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At least 343 records · Page 19

Air Traffic Management Research at NASA Ames

The Aviation Systems Division at the NASA Ames Research Center conducts leading edge research in air traffic management concepts and technologies. This overview will present concepts and simulation results for research in traffic flow management, safe and efficient airport surface operations, super density terminal area operations, separation assurance and system wide modeling and simulation. A brief review of the ongoing air traffic management technology demonstration (ATD-1) will also be presented. A panel discussion, with Mr. Davis serving as a panelist, on air traffic research will follow the briefing.

Davis, Thomas J.↗

How to Compute a Slot Marker - Calculation of Controller Managed Spacing Tools for Efficient Descents with Precision Scheduling

This paper describes the underlying principles and algorithms for computing the primary controller managed spacing (CMS) tools developed at NASA for precisely spacing aircraft along efficient descent paths. The trajectory-based CMS tools include slot markers, delay indications and speed advisories. These tools are one of three core NASA technologies integrated in NASAs ATM technology demonstration-1 (ATD-1) that will operationally demonstrate the feasibility of fuel-efficient, high throughput arrival operations using Automatic Dependent Surveillance Broadcast (ADS-B) and ground-based and airborne NASA technologies for precision scheduling and spacing.

efficient arrivals↗

An Overview of Current Capabilities and Research Activities in the Airspace Operations Laboratory at NASA Ames Research Center

The Airspace Operations Laboratory at NASA Ames conducts research to provide a better understanding of roles, responsibilities, and requirements for human operators and automation in future air traffic management (ATM) systems. The research encompasses developing, evaluating, and integrating operational concepts and technologies for near-, mid-, and far-term air traffic operations. Current research threads include efficient arrival operations, function allocation in separation assurance and efficient airspace and trajectory management. The AOL has developed powerful air traffic simulation capabilities, most notably the Multi Aircraft Control System (MACS) that is used for many air traffic control simulations at NASA and its partners in government, academia and industry. Several additional NASA technologies have been integrated with the AOL's primary simulation capabilities where appropriate. Using this environment, large and small-scale system-level evaluations can be conducted to help make near-term improvements and transition NASA technologies to the FAA, such as the technologies developed under NASA's Air Traffic Management Demonstration-1 (ATD-1). The AOL's rapid prototyping and flexible simulation capabilities have proven a highly effective environment to progress the initiation of trajectory-based operations and support the mid-term implementation of NextGen. Fundamental questions about accuracy requirements have been investigated as well as realworld problems on how to improve operations in some of the most complex airspaces in the US. This includes using advanced trajectory-based operations and prototype tools for coordinating arrivals to converging runways at Newark airport and coordinating departures and arrivals in the San Francisco and the New York metro areas. Looking beyond NextGen, the AOL has started exploring hybrid human/automation control strategies as well as highly autonomous operations in the air traffic control domain. Initial results indicate improved capacity, low operator workload, good situation awareness and acceptability for controllers teaming with autonomous air traffic systems. While much research and development needs to be conducted to make such concepts a reality, these approaches have the potential to truly transform the airspace system towards increased mobility, safe and efficient growth in global operations and enabling many of the new vehicles and operations that are expected over the next decades. This paper describes how the AOL currently contributes to the ongoing air transportation transformation.

simulation↗

An Evaluation of a Flight Deck Interval Management Algorithm Including Delayed Target Trajectories

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature air traffic management technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise timebased scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise in-trail spacing. During high demand operations, TMA-TM may produce a schedule and corresponding aircraft trajectories that include delay to ensure that a particular aircraft will be properly spaced from other aircraft at each schedule waypoint. These delayed trajectories are not communicated to the automation onboard the aircraft, forcing the IM aircraft to use the published speeds to estimate the target aircraft's estimated time of arrival. As a result, the aircraft performing IM operations may follow an aircraft whose TMA-TM generated trajectories have substantial speed deviations from the speeds expected by the spacing algorithm. Previous spacing algorithms were not designed to handle this magnitude of uncertainty. A simulation was conducted to examine a modified spacing algorithm with the ability to follow aircraft flying delayed trajectories. The simulation investigated the use of the new spacing algorithm with various delayed speed profiles and wind conditions, as well as several other variables designed to simulate real-life variability. The results and conclusions of this study indicate that the new spacing algorithm generally exhibits good performance; however, some types of target aircraft speed profiles can cause the spacing algorithm to command less than optimal speed control behavior.

Swieringa, Kurt A.↗

Experimental Photogrammetric Techniques Used on Five Full-Scale Aircraft Crash Tests

Between 2013 and 2015, full-scale crash tests were conducted on five aircraft at the Landing and Impact Research Facility (LandIR) at NASA Langley Research Center (LaRC). Two tests were conducted on CH-46E airframes as part of the Transport Rotorcraft Airframe Crash Testbed (TRACT) project, and three tests were conduced on Cessna 172 aircraft as part of the Emergency Locator Transmitter Survivability and Reliability (ELTSAR) project. Each test served to evaluate a variety of crashworthy systems including: seats, occupants, restraints, composite energy absorbing structures, and Emergency Locator Transmitters. As part of each test, the aircraft were outfitted with a variety of internal and external cameras that were focused on unique aspects of the crash event. A subset of three camera was solely used in the acquisition of photogrammetric test data. Examples of this data range from simple two-dimensional marker tracking for the determination of aircraft impact conditions to entire full-scale airframe deformation to markerless tracking of Anthropomorphic Test Devices (ATDs, a.k.a. crash test dummies) during the crash event. This report describes and discusses the techniques used and implications resulting from the photogrammetric data acquired from each of the five tests.

Littell, Justin D.↗

The String Stability of a Trajectory-Based Interval Management Algorithm in the Midterm Airspace

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides terminal controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain a precise spacing interval behind a target aircraft. As the percentage of IM equipped aircraft increases, controllers may provide IM clearances to sequences, or strings, of IM-equipped aircraft. It is important for these strings to maintain stable performance. This paper describes an analytic analysis of the string stability of the latest version of NASA's IM algorithm and a fast-time simulation designed to characterize the string performance of the IM algorithm. The analytic analysis showed that the spacing algorithm has stable poles, indicating that a spacing error perturbation will be reduced as a function of string position. The fast-time simulation investigated IM operations at two airports using constraints associated with the midterm airspace, including limited information of the target aircraft's intended speed profile and limited information of the wind forecast on the target aircraft's route. The results of the fast-time simulation demonstrated that the performance of the spacing algorithm is acceptable for strings of moderate length; however, there is some degradation in IM performance as a function of string position.

Swieringa, Kurt A.↗

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

scheduling↗

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5 percent per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM (Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas-Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte-Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration-2 (ATD-2) project for technology demonstration of Integrated Arrival-Departure-Surface (IADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement), KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool.

surface operations analysis↗

System Performance of an Integrated Airborne Spacing Algorithm with Ground Automation

The National Aeronautics and Space Administration's (NASA's) first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the Terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools to enable precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise spacing behind another aircraft. Recent simulations and IM algorithm development at NASA have focused on trajectory-based IM operations where aircraft equipped with IM avionics are expected to achieve a spacing goal, assigned by air traffic controllers, at the final approach fix. The recently published IM Minimum Operational Performance Standards describe five types of IM operations. This paper discusses the results and conclusions of a human-in-the-loop simulation that investigated three of those IM operations. The results presented in this paper focus on system performance and integration metrics. Overall, the IM operations conducted in this simulation integrated well with ground-based decisions support tools and certain types of IM operational were able to provide improved spacing precision at the final approach fix; however, some issues were identified that should be addressed prior to implementing IM procedures into real-world operations.

Swieringa, Kurt A.↗

Flight Crew Survey Responses from the Interval Management (IM) Avionics Phase 2 Flight Test

The Interval Management (IM) Avionics Phase 2 flight test used three aircraft over a nineteen day period to operationally evaluate a prototype IM avionics. Quantitative data were collected on aircraft state data and IM spacing algorithm performance, and qualitative data were collected through end-of-scenario and end-of-day flight crew surveys. The majority of the IM operations met the performance goals established for spacing accuracy at the Achieve-by Point and the Planned Termination Point, however there were operations that did not meet goals for a variety of reasons. While the positive spacing accuracy results demonstrate the prototype IM avionics can contribute to the overall air traffic goal, critical issues were also identified that need to be addressed to enhance IM performance. The first category was those issues that impacted the conduct and results of the flight test, but are not part of the IM concept or procedures. These included the design of arrival and approach procedures was not ideal to support speed as the primary control mechanism, the ground-side of the Air Traffic Management Technology Demonstration (ATD-1) integrated concept of operations was not part of the flight test, and the high workload to manually enter the information required to conduct an IM operation. The second category was issues associated with the IM spacing algorithm or flight crew procedures. These issues include the high frequency of IM speed changes and reversals (accelerations), a mismatch between the deceleration rate used by the spacing algorithm and the actual aircraft performance, and some spacing error calculations were sensitive to normal operational variations in aircraft airspeed or altitude which triggered additional IM speed changes. Once the issues in these two categories are addressed, the future IM avionics should have considerable promise supporting the goals of improving system throughput and aircraft efficiency.

Baxley, Brian T.↗

Flight Deck Interval Management Flight Test Final Report

This document provides a summary of the avionics design, implementation, and evaluation activities conducted for the ATD-1 Avionics Phase 2. The flight test data collection and a subset of the analysis results are described. This report also documents lessons learned, conclusions, and recommendations to guide further development efforts.

Tulder, Paul V.↗

Flight Test Assessments of Pilot Workload, System Usability, and Situation Awareness of TASAR

Traffic Aware Strategic Aircrew Requests (TASAR) is an onboard automation concept intended to identify trajectory optimizations, in terms of fuel and time saving objectives, clear of known traffic, weather, and airspace restrictions prior to the aircrew initiating a route-change request to Air Traffic Control (ATC). The software implementation of the TASAR concept is the Traffic Aware Planner (TAP). TASAR analysis and development is being executed by the NASA Langley Research Center's Crew Systems and Aviation Operations Branch (CSAOB) under the sponsorship of the Airspace Technology Demonstration (ATD) Project of the NASA Airspace Operations and Safety Program (AOSP). The TASAR Flight Trial-2 (FT-2) was conducted in June, 2015 out of the Newport News/Williamsburg International Airport. This flight trial was conducted using a Piaggio Avanti flight test aircraft and consisted of 12 Evaluation Flights with airline commercial pilots participating as the Evaluation Pilots, three destination airports in Atlanta and Jacksonville Air Route Traffic Control Centers, and one pair of flight plans associated with each destination airport. The primary goal of FT-2 was to reduce risk for upcoming operational trials with NASA partner airlines, Alaska Airlines and Virgin America. To accomplish this primary goal, six independent objectives were conducted during FT-2, however, this paper will report only the findings of Objective 5; the assessment of system usability, pilot perceived workload, and the degree of pilot acceptability of the TAP Human Machine Interface (HMI) during flight operations, via the administration of several subjective measures.

TASAR↗

TSTR HITL Results

This briefing presents the summary and results of the ATD-2 HITL #2, Tactical Surface Tool for Ramp (TSTR). The original presentation was completed in Aug 2016.

Verma, Savita↗

Ramp Traffic Console (RTC) Ramp Manager Traffic Console (RMTC) Observer Mode User Manual

This document serves as a user manual for the Observer Mode Ramp Traffic Console (RTC) in Charlotte Douglas International Airport Ramp Control Tower. It describes the elements of the full RTC interface and provides explanations for how to interact with the RTC while managing ramp traffic using one of the four RTC sector displays. The RTC provides digitally updated data for all flights including Earliest Off Block Times (EOBT) and Traffic Management Initiatives. Use of the RTC in observer mode allows only for observer and reading of data provided on RTC. In Observer Mode, the RTC may not be used to make data entries. This includes pushback, holds, and proceed inputs as well as updates to a flights data using the flight menu. However, using the RTC in Observer Mode allows for real time observation of ramp operations including pushback and hold entries made by the ramp sector controllers. The pushback advisories and Traffic Management Initiative information is also provided in Observer Mode. The RTC also provides notifications, runway departure counts and lists and near arrival flight lists as additional sources of information for management of ramp traffic. There are also detailed instructions for how to manage traffic with Surface Time Based Metering (STBM) advisories provided on RTC if in STBM mode. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) while performing ramp manager functions such as managing the priority flight list, setting ramp status, and setting the metering mode. The RTC and RMTC ramp tool are one component of a suite of ATD-2 Tools.

Stevens, Lindsay K.↗

Assessing Tactical Scheduling Options for Time-Based Surface Metering

This paper presents a parametric analysis of the most recent tactical scheduler design for NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project, committed to demonstrating time-based surface metering at Charlotte Douglas International Airport (CLT). The tactical scheduler design is implemented in a fast-time simulation model of CLT using NASA’s Surface Operations Simulator and Scheduler. The tactical scheduler is supported by three basic functions: trajectory prediction, runway scheduling, and advisory generation. A key parameter of the advisory generation function is the taxi time delay buffer used when calculating target gate pushback times from runway schedule. Multiple simulations that varied the amount of taxi time delay buffer were analyzed to determine the effect on tactical scheduler performance. The results show an improvement in tactical scheduler performance when the buffer is made sufficiently large to release departures from their gates early enough to maintain scheduler predicted runway throughput.

Zelinski, Shannon↗

Evaluation of Usability and Workload Associated with Paper Strips as Compared to Virtual Flight Strips Used for Ramp Operations

This paper describes a study comparing the use of paper strips with virtual flight strips depicted on a new user interface, the Ramp Traffic Console (RTC), designed for use by ramp controllers to be used in place of paper strips. A Human-In-the-Loop (HITL) experiment was performed as the fifth in a series of six HITL simulation studies designed to evaluate a pushback Decision Support Tool (DST) concept for Charlotte Douglas International Airport (CLT). Workload and usability were assessed in post-run and post-study questionnaires. In the RTC virtual flight strip condition, post-run questionnaire results show lower workload ratings across all aspects of workload; additionally a trend is found toward increased usability ratings. Post-study questionnaire results indicate a preference for RTC over paper strips. Additional research is suggested with more training runs and a greater number of participants to increase statistical power. It is also suggested that this new technology be re-evaluated as a part of the ATD-2 (Airspace Technology Demonstration 2) field testing activities.

Human Factors↗

Effects of EOBT Accuracy on the On-Time Performance

This analysis shows the effects of Earliest Off-Block Time (EOBT) accuracy on the on-time performance metrics, such as A0 and A14 of outbound flights, and Target Takeoff Time (TTOT) compliance. This was originally presented to the ATD-2 Analytics team in March 2018.

Lee, Hanbong↗

Soyuz Occupant Risk

Spaceflight has unique challenges for Occupant Protection. Current NASA Occupant Protection Requirements are based on military and automotive biodynamics research: Brinkley Dynamic Response Criteria; Hybrid III Anthropomorphic Test Device (ATD). Soyuz offers unique insight into the role of spaceflight deconditioning on impact tolerance. Project Objectives: 1. Develop a landing injury database; 2. Obtain seat acceleration data from TMA (Soyuz-TMA: Transport Modified Anthropometric) landings; 3. Re-create Soyuz landings using models; 4. Update NASA occupant protection standards as needed.

Newby, Nate↗