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28 records · Page 2

CTAS and NASA Air Traffic Management Fact Sheets for En Route Descent Advisor and Surface Management System

The Surface Management System (SMS) is a decision support tool that will help controllers, traffic managers, and NAS users manage the movements of aircraft on the surface of busy airports, improving capacity, efficiency, and flexibility. The Advanced Air Transportation Technologies (AATT) Project at NASA is developing SMS in cooperation with the FAA's Free Flight Phase 2 (FFP2) pro5ram. SMS consists of three parts: a traffic management tool, a controller tool, and a National Airspace System (NAS) information tool.

Lee, Katharine↗

SARDA HITL #6 Simulation: System Performance Analysis (Initial Results)

This presentation discusses the results of the 6th human-in-the-loop simulation of the Spot and Runway Departure Advisor (SARDA). SARDA is a research prototype decision support tool for both Air Traffic Control Tower controllers and airlines ramp controllers to assit in controlling surface traffic of a busy airport. Data was collected during the human-in-the-loop simulations of SARDA for ramp operatoins at Charlotte International Airport (Oct-Nov 2014). The performance results include taxi time, taxi delay, total delay, and runway usage.

surface management↗

Exact and Heuristic Algorithms for Runway Scheduling

This paper explores the Single Runway Scheduling (SRS) problem with arrivals, departures, and crossing aircraft on the airport surface. Constraints for wake vortex separations, departure area navigation separations and departure time window restrictions are explicitly considered. The main objective of this research is to develop exact and heuristic based algorithms that can be used in real-time decision support tools for Air Traffic Control Tower (ATCT) controllers. The paper provides a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the SRS problem, but may prove unusable for application in real-time environment due to large computation times for moderate sized problems. We next propose a second algorithm that uses heuristics to restrict the search space for the DP based algorithm. A third algorithm based on a combination of insertion and local search (ILS) heuristics is then presented. Simulation conducted for the east side of Dallas/Fort Worth International Airport allows comparison of the three proposed algorithms and indicates that the ILS algorithm performs favorably in its ability to find efficient solutions and its computation times.

safe & surface operations↗

Impact of ATD-2 Tools on Human Factors Metrics at Charlotte Douglas International Airport

New decision support tools were introduced at Charlotte Douglas International Airport (CLT) as part of NASA’s Air Traffic Demonstration 2 (ATD-2) project. ATD-2 is based on concepts which enable integrated arrival, departures, and surface (IADS) operations in a metroplex environment. Metrics on environmental benefits from ATD-2’s surface metering at CLT have shown impressive reductions in fuel consumption and CO2 emissions. Questions have remained on 1) the human factors impact of these new ATD-2 tools and surface metering and 2) the users’ perceptions of how these tools affect operations. To address these questions, post-bank surveys were designed for the four types of users of the new tools at CLT: Ramp Controllers, Ramp Managers, Tower Traffic Management Coordinators (TMCs) and Terminal Radar Approach Control (TRACON) TMCs. These surveys were administered during five-day blocks at three different times. Three types of banks were compared: No ATD-2 tool use, ATD-2 tool use, and ATD-2 use plus surface metering. Results indicate that higher workload or decreased situation awareness was not significantly associated with ATD-2 tool use more than no ATD-2 tool use--in fact for many users the opposite was true. Also, acceptability and operational efficiency measures indicate that the users did not perceive that banks with ATD-2 tools were significantly less acceptable or less efficient than banks without ATD-2 tools.

Airspace Technology Demonstration 2↗

Impact of ATD-2 Tools on Human Factor Metrics at Charlotte Douglas International Airport

New decision support tools were introduced at Charlotte Douglas International Airport (CLT) as part of NASA’s Air Traffic Demonstration 2 (ATD-2) project. ATD-2 is based on concepts which enable integrated arrival, departures, and surface (IADS) operations in a metroplex environment. Metrics on environmental benefits from ATD-2’s surface metering at CLT have shown impressive reductions in fuel consumption and CO2 emissions. Questions have remained on 1) the human factors impact of these new ATD-2 tools and surface metering and 2) the users’ perceptions of how these tools affect operations. To address these questions, post-bank surveys were designed for the four types of users of the new tools at CLT: Ramp Controllers, Ramp Managers, Tower Traffic Management Coordinators (TMCs) and Terminal Radar Approach Control (TRACON) TMCs. These surveys were administered during five-day blocks at three different times. Three types of banks were compared: No ATD-2 tool use, ATD-2 tool use, and ATD-2 use plus surface metering. Results indicate that higher workload or decreased situation awareness was not significantly associated with ATD-2 tool use more than no ATD-2 tool use--in fact for many users the opposite was true. Also, acceptability and operational efficiency measures indicate that the users did not perceive that banks with ATD-2 tools were significantly less acceptable or less efficient than banks without ATD-2 tools.

Bonny K Parke↗

Flight Deck Robustness/Conformance Testing with a Surface Management System: An Integrated Pilot-Controller Human-in-the-Loop Surface Operations Simulation

An integrated flight deck and controller human-in-the-loopsimulation was conducted with a total of 120 Dallas-Ft.Worth (DFW) taxi-out operations. In this first integratedPilot-Controller Spot and Runway Departure Advisor(SARDA) simulation, ATC Ground and Local Controllersused the SARDA decision support tool to plan and issuespot release clearances and departure clearances. TheAirport and Terminal Area Simulator (ATAS), a simulatedB737NG piloted, in turn, by 10 commercial transportparticipant pilots, was integrated into the realisticsimulation traffic environment. In the simulation,controllers used SARDA advisories to issue spot release,taxi route, and runway/departure radio voice clearances toall aircraft on the airport surface. Simulation resultsindicated that under a variety of observed pilot/aircraftperformance variations, SARDA yielded controlleradvisories that were: Supportive of current-day time-basedoperations; Compatible with controllers’ expectations;Predictive of actual take-off times; and, Adaptable to offnominalevents. An Information Sharing Display, thatpresented SARDA sequence and timing information on theflight deck, was considered useful for both NextGenoperations and current-day time-based Traffic ManagementInitiative (TMI) operations.

Foyle, David C.↗

Airport Runway Configuration Management with Offline Model-free Reinforcement Learning

Runway configuration management (RCM) deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction and other environmental variables. RCM is one of the most challenging tasks in air traffic management, as it relies on operational and environmental variables (e.g., weather forecast) that are highly uncertain and complex to model. In this paper, an innovative and automated approach is deployed using offline model-free reinforcement learning to provide decision-support for RCM. The proposed technology processes historical data about variables of interest, decisions made regarding RCM, and their subsequent outcome, to identify a policy that would encourage good decisions and avoid the poor ones. The policy search is guided by an appropriately chosen weighted utility function (e.g., based on minimizing delays and go-arounds). Finally, the performance of the proposed tool is validated using Charlotte Douglas International Airport as the case study, which shows that the proposed method is superior to other conventional rule-based approaches.

Milad Memarzadeh↗

Airport Runway Configuration Management with Offline Model-free Reinforcement Learning

Runway configuration management (RCM) deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction and other environmental variables. RCM is one of the most challenging tasks in air traffic management, as it relies on operational and environmental variables (e.g., weather forecast) that are highly uncertain and complex to model. In this paper, an innovative and automated approach is deployed using offline model-free reinforcement learning to provide decision-support for RCM. The proposed technology processes historical data about variables of interest, decisions made regarding RCM, and their subsequent outcome, to identify a policy that would encourage good decisions and avoid the poor ones. The policy search is guided by an appropriately chosen weighted utility function (e.g., based on minimizing delays and go-arounds). Finally, the performance of the proposed tool is validated using Charlotte Douglas International Airport as the case study, which shows that the proposed method is superior to other conventional rule-based approaches.

Milad Memarzadeh↗

A Concept and Implementation of Optimized Operations of Airport Surface Traffic

This paper presents a new concept of optimized surface operations at busy airports to improve the efficiency of taxi operations, as well as reduce environmental impacts. The suggested system architecture consists of the integration of two decoupled optimization algorithms. The Spot Release Planner provides sequence and timing advisories to tower controllers for releasing departure aircraft into the movement area to reduce taxi delay while achieving maximum throughput. The Runway Scheduler provides take-off sequence and arrival runway crossing sequence to the controllers to maximize the runway usage. The description of a prototype implementation of this integrated decision support tool for the airport control tower controllers is also provided. The prototype decision support tool was evaluated through a human-in-the-loop experiment, where both the Spot Release Planner and Runway Scheduler provided advisories to the Ground and Local Controllers. Initial results indicate the average number of stops made by each departure aircraft in the departure runway queue was reduced by more than half when the controllers were using the advisories, which resulted in reduced taxi times in the departure queue.

Jung, Yoon C.↗

Progress Toward Future Runway Management

The runway is universally acknowledged as a constraining factor to capacity in the National Airspace System (NAS). It follows that investigation of the effective use of runways, both in terms of selection and assignment, is paramount to the efficiency of future NAS operations. The need to address runway management is not a new idea; however, as the complexities of factors affecting runway selection and usage increase, the need for effective research in this area correspondingly increases. Under the National Aeronautics and Space Administration s Airspace Systems Program, runway management is a key research area. To address a future NAS which promises to be a complex landscape of factors and competing interests among users and operators, effective runway management strategies and capabilities are required. This effort has evolved from an assessment of current practices, an understanding of research activities addressing surface and airspace operations, traffic flow management enhancements, among others. This work has yielded significant progress. Systems analysis work indicates that the value of System Oriented Runway Management tools is significantly increased in the metroplex environment over that of the single airport case. Algorithms have been developed to provide runway configuration recommendations for a single airport with multiple runways. A benefits analysis has been conducted that indicates the SORM benefits include supporting traffic growth, cost reduction as a result of system efficiency, NAS optimization from metroplex operations, fairness in aircraft operations, and rational decision making.

Lohr, Gary W.↗