Search NASA⌕ Search

SEARCH · Search NASA

Results for “airport surface operations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Study of Future Communications Concepts and Technologies for the National Airspace System-Part III

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating current and anticipated wireless communications concepts and technologies that the National Airspace System (NAS) may need in the next 50 years. NASA has awarded three NASA Research Announcements (NAR) studies with the objective to determine the most promising candidate technologies for air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. This paper will present progress made in the studies and describe the communications challenges and opportunities that have been identified as part of the study. NASA's NextGen Concepts and Technology Development (CTD) Project integrates solutions for a safe, efficient and high-capacity airspace system through joint research efforts and partnerships with other government agencies. The CTD Project is one of two within NASA's Airspace Systems Program and is managed by the NASA Ames Research Center. Research within the CTD Project is in support the 2011 NASA Strategic Plan Sub-Goal 4.1: Develop innovative solutions and advanced technologies, through a balanced research portfolio, to improve current and future air transportation. The focus of CTD is on developing capabilities in traffic flow management, dynamic airspace configuration, separation assurance, super density operations and airport surface operations. Important to its research is the development of human/automation information requirements and decisionmaking guidelines for human-human and human-machine airportal decision-making. Airborne separation, oceanic intrail climb/descent and interval management applications depend on location and intent information of surrounding aircraft. ADS-B has been proposed to provide the information exchange, but other candidates such as satellite-based receivers, broadband or airborne internet, and cellular communications are possible candidate's.

Navigation↗
NASA NTRSDate not supplied

Runway Configuration Management with Offline Reinforcement Learning

Runway configuration management (RCM) is a challenging task, and it affects the efficiency of the National Airspace System (NAS) and airport surface operations significantly. Each airport, depending on the geometry, capacity, local climate patterns, etc. has multiple configurations for the runway usage for arriving and departing flights. Many factors such as the incoming/outgoing traffic load, wind direction and speed, convective weather, cloud ceiling and other environmental factors might affect the choice of a runway configuration at any point in time. However, other factors such as safety measures and regulations, noise abatement, capacity of each configuration, and preference of the air traffic controllers (ATCs) can also play a significant role in selecting the configuration. A sub-optimal selection of the runway configuration, or delay in making configuration changes might result in significant increase in taxi times for aircraft on the surface of the airport, fuel and energy use of the aircraft, and maintenance costs. It can also lead to safety concerns, such as an aircraft performing one or more go-arounds before being able to land. All these factors make RCM an extremely important and challenging decision-making process for the ATCs. The current state of practice sets the runway configuration by the ATCs based on relevant information available at the time including weather, traffic, noise abatement, safety bounds, etc. This makes the decision-making process subjective based on the accuracy of the available information and the bias in human decision making. Unfortunately, this approach yields poor results (e.g., significant delays) if the predicted outcomes are uncertain and their relative impact is not well understood. This is especially evident when the uncertainty increases the size of possible predicted outcomes (combinatorial explosion in possible scenarios) that cannot be handled by human reasoning. On the other hand, an automated approach based on machine intelligence can make use of historical data and search through all (or significant amount of) possible scenarios under uncertainty and make well-informed decisions.

Milad Memarzadeh↗
NASA NTRS2001

Concept of Operations for Commercial and Business Aircraft Synthetic Vision Systems

A concept of operations (CONOPS) for the Commercial and Business (CaB) aircraft synthetic vision systems (SVS) is described. The CaB SVS is expected to provide increased safety and operational benefits in normal and low visibility conditions. Providing operational benefits will promote SVS implementation in the Net, improve aviation safety, and assist in meeting the national aviation safety goal. SVS will enhance safety and enable consistent gate-to-gate aircraft operations in normal and low visibility conditions. The goal for developing SVS is to support operational minima as low as Category 3b in a variety of environments. For departure and ground operations, the SVS goal is to enable operations with a runway visual range of 300 feet. The system is an integrated display concept that provides a virtual visual environment. The SVS virtual visual environment is composed of three components: an enhanced intuitive view of the flight environment, hazard and obstacle defection and display, and precision navigation guidance. The virtual visual environment will support enhanced operations procedures during all phases of flight - ground operations, departure, en route, and arrival. The applications selected for emphasis in this document include low visibility departures and arrivals including parallel runway operations, and low visibility airport surface operations. These particular applications were selected because of significant potential benefits afforded by SVS.

Williams Daniel M.↗
NASA NTRS1997

The Taxiway Navigation and Situation Awareness (T-NASA) System

The goal of NASA's Terminal Area Productivity (TAP) Low-Visibility Landing and Surface Operations (LVLASO) subelement is to improve the efficiency of airport surface operations for commercial aircraft operating in weather conditions to Category IIIB while maintaining a high degree of safety. Currently, surface operations are one of the least technologically sophisticated components of the air transport system, being conducted in the 1990's with the same basic technology as in the 1930's. Pilots are given little or no explicit information about their current position, and routing information is limited to ATC communications and airport charts. In TAP/LVLASO, advanced technologies such as satellite navigation systems, digital data communications, advanced information presentation technology, and ground surveillance systems will be integrated into flight deck displays to enable expeditious and safe traffic movement on the airport surface. The cockpit display suite is called the T-NASA (Taxiway Navigation and Situation Awareness) System. This system has three integrated components: 1) Moving Map track-up airport surface display with own-ship, traffic and graphical route guidance 2) Scene-Linked Symbology - route/taxi information virtually projected via a Head-up Display (HUD) onto the forward scene; and, 3) 3-D Audio Ground Collision Avoidance and Navigation system - spatially-localized auditory traffic and navigation alerts. In the current paper, the design philosophy of the T-NASA system will be presented, and the T-NASA system display components described.

Foyle, David C.↗
NASA NTRS2007

Synthetic Vision Enhanced Surface Operations With Head-Worn Display for Commercial Aircraft

Experiments and flight tests have shown that airport surface operations can be enhanced by using synthetic vision and associated technologies, employed on a Head-Up Display (HUD) and head-down display electronic moving maps (EMM). Although HUD applications have shown the greatest potential operational improvements, the research noted that two major limitations during ground operations were its monochrome form and limited, fixed field-of-regard. A potential solution to these limitations may be the application of advanced Head Worn Displays (HWDs) particularly during low-visibility operations wherein surface movement is substantially limited because of the impaired vision of pilots and air traffic controllers. The paper describes the results of ground simulation experiments conducted at the NASA Langley Research Center. The results of the experiments showed that the fully integrated HWD concept provided significantly improved path performance compared to using paper charts alone. When comparing the HWD and HUD concepts, there were no statistically-significant differences in path performance or subjective ratings of situation awareness and workload. Implications and directions for future research are described.

Arthur, Jarvis J., III↗
NASA NTRS2019

Prediction of Pushback Times and Ramp Taxi Times for Departures at Charlotte Airport

When optimizing the takeoff sequence and schedule for departures at busy airports, it is important to accurately predict the taxi times from gate to runway because those are used to calculate the earliest possible takeoff times. Several airports like Charlotte Douglas International Airport show relatively long taxi times inside the ramp area with large variations, with respect to the travel times in the airport movement area. Also, the pushback process times have not been accurately modeled so far mainly due to the lack of accurate data. The recent deployment of the integrated arrival, departure, and surface traffic management system at Charlotte airport by NASA enables more accurate flight data in the airport surface operations to be obtained. Taking advantage of this system, actual pushback times and ramp taxi times from historical flight data at this airport are analyzed. Based on the analysis, a simple, data-driven prediction model is introduced for estimating pushback times and ramp transit times of individual departure flights. To evaluate the performance of this prediction model, several machine learning techniques are also applied to the same dataset. The prediction results show that the data-driven prediction model is as good as the machine learning algorithms when comparing various prediction performance metrics.

airport surface operations↗
NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗
NASA NTRS2015

SOSS User Guide

This User Guide describes SOSS (Surface Operations Simulator and Scheduler) software build and graphic user interface. SOSS is a desktop application that simulates airport surface operations in fast time using traffic management algorithms. It moves aircraft on the airport surface based on information provided by scheduling algorithm prototypes, monitors separation violation and scheduling conformance, and produces scheduling algorithm performance data.

air traffic control↗
NASA NTRS2018

Airspace Technology Demonstration 2 (ATD-2) Phase 1 Concept of Use (ConUse)

This document presents an operational Concept of Use (ConUse) for the Phase 1 Baseline Integrated Arrival, Departure, and Surface (IADS) prototype system of NASA's Airspace Technology Demonstration 2 (ATD-2) sub-project, which began demonstration in 2017 at Charlotte Douglas International Airport (CLT). NASA is developing the IADS system under the ATD-2 sub-project in coordination with the Federal Aviation Administration (FAA) and aviation industry partners. The primary goal of ATD-2 sub-project is to improve the predictability and the operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 effort is a five-year research activity through 2020. The initial phase of the ATD-2 sub-project, which is the focus of this document, will demonstrate the Phase 1 Baseline IADS capability at CLT in 2017. The Phase 1 Baseline IADS capabilities of the ATD-2 sub-project consists of: (a) Strategic and tactical surface scheduling to improve efficiency and predictability of airport surface operations, (b) Tactical departure scheduling to enhance merging of departures into overhead traffic streams via accurate predictions of takeoff times and automated coordination between the Airport Traffic Control Tower (ATCT, or Tower) and the Air Route Traffic Control Center (ARTCC, or Center), (c) Improvements in departure surface demand predictions in Time Based Flow Management (TBFM), (d) A prototype Electronic Flight Data (EFD) system provided by the FAA via the Terminal Flight Data Manager (TFDM) early implementation effort, and (e) Improved situational awareness and demand predictions through integration with the Traffic Flow Management System (TFMS), TBFM, and TFDM (3Ts) for electronic data integration and exchange, and an on-screen dashboard displaying pertinent analytics in real-time. The surface scheduling and metering element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 Upon successful demonstration of the Phase 1 Baseline IADS capability, follow-on demonstrations of the matured IADS traffic management capabilities will be conducted in the 2018-2020 timeframe. At the end of each phase of the demonstrations, NASA will transfer the ATD-2 sub-project technology to the FAA and industry partners.

integrated arrival↗
NASA NTRS2011

Simulator Evaluation of Runway Incursion Prevention Technology for General Aviation Operations

A Runway Incursion Prevention System (RIPS) has been designed under previous research to enhance airport surface operations situation awareness and provide cockpit alerts of potential runway conflict, during transport aircraft category operations, in order to prevent runway incidents while also improving operations capability. This study investigated an adaptation of RIPS for low-end general aviation operations using a fixed-based simulator at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC). The purpose of the study was to evaluate modified RIPS aircraft-based incursion detection algorithms and associated alerting and airport surface display concepts for low-end general aviation operations. This paper gives an overview of the system, simulation study, and test results.

Jones, Denise R.↗
NASA NTRS2007

Design and Testing of an Unlimited Field-of-regard Synthetic Vision Head-worn Display for Commercial Aircraft Surface Operations

Experiments and flight tests have shown that a Head-Up Display (HUD) and a head-down, electronic moving map (EMM) can be enhanced with Synthetic Vision for airport surface operations. While great success in ground operations was demonstrated with a HUD, the research noted that two major HUD limitations during ground operations were their monochrome form and limited, fixed field of regard. A potential solution to these limitations found with HUDs may be emerging Head Worn Displays (HWDs). HWDs are small, lightweight full color display devices that may be worn without significant encumbrance to the user. By coupling the HWD with a head tracker, unlimited field-of-regard may be realized for commercial aviation applications. In the proposed paper, the results of two ground simulation experiments conducted at NASA Langley are summarized. The experiments evaluated the efficacy of head-worn display applications of Synthetic Vision and Enhanced Vision technology to enhance transport aircraft surface operations. The two studies tested a combined six display concepts: (1) paper charts with existing cockpit displays, (2) baseline consisting of existing cockpit displays including a Class III electronic flight bag display of the airport surface; (3) an advanced baseline that also included displayed traffic and routing information, (4) a modified version of a HUD and EMM display demonstrated in previous research; (5) an unlimited field-of-regard, full color, head-tracked HWD with a conformal 3-D synthetic vision surface view; and (6) a fully integrated HWD concept. The fully integrated HWD concept is a head-tracked, color, unlimited field-of-regard concept that provides a 3-D conformal synthetic view of the airport surface integrated with advanced taxi route clearance, taxi precision guidance, and data-link capability. The results of the experiments showed that the fully integrated HWD provided greater path performance compared to using paper charts alone. Further, when comparing the HWD with the HUD concept, there were no differences in path performance. In addition, the HWD and HUD concepts were rated via paired-comparisons the same in terms of situational awareness and workload. However, there were over twice as many taxi incursion events with the HUD than the HWD.

Arthur, Jarvis J., III↗
NASA NTRS2008

Head-Worn Display Concepts for Surface Operations for Commerical Aircraft

Experiments and flight tests have shown that a Head-Up Display (HUD) and a head-down electronic moving map (EMM) can be enhanced with Synthetic Vision for airport surface operations. While great success in ground operations was demonstrated with a HUD, the research noted that two major HUD limitations during ground operations were its monochrome form and limited, fixed field-of-regard. A potential solution to these limitations found with HUDs may be emerging with Head Worn Displays (HWDs). HWDs are small display devices that may be worn without significant encumbrance to the user. By coupling the HWD with a head tracker, unlimited field-of-regard may be realized. The results of three ground simulation experiments conducted at NASA Langley Research Center are summarized. The experiments evaluated the efficacy of head-worn display applications of Synthetic Vision and Enhanced Vision technology to improve transport aircraft surface operations. The results of the experiments showed that the fully integrated HWD provided greater pilot performance with respect to staying on the path compared to using paper charts alone. Further, when comparing the HWD with the HUD concept, there were no differences in path performance. In addition, the HWD and HUD concepts were rated via paired-comparisons the same in terms of situation awareness and workload.

Arthur, Jarvis J., III↗
NASA NTRS2019

Prediction of Pushback Times and Ramp Taxi Times for Departures at Charlotte Airport

When optimizing the takeoff sequence and schedule for departures at busy airports, it is important to accurately predict the taxi times from gate to runway because those are used to calculate the earliest possible takeoff times. Several airports like Charlotte Douglas International Airport show relatively long taxi times inside the ramp area with large variations, with respect to the travel times in the airport movement area. Also, the pushback process times have not been accurately modeled so far mainly due to the lack of accurate data. The recent deployment of the integrated arrival, departure, and surface traffic management system at Charlotte airport by NASA enables more accurate flight data in the airport surface operations to be obtained. Taking advantage of this system, actual pushback times and ramp taxi times from historical flight data at this airport are analyzed. Based on the analysis, a simple, data-driven prediction model is introduced for estimating pushback times and ramp transit times of individual departure flights. To evaluate the performance of this prediction model, several machine learning techniques are also applied to the same dataset. The prediction results show that the data-driven prediction model is as good as the machine learning algorithms when comparing various prediction performance metrics.

Lee, Hanbong↗
NASA NTRS2018

Operational Impact of the Baseline Integrated Arrival, Departure and Surface System Field Demonstration

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA (Federal Aviation Administration) and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

air traffic optimization↗
NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗
NASA NTRSDate not supplied

ATD-2 Digital Services / DIP

The path to NAS-wide implementation for ATD-2 multi-airport IADS is as a digital service for flight operators that builds on and supplements FAA TBO investments. This session will focus on a suite of Machine Learning (ML) services the ATD-2 team developed to model airport surface operations. The approach used to leverage SWIM data sets will be described and a preliminary analysis of ML model accuracy will be presented. NASA’s plans to build on this work under the ATM-X Digital Information Platform (DIP) sub-project will be discussed.

ATD TIM, ATD-2 Digital Services, DIP↗
NASA NTRS2011

Characterization of Tactical Departure Scheduling in the National Airspace System

This paper discusses and analyzes current day utilization and performance of the tactical departure scheduling process in the National Airspace System (NAS) to understand the benefits in improving this process. The analysis used operational air traffic data from over 1,082,000 flights during the month of January, 2011. Specific metrics included the frequency of tactical departure scheduling, site specific variances in the technology's utilization, departure time prediction compliance used in the tactical scheduling process and the performance with which the current system can predict the airborne slot that aircraft are being scheduled into from the airport surface. Operational data analysis described in this paper indicates significant room for improvement exists in the current system primarily in the area of reduced departure time prediction uncertainty. Results indicate that a significant number of tactically scheduled aircraft did not meet their scheduled departure slot due to departure time uncertainty. In addition to missed slots, the operational data analysis identified increased controller workload associated with tactical departures which were subject to traffic management manual re-scheduling or controller swaps. An analysis of achievable levels of departure time prediction accuracy as obtained by a new integrated surface and tactical scheduling tool is provided to assess the benefit it may provide as a solution to the identified shortfalls. A list of NAS facilities which are likely to receive the greatest benefit from the integrated surface and tactical scheduling technology are provided.

Capps, Alan↗
NASA NTRS2001

Aviation System Capacity Program Terminal Area Productivity Project: Ground and Airborne Technologies

Ground and airborne technologies were developed in the Terminal Area Productivity (TAP) project for increasing throughput at major airports by safely maintaining good-weather operating capacity during bad weather. Methods were demonstrated for accurately predicting vortices to prevent wake-turbulence encounters and to reduce in-trail separation requirements for aircraft approaching the same runway for landing. Technology was demonstrated that safely enabled independent simultaneous approaches in poor weather conditions to parallel runways spaced less than 3,400 ft apart. Guidance, control, and situation-awareness systems were developed to reduce congestion in airport surface operations resulting from the increased throughput, particularly during night and instrument meteorological conditions (IMC). These systems decreased runway occupancy time by safely and smoothly decelerating the aircraft, increasing taxi speed, and safely steering the aircraft off the runway. Simulations were performed in which optimal trajectories were determined by air traffic control (ATC) and communicated to flight crews by means of Center TRACON Automation System/Flight Management System (CTASFMS) automation to reduce flight delays, increase throughput, and ensure flight safety.

Giulianetti, Demo J.↗