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The present research investigates characteristics exhibited in pilot convective weather decision making in en route airspace. In a part-task study, pilots performed weather avoidance under various encounter scenarios. Results showed that the margins of safety that pilots maintain from storms are as fluid as deviation decisions themselves.
This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices
This paper presents an overview of the third major revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 11 (ASTAR11). This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required time-of-arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft.
This requirements framework document is designed to support the capture of requirements and capabilities for state-of-the-art trajectory predictors (TPs). This framework has been developed to assist TP experts in capturing a clear, consistent, and cross-comparable set of requirements and capabilities. The goal is to capture capabilities (types of trajectories that can be built), functional requirements (including inputs and outputs), non-functional requirements (including prediction accuracy and computational performance), approaches for constraint relaxation, and input uncertainties. The sections of this framework are based on the Common Trajectory Predictor structure developed by the FAA/Eurocontrol Cooperative R&D Action Plan 16 Committee on Common Trajectory Prediction. It is assumed that the reader is familiar with the Common TP Structure.1 This initial draft is intended as a first cut capture of the En Route TS Capabilities and Requirements. As such, it contains many annotations indicating possible logic errors in the CTAS code or in the description provided. It is intended to work out the details of the annotations with NASA and to update this document at a later time.
Delays caused by uncertainty in weather forecasts can be reduced by improving traffic flow management decisions. This paper presents a methodology for traffic flow management under uncertainty in convective weather forecasts. An algorithm for assigning departure delays and reroutes to aircraft is presented. Departure delay and route assignment are executed at multiple stages, during which, updated weather forecasts and flight schedules are used. At each stage, weather forecasts up to a certain look-ahead time are treated as deterministic and flight scheduling is done to mitigate the impact of weather on four-dimensional flight trajectories. Uncertainty in weather forecasts during departure scheduling results in tactical airborne holding of flights. The amount of airborne holding depends on the accuracy of forecasts as well as the look-ahead time included in the departure scheduling. The weather forecast look-ahead time is varied systematically within the experiments performed in this paper to analyze its effect on flight delays. Based on the results, longer look-ahead times cause higher departure delays and additional flying time due to reroutes. However, the amount of airborne holding necessary to prevent weather incursions reduces when the forecast look-ahead times are higher. For the chosen day of traffic and weather, setting the look-ahead time to 90 minutes yields the lowest total delay cost.
This document describes an algorithm for the generation of a four dimensional trajectory. Input data for this algorithm are similar to an augmented Standard Terminal Arrival (STAR) with the augmentation in the form of altitude or speed crossing restrictions at waypoints on the route. This version of the algorithm accommodates constant radius turns and cruise altitude waypoints with calibrated airspeed, versus Mach, constraints. The algorithm calculates the altitude, speed, along path distance, and along path time for each waypoint. Wind data at each of these waypoints are also used for the calculation of ground speed and turn radius.
This paper presents an overview of the fifth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 12 (ASTAR12). This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of- arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm includes a ground speed feedback term to compensate for slower than expected traffic aircraft speeds based on the accepted air traffic control tendency to slow aircraft below the nominal arrival speeds when they are farther from the airport.
NASA's Air Traffic Management Technology Demonstration-1 (ATD-1) will operationally demonstrate the feasibility of efficient arrival operations combining ground-based and airborne NASA technologies. The ATD-1 integrated system consists of the Traffic Management Advisor with Terminal Metering which generates precise time-based schedules to the runway and merge points; Controller Managed Spacing decision support tools which provide controllers with speed advisories and other information needed to meet the schedule; and Flight deck-based Interval Management avionics and procedures which allow flight crews to adjust their speed to achieve precise relative spacing. Initial studies identified air-ground challenges related to the integration of these three scheduling and spacing technologies, and NASA's airborne spacing algorithm was modified to address some of these challenges. The Research and Procedural Testing of Routes human-in-the-loop experiment was then conducted to assess the performance of the new spacing algorithm. The results of this experiment indicate that the algorithm performed as designed, and the pilot participants found the airborne spacing concept, air-ground procedures, and crew interface to be acceptable. However, the researchers concluded that the data revealed issues with the frequency of speed changes and speed reversals.
This paper presents an overview of the sixth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm adds the state-based capability in support of evolving industry standards relating to airborne self-spacing.
This paper presents an overview of the seventh revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This paper supersedes the previous documentation and presents a modification to the algorithm referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm adds the state-based capability in support of evolving industry standards relating to airborne self-spacing.
There is an overwhelming desire to create and enhance communication mechanisms between entities that operate within the National Airspace System. Furthermore, airlines are always extremely interested in increasing the efficiency of their flights. An innovative system prototype was developed and tested that improves collaborative decision making without modifying existing infrastructure or operational procedures within the current Air Traffic Management System. This system enables collaboration between flight crew and airline dispatchers to share and assess optimized flight routes through an Internet connection. Using a sophisticated medium-fidelity flight simulation environment, a rapid-prototyping development, and a unified modeling language, the software was designed to ensure reliability and scalability for future growth and applications. Ensuring safety and security were primary design goals, therefore the software does not interact or interfere with major flight control or safety systems. The system prototype demonstrated an unprecedented use of in-flight Internet to facilitate effective communication with Airline Operations Centers, which may contribute to increased flight efficiency for airlines.
Today's air traffic control system has reached a limit to the number of aircraft that can be safely managed at the same time. This air traffic capacity bottleneck is a critical problem along the path to modernization for air transportation. The design of the next separation assurance system to address this problem is a cornerstone of air traffic management research today. This report reviews recent work by NASA and others in the areas of function allocation and en route separation assurance. This includes: separation assurance algorithms and technology prototypes; concepts of operations and designs for advanced separation assurance systems; and specific investigations into air-ground and human-automation function allocation.
Within the framework of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project phase 2 (ALMIP-2), this study evaluates the water balance simulated by the Interactions between Soil, Biosphere, and Atmosphere (ISBA) over the upper Oum River basin, in Benin, using a mesoscale river routing scheme (RRS). The RRS is based on the nonlinear Muskingum Cunge method coupled with two linear reservoirs that simulate the time delay of both surface runoff and base flow that are produced by land surface models. On the basis of the evidence of a deep water-table recharge in that region,a reservoir representing the deep-water infiltration (DWI) is introduced. The hydrological processes of the basin are simulated for the 2005-08 AMMA field campaign period during which rainfall and stream flow data were intensively collected over the study area. Optimal RRS parameter sets were determined for three optimization experiments that were performed using daily stream flow at five gauges within the basin. Results demonstrate that the RRS simulates stream flow at all gauges with relative errors varying from -22% to 3% and Nash-Sutcliffe coefficients varying from 0.62 to 0.90. DWI varies from 24% to 67% of the base flow as a function of the sub-basin. The relatively simple reservoir DWI approach is quite robust, and further improvements would likely necessitate more complex solutions (e.g., considering seasonality and soil type in ISBA); thus, such modifications are recommended for future studies. Although the evaluation shows that the simulated stream flows are generally satisfactory, further field investigations are necessary to confirm some of the model assumptions.
This paper presents an overview of the eighth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This paper supersedes the previous documentation and presents a modification to the algorithm referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval with another aircraft. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm supports the evolving industry standards relating to airborne self-spacing.
The Traffic Aware Planner (TAP), developed for NASA Langley Research Center to support the Traffic Aware Strategic Aircrew Requests (TASAR) project, is a flight-efficiency software application developed for an Electronic Flight Bag (EFB). Tested in two flight trials and planned for operational testing by two commercial airlines, TAP is a real-time trajectory optimization application that leverages connectivity with onboard avionics and broadband Internet sources to compute and recommend route modifications to flight crews to improve fuel and time performance. The application utilizes a wide range of data, including Automatic Dependent Surveillance Broadcast (ADS-B) traffic, Flight Management System (FMS) guidance and intent, on-board sensors, published winds and weather, and Special Use Airspace (SUA) schedules. This paper discusses the challenges of developing and deploying TAP to various EFB platforms, our solutions to some of these challenges, and lessons learned, to assist commercial software developers and hardware manufacturers in their efforts to implement and extend TAP functionality in their environments. EFB applications (such as TAP) typically access avionics data via an ARINC 834 Simple Text Avionics Protocol (STAP) server hosted by an Aircraft Interface Device (AID) or other installed hardware. While the protocol is standardized, the data sources, content, and transmission rates can vary from aircraft to aircraft. Additionally, the method of communicating with the AID may vary depending on EFB hardware and/or the availability of onboard networking services, such as Ethernet, WIFI, Bluetooth, or other mechanisms. EFBs with portable and installed components can be implemented using a variety of operating systems, and cockpits are increasingly incorporating tablet-based technologies, further expanding the number of platforms the application may need to support. Supporting multiple EFB platforms, AIDs, avionics datasets, and user interfaces presents a challenge for software developers and the management of their code baselines. Maintaining multiple baselines to support all deployment targets can be extremely cumbersome and expensive. Certification also needs to be considered when developing the application. Regardless of whether the software is itself destined to be certified, data requirements in support of the application and user interface elements may introduce certification requirements for EFB manufacturers and the airlines. The example of TAP, the challenges faced, solutions implemented, and lessons learned will give EFB application and hardware developers insight into future potential requirements in deploying TAP or similar flight-deck EFB applications.
A fast time simulation was conducted to test the detect and avoid Well Clear definition designed for en route use when an unmanned aircraft (UA) is approaching the landing pattern of the terminal area. Measures focused on were loss of well clear and alerts intended to help the pilot avoid loss of well clear. Data indicated warning-level alerts will occur outside the typical Class D airspace which may prevent the UA from normal operations in the terminal airspace. Other aircraft on 45o entry could result in “nuisance” alerts which may also prevent the UA from normal operations in the terminal airspace. However, eliminating horizontal proximity (τmod) has the potential to increase “nuisance” alerts on the 45o entry and downwind legs. Overall, this suggests that a more stringent definition of Well Clear may be advisable in the landing pattern of the terminal area.
Concept overview and status for the ATD-3 (Air Traffic Management Technology Demonstration-3) Dynamic Routes for Arrivals in Weather (ATD-3 DRAW) project.
The Airborne Spacing for Terminal Arrival Routes (ASTAR) Flight Test was conducted by the NASA Air Traffic Management Technology Demonstration – 1 (ATD- 1) project to demonstrate the use of NASA’s ASTAR algorithm beyond a simulated environment and assess the operational risks of performing a multi-aircraft flight test of Flight-deck Interval Management (FIM). Utilizing contemporary tools of the Federal Aviation Administration’s Next Generation Air Transportation System (NextGen) such as ADS-B, the ASTAR algorithm calculated speeds that the flight crew flew to achieve a precise spacing interval behind another aircraft at the final approach fix. Airspeed commands issued by the algorithm were flown by the flight crew of the FIM-equipped aircraft to achieve or maintain an assigned spacing goal from a target vehicle. The ASTAR algorithm was integrated with the Boeing supplied B-787 ecoDemonstrator aircraft, and five flight trials were conducted as a joint effort between NASA and Boeing on December 12, 2014. Initial results indicated arrival times within several seconds of accuracy of the planned termination point between two aircraft performing FIM in a real world environment. This flight test opened the way for the much more expansive ATD-1 Avionics Phase II flight test which occurred in early 2017. The flight trials under Phase II preceded further testing by the community in preparation for inclusion of the Interval Management concept as a part of the NextGen environment.