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At least 37 records · Page 2

Investigation of Intelligent Resource Management for Aviation Communications

The emergence of new aerial vehicles into the airspace as part of new initiatives, such as Advanced Air Mobility (AAM), will place growing demand for spectrum resources to support airspace operations. The traditional approach of using fixed channel allocations within standard service volumes will not allow for dynamic and efficient distribution of resources based on airspace demand; consequently, a new approach to aviation spectrum management will be required to meet the anticipated needs of airspace users. The National Aeronautics and Space Administration (NASA) is investigating the application of advanced concepts to implement a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the quality of service prescribed by aeronautical standards. This technical investigation evaluates the dynamic assignment of resources for both air-ground and air-air communication links applicable to both the emerging AAM initiative as well as the existing air traffic management system. The performance of the proposed spectrum management concepts will be evaluated using a custom modeling and simulation capability that is currently under development. The implementation of these approaches is anticipated to facilitate increased spectrum utilization efficiency and enhanced airspace capacity, which will better serve the needs of future applications.

Eric Knoblock↗

Auction Mechanism to Allocate Air Traffic Control Slots

This article deals with an auction mechanism for airspace slots, as a means of solving the European airspace congestion problem. A disequilibrium, between Air Traffic Control (ATC) services supply and ATC services demand are at the origin of almost one fourth of delays in the air transport industry in Europe. In order to tackle this congestion problem, we suggest modifying both pricing and allocation of ATC services, by setting up an auction mechanism. Objects of the auction will be the right for airlines to cross a part of the airspace, and then to benefit from ATC services over a period corresponding to the necessary time for the crossing. Allocation and payment rules have to be defined according to the objectives of this auction. The auctioneer is the public authority in charge of ATC services, whose aim is to obtain an efficient allocation. Therefore, the social value will be maximized. Another objective is to internalize congestion costs. To that end, we apply the principle of Clarke-Groves mechanism auction: each winner has to pay the externalities imposed on other bidders. The complex context of ATC leads to a specific design for this auction.

Raffarin, Marianne↗

Development of an Airspace Simulation and Modeling Tool for Enhanced Spectrum Management

The emergence of new aerial vehicles into the National Airspace System creates an increased demand for aeronautical communications to support aviation operations. However, the issue of spectrum scarcity remains an ever-present concern, and the growing demand cannot be supported using existing spectrum allocation strategies. As a result, a new spectrum management approach is required, and the National Aeronautics and Space Administration (NASA) is investigating advanced concepts to modernize the management and use of aviation spectrum by leveraging the latest advancements in wireless communications, big data and machine learning. This research proposes an autonomous spectrum allocation concept, which allocates communications resources, such as spectrum and power, based on the predicted communications and air traffic demands throughout the airspace, as opposed to the use of fixed allocations as is done today. This approach will result in improved spectrum utilization efficiency and enhanced airspace capacity. The autonomous spectrum allocation concept decomposes into three research areas: demand prediction, resource allocation, and use case evaluation. As part of the use case evaluation effort, a modeling and simulation capability is currently under development. This simulation capability includes the implementation of various features, including visualization of both live or virtually-generated airspace traffic, simulation scenario development, simulation management with data collection, and flight plan creation with corresponding trajectory generation. This modeling and simulation capability will continue to evolve as new and advanced airspace applications are introduced into existing and emerging operational environments.

Eric J. Knoblock↗

Airspace Automation Flight Tabletop Exercise

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

National Campaign↗

An Approach to Reasoning Service Migration in Data and Reasoning Fabric (DRF) Implementation

In this paper we consider service migration problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, estimates of the response time, consumed energy and total cost are defined for each potential compute location. A mixed-integer linear program is then formulated and solved to identify optimal compute locations given QoS constraints, network infrastructure limitations, with worst-case vehicle positioning. The approach is applied to trajectory re-planning use case to avoid a collision with an emergency vehicle in real time.

Air mobility↗

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↗

An Approach to Reasoning Service Migration in Data and Reasoning Fabric (DRF) Implementation

In this paper we consider service placement problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, we estimate for each potential location the response time, consumed energy and total cost; formulate an optimization problem for cost minimization given the users QoS constraints and network infrastructure limitations; and solve it using nonlinear programming tools. The approach is applied to trajectory re-planning use case to handle a no-fly zone contingency in real time.

Vahram Stepanyan↗

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↗

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↗

Management by Trajectory Trade Study of Roles and Responsibilities Between Participants and Automation Report

This report describes a trade study of roles and responsibilities associated with the Management by Trajectory (MBT) concept. The MBT concept describes roles, responsibilities, and information and automation requirements for providing air traffic controllers and managers the ability to quickly generate, evaluate and implement changes to an aircraft's trajectory. In addition, the MBT concept describes mechanisms for imposing constraints on flight operator preferred trajectories only to the extent necessary to maintain safe and efficient traffic flows, and the concept provides a method for the exchange of trajectory information between ground automation systems and the aircraft that allows for trajectory synchronization and trajectory negotiation. The participant roles considered in this trade study include: airline dispatcher, flight crew, radar controller, traffic manager, and Air Traffic Control System Command Center (ATCSCC) traffic management specialists. The proposed allocation of roles and responsibilities was based on analysis of several use cases that were developed for this purpose as well as for walking through concept elements. The resulting allocation of roles and responsibilities reflects both increased automation capability to support many aviation functions, as well as increased flexibility to assign responsibilities to different participants - in many cases afforded by the increased automation capabilities. Note that the selection of participants to consider for allocation of each function is necessarily rooted in the current environment, in that MBT is envisioned as an evolution of the National Airspace System (NAS), and not a revolution. A key feature of the MBT allocations is a vision for the traffic management specialist to take on a greater role. This is facilitated by the vision that separation management functions, in addition to traffic management functions, will be carried out as trajectory management functions. This creates an opportunity for flexibility, allowing the traffic management specialist to carry out tasks that today can only be carried out by the controller currently in contact with the aircraft. This additional tasking for the traffic management specialist comes with requirements for workload management. An increased role for the Data-side (D-side) controller relative to the Radar-side (R-side) controller is a potential approach to mitigating workload for the traffic management specialist, as the D-side controller would have similar ability to perform separation management functions in what today might be considered the "trajectory management" timeframe. This analysis did not distinguish between the D-side and R-side controllers since in many cases the R-side controller works unassisted.

Fernandes, Alicia D.↗

Function Allocation between Automation and Human Pilot for Airborne Separation Assurance

Maintaining safe separation between aircraft is a key determinant of the airspace capacity to handle air transportation. With the advent of satellite-based surveillance, aircraft equipped with the needed technologies are now capable of maintaining awareness of their location in the airspace and sharing it with their surrounding traffic. As a result, concepts and cockpit automation are emerging to enable delegating the responsibility of maintaining safe separation from traffic to the pilot; thus increasing the airspace capacity by alleviating the limitation of the current non-scalable centralized ground-based system. In this paper, an analysis of allocating separation assurance functions to the human pilot and cockpit automation is presented to support the design of these concepts and technologies. A task analysis was conducted with the help of Petri nets to identify the main separation assurance functions and their interactions. Each function was characterized by three behavior levels that may be needed to perform the task: skill, rule and knowledge based levels. Then recommendations are made for allocating each function to an automation scale based on their behavior level characterization and with the help of Subject matter experts.

Idris, Husni↗

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗

Investigation and Evaluation of Advanced Spectrum Management Concepts for Aeronautical Communications

With the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations, there will be an increasing demand for voice and data communications within the National Airspace System (NAS). The continued use of existing VHF and UHF frequency allocations is not a sustainable approach, and as a result, a new spectrum management solution is required to support future mission needs. The proposed spectrum management concepts leverage modern advancements such as artificial intelligence (AI) and big data to dynamically optimize the spectrum utilization based on the predicted communications demand throughout the airspace. This technical investigation considers both air-ground and air-air communications networks, and can be applied to both existing applications such as the air traffic control (ATC) system, as well as future applications, such as the emerging Advanced Air Mobility (AAM). To support the evaluation of the proposed concepts and technologies, a modeling and simulation capability is currently under development and will continue to evolve to support new and advanced airspace applications. It is anticipated that this proposed spectrum concept will better serve the spectrum needs of future NAS applications.

Eric J Knoblock↗

Investigation and Evaluation of Advanced Spectrum Management Concepts for Aeronautical Communications

With the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations, there will be an increasing demand for voice and data communications within the National Airspace System (NAS). The continued use of existing VHF and UHF frequency allocations is not a sustainable approach, and as a result, a new spectrum management solution is required to support future mission needs. The proposed spectrum management concepts leverage modern advancements such as artificial intelligence (AI) and big data to dynamically optimize the spectrum utilization based on the predicted communications demand throughout the airspace. This technical investigation considers both air-ground and air-air communications networks, and can be applied to both existing applications such as the air traffic control (ATC) system, as well as future applications, such as the emerging Advanced Air Mobility (AAM). To support the evaluation of the proposed concepts and technologies, a modeling and simulation capability is currently under development and will continue to evolve to support new and advanced airspace applications. It is anticipated that this proposed spectrum concept will better serve the spectrum needs of future NAS applications.

Eric J Knoblock↗

Advisory Algorithm for Scheduling Open Sectors, Operating Positions, and Workstations

Air traffic controller supervisors configure available sector, operating position, and work-station resources to safely and efficiently control air traffic in a region of airspace. In this paper, an algorithm for assisting supervisors with this task is described and demonstrated on two sample problem instances. The algorithm produces configuration schedule advisories that minimize a cost. The cost is a weighted sum of two competing costs: one penalizing mismatches between configurations and predicted air traffic demand and another penalizing the effort associated with changing configurations. The problem considered by the algorithm is a shortest path problem that is solved with a dynamic programming value iteration algorithm. The cost function contains numerous parameters. Default values for most of these are suggested based on descriptions of air traffic control procedures and subject-matter expert feedback. The parameter determining the relative importance of the two competing costs is tuned by comparing historical configurations with corresponding algorithm advisories. Two sample problem instances for which appropriate configuration advisories are obvious were designed to illustrate characteristics of the algorithm. Results demonstrate how the algorithm suggests advisories that appropriately utilize changes in airspace configurations and changes in the number of operating positions allocated to each open sector. The results also demonstrate how the advisories suggest appropriate times for configuration changes.

Bloem, Michael↗

Delay Banking for Managing Air Traffic

Delay banking has been invented to enhance air-traffic management in a way that would increase the degree of fairness in assigning arrival, departure, and en-route delays and trajectory deviations to aircraft impacted by congestion in the national airspace system. In delay banking, an aircraft operator (airline, military, general aviation, etc.) would be assigned a numerical credit when any of their flights are delayed because of an air-traffic flow restriction. The operator could subsequently bid against other operators competing for access to congested airspace to utilize part or all of its accumulated credit. Operators utilize credits to obtain higher priority for the same flight, or other flights operating at the same time, or later, in the same airspace, or elsewhere. Operators could also trade delay credits, according to market rules that would be determined by stakeholders in the national airspace system. Delay banking would be administered by an independent third party who would use delay banking automation to continually monitor flights, allocate delay credits, maintain accounts of delay credits for participating airlines, mediate bidding and the consumption of credits of winning bidders, analyze potential transfers of credits within and between operators, implement accepted transfers, and ensure fair treatment of all participating operators. A flow restriction can manifest itself in the form of a delay in assigned takeoff time, a reduction in assigned airspeed, a change in the position for the aircraft in a queue of all aircraft in a common stream of traffic (e.g., similar route), a change in the planned altitude profile for an aircraft, or change in the planned route for the aircraft. Flow restrictions are typically imposed to mitigate traffic congestion at an airport or in a region of airspace, particularly congestion due to inclement weather, or the unavailability of a runway or region of airspace. A delay credit would be allocated to an operator of a flight that has accepted, or upon which was imposed, a flow restriction. The amount of the credit would increase with the amount of delay caused by the flow restriction, the exact amount depending on which of several candidate formulas is eventually chosen. For example, according to one formula, there would be no credit for a delay smaller than some threshold value (e.g., 30 seconds) and the amount of the credit for a longer delay would be set at the amount of the delay minus the threshold value. Optionally, the value of a delay credit could be made to decay with time according to a suitable formula (e.g., an exponential decay). Also, optionally, a transaction charge could be assessed against the value of a delay credit that an operator used on a flight different from the one for which the delay originated or that was traded with a different operator. The delay credits accumulated by a given airline could be utilized in various ways. For example, an operator could enter a bid for priority handling in a new flow restriction that impacts one or more of the operator s flights; if the bid were unsuccessful, all or a portion of the credit would be returned to the bidder. If the bid pertained to a single aircraft that was in a queue, delay credits could be consumed in moving the aircraft to an earlier position within the queue. In the case of a flow restriction involving a choice of alternate routes, planned altitude profile, aircraft spacing, or other non-queue flow restrictions, delay credits could be used to bid for an alternative assignment.

Green, Steve↗

Capturing Safety Requirements to Enable Effective Task Allocation Between Humans and Automaton in Increasingly Autonomous Systems

There is a current drive towards enabling the deployment of increasingly autonomous systems in the National Airspace System (NAS). However, shifting the traditional roles and responsibilities between humans and automation for safety critical tasks must be managed carefully, otherwise the current emergent safety properties of the NAS may be disrupted. In this paper, a verification activity to assess the emergent safety properties of a clearly defined, safety critical, operational scenario that possesses tasks that can be fluidly allocated between human and automated agents is conducted. Task allocation role sets were proposed for a human-automation team performing a contingency maneuver in a reduced crew context. A safety critical contingency procedure (engine out on takeoff) was modeled in the Soar cognitive architecture, then translated into the Hybrid Input Output formalism. Verification activities were then performed to determine whether or not the safety properties held over the increasingly autonomous system. The verification activities lead to the development of several key insights regarding the implicit assumptions on agent capability. It subsequently illustrated the usefulness of task annotations associated with specialized requirements (e.g., communication, timing etc.), and demonstrated the feasibility of this approach.

Neogi, Natasha A.↗

A Controller-in-the Loop Simulation of Ground-Based Automated Separation Assurance in a NextGen Environment

A controller-in-the-loop simulation was conducted in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center to investigate the functional allocation aspects associated with ground-based automated separation assurance in a far-term NextGen environment. In this concept, ground-based automation handled the detection and resolution of strategic and tactical conflicts and alerted the controller to deferred situations. The controller was responsible for monitoring the automation and managing situations by exception. This was done in conditions both with and without arrival time constraints across two levels of traffic density. Results showed that although workload increased with an increase in traffic density, it was still manageable in most situations. The number of conflicts increased similarly with a related increase in the issuance of resolution clearances. Although over 99% of conflicts were resolved, operational errors did occur but were tied to local sector complexities. Feedback from the participants revealed that they thought they maintained reasonable situation awareness in this environment, felt that operations were highly acceptable at the lower traffic density level but were less so as it increased, and felt overall that the concept as it was introduced here was a positive step forward to accommodating the more complex environment envisioned as part of NextGen.

Homola, J.↗