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At least 577 records · Page 32

Analysis and Prediction of Weather Impacted Ground Stop Operations

When the air traffic demand is expected to exceed the available airport's capacity for a short period of time, Ground Stop (GS) operations are implemented by Federal Aviation Administration (FAA) Traffic Flow Management (TFM). The GS requires departing aircraft meeting specific criteria to remain on the ground to achieve reduced demands at the constrained destination airport until the end of the GS. This paper provides a high-level overview of the statistical distributions as well as causal factors for the GSs at the major airports in the United States. The GS's character, the weather impact on GSs, GS variations with delays, and the interaction between GSs and Ground Delay Programs (GDPs) at Newark Liberty International Airport (EWR) are investigated. The machine learning methods are used to generate classification models that map the historical airport weather forecast, schedule traffic, and other airport conditions to implemented GS/GDP operations and the models are evaluated using the cross-validations. This modeling approach produced promising results as it yielded an 85% overall classification accuracy to distinguish the implemented GS days from the normal days without GS and GDP operations and a 71% accuracy to differentiate the GS and GDP implemented days from the GDP only days.

Analysis↗

Effects of Transparency on Pilot Trust and Agreement in the Autonomous Constrained Flight Planner

We performed a human-in-the-loop study to explore the role of transparency in engendering trust and reliance within highly automated systems. Specifically, we examined how transparency impacts trust in and reliance upon the Autonomous Constrained Flight Planner (ACFP), a critical automated system being developed as part of NASA's Reduced Crew Operations (RCO) Concept. The ACFP is designed to provide an enhanced ground operator, termed a super dispatcher, with recommended diversions for aircraft when their primary destinations are unavailable. In the current study, 12 commercial transport rated pilots who played the role of super dispatchers were given six time-pressured all land scenarios where they needed to use the ACFP to determine diversions for multiple aircraft. Two factors were manipulated. The primary factor was level of transparency. In low transparency scenarios the pilots were given a recommended airport and runway, plus basic information about the weather conditions, the aircraft types, and the airport and runway characteristics at that and other airports. In moderate transparency scenarios the pilots were also given a risk evaluation for the recommended airport, and for the other airports if they requested it. In the high transparency scenario additional information including the reasoning for the risk evaluations was made available to the pilots. The secondary factor was level of risk, either high or low. For high-risk aircraft, all potential diversions were rated as highly risky, with the ACFP giving the best option for a bad situation. For low-risk aircraft the ACFP found only low-risk options for the pilot. Both subjective and objective measures were collected, including rated trust, whether the pilots checked the validity of the automation recommendation, and whether the pilots eventually flew to the recommended diversion airport. Key results show that: 1) Pilots trust increased with higher levels of transparency, 2) Pilots were more likely to verify ACFPs recommendations with low levels of transparency and when risk was high, 3) Pilots were more likely to explore other options from the ACFP in low transparency conditions and when risk was high, and 4) Pilots decision to accept or reject ACFPs recommendations increased as a function of the transparency in the explanation. The finding that higher levels of transparency was coupled with higher levels of trust, a lower need to verify other options, and higher levels of agreement with ACFP recommendations, confirms the importance of transparency in aiding reliance on automated recommendations. Additional analyses of qualitative data gathered from subjects through surveys and during debriefing interviews also provided the basis for new design recommendations for the ACFP.

trust↗

Evaluation of the Terminal Area Precision Scheduling and Spacing System for Performance-Based Navigation Arrivals

The growth of global demand for air transportation has put increasing strain on the nation's air traffic management system. To relieve this strain, the International Civil Aviation Organization has urged all nations to adopt Performance-Based Navigation (PBN), which can help to reduce air traffic congestion, decrease aviation fuel consumption, and protect the environment. NASA has developed a Terminal Area Precision Scheduling and Spacing (TAPSS) system that can support increased use of PBN during periods of high traffic, while supporting fuel-efficient, continuous descent approaches. In the original development of this system, arrival aircraft are assigned fuel-efficient Area Navigation (RNAV) Standard Terminal Arrival Routes before their initial descent from cruise, with routing defined to a specific runway. The system also determines precise schedules for these aircraft that facilitate continuous descent through the assigned routes. To meet these schedules, controllers are given a set of advisory tools to precisely control aircraft. The TAPSS system has been evaluated in a series of human-in-the-loop (HITL) air traffic simulations during 2010 and 2011. Results indicated increased airport arrival throughput up to 10 over current operations, and maintained fuel-efficient aircraft decent profiles from the initial descent to landing with reduced controller workload. This paper focuses on results from a joint NASA and FAA HITL simulation conducted in 2012. Due to the FAA rollout of the advance terminal area PBN procedures at mid-sized airports first, the TAPSS system was modified to manage arrival aircraft as they entered Terminal Radar Approach Control (TRACON). Dallas-Love Field airport (DAL) was selected by the FAA as a representative mid-sized airport within a constrained TRACON airspace due to the close proximity of a major airport, in this case Dallas-Ft Worth International Airport, one of the busiest in the world. To address this constraint, RNAV routes and Required Navigation Performance with the particular capability known as Radius-to-Fix (RNP-RF) approaches to a short final were used. The purpose of this simulation was to get feedback on how current operations could benefit with the TAPSS system and also to evaluate the efficacy of the advisory tools to support the broader use of PBN in the US National Airspace System. For this NASA-FAA joint experiment, an Air Traffic Control laboratory at NASA Ames was arranged to simulate arrivals into DAL in Instrument Meteorological Conditions utilizing parallel dependent approaches, with two feeder positions that handed off traffic to one final position. Four FAA controllers participated, alternately covering these three positions. All participants were Full-Performance Level terminal controllers and members of the National Air Traffic Controllers Association. During the simulation, PBN arrival operations were compared and contrasted in three conditions. They were the Baseline, where none of the TAPSS systems TRACON controller decision support advisories were provided, the Limited Advisories, reflecting the existing but dormant capabilities of the current terminal automation equipment with providing a subset of the TAPSS systems advisories; numerical delay, landing sequence, and runway assignment information, and the Full Advisories, with providing the following in addition to the ones in the Limited condition; trajectory slot markers, timelines of estimated times of arrivals and sched

Performance based navigation↗

Exploring Management of Arrival Spacing Using Route Extensions with Terminal Spacing Tools

Airports with shared runway operations between arrivals and departures can experience severe departure gridlock and delays during a heavy arrival push due to insufficient gaps in the arrival stream for aircraft to depart. The problem is accentuated in situations when a large gap in the arrival spacing has to be created at the last minute due to wake vortex separation requirements. At LaGuardia airport, wake vortex separation problems arise when a heavy jet, such as a B757, departing on Runway 31 needs additional spacing between arrivals on Runway 22. A standard solution for controllers in many airports in situations such as this is to extend the downwind leg of arrival aircraft to create extra space between the arrivals. The question addressed in this paper is how such route extensions would work with terminal scheduling operations, namely (1) the automated Terminal Sequencing and Spacing (TSS) tools and (2) a new scheduling tool which increases the availability of gaps for departure aircraft (Departure Sensitive Arrival Spacing or DSAS). In a simulated LaGuardia airport (LGA) Terminal Radar Approach Control (TRACON) airspace, two new RNAV arrival routes were created along with extensions to these routes. The arrival route from the south had a downwind leg extension near the airport in the final sector. The arrival route from the north had an extension in a feeder sector further from the airport. An exploratory one-hour run with the route extensions was compared to an hour run without the extensions. Topics included in the paper are 1) how the route extensions were developed, 2) a procedure outlining how the aircraft could be scheduled to the extensions and who would do it, and 3) the results of the exploratory run compared to the original run without the extensions. The results indicated that the extended downwind leg route helped to create a B757 departure gap in the middle of a packed arrival stream, resulting in a reduction of 11 minutes in average wait time for the B757s, but at a cost of increased controller self-reported workload from low to moderate.

time based flow management↗

Analysis of Impacts of Terminal Restrictions on Departures in D10 TRACON

The D10 – Dallas-Fort Worth Terminal Radar Approach CONtrol (TRACON) is an air traffic facility that controls and manages aircraft and airspace that consists of multiple airports located in the North Texas area. From an air traffic management standpoint, one of the main challenges in the D10 TRACON is the departure fix capacity as multiple airports compete for resources. This problem is magnified when en route demand/capacity imbalance and inclement weather around the TRACON reduce the capacity at the terminal fixes. This leads to multiple, dynamic Traffic Management Initiative (TMI) restrictions being issued by the Air Traffic Control (ATC) on departing flights. This, in turn, propagates delay to the surface of each airport within the metroplex. The NASA Airspace Technology Demonstration 2 (ATD-2) Phase 3 is deployed in D10 to demonstrate new technologies developed to manage the Integrated Arrival, Departure, and Surface (IADS) traffic in a metroplex environment where multiple airports are interacting and sharing resources at the terminal boundary. This paper uses the ATD-2 terminal restriction data collected in the D10 TRACON to quantify the impact of restrictions on the demand, analyze the relation between terminal restrictions and departure taxi time on airport surface, and establish relationships between restrictions and surface delay. We found that the restrictions on departure flights have a direct adverse effect on departure excess taxi time on the airport surface.

ATD-2↗

Analysis of Impacts of Terminal Restrictions on Departures in D10 TRACON

The D10 – Dallas-Fort Worth Terminal Radar Approach CONtrol (TRACON) is an air traffic facility that controls and manages aircraft and airspace that consists of multiple airports located in the North Texas area. From an air traffic management standpoint, one of the main challenges in the D10 TRACON is the departure fix capacity as multiple airports compete for resources. This problem is magnified when en route demand/capacity imbalance and inclement weather around the TRACON reduce the capacity at the terminal fixes. This leads to multiple, dynamic Traffic Management Initiative (TMI) restrictions being issued by the Air Traffic Control (ATC) on departing flights. This, in turn, propagates delay to the surface of each airport within the metroplex. The NASA Airspace Technology Demonstration 2 (ATD-2) Phase 3 is deployed in D10 to demonstrate new technologies developed to manage the Integrated Arrival, Departure, and Surface (IADS) traffic in a metroplex environment where multiple airports are interacting and sharing resources at the terminal boundary. This paper uses the ATD-2 terminal restriction data collected in the D10 TRACON to quantify the impact of restrictions on the demand, analyze the relation between terminal restrictions and departure taxi time on airport surface, and establish relationships between restrictions and surface delay. We found that the restrictions on departure flights have a direct adverse effect on departure excess taxi time on the airport surface.

ATD-2↗

Predicting Air Traffic Management Initiatives Using Supervised Learning

Terminal Traffic Management Initiatives (TMIs) such as Ground Stops (GS) and Ground Delay Programs (GDP) are implemented to manage excess demand or lowered capacity at an airport. Air Traffic Flow Management (TFM) specialists identify situations such as aviation constraints, current and forecasted weather conditions, airport demand and capacity, and initiate TMIs for safe and orderly movement of air traffic. In this paper, we outline supervised learning techniques that can be used to predict and recommend TMIs at an airport based on current weather and airport conditions. Our research involves building classic Machine Learning (ML) models such as Logistic Regression, K-Nearest Neighbor, Random Forest and XGBoost, as well as Long short-term memory (LSTM) networks. We trained the models on 3-year historical data (weather, airport demand, capacity and TMIs) from Newark (EWR) airport which was selected based on its higher TMI implementation rates and varied weather conditions. Although Random Forest and XGBoost algorithms are able to predict if a TMI is needed or not, they have difficulty in predicting specific program type. For this purpose, we found that LSTM time-series forecasting models performed better as they also learn from past TMI program type sequences. This study also lays down the foundation for advanced modeling techniques and architectures to predict TMIs in advance for future periods. The ability to predict TMIs in advance will be highly beneficial to the traffic controllers and managers as this will help them to prepare for and manage TMIs more efficiently.

Manoj Agrawal↗

Scheduler Design Criteria: Requirements and Considerations

This presentation covers fundamental requirements and considerations for developing schedulers in airport operations. We first introduce performance and functional requirements for airport surface schedulers. Among various optimization problems in airport operations, we focus on airport surface scheduling problem, including runway and taxiway operations. We then describe a basic methodology for airport surface scheduling such as node-link network model and scheduling algorithms previously developed. Next, we explain how to design a mathematical formulation in more details, which consists of objectives, decision variables, and constraints. Lastly, we review other considerations, including optimization tools, computational performance, and performance metrics for evaluation.

NASA-KAIA/KARI research collaboration↗

Emotionality in response to aircraft noise: A report of development work

A literature search and pilot study conducted to investigate the topic of emotional response to aircraft noise are described. A Tell-A-Story Technique was developed for use in the pilot study which required respondents to make up stories for a series of aircraft-related and non-aircraft-related pictures. A content analysis of these stories was made. The major finding was that response patterns varied among three groups of respondents - those currently living near airports, those who had lived near airports in the past, and those who had never lived near airports. Negative emotional feelings toward aircraft were greatest among respondents who had lived near airports in the past but no longer did. A possible explanation offered for this finding was that people currently living near airports might adapt to the situation by denying some of their negative feelings, which they might feel more free to express after they had moved away from the situation. Other techniques used in the pilot study are also described, including group interviews and a word association task.

Klaus, P. A.↗

Continued research on selected parameters to minimize community annoyance from airplane noise

Results from continued research on selected parameters to minimize community annoyance from airport noise are reported. First, a review of the initial work on this problem is presented. Then the research focus is expanded by considering multiobjective optimization approaches for this problem. A multiobjective optimization algorithm review from the open literature is presented. This is followed by the multiobjective mathematical formulation for the problem of interest. A discussion of the appropriate solution algorithm for the multiobjective formulation is conducted. Alternate formulations and associated solution algorithms are discussed and evaluated for this airport noise problem. Selected solution algorithms that have been implemented are then used to produce computational results for example airports. These computations involved finding the optimal operating scenario for a moderate size airport and a series of sensitivity analyses for a smaller example airport.

Frair, L.↗

An Operational Wake Vortex Sensor Using Pulsed Coherent Lidar

NASA and FAA initiated a program in 1994 to develop methods of setting spacings for landing aircraft by incorporating information on the real-time behavior of aircraft wake vortices. The current wake separation standards were developed in the 1970's when there was relatively light airport traffic and a logical break point by which to categorize aircraft. Today's continuum of aircraft sizes and increased airport packing densities have created a need for re-evaluation of wake separation standards. The goals of this effort are to ensure that separation standards are adequate for safety and to reduce aircraft spacing for higher airport capacity. Of particular interest are the different requirements for landing under visual flight conditions and instrument flight conditions. Over the years, greater spacings have been established for instrument flight than are allowed for visual flight conditions. Preliminary studies indicate that the airline industry would save considerable money and incur fewer passenger delays if a dynamic spacing system could reduce separations at major hubs during inclement weather to the levels routinely achieved under visual flight conditions. The sensor described herein may become part of this dynamic spacing system known as the "Aircraft VOrtex Spacing System" (AVOSS) that will interface with a future air traffic control system. AVOSS will use vortex behavioral models and short-term weather prediction models in order to predict vortex behavior sufficiently into the future to allow dynamic separation standards to be generated. The wake vortex sensor will periodically provide data to validate AVOSS predictions. Feasibility of measuring wake vortices using a lidar was first demonstrated using a continuous wave (CW) system from NASA Marshall Space Flight Sensor and tested at the Volpe National Transportation Systems Center's wake vortex test site at JFK International Airport. Other applications of CW lidar for wake vortex measurement have been made more recently, including a system developed by the MIT Lincoln Laboratory. This lidar has been used for detailed measurements of wake vortex velocities in support of wake vortex model validation. The first measurements of wake vortices using a pulsed, lidar were made by Coherent Technologies, Inc. (CTI) using a 2 micron solid-state, flashlamp-pumped system operating at 5 Hz. This system was first deployed at Denver's Stapleton Airport. Pulsed lidar has been selected as the baseline technology for an operational sensor due to its longer range capability.

Barker, Ben C., Jr.↗

Automated Traffic Management System and Method

A data management system and method that enables acquisition, integration, and management of real-time data generated at different rates, by multiple heterogeneous incompatible data sources. The system achieves this functionality by using an expert system to fuse data from a variety of airline, airport operations, ramp control, and air traffic control tower sources, to establish and update reference data values for every aircraft surface operation. The system may be configured as a real-time airport surface traffic management system (TMS) that electronically interconnects air traffic control, airline data, and airport operations data to facilitate information sharing and improve taxi queuing. In the TMS operational mode, empirical data shows substantial benefits in ramp operations for airlines, reducing departure taxi times by about one minute per aircraft in operational use, translating as $12 to $15 million per year savings to airlines at the Atlanta, Georgia airport. The data management system and method may also be used for scheduling the movement of multiple vehicles in other applications, such as marine vessels in harbors and ports, trucks or railroad cars in ports or shipping yards, and railroad cars in switching yards. Finally, the data management system and method may be used for managing containers at a shipping dock, stock on a factory floor or in a warehouse, or as a training tool for improving situational awareness of FAA tower controllers, ramp and airport operators, or commercial airline personnel in airfield surface operations.

Glass, Brian J.↗

Virtual Planning at Work: A Tour of NASA Future Flight Central

FutureFlight Central will permit integration of tomorrow's technologies in a risk-free simulation of any airport, airfield, and tower cab environment. The facility provides an opportunity for airlines to mitigate passenger delays by fine tuning airport hub operations, gate management and ramp movement procedures. It also allows airport managers an opportunity to study effects of various improvements at their airports. Finally, it enables air traffic controllers to provide feedback and to become familiar with new airport operations and technologies before final installation.

McClenahen, Jim↗

Wake-Vortex Separation Distances when Flight-Path Corridors are Constrained

Since the vortex wakes of large transport aircraft can pose a hazard to smaller following aircraft during landing and takeoff operations, certain separation guidelines are followed while aircraft are in the approach and departure corridors at airports. These guidelines reduce the capacity of airports because the separation distances are larger than other airport factors require. This paper studies the effect that a decrease in the size of the cross-section of the flight corridors for air traffic control would have on the wake-vortex separation guidelines; e.g., when the Global Positioning System (GPS) is implemented for air traffic control. It is first shown why smaller flight corridors permit reduced spacings at airports. Several arrangements of smaller flight corridors are then presented to illustrate how differing atmospheric and airport conditions can be accommodated. These considerations indicate that a reduction is then permissible in the wake-vortex spacings while still retaining the same or an improved degree of safety.

Rossow, Vernon J.↗

On Use of Global Positioning Technology for Solution of Wake Vortex Problem

Improved precision of the flight paths used by aircraft to approach and depart airports is becoming available when the Global Positioning System (GPS) is implemented at airports. An overview will be given of published information on how GPS precision guidance at airports can be used to avoid encounters with the lift-generated vortices shed by preceding aircraft during landing. It is pointed out that GPS provides two needed services to bring about improved avoidance capability. Firstly, GPS pseudolites are being built and installed at airports so that, when coupled with autopilot systems currently available on subsonic transport aircraft, the aircraft can make precision approaches for zero visibility landings. The same equipment can also be used for precision approaches for wake-vortex avoidance. Secondly, regular monitoring of atmospheric motions along the approach corridor can be obtained by use of GPS equipment on board aircraft that are in the flight corridors. That is, wind velocity is determined by use of GPS equipment to measure the ground speed of the aircraft and then combined with onboard instrumentation to measure the airspeed of the aircraft. The difference between the two measurements yields the wind velocity. When the measured wind velocities are transmitted to an airport ground station they are used to monitor whether air motions adverse for safety in the flight corridor are present. If any parts of the corridor are unsafe, the spacing of the aircraft, or the location of the flight corridor being used, is modified. It is estimated that the spacings between any combination of aircraft can then be safely reduced to a uniform 3 n. mi. Information to be presented is contained in an article published in the AIAA Journal of Aircraft, May-June 1996.

Rossow, Vernon J.↗

The Conference Proceedings of the 2001 Air Transport Research Society (ATRS) of the WCTR Society

The ATRS held its 5th Annual conference at the City University of Hong Kong Campus in July 2001. The conference was a success with nearly 140 participants including 70 presenters. Titles that comprise Volume 2 include: Intelligent Airport Gate Assignment System; A Study on the Effects of the Personality Compatibility to the Job Performance; ITS/CVO Application for Air cargo Transportation in Korea; An Airport as a Logistics and Economic Hub: The Case of Incheon International Airport; The Impact Of Aviation Safety over the Consumer's Behavior; The Integration of China and Taiwan Air Networks for Direct Air Cargo Services; Quality perception and carrier choice in Civil Aviation; Future Trends in Business Travel Decision Making; Cooperation Among German Airports in Europe; Inbound and Outbound Air Passenger Traffic Forecasting between the United States and Selected Asian countries; An Evaluation of Alternative Facilities for Airport Redevelopment using Fuzzy Linguistic Approach; Economic Analysis of Airline Alliances; The Aviation Cooperation between the two Koreas Preparing for the Reunification of the Peninsula; and A Study on the Air Transport Cooperation in Northeast Asia between China, Japan and Korea.

Lee, Yeong-Heok↗

Future Air Traffic Growth and Schedule Model User's Guide

The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

Kimmel, William M.↗

Future Air Traffic Growth and Schedule Model, Supplement

The Future Air Traffic Growth and Schedule Model was developed as an implementation of the Fratar algorithm to project future traffic flow between airports in a system and of then scheduling the additional flights to reflect current passenger time-of-travel preferences. The methodology produces an unconstrained future schedule from a current (or baseline) schedule and the airport operations growth rates. As an example of the use of the model, future schedules are projected for 2010 and 2022 for all flights arriving at, departing from, or flying between all continental United States airports that had commercial scheduled service for May 17, 2002. Inter-continental US traffic and airports are included and the traffic is also grown with the Fratar methodology to account for their arrivals and departures to the continental US airports. Input data sets derived from the Official Airline Guide (OAG) data and FAA Terminal Area Forecast (TAF) are included in the examples of the computer code execution.

Kimmel, William M.↗