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At least 289 records · Page 16

Applying Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗

Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗

A simulation study of data link message exchange - Flight deck perspective

Data link message exchange for Air Traffic Control (ATC) offers the potential of increasing flight safety and efficiency by reducing communication errors and enabling more information to be exchanged between aircraft and ground facilities. Digital communication also presents an opportunity to relieve the overloading of air traffic control radio frequencies, which hampers efficient message exchange during peak traffic periods in many busy terminal areas. A study has been completed at NASA Langley Research Center to compare the use of data link, for tactical ATC messages and ATIS reports, to conventional voice communication. The results indicate that flight crews prefer the data link message exchange for routine communication with air traffic control facilities. The data link communication process, however, entailed delays related to the physical characteristics of the link and the nature of the interface explored in this study. Consequently, the crews preferred voice radio when exchanging time critical messages.

Waller, Marvin C.↗

User Acceptability of Physiological and Other Measures of Hazardous States of Awareness

Two studies explored user acceptance of devices that measure hazardous states of awareness. In the first study, critical incident data were collected in two workshops from 11 operators working as air traffic controllers or commercial pilots. These critical incident data were used to develop a survey of the acceptability of awareness measures. In the second study, the survey was administered to 100 people also working as air traffic controllers or commercial pilots. Results show that operators are open to the inclusion of technology to measure HSAs even if that technology is somewhat invasive as long as feedback about the HSAs is considered to be useful and helpful. Nonetheless, a major concern is the legal complications associated with being recorded, particularly for older and more experienced operators. Air traffic controllers emphasized the importance of sharing technology information with supervisors in order to receive backup or assistance under conditions of task overload, whereas pilots emphasized the influence of work schedules on problems with awareness. Recommendations are offered concerning the implementation of devices to measure hazardous states of awareness.

Dickinson, Terry L.↗

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

aircraft scheduling,traffic flow management,autono↗

A proof-of-principle getaway special free-flying satellite demonstration

An air traffic control radar calibration satellite is described that will be used by the U.S. Federal Aviation Administration, U.S. military agencies and cooperating governments around the world to measure antenna patterns associated with the existing international air traffic control network. The satellite will employ three L-band receivers, a UHF command receiver, a VHF telemetry transmitter, associated antennas, a microprocessor, fixed solar arrays, and a power supply to acquire, store and forward signal strength data from some of the tracking radars. A second satellite is planned for launch in 1986 into a high altitude polar orbit with a lifetime of several years in order to provide a long-lived calibration service to the entire international air traffic control system. The initial satellite and associated ground station are being designed and built by a volunteer consortium of three educational institutions and more than a dozen aerospace companies. Following this initial demonstration of a free-flying Getaway Special satellite, a substantial number of organizations are contemplating commercial uses of the concept. Discussions are being held with NASA concerning the establishing of an appropriate fee for this new class of service.

Moore, R. G.↗

Model-Based Design of Air Traffic Controller-Automation Interaction

A model of controller and automation activities was used to design the controller-automation interactions necessary to implement a new terminal area air traffic management concept. The model was then used to design a controller interface that provides the requisite information and functionality. Using data from a preliminary study, the Crew Activity Tracking System (CATS) was used to help validate the model as a computational tool for describing controller performance.

Romahn, Stephan↗

Advanced concepts transport aircraft of 1995

The components of the Advanced Concepts Flight Simulation Facilities used to evaluate proposed human-machine interfaces are described. The facilities consist of: (1) an advanced concept flight station, which is a wide-body, composite airframe propelled by two turbo-fan engines; (2) an integrated air traffic control simulation; and (3) experimenter/observer stations. The flight controls and displays, and their operation are studied. The air traffic control provided in the simulation is examined. The control of the flight conditions and data collection by the experimenter are discussed.

Chappell, S. L.↗

The Human Performance Envelope: Past Research, Present Activities and Future Directions

Air traffic controllers (ATCOs) must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness can co-occur, and interact, to effect performance. However, multifactor influences and the association with performance are under-researched. This study utilized a high fidelity human in the loop enroute air traffic control simulation to investigate the relationship between workload, situation awareness and ATCO performance. The study aimed to replicate and extend Edwards, Sharples, Wilson and Kirwans (2012) previous study and confirm multifactor interactions with a participant sample of ex-controllers. The study also aimed to extend Edwards et als previous research by comparing multifactor relationships across 4 automation conditions. Results suggest that workload and SA may interact to produce a cumulative impact on controller performance, although the effect of the interaction on performance may be dependent on the context and amount of automation present. Findings have implications for human-automation teaming in air traffic control, and the potential prediction and support of ATCO performance.

human performance envelope↗

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↗

From where they look to what they think: Determining controller cognitive strategies from oculometer scanning data

The behavior and cognition of air traffic controllers from oculometer scanning data already obtained for another purpose was studied. There was very little work done to develop models of air traffic controllers, much of what was done was done at Langley. One aim of developing such models is to use them as the basis of decision-support or expert-system tools to assist controllers in their tasks. Such tools are more likely to be effective if they incorporate the strategies that controllers actually use, rather than steering them in what might be felt to be unnatural directions.

Cushing, Steven↗

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗

Controller evaluations of the descent advisor automation aid

An automation aid to assist air traffic controllers in efficiently spacing traffic and meeting arrival times at a fix has been developed at NASA Ames Research Center. The automation aid, referred to as the descent advisor (DA), is based on accurate models of aircraft performance and weather conditions. The DA generates suggested clearances, including both top-of-descent point and speed profile data, for one or more aircraft in order to achieve specific time or distance separation objectives. The DA algorithm is interfaced with a mouse-based, menu-driven controller display that allows the air traffic controller to interactively use its accurate predictive capability to resolve conflicts and issue advisories to arrival aircraft. This paper focuses on operational issues concerning the utilization of the DA, specifically, how the DA can be used for prediction, intrail spacing, and metering. In order to evaluate the DA, a real time simulation was conducted using both current and retired controller subjects. Controllers operated in teams of two, as they do in the present environment; issues of training and team interaction will be discussed. Evaluations by controllers indicated considerable enthusiasm for the DA aid, and provided specific recommendations for using the tool effectively.

Tobias, Leonard↗

Design of an air traffic computer simulation system to support investigation of civil tiltrotor aircraft operations

This research project addresses the need to provide an efficient and safe mechanism to investigate the effects and requirements of the tiltrotor aircraft's commercial operations on air transportation infrastructures, particularly air traffic control. The mechanism of choice is computer simulation. Unfortunately, the fundamental paradigms of the current air traffic control simulation models do not directly support the broad range of operational options and environments necessary to study tiltrotor operations. Modification of current air traffic simulation models to meet these requirements does not appear viable given the range and complexity of issues needing resolution. As a result, the investigation of systemic, infrastructure issues surrounding the effects of tiltrotor commercial operations requires new approaches to simulation modeling. These models should be based on perspectives and ideas closer to those associated with tiltrotor air traffic operations.

Rogers, Ralph V.↗

Refinement for fault-tolerance: An aircraft hand-off protocol

Part of the Advanced Automation System (AAS) for air-traffic control is a protocol to permit flight hand-off from one air-traffic controller to another. The protocol must be fault-tolerant and, therefore, is subtle -- an ideal candidate for the application of formal methods. This paper describes a formal method for deriving fault-tolerant protocols that is based on refinement and proof outlines. The AAS hand-off protocol was actually derived using this method; that derivation is given.

Marzullo, Keith↗

Concept of Operations for Interval Management Arrivals and Approach

This paper presents the concept of operations for interval management operations to be deployed in the US National Airspace System (NAS) by the Federal Aviation Administration (FAA) after 2020. The use of interval management operations is described that begin in en route airspace and continue to a termination point inside the arrival terminal area, in a terminal environment that includes other arrival management tools such as arrival metering, Ground-based Interval Management - Spacing (GIM-S), and Terminal Sequencing and Spacing (TSAS). The roles of Air Traffic Controllers and Flight Crews and the ground automation tools that are used by Air Traffic Controllers to enable the primary operation and variations are described.

Hicok, Daniel S.↗

A simulator investigation of the use of digital data link for pilot/ATC communications in a single pilot operation

Studies have shown that radio communications between pilots and air traffic control contribute to high pilot workload and are subject to various errors. These errors result from congestion on the voice radio channel, and missed and misunderstood messages. The use of digital data link has been proposed as a means of reducing this workload and error rate. A critical factor, however, in determining the potential benefit of data link will be the interface between future data link systems and the operator of those systems, both in the air and on the ground. The purpose of this effort was to evaluate the pilot interface with various levels of data link capability, in simulated general aviation, single-pilot instrument flight rule operations. Results show that the data link reduced demands on pilots' short-term memory, reduced the number of communication transmissions, and permitted the pilots to more easily allocate time to critical cockpit tasks while receiving air traffic control messages. The pilots who participated unanimously indicated a preference for data link communications over voice-only communications. There were, however, situations in which the pilot preferred the use of voice communications, and the ability for pilots to delay processing the data link messages, during high workload events, caused delays in the acknowledgement of messages to air traffic control.

Hinton, David A.↗

Automatic Dependent Surveillance Rebroadcast Technology Analysis

In lieu of eminent future air traffic in the next 10-30 years for the United States North American air space, also known as the National Air Space (NAS), many technologies are being investigated for enhancing Air Traffic Control (ATC). This increase in air traffic includes the increase of manned and unmanned aerial vehicles (AVs) of all sizes, at all altitudes, and varying average speeds. The technology of Automatic Dependent Surveillance Rebroadcasting (ADS-R) combines the existing technology used with manned AVs in the NAS called, Automatic Dependent Surveillance Broadcast (ADS-B), and an ‘physical layer’ digital communications technology called flooding. Flooding allows the retransmission of the existing ADS-B AV flight information to ‘in the area’ adjacent AVs, where in a few retransmission epochs will have communicated to all AVs in the designated geographic area.

Konstantin J. Matheou↗