Results for “surface surveillance”

NASA NTRS2017

Assessing Tactical Scheduler Options for Time-Based Surface Metering

NASA is committed to demonstrating a concept of integrated arrival, departure, and surface operations by 2020 under the Airspace Technology Demonstration 2 (ATD2) sub-project. This will be accomplished starting with a demonstration of flight specific time-based departure metering at Charlotte Douglass International Airport (CLT). ATD2 tactical metering capability is based on NASAs Spot And Runway Departure Advisor (SARDA) which has been tested successfully in human-in-the-loop simulations of CLT. SARDA makes use of surface surveillance data and surface modeling to estimate the earliest takeoff time for each flight active on the airport surface or ready for pushback from the gate. The system then schedules each flight to its assigned runway in order of earliest takeoff time and assigns a target pushback time, displayed to ramp controllers as an advisory gate hold time. The objective of this method of departure metering is to move as much delay as possible to the gate to minimize surface congestion and engine on-time, while keeping sufficient pressure on the runway to maintain throughput. This flight specific approached enables greater flight efficiency and predictability, facilitating trajectory-based operations and surface-airspace integration, which ATD2 aims to achieve.Throughout ATD2 project formulation and system development, researchers have continuously engaged with stakeholders and future users, uncovering key system requirements for tactical metering that SARDA did not address. The SARDA scheduler is updated every 10 seconds using real-time surface surveillance data to ensure the most up-to-date information is used to predict runway usage. However, rapid updates also open the potential for fluctuating advisories, which Ramp controllers at a busy airport like CLT find unacceptable. Therefore, ATD2 tactical metering requires that all advisories freeze once flights are ready so that Ramp controllers may communicate a single hold time when responding to pilot ready calls.

Zelinski, Shannon↗

NASA NTRS2002

Contributions to the AIAA Guidance, Navigation and Control Conference

This report contains six papers presented by the Lincoln Laboratory Air Traffic Control Systems Group at the American Institute of Aeronautics & Astronautics (AIAA) Guidance, Navigation and Control (GNC) conference on 6-9 August 2001 in Montreal, Canada. The work reported was sponsored by the NASA Advanced Air Transportation Technologies (AATT) program and the FAA Free Flight Phase 1 (FFP1) program. The papers are based on studies completed at Lincoln Laboratory in collaboration with staff at NASA Ames Research Center. These papers were presented in the Air Traffic Automation Session of the conference and fall into three major areas: Traffic Analysis & Benefits Studies, Weather/Automation Integration and Surface Surveillance. In the first area, a paper by Andrews & Robinson presents an analysis of the efficiency of runway operations at Dallas/Ft. Worth using a tool called PARO, and a paper by Welch, Andrews & Robinson presents a delay benefit results for the Final Approach Spacing Tool (FAST). In the second area, a paper by Campbell, et al describes a new weather distribution systems for the Center/TRACON Automation System (CTAS) that allows ingestion of multiple weather sources, and a paper by Vandevenne, Lloyd & Hogaboom describes the use of the NOAA Eta model as a backup wind data source for CTAS. Also in this area, a paper by Murphy & Campbell presents initial steps towards integrating weather impacted routes into FAST. In the third area, a paper by Welch, Bussolari and Atkins presents an initial operational concept for using surface surveillance to reduce taxi delays.

Campbell, S. D.↗

NASA NTRS2011

TPSAS-NF1676L-12441-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗

NASA NTRS2011

TPSAS-NF1676L-12263-DND

The increasing presence of airport surface surveillance technologies has spawned a strong interest in airport surface traffic management research; the vast majority has assumed that the airport’s runway configuration is known and constant. Tactical Runway Configuration Management (TRCM), one component of NASA’s System Oriented Runway Management concept, plans the airport configuration to optimize traffic efficiency for the forecast weather, traffic, and other factors. While planning runway configuration can provide benefit and is required by other automation concepts, larger benefits are possible by planning other airport configuration decisions, such as runway assignment policies, that are currently made manually by controllers. A laboratory prototype of the TRCM algorithm which selects optimal airport configuration schedules has been implemented and studied within a simulation environment. The presentation will describe simulation results for several airports, under various weather and traffic conditions. The sequence of airport configurations recommended by TRCM result in significantly less delay than the airport configurations that were actually used by controllers, illustrating both the potential benefit from airport configuration optimization and the ability of TRCM to provide effective airport configuration schedules. The application to several, distinct airports demonstrates the approach is capable of handling the differences between airports with a common algorithm, while providing decision support that respects the current procedures at those airports. Consequently, TRCM is able to be deployed to any airport within the current National Airspace System. The TRCM algorithmic approach is also extensible to future operational scenarios. NASA is in the process of transferring the initial TRCM technology to the FAA. Future research will extend the concept and algorithm to provide coordinated plans for metroplex airports and study NextGen applications.

Stephen Atkins↗

NASA NTRS2009

Surface Operations Systems Improve Airport Efficiency

With Small Business Innovation Research (SBIR) contracts from Ames Research Center, Mosaic ATM of Leesburg, Virginia created software to analyze surface operations at airports. Surface surveillance systems, which report locations every second for thousands of air and ground vehicles, generate massive amounts of data, making gathering and analyzing this information difficult. Mosaic?s Surface Operations Data Analysis and Adaptation (SODAA) tool is an off-line support tool that can analyze how well the airport surface operation is working and can help redesign procedures to improve operations. SODAA helps researchers pinpoint trends and correlations in vast amounts of recorded airport operations data.

Source record↗

NASA NTRS2016

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Safe and efficient surface operations↗

NASA NTRS1998

Integrated Airport Surface Operations

The current air traffic environment in airport terminal areas experiences substantial delays when weather conditions deteriorate to Instrument Meteorological Conditions (IMC). Research activity at NASA has culminated in the development, flight test and demonstration of a prototype Low Visibility Landing and Surface Operations (LVLASO) system. A NASA led industry team and the FAA developed the system which integrated airport surface surveillance systems, aeronautical data links, DGPS navigation, automation systems, and controller and flight deck displays. The LVLASO system was demonstrated at the Hartsfield-Atlanta International Airport using a Boeing 757-200 aircraft during August, 1997. This report documents the contractors role in this testing particularly in the area of data link and DGPS navigation.

Koczo, S.↗

NASA NTRS1999

NASA Low Visibility Landing and Surface Operations (LVLASO) Atlanta Demonstration: Surveillance Systems Performance Analysis

NASA conducted a series of flight experiments at Hartsfield Atlanta International Airport as part of the Low Visibility Landing and Surface Operations (LVLASO) Program. LVLASO is one of the subelements of the NASA Terminal Area Productivity (TAP) Program, which is focused on providing technology and operating procedures for achieving clear-weather airport capacity in instrument-weather conditions, while also improving safety. LVLASO is investigating various technologies to be applied to airport surface operations, including advanced flight deck displays and surveillance systems. The purpose of this report is to document the performance of the surveillance systems tested as part of the LVLASO flight experiment. There were three surveillance sensors tested: primary radar using Airport Surface Detection Equipment (ASDE-3) and the Airport Movement Area Safety System (AMASS), Multilateration using the Airport Surface Target Identification System (ATIDS), and Automatic Dependent Surveillance - Broadcast (ADS-B) operating at 1090 MHz. The performance was compared to the draft requirements of the ICAO Advanced Surface Movement Guidance and Control System (A-SMGCS). Performance parameters evaluated included coverage, position accuracy, and update rate. Each of the sensors was evaluated as a stand alone surveillance system.

Cassell, Rick↗

NASA NTRS2016

Methods for Determining Aircraft Surface State at Lesser-Equipped Airports

Tactical departure scheduling within a terminal airspace must accommodate a wide spectrum of surveillance and communication capabilities at multiple airports. The success of such a scheduler is highly dependent upon the knowledge of a departure's state while it is still on the surface. Airports within a common Terminal RAdar CONtrol (TRACON) airspace possess varying levels of surface surveillance infrastructure which directly impacts uncertainties in wheels-off times. Large airports have access to surface surveillance data, which is shared with the TRACON, while lesser-equipped airports still rely solely on controllers in Air Traffic Control Towers (Towers). Coordination between TRACON and Towers can be greatly enhanced when the TRACON controller has access to the surface surveillance and the associated decision-support tools at well-equipped airports. Similar coordination at lesser-equipped airports is still based on verbal communications. This paper investigates possible methods to reduce the uncertainty in wheels-off time predictions at the lesser-equipped airports through the novel use of Over-the-Air (OTA) data transmissions. We also discuss the methods and equipment used to collect sample data at lesser-equipped airports within a large US TRACON, as well as the data evaluation to determine if meaningful information can be extracted from it.

departure scheduling↗

NASA NTRS1975

Design definition study of NASA/Navy lift/cruise fan V/STOL aircraft. Volume 1: Summary report of Navy multimission aircraft

This report presents results of a study by the Rockwell International Corporation for the NASA Ames Research Center and the Naval Air Systems Command of promising Navy lift-cruise fan V/STOL aircraft for the 1980-1985 time period. The purpose of the study was to identify the likely technical and operating characteristics and technology requirements for the ultimate development of this type aircraft. The study focused on identifying aircraft individually optimized to perform the anti-submarine warfare, carrier onboard delivery, combat search and rescue, surveillance and surface attack missions, and a multi-purpose aircraft concept capable of performing all five missions at minimum total program cost. The configuration features the use of two 1.3 fan pressure ratio, single stage lift-cruise fans and three current design J97 gas generators with a high mounted high aspect ratio wing with winglets. The design missions can be performed at takeoff weights ranging from approximately 32,000 to 39,000 pounds. Top speed is 0.80 Mach number at sea level and 0.885 at altitude, Advanced composite structural technology and advanced subsystem concepts are employed. One basic fuselage design, with alternate bolt-in floor structures, meets all the mission requirements.

Robert L Cavage↗

NASA NTRS1993

Compact Robotic Vehicle

Radio-controlled microrover features light weight and agility. Miniature robotic vehicle, called Go-For, implements new fork-wheeled mobility concept to traverse extremely rough terrain. Weighs 4 kg and is 0.4 m long, climbs over obstacles as large as 60 percent of its length. Mobility concept applied to much larger vehicles. Demonstrates such applications as exploration of planetary surfaces, military surveillance, and assessing hazardous situations. Video camera on vehicle sends images to control station, where human supervisor chooses sequence of paths to traverse to reach locations of interest. For planetary exploration, spectrometer and seisometer on vehicle sends scientific data to control station, and onboard tools collect soil and rock samples. Terrestrial version equipped similarly to take samples in chemically and/or biologically contaminated areas.

Wilcox, Brian H.↗

NASA NTRS1998

Flight Demonstration of Integrated Airport Surface Movement Technologies

This document describes operations associated with a set of flight experiments and demonstrations using a Boeing-757-200 research aircraft as part of low visibility landing and surface operations (LVLASO) research activities. To support this experiment, the B-757 performed flight and taxi operations at the Atlanta Hartsfield International Airport in Atlanta, GA. The test aircraft was equipped with experimental displays that were designed to provide flight crews with sufficient information to enable safe, expedient surface operations in any weather condition down to a runway visual range of 300 feet. In addition to flight deck displays and supporting equipment onboard the B-757, there was also a ground-based component of the system that provided for ground controller inputs and surveillance of airport surface movements. Qualitative and quantitative results are discussed.

Young, Steven D.↗

NASA NTRS1998

Flight Testing of an Airport Surface Guidance, Navigation, and Control System

This document describes operations associated with a set of flight experiments and demonstrations using a Boeing-757-200 (B-757) research aircraft as part of low visibility landing and surface operations (LVLASO) research activities. To support this experiment, the B-757 performed flight and taxi operations at the Hartsfield-Atlanta International Airport (ATL) in Atlanta, GA. The B-757 was equipped with experimental displays that were designed to provide flight crews with sufficient information to enable safe, expedient surface operations in any weather condition down to a runway visual range (RVR) of 300 feet. In addition to flight deck displays and supporting equipment onboard the B-757, there was also a ground-based component of the system that provided for ground controller inputs and surveillance of airport surface movements. The integrated ground and airborne components resulted in a system that has the potential to significantly improve the safety and efficiency of airport surface movements particularly as weather conditions deteriorate. Several advanced technologies were employed to show the validity of the operational concept at a major airport facility, to validate flight simulation findings, and to assess each of the individual technologies performance in an airport environment. Results show that while the maturity of some of the technologies does not permit immediate implementation, the operational concept is valid and the performance is more than adequate in many areas.

Young, Steven D.↗

NASA NTRSDate not supplied

Introduction to Air Traffic Management

The presentation introduces students and faculty to air traffic management with focus on air traffic data for data-science. Starting with the common attributes of transportation systems — highway transportation, air transportation and data transportation, the initial set of slides discuss the purpose of data-science in air traffic management, reasons why air traffic management is challenging, and the multidisciplinary nature of air traffic management research. The history of flight from 1903 — Wright Flyer — to 1987 — formation of the National Air Traffic Controllers Association — is briefly discussed. The national airspace system is described in terms of airports in the U. S., air traffic control facilities (flight service stations, terminal, enroute and system command center), airspace geometry (sectors, airways and navaids), governing regulations and directives, airspace classification (Class A through G), special use airspace, visual flight rules and instrument flight rules. The contents of a flight-plan are described. Weather briefing is discussed. The surveillance equipment used for surface, terminal area and enroute are described, and the aircraft states obtained using the surveillance data are listed. Airline operations control functions — schedule development, flight planning, resource scheduling and flight following — are noted. Next, the roles and responsibilities of air traffic controllers and traffic flow managers are discussed. Separation standards and conflict resolution techniques are outlined. Finally, traffic flow management techniques are reviewed with an illustrative example.

Air Traffic Management↗

NASA NTRSDate not supplied

Introduction to Air Traffic Management

The presentation introduces students and faculty to air traffic management with focus on air traffic data for data-science. Starting with the common attributes of transportation systems — highway transportation, air transportation and data transportation, the initial set of slides discuss the purpose of data-science in air traffic management, reasons why air traffic management is challenging, and the multidisciplinary nature of air traffic management research. The history of flight from 1903 — Wright Flyer — to 1987 — formation of the National Air Traffic Controllers Association — is briefly discussed. The national airspace system is described in terms of airports in the U. S., air traffic control facilities (flight service stations, terminal, enroute and system command center), airspace geometry (sectors, airways and navaids), governing regulations and directives, airspace classification (Class A through G), special use airspace, visual flight rules and instrument flight rules. The contents of a flight-plan are described. Weather briefing is discussed. The surveillance equipment used for surface, terminal area and enroute are described, and the aircraft states obtained using the surveillance data are listed. Airline operations control functions — schedule development, flight planning, resource scheduling and flight following — are noted. Next, the roles and responsibilities of air traffic controllers and traffic flow managers are discussed. Separation standards and conflict resolution techniques are outlined. Finally, traffic flow management techniques are reviewed with an illustrative example.

Air Traffic Management↗

NASA NTRS2008

Effect of Surface Traffic Count on Taxi Time at Dallas-Fort Worth (DFW) International Airport

As the amount of air traffic increases over the years, most airports simply do not have the means of expanding to handle the intensified traffic on the surface that will ensue. Precise surveillance equipment and automation concepts, as well as advanced surface traffic algorithms are being developed to improve airport efficiency. These surface algorithms require inputs unique to each airport to ensure maximum efficiency, and minimal taxi delay. This study analyzes surface traffic at Dallas-Fort Worth International Airport (DFW) to determine the effect of the number of aircraft on the surface and the amount of stop and go situations they experience to the amount of additional taxi time encountered. If the surface capacity of an airport is known, minimal delay can be accomplished by limiting the number of taxiing aircraft to that capacity. This concept is related to highways, where traffic flow drastically decreases as more cars occupy the road. An attempt to minimize this effect on highways is seen with the use of metering lights at freeway on-ramps. Since the surface traffic at airports is highly regulated, and aircraft are less mobile on the ground, limiting the surface count to a certain number can greatly reduce the amount of additional taxi time encountered, as well as reduce hazardous emissions. This study will also find the regions of an airport that encounter the most additional taxi time when the number of aircraft in that area is increased. This could help surface traffic algorithms avoid congesting that area, or re-route aircraft to different runways when that area reaches its capacity. The relationship between the amount of stop and go situations an aircraft encounters and their effect on the taxi time of that aircraft will also be investigated. This will help to determine the effect of holding an aircraft on the taxiway as opposed to re-routing it. The lesser of the two should be used when developing surface traffic algorithms to further minimize the delay encountered. The fields investigated in this study include taxi time, the number of aircraft on the surface, the number of stop and go situations, and the time stopped for each aircraft. Taxi time is defined as spot to runway for departures, and runway to spot for arrivals. It does not include ramp area taxi time because the ramp area is controlled differently, and surface traffic schedulers do not currently incorporate them. Taxi time is found by finding the difference between take-off time (OFF) and spot crossing time for departures, and spot crossing time and landing time (ON) for arrivals. All surface data was either found directly using the Surface Operations Data Analysis and Adaptation (SODAA), a tool to analyze the Surface Management System (SMS) generated log files, or indirectly from SODAA using Matlab to derive values from SODAA data. The number of aircraft on the surface is found by looping through the ON times, OFF times, and spot times for each aircraft during a particular day. For each departure aircraft, surface counts are taken at its spot crossing and OFF time. The average of these two is used as the surface count for that aircraft. For arrivals, surface counts are taken at its ON time and its spot crossing time. The average of these two is used.

Kistler, Matthew Stephen↗

NASA NTRS1997

Airport Surface Movement Technologies: Atlanta Demonstrations Overview

A flight demonstration was conducted in August 1997 at the Hartsfield Atlanta (ATL) International Airport as part of low visibility landing and surface operations (LVLASO) research activities. This research was aimed at investigating technology to improve the safety and efficiency of aircraft movements on the surface during the operational phases of roll-out, turnoff, and taxi in any weather condition down to a runway visual range of 300 feet. The system tested at ATL was composed of airborne and ground-based components that were integrated to provide both the flight crew and controllers with supplemental information to enable safe, expedient surface operations. Experimental displays were installed on a Boeing 757-200 research aircraft in both headup and head-down formats. On the ground, an integrated system maintained surveillance of the airport surface and a controller interface provided routing and control instructions. While at ATL, the research aircraft performed a series of flight and taxi operations to show the validity of the operational concept at a major airport facility, to validate simulation findings, and to assess each of the individual technologies performance in an airport environment. The concept was demonstrated to over 100 visitors from the Federal Aviation Administration (FAA) and the aviation community. This paper gives an overview of the LVLASO system and ATL test activities.

Jones, Denise R.↗

NASA NTRS2005

Severe Weather Forecast Decision Aid

This report presents a 15-year climatological study of severe weather events and related severe weather atmospheric parameters. Data sources included local forecast rules, archived sounding data, Cloud-to-Ground Lightning Surveillance System (CGLSS) data, surface and upper air maps, and two severe weather event databases covering east-central Florida. The local forecast rules were used to set threat assessment thresholds for stability parameters that were derived from the sounding data. The severe weather events databases were used to identify days with reported severe weather and the CGLSS data was used to differentiate between lightning and non-lightning days. These data sets provided the foundation for analyzing the stability parameters and synoptic patterns that were used to develop an objective tool to aid in forecasting severe weather events. The period of record for the analysis was May - September, 1989 - 2003. The results indicate that there are certain synoptic patterns more prevalent on days with severe weather and some of the stability parameters are better predictors of severe weather days based on locally tuned threat values. The results also revealed the stability parameters that did not display any skill related to severe weather days. An interactive web-based Severe Weather Decision Aid was developed to assist the duty forecaster by providing a level of objective guidance based on the analysis of the stability parameters, CGLSS data, and synoptic-scale dynamics. The tool will be tested and evaluated during the 2005 warm season.

Bauman, William H., III↗