Sequencing and Scheduling

In order to ensure that the safe capacity of the terminal area is not exceeded, Air Traffic Management ATM often places restrictions on arriving flights transitioning from en route airspace to terminal airspace. This restriction of arrival traffic is commonly referred to as arrival flow management, and includes techniques such as metering, vectoring, fix-load balancing, and the imposition of miles-in-trail separations. These restrictions are enacted without regard for the relative priority which airlines may be placing on individual flights based on factors such as crew criticality, passenger connectivity, critical turn times, gate availability, on-time performance, fuel status, or runway preference. The development of new arrival flow management techniques which take into consideration priorities expressed by air carriers will likely reduce the economic impact of ATM restrictions on the airlines and lead to increased airline economic efficiency by allowing airlines to have greater control over their individual arrival banks of aircraft. NASA and the Federal Aviation Administration (FAA) have designed and developed a suite of software decision support tools (DSTs) collectively known as the Center TRACON Automation System (CTAS). One of these tools, the Traffic Management Advisor (TMA) is currently being used at the Fort Worth Air Route Traffic Control Center to perform arrival flow management of traffic into the Dallas/Fort Worth airport (DFW). The TMA is a time-based strategic planning tool that assists Traffic Management Coordinators (TMCs) and En Route Air Traffic Controllers in efficiently balancing arrival demand with airport capacity. The primary algorithm in the TMA is a real-time scheduler which generates efficient landing sequences and landing times for arrivals within about 200 no a. from touchdown. This scheduler will sequence aircraft so that they arrive in a first- come - first-served (FCFS) order. While FCFS sequencing establishes a fair order based on estimated times of arrival, it does not take into account individual airline priorities among incoming flights. NASA is exploring the possibility of allowing airlines to express relative arrival priorities to air traffic management through the development of new CTAS scheduling algorithms which take into consideration airline arrival preferences. The accommodation of airline priorities in arrival sequencing and scheduling would under most circumstances result in a deviation from a "natural" or FCFS arrival order. As a First step toward developing airline influenced sequencing algorithms, an investigation was conducted to determine the feasibility of reordering arrival traffic from a strict FCFS sequence. A fast-time simulation has been developed which allows statistical evaluation of sequencing and scheduling algorithms for arrival traffic at the Dallas/Fort Worth Airport. In contrast to real-time simulation or field tests, which would require on the order of ninety minutes to examine a single traffic rush period, the fast-time simulation allows examination of multiple rush periods in a matter of seconds.

Carr, Greg↗

NASA NTRS2015

A Wavelet Analysis Approach for Categorizing Air Traffic Behavior

In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.

wavelet analysis↗

DOE OSTI2021

A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction

Here, we put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements for air traffic improvements. Toward emerging applications of digital twins in aviation, the proposed approach allows for constructing a realtime predictive tool for wake-vortex transport and decay systems. We build on the fact that in realistic application, there are uncertainties in initial and boundary conditions, model parameters, as well as measurements. Moreover, conventional nonlinear ROMs based on Galerkin projection (GROMs) suffer from imperfection and solution instabilities, especially for advection-dominated flows with slow decay in the Kolmogorov n-width. In the presented LSTM nudging (LSTM-N) approach, we fuse forecasts from a combination of imperfect GROM and uncertain state estimates, with sparse Eulerian sensor measurements to provide more reliable predictions in a dynamical data assimilation framework. We illustrate our concept by solving the two-dimensional vorticity transport equation. We investigate the effects of measurements noise and state estimate uncertainty on the performance of the LSTM-N behavior. We also demonstrate that it can sufficiently handle different levels of temporal and spatial measurement sparsity, and offer a huge potential in developing next-generation digital twin technologies for aerospace applications.

42 ENGINEERING↗

NASA NTRS2020

Integrated Demand Management: The FCA Balancing Algorithm

The Collaborative Trajectory Options Program (CTOP) is a new NextGen function that resides within the FAA’s Traffic Flow Management System (TFMS) software. CTOP was designed to be used in the United States’ national airspace to control the distribution of air traffic demand, both temporally and geographically, through a set of Flow Constrained Areas (FCAs). Each FCA is assigned capacity values that represent an estimated upper limit of manageable demand, and CTOP controls to that capacity by using Expect Departure Clearance Time (EDCT) air traffic control clearances, and/or rerouting flights to an alternate FCA or out of the CTOP completely. CTOP’s decisions about which control options best meet system and user needs are based on the Trajectory Options Set (TOS) submitted by airline operators for each flight. The FCA Balancing Algorithm (FBA) described in this document is a proposed decision support capability that generates CTOP capacity entries for FCAs controlling traffic to a common downstream constraint. The FBA provides an equitable distribution of impact, and addresses the added complexity of assigning FCA capacity values for this specific type of use case, greatly simplifying the FAA air traffic manager’s task.

IDM↗

NASA NTRS1973

An analytic study of near terminal area optimal sequencing and flow control techniques

Optimal flow control and sequencing of air traffic operations in the near terminal area are discussed. The near terminal area model is based on the assumptions that the aircraft enter the terminal area along precisely controlled approach paths and that the aircraft are segregated according to their near terminal area performance. Mathematical models are developed to support the optimal path generation, sequencing, and conflict resolution problems.

Park, S. K.↗

NASA NTRS2017

Models of Sector Flows Under Local, Regional and Airport Weather Constraints

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

Kulkarni, Deepak↗

NASA NTRS2019

Management by Trajectory: Improving Predictability for Airspace Operations

In the present-day National Airspace System, the air traffic management system attempts to predict the trajectory for each flight based on the flight plan and scheduled or controlled departure time. However, gaps in trajectory data and models, coupled with tactical control actions that are not communicated to automation systems or other stakeholders, lead to trajectory predictions that are less accurate than they could be. This affects traffic flow management performance. Management by Trajectory (MBT) is a NASA concept for air traffic management in which every flight operates in accordance with a 4D trajectory that is negotiated between the airspace user and the FAA to account for the airspace user’s goals while complying with NAS constraints. The primary benefit of MBT is an improvement in system performance due to increased trajectory predictability and stability, which result from managing traffic in all four dimensions (2D route, vertical, and time), ensuring that changes to the flight’s trajectory are incorporated into the assigned trajectory, and utilizing improved time or arrival control standards. Importantly, the performance improvements support increasing efficiency without increasing collision risk. This paper provides an overview of MBT and describes fast-time simulation results evaluating the safety, performance, and efficiency effects of MBT.

Fernandes, Alicia B.↗

NASA NTRS2017

An Advanced Trajectory-Based Operations Prototype Tool and Focus Group Evaluation

Trajectory-based operations (TBO) is a key concept in the Next Generation Air Transportation System transformation of the National Airspace System (NAS) that will increase the predictability and stability of traffic flows, support a common operational picture through the use of digital data sharing, facilitate more effective collaborative decision making between airspace users and air navigation service providers, and enable increased levels of integrated automation across the NAS. The National Aeronautics and Space Administration (NASA) has been developing trajectory-based systems to improve the efficiency of the NAS during specific phases of flight and is now also exploring Advanced 4-Dimensional Trajectory (4DT) operational concepts that will integrate these technologies and incorporate new technology where needed to create both automation and procedures to support gate-to-gate TBO. A TBO Prototype simulation toolkit has been developed that demonstrates initial functionality that may reside in an Advanced 4DT TBO concept. Pilot and controller subject matter experts (SMEs) were brought to the Air Traffic Operations Laboratory at NASA Langley Research Center for discussions on an Advanced 4DT operational concept and were provided an interactive demonstration of the TBO Prototype using four example scenarios. The SMEs provided feedback on potential operational, technological, and procedural opportunities and concerns. After viewing the interactive demonstration scenarios, the SMEs felt the operational capabilities demonstrated would be useful for performing TBO while maintaining situation awareness and low mental workload. The TBO concept demonstrated produced defined routings around weather which resulted in a more organized, consistent flow of traffic where it was clear to both the controller and pilot what route the aircraft was to follow. In general, the controller SMEs felt that traffic flow management should be responsible for generating and negotiating the operational constraints demonstrated, in cooperation with the Air Traffic Control System Command Center, while air traffic control should be responsible for the implementation of those constraints. The SMEs also indicated that digital data communications would be very beneficial for TBO operations and would result in less workload due to reduced communications, would eliminate issues due to language barriers and frequency problems, and would make receiving, loading, accepting, and executing clearances easier, less ambiguous, and more expeditious. This paper describes an Advanced 4DT operational concept, the TBO Prototype, the demonstration scenarios and methods used, and the feedback obtained from the pilot and controller SMEs in this focus group evaluation.

Guerreiro, Nelson M.↗