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NASA NTRS2020

Integrated Demand Management: Concepts and Procedures

This report provides a comprehensive description of the Integrated Demand Management concept. Motivation: NASA’s Integrated Demand Management (IDM) research explores the idea that, under certain conditions, time-based flow management (TBFM) arrival operations can benefit from the coordinated use of a strategic traffic management initiative (TMI) to “precondition” the inbound demand. The research was motivated by the observation that TBFM was usually turned off during convective weather, even in facilities where it was routinely used. Our hypothesis was that strategic adjustments to the inbound traffic so that it provided a better match to the off-nominal changes in capacity observed during these conditions could enable TBFM scheduling to continue to provide effective support for arrival traffic management. Concept: IDM proposes that a TMI (e.g., a Collaborative Trajectory Options Program, or CTOP) be used to adjust the rate and/or geographic distribution across flows of the traffic inbound to a high-demand, TBFM-managed airport before that traffic reaches the TBFM planning horizon. After this strategic preconditioning, TBFM can then tactically fine-tune the demand to deliver a well-managed, orderly feed to the destination airport. Coordinated use of these two flow management capabilities is intended to improve system performance in terms of: • Equity of ground delay assignment, avoiding excessive ground delay for TBFM-scheduled departures, without penalizing longer flights; • Throughput, by distributing traffic to maximize use of available capacity; • Predictability for operators, providing advance notice about the impact on individual flights; • Increased flexibility, supporting operator mitigation strategies such as slot swapping or trajectory options; • Efficiency of flight operations, using ground delay more effectively and reducing airborne delay. The operational description in this document highlights how the IDM concept builds upon already existing tools and procedures, and also indicates where tool enhancements could facilitate conduct of IDM operations. However, enhanced tools are not a requirement for concept introduction. In fact, initial deployment that focused on training procedures and rationale for coordinated use of TFMS and TBFM, without changes to existing tools, might be a simpler way to introduce and to familiarize traffic managers with the idea of preconditioning. The concept and procedures described in this document can hopefully provide useful guidance for introduction of IDM into field operations..

IDM↗

NASA NTRS2011

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

In 2007 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organizations to find ways to reduce the cost of operations for supporting the International Space Station (ISS) in the Mission Control Center (MCC). Each MOD organization was asked to define and execute projects that would help them attain cost reductions by 2012. The MOD Operations Division Flight Planning Branch responded to this challenge by launching several software automation projects that would allow them to greatly improve console operations and reduce ISS console staffing and intern reduce operating costs. These tasks ranged from improving the management and integration mission plan changes, to automating the uploading and downloading of information to and from the ISS and the associated ground complex tasks that required multiple decision points. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture; as well as engaging a previously TRL 4-5 technology developed by Ames Research Center (ARC) that utilized an intelligent agent-based system to manage and automate file traffic flow, archive data, and generate console logs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the goal of eliminating a second full time ISS console support position by 2012. The team will also reduce one long range planning console position by 2014. When complete, these Flight Planning Branch projects will account for the elimination of 3 console positions and a reduction in staffing of 11 engineering personnel (EP) for ISS.

Hall, Timothy A.↗

NASA NTRS2015

Methodology to Define Delivery Accuracy Under Current Day ATC Operations

In order to enable arrival management concepts and solutions in a NextGen environment, ground- based sequencing and scheduling functions have been developed to support metering operations in the National Airspace System. These sequencing and scheduling algorithms as well as tools are designed to aid air traffic controllers in developing an overall arrival strategy. The ground systems being developed will support the management of aircraft to their Scheduled Times of Arrival (STAs) at flow-constrained meter points. This paper presents a methodology for determining the undelayed delivery accuracy for current day air traffic control operations. This new method analyzes the undelayed delivery accuracy at meter points in order to understand changes of desired flow rates as well as enabling definition of metrics that will allow near-future ground automation tools to successfully achieve desired separation at the meter points. This enables aircraft to meet their STAs while performing high precision arrivals. The research presents a possible implementation that would allow delivery performance of current tools to be estimated and delivery accuracy requirements for future tools to be defined, which allows analysis of Estimated Time of Arrival (ETA) accuracy for Time-Based Flow Management (TBFM) and the FAA's Traffic Management Advisor (TMA). TMA is a deployed system that generates scheduled time-of-arrival constraints for en- route air traffic controllers in the US. This new method of automated analysis provides a repeatable evaluation of the delay metrics for current day traffic, new releases of TMA, implementation of different tools, and across different airspace environments. This method utilizes a wide set of data from the Operational TMA-TBFM Repository (OTTR) system, which processes raw data collected by the FAA from operational TMA systems at all ARTCCs in the nation. The OTTR system generates daily reports concerning ATC status, intent and actions. Due to its availability, ease of use, and vast collection of data across several airspaces it was determined that the OTTR data set would be the best method to utilize moving forward with this analysis. The particular variables needed for further analysis were determined along with the necessary OTTR reports, by working closely with the repository team additional analysis reports were developed that provided key ETA and STA information at the freeze horizon. One major benefit of the OTTR data is that using the correct reports the data across several airports could be analyzed over large periods of time. The OTTR data processes the TBFM data daily and is stored in various formats across several airspaces. This allowed us to develop our own parsing methods and raw data processing that would not rely on other computationally expensive tools that perform more in depth analysis of similar sets of data. The majority of this work consisted of the development of the ability to filter flights to create a subset of flights that could be considered undelayed, which is defined as a flight at the freeze horizon with an ETA and STA difference that was minimal or close to zero. This was a broad method that allowed the consideration of a large data set which consisted of all the traffic across a two month period in 2013, the hottest and coldest months, arriving into four airports: George Bush Intercontinental, Denver International, Los Angeles International, and Phoenix Sky Harbor.

delivery accuracy↗

NASA NTRSDate not supplied

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↗

NASA NTRS1985

Simulation of time-control procedures for terminal area flow management

Simulations of a terminal area traffic-management system incorporating automated scheduling and time-control (four-dimensional) techniques conducted at NASA Ames Research Center jointly with the Federal Aviation Administration, have shown that efficient procedures can be developed for handling a mix of 4D-equipped and conventionally equipped aircraft. A crucial role in this system is played by an ATC host computer algorithm, referred to as a speed advisory, that allows controllers to maintain accurate time schedules of the conventionally equipped aircraft in the traffic mix. Results are of the most recent simulations in which two important special cases were investigated. First, the effects of a speed advisory on touchdown time scheduling are examined, when unequipped aircraft are constrained to follow fuel-optimized profiles in the near-terminal area, and rescheduling procedures are developed to handle missed approaches of 4D-equipped aircraft. Various performance measures, including controller opinion, are used to evaluate the effectiveness of the procedures.

Alcabin, M.↗

NASA NTRS2005

Expanding the Use of Time-Based Metering: Multi-Center Traffic Management Advisor

Time-based metering is an efficient air traffic management alternative to the more common practice of distance-based metering (or "miles-in-trail spacing"). Despite having demonstrated significant operational benefit to airspace users and service providers, time-based metering is used in the United States for arrivals to just nine airports and is not used at all for non-arrival traffic flows. The Multi-Center Traffic Management Advisor promises to bring time-based metering into the mainstream of air traffic management techniques. Not constrained to operate solely on arrival traffic, Multi-Center Traffic Management Advisor is flexible enough to work in highly congested or heavily partitioned airspace for any and all traffic flows in a region. This broader and more general application of time-based metering is expected to bring the operational benefits of time-based metering to a much wider pool of beneficiaries than is possible with existing technology. It also promises to facilitate more collaborative traffic management on a regional basis. This paper focuses on the operational concept of the Multi-Center Traffic Management Advisor, touching also on its system architecture, field test results, and prospects for near-term deployment to the United States National Airspace System.

Landry, Steven J.↗

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 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 NTRS2013

Research Traffic Management Advisor (rTMA) Up-level Final Report

The FAA Time Based Flow Management (TBFM) Program provides for operational use and continued development of the Traffic Management Advisor (TMA) technology that NASA demonstrated in 1996. Although NASA's Center-TRACON Automation System (CTAS) software baseline includes advanced versions of TMA, some research activities are better served by a version of TMA that more closely matches the FAA's TBFM software. Beginning in 2009, NASA created Research TMA (rTMA) to enable researchers to work with FAA TBFM software in a research environment. The original rTMA was derived from TBFM v3.10 and later up-leveled to TBFM v3.12. This report documents the most recent up-level effort in which rTMA was re-derived from TBFM v4.00.07.

traffic management↗

NASA NTRS2015

Evaluation of Pushback Decision-Support Tool Concept for Charlotte Douglas International Airport Ramp Operations

This paper proposes a new departure pushback decision-support tool (DST) for airport ramp-tower controllers. It is based on NASA's Spot and Runway Departure Advisor (SARDA) collaborative decision-making concept, except with the modification that the gate releases now are controlled by tactical pushback (or gate-hold) advisories instead of strategic pre-assignments of target pushback times to individual departure flights. The proposed ramp DST relies on data exchange with the airport traffic control tower (ATCT) to coordinate pushbacks with the ATCT's flow-management intentions under current operational constraints, such as Traffic Management Initiative constraints. Airlines would benefit in reduced taxi delay and fuel burn. The concept was evaluated in a human-in-the-loop simulation experiment with current ramp-tower controllers at the Charlotte Douglas International Airport as participants. The results showed that the tool helped reduce taxi time by one minute per flight and overall departure flight fuel consumption by 10-12% without reducing runway throughput. Expect Departure Clearance Time (EDCT) conformance also was improved when advisories were provided. These benefits were attained without increasing the ramp-tower controllers' workload. Additionally, the advisories reduced the ATCT controllers' workload.

aerospace human factors↗

NASA NTRSDate not supplied

Transcribing Air Traffic Control System Command Center Planning Telecons Using Cloud-Based Automatic Speech Recognition

This paper addresses the challenge of using Automatic Speech Recognition (ASR) technology to transcribe regular teleconferences that happen between FAA Air Traffic Control System Command Center (ATCSCC) planners, stakeholders and air users. These planning teleconferences (aka telecons or planning webinars) are an integral part of managing air traffic in the U.S. National Airspace System (NAS). In particular, the meetings facilitate the creation and modification of various traffic management initiatives (TMIs), that are used to regulate the flow of air traffic. This is typically a human intensive process, requiring specialists to listen to the entire meeting audio (10-20 minutes duration) and inferring the state of the NAS (e.g., weather phenomenon) that was discussed. It would be advantageous to have digital transcripts of the audio and have useful information (e.g., related to TMIs) automatically extracted from the transcripts. In this regard, we are exploring the adoption of state-of-the-art speech to text and Natural Language Processing (NLP) tools that will achieve our objective of digitizing the webinar audio. Unfortunately, the highly technical phraseology present in the audio and limited data availability for model building make ASR difficult. To overcome this challenge, we have taken the critical first step in creating a human transcription dataset from ~20 hours of speech in the ATCSCC audio with the help of subject matter experts. A novelty of our work is the creation of a ground truth transcription dataset for ATCSCC teleconference webinars, which is particularly important for Aviation domain-specific NLP tasks. Using Microsoft Speech Studio, a cloud-based ASR platform, we have fine-tuned the English pre-trained ASR models (available in speech studio) and achieved an average word error rate (WER) of 6.81%. The baseline ASR also provides a digital version of each planning webinar, making it accessible and text-searchable for future references. Additionally, the transcriptions can serve as a bridge between raw audio data and a range of text-based NLP tasks, such as named entity recognition (NER) and intent classification, potentially enhancing the digital footprint of the webinars and other connected data sources. Our work has several potential applications. Firstly, the transcriptions can be analyzed to understand the complex decision process of creating, implementing and modifying TMIs and may also contribute to TMI prediction services. Secondly, our dataset and model can be used to develop more accurate ASR systems for aviation-specific language, which can bring about digital communication in the aviation industry (and aid current “voice only” communications, which are inherently error-prone). Lastly, the transcriptions themselves can be used as a valuable resource for training other NLP models.

Stephen S. B. Clarke↗

NASA NTRS2011

System Oriented Runway Management: A Research Update

The runway configuration used by an airport has significant implications with respect to its capacity and ability to effectively manage surface and airborne traffic. Aircraft operators rely on runway configuration information because it can significantly affect an airline's operations and planning of their resources. Current practices in runway management are limited by a relatively short time horizon for reliable weather information and little assistance from automation. Wind velocity is the primary consideration when selecting a runway configuration; however when winds are below a defined threshold, discretion may be used to determine the configuration. Other considerations relevant to runway configuration selection include airport operator constraints, weather conditions (other than winds) traffic demand, user preferences, surface congestion, and navigational system outages. The future offers an increasingly complex landscape for the runway management process. Concepts and technologies that hold the potential for capacity and efficiency increases for both operations on the airport surface and in terminal and enroute airspace are currently under investigation. Complementary advances in runway management are required if capacity and efficiency increases in those areas are to be realized. The System Oriented Runway Management (SORM) concept has been developed to address this critical part of the traffic flow process. The SORM concept was developed to address all aspects of runway management for airports of varying sizes and to accommodate a myriad of traffic mixes. SORM, to date, addresses the single airport environment; however, the longer term vision is to incorporate capabilities for multiple airport (Metroplex) operations as well as to accommodate advances in capabilities resulting from ongoing research. This paper provides an update of research supporting the SORM concept including the following: a concept of overview, results of a TRCM simulation, single airport and Metroplex modeling effort and a benefits assessment.

Lohr, Gary W.↗

NASA NTRS2017

Models of Sector Aircraft Counts in the Presence of Local, Regional and Airport Constraints

Kulkarni, Deepak↗

NASA NTRS1990

The Traffic Management Advisor

The traffic management advisor (TMA) is comprised of algorithms, a graphical interface, and interactive tools for controlling the flow of air traffic into the terminal area. The primary algorithm incorporated in it is a real-time scheduler which generates efficient landing sequences and landing times for arrivals within about 200 n.m. from touchdown. A unique feature of the TMA is its graphical interface that allows the traffic manager to modify the computer-generated schedules for specific aircraft while allowing the automatic scheduler to continue generating schedules for all other aircraft. The graphical interface also provides convenient methods for monitoring the traffic flow and changing scheduling parameters during real-time operation.

Nedell, William↗

NASA NTRS1994

A knowledge-based system for controlling automobile traffic

Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

Maravas, Alexander↗

NASA NTRS1998

The Future of Air Traffic Management

A system for the control of terminal area traffic to improve productivity, referred to as the Center-TRACON Automation System (CTAS), is being developed at NASA's Ames Research Center under a joint program with the FAA. CTAS consists of a set of integrated tools that provide computer-generated advisories for en-route and terminal area controllers. The premise behind the design of CTAS has been that successful planning of traffic requires accurate trajectory prediction. Data bases consisting of representative aircraft performance models, airline preferred operational procedures and a three dimensional wind model support the trajectory prediction. The research effort has been the design of a set of automation tools that make use of this trajectory prediction capability to assist controllers in overall management of traffic. The first tool, the Traffic Management Advisor (TMA), provides the overall flow management between the en route and terminal areas. A second tool, the Final Approach Spacing Tool (FAST) provides terminal area controllers with sequence and runway advisories to allow optimal use of the runways. The TMA and FAST are now being used in daily operations at Dallas/Ft. Worth airport. Additional activities include the development of several other tools. These include: 1) the En Route Descent Advisor that assist the en route controller in issuing conflict free descents and ascents; 2) the extension of FAST to include speed and heading advisories and the Expedite Departure Path (EDP) that assists the terminal controller in management of departures; and 3) the Collaborative Arrival Planner (CAP) that will assist the airlines in operational decision making. The purpose of this presentation is to review the CTAS concept and to present the results of recent field tests. The paper will first discuss the overall concept and then discuss the status of the individual tools.

Denery, Dallas G.↗

NASA NTRS1990

A conflict analysis of 4D descent strategies in a metered, multiple-arrival route environment

A conflict analysis was performed on multiple arrival traffic at a typical metered airport. The Flow Management Evaluation Model (FMEM) was used to simulate arrival operations using Denver Stapleton's arrival route structure. Sensitivities of conflict performance to three different 4-D descent strategies (clear-idle Mach/Constant AirSpeed (CAS), constant descent angle Mach/CAS and energy optimal) were examined for three traffic mixes represented by those found at Denver Stapleton, John F. Kennedy and typical en route metering (ERM) airports. The Monte Carlo technique was used to generate simulation entry point times. Analysis results indicate that the clean-idle descent strategy offers the best compromise in overall performance. Performance measures primarily include susceptibility to conflict and conflict severity. Fuel usage performance is extrapolated from previous descent strategy studies.

Izumi, K. H.↗

NASA NTRS2017

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies that will inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. This paper also describes the initial validation of individual components of the automated simulation capability, and an example application comparing the performance of the IDM concept under two TBFM scheduling paradigms. The results and conclusions from this simulation compare closely to those from previous HITL simulations using similar scenarios, providing an initial validation of the automated simulation capability.

Integrated Demand Management↗