Results for “Scheduling Service” — Page 2

NASA NTRS1991

Using C to build a satellite scheduling expert system: Examples from the Explorer Platform planning system

A C-based artificial intelligence (AI) development effort which is based on a software tools approach is discussed with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching, and blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) Shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May of 1987 and will be used for operations scheduling of the Explorer Platform in Nov. of 1991.

Mclean, David R.↗

NASA NTRS2019

Cognitive Communications for NASA Space Systems

The growing complexity of spacecraft constellations, communication relay offerings, and mission architectures drives the need for the development of autonomous communication systems. NASA has traditionally launched single spacecraft missions that are served by the Space Communication and Navigation (SCaN) program. Operations on SCaN networks are typically scheduled weeks in advance, and often each asset serves a single user spacecraft at a time. Recent movement towards swarm missions could make the current approach unsustainable. Additionally, the integration of commercial communication service providers will substantially increase the data transfer options available to new missions. NASA science missions have found benefit in launching swarms of spacecraft, allowing coordinated simultaneous observations from different perspectives. Inter-spacecraft communication (mesh networking) is an enabler for this architecture, as are CubeSats that allow cost-effective provisioning of distributed mission assets. As more complex swarm missions launch, one challenge is coordinating communication within the swarm and choosing the appropriate mechanism for telemetry, tracking, control, and data services to and from Earth. Cognitive communications research conducted by SCaN aims to mitigate the increasing communication complexity for mission users by increasing the autonomy of links, networks, and service scheduling. By considering automation techniques including recent advances in artificial intelligence and machine learning, cognitive algorithms and related approaches enable increased mission science return, improved resource utilization for service provider networks, and resiliency in unpredictable or unplanned environments. The Cognitive Communications Project at the NASA Glenn Research Center develops applications of data-driven, non-deterministic methods to improve the autonomy of space communication. The project emphasizes development of decentralized space networks with artificial intelligence agents optimizing communication link throughput, data routing, and system-wide asset management. This paper discusses the objectives, approaches, and opportunities of the research to address growing needs of the space communications community.

Chelmins, David↗

NASA NTRS2019

Prototyping Operational Autonomy for Space Traffic Management

Current state of the art in Space Traffic Management (STM) relies on a handful of providers for surveillance and collision prediction, and manual coordination between operators. Neither is scalable to support the expected 10x increase in spacecraft population in less than 10 years, nor does it support automated manuever planning. We present a software prototype of an STM architecture based on open Application Programming Interfaces (APIs), drawing on previous work by NASA to develop an architecture for low-altitude Unmanned Aerial System Traffic Management. The STM architecture is designed to provide structure to the interactions between spacecraft operators, various regulatory bodies, and service suppliers, while maintaining flexibility of these interactions and the ability for new market participants to enter easily. Autonomy is an indispensable part of the proposed architecture in enabling efficient data sharing, coordination between STM participants and safe flight operations. Examples of autonomy within STM include syncing multiple non-authoritative catalogs of resident space objects, or determining which spacecraft maneuvers when preventing impending conjunctions between multiple spacecraft. The STM prototype is based on modern micro-service architecture adhering to OpenAPI standards and deployed in industry standard Docker containers, facilitating easy communication between different participants or services. The system architecture is designed to facilitate adding and replacing services with minimal disruption. We have implemented some example participant services (e.g. a space situational awareness provider/SSA, a conjunction assessment supplier/CAS, an automated maneuver advisor/AMA) within the prototype. Different services, with creative algorithms folded into then, can fulfil similar functional roles within the STM architecture by flexibly connecting to it using pre-defined APIs and data models, thereby lowering the barrier to entry of new players in the STM marketplace. We demonstrate the STM prototype on a multiple conjunction scenario with multiple maneuverable spacecraft, where an example CAS and AMA can recommend optimal maneuvers to the spacecraft operators, based on a predefined reward function. Such tools can intelligently search the space of potential collision avoidance maneuvers with varying parameters like lead time and propellant usage, optimize a customized reward function, and be implemented as a scheduling service within the STM architecture. The case study shows an example of autonomous maneuver planning is possible using the API-based framework. As satellite populations and predicted conjunctions increase, an STM architecture can facilitate seamless information exchange related to collision prediction and mitigation among various service applications on different platforms and servers. The availability of such an STM network also opens up new research topics on satellite maneuver planning, scheduling and negotiation across disjoint entities.

space traffic management↗

NASA NTRS2006

Projecting Future Scheduled Airline Demand, Schedules and NGATS Benefits Using TSAM

The Transportation Systems Analysis Model (TSAM) developed by Virginia Tech s Air Transportation Systems Lab and NASA Langley can provide detailed analysis of the effects on the demand for air travel of a full range of NASA and FAA aviation projects. TSAM has been used to project the passenger demand for very light jet (VLJ) air taxi service, scheduled airline demand growth and future schedules, Next Generation Air Transportation System (NGATS) benefits, and future passenger revenues for the Airport and Airway Trust Fund. TSAM can project the resulting demand when new vehicles and/or technology is inserted into the long distance (100 or more miles one-way) transportation system, as well as, changes in demand as a result of fare yield increases or decreases, airport transit times, scheduled flight times, ticket taxes, reductions or increases in flight delays, and so on. TSAM models all long distance travel in the contiguous U.S. and determines the mode choice of the traveler based on detailed trip costs, travel time, schedule frequency, purpose of the trip (business or non-business), and household income level of the traveler. Demand is modeled at the county level, with an airport choice module providing up to three airports as part of the mode choice. Future enplanements at airports can be projected for different scenarios. A Fratar algorithm and a schedule generator are applied to generate future flight schedules. This paper presents the application of TSAM to modeling future scheduled air passenger demand and resulting airline schedules, the impact of NGATS goals and objectives on passenger demand, along with projections for passenger fee receipts for several scenarios for the FAA Airport and Airway Trust Fund.

Dollyhigh, Samuel↗

NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗

NASA NTRS2021

Separation at Crossing Waypoints Under Wind Uncertainty in Urban Air Mobility

To enable high-density operations in major metropolitan areas, urban air mobility networks are anticipated to have air traffic management with higher levels of autonomy. To ensure that this type of autonomy is feasible, one of the critical steps from a safety and efficiency perspective is understanding various factors that affect the spatial separation between airborne flights and ensure that these factors can be managed. In terms of separation assurance and scheduling, an important real-world concern is that future states of aircraft cannot be perfectly predicted. The focus of this research paper is to understand how these prediction errors affect separation and scheduling services and to explore mitigation strategies to handle these errors. In this research, we have simulated these types of uncertainty by adding wind-prediction errors to trajectory predictions for separation. With these wind-prediction errors, we decompose the problem into two separate questions. First, using both simulation and analytical methods, we look at conflict-detection-only scenarios to understand how the wind errors affect required minimum temporal separation between crossing flights to ensure a specific spatial separation. Next, we study how trajectory errors effect conflict resolution, and we explore different combinations of scheduling and separation assurance to mitigate the effects of uncertainty between crossing flights. The conflict resolution algorithm aims to minimize necessary temporal separation between crossing flights under uncertainty, still ensuring safety-critical spatial separation. In summary, this research suggests that the required minimum temporal separation at a crossing waypoint is dependent on factors such as inbound crossing angle, the relative angle between wind direction and bearing of each route, wind magnitude, wind magnitude uncertainty, nominal cruise airspeed of aircraft, and look-ahead time of the conflict detection algorithm. This research also suggests that different combinations of scheduling and separation have different qualitative results. Using a combination of strategic, flow-based scheduling, tactical scheduling at crossings, speed control near crossing points, and separation management leads to a system that is insensitive to trajectory prediction errors with high throughput and flexibility for aircraft away from shared resources.

urban air mobility↗

NASA NTRS1999

STS-103 Crew Training

The Hubble Space Telescope (HST) team is preparing for NASA's third scheduled service call to Hubble. This mission, STS-103, will launch from Kennedy Space Center aboard the Space Shuttle Discovery. The seven flight crew members are Commander Curtis L. Brown, Pilot Scott J. Kelly, European Space Agency (ESA) astronaut Jean-Francois Clervoy who will join space walkers Steven L. Smith, C. Michael Foale, John M. Grunsfeld, and ESA astronaut Claude Nicollier. The objectives of the HST Third Servicing Mission (SM3A) are to replace the telescope's six gyroscopes, a Fine-Guidance Sensor, an S-Band Single Access Transmitter, a spare solid-state recorder and a high-voltage/temperature kit for protecting the batteries from overheating. In addition, the crew plans to install an advanced computer that is 20 times faster and has six times the memory of the current Hubble Space Telescope computer. To prepare for these extravehicular activities (EVAs), the SM3A astronauts participated in Crew Familiarization sessions with the actual SM3A flight hardware. During these sessions the crew spent long hours rehearsing their space walks in the Guidance Navigation Simulator and NBL (Neutral Buoyancy Laboratory). Using space gloves, flight Space Support Equipment (SSE), and Crew Aids and Tools (CATs), the astronauts trained with and verified flight orbital replacement unit (ORU) hardware. The crew worked with a number of trainers and simulators, such as the High Fidelity Mechanical Simulator, Guidance Navigation Simulator, System Engineering Simulator, the Aft Shroud Door Trainer, the Forward Shell/Light Shield Simulator, and the Support Systems Module Bay Doors Simulator. They also trained and verified the flight Orbital Replacement Unit Carrier (ORUC) and its ancillary hardware. Discovery's planned 10-day flight is scheduled to end with a night landing at Kennedy.

Source record↗

NASA NTRS1972

International Air Transport and Federal Policy

The Federal policy which establishes guidelines for future U.S. participation in the international air transportation industry is discussed. The policy issues discussed include the following: (1) aircraft hijacking, both foreign and domestic, (2) relationship of scheduled services and charter services, (3) capacity problems, and (4) rate regulation.

Binder, R. H.↗

NASA NTRS1973

Flight evaluation of two segment approaches for jet transport noise abatement

A 75 flight-hour operational evaluation was conducted with a representative four-engine fan-jet transport in a representative airport environment. The flight instrument systems were modified to automatically provide pilots with smooth and continuous pitch steering command information during two-segment approaches. Considering adverse weather, minimum ceiling and flight crew experience criteria, a transition initiation altitude of approximately 800 feet AFL would have broadest acceptance for initiating two-segment approach procedures in scheduled service. The profile defined by the system gave an upper glidepath of approximately 6 1/2 degrees. This was 1/2 degree greater than inserted into the area navigation system. The glidepath error is apparently due to an erroneous along-track, distance-to-altitude profile.

Rogers, R. A.↗

NASA NTRS1973

Noise measurements taken at LAX during operational evaluation of two-segment approaches in a 727-200 aircraft

A series of seven noise measurements were made each day over a period of fifteen days. The first and last flights each day were made by a specially instrumented 727-200 aircraft being used to evaluate the operational effectiveness of two-segment noise abatement approaches in scheduled service. Noise measurements were made to determine the noise reduction benefits of the two-segment approaches.

Tanner, C. S.↗

NASA NTRS1981

An automated system for global atmospheric sampling using B-747 airliners

The global air sampling program utilizes commercial aircrafts in scheduled service to measure atmospheric constituents. A fully automated system designed for the 747 aircraft is described. Airline operational constraints and data and control subsystems are treated. The overall program management, system monitoring, and data retrieval from four aircraft in global service is described.

Lew, K. Q.↗

NASA NTRS1984

Space station task force perspective

Space station planning quidelines; architecture; functions; preliminary mission data base; scope for international and commercial participation; schedules; servicing capability; technology development; and space station program interfaces are discussed.

Hicks, C.↗

NASA NTRS1995

TDRS MA phased-array antenna simulations

The NASA's Space Network (SN) nominal user services are prescheduled to allocate service type and required equipment to a user of the network. The availability of a resource for a given user is then communicated back to the user prior to requested service time. A proposed Demand Assignment Multiple Access (DAMA) system for NASA's SN to make it easier to allow a real time changes to add new user to the service schedule, is presented. The goals of the project are to improve the current operational modes by (1) reducing the support overhead required to maintain the overall scheduling requirements in this area; (2) allowing for more users to access the system especially those who traditionally have not considered SN access available to them; and (3) providing additional scheduling flexibility.

Caballero, Ruben↗

NASA NTRS1999

STS-103 Crew at Breakfast, Suiting, Departing O&C

The Hubble Space Telescope (HST) team is preparing for NASA's third scheduled service call to Hubble. This mission, STS-103, will launch from Kennedy Space Center aboard the Space Shuttle Discovery. The seven flight crew members for STS-103 are: Commander Curtis L. Brown (his sixth flight), Pilot Scott J. Kelly and European Space Agency (ESA) astronaut Jean-Francois Clervoy (his third flight) will join space walkers Steven L. Smith (his third flight), C. Michael Foale (his fifth flight), John M. Grunsfeld (his third flight) and ESA astronaut Claude Nicollier (his fourth flight). This current video presents a live footage of the seven STS-103 crewmembers eating breakfast, suiting, and departing the O&C (Operations and Checkout) before the 6:50 p.m. lift-off.

Source record↗

NASA NTRS2004

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.↗

NASA NTRS2004

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.↗

NASA NTRS2015

On-Demand Mobility (ODM) Technical Pathway: Enabling Ease of Use and Safety

On-demand mobility (ODM) through aviation refers to the ability to quickly and easily move people or equivalent cargo without delays introduced by lack of, or infrequently, scheduled service. A necessary attribute of ODM is that it be easy to use, requiring a minimum of special training, skills, or workload. Fully-autonomous vehicles would provide the ultimate in ease-of-use (EU) but are currently unproven for safety-critical applications outside of a few, situationally constrained applications (e.g. automated trains operating in segregated systems). Applied to aviation, the current and near-future state of the art of full-autonomy, may entail undesirable trade-offs such as very conservative operational margins resulting in reduced trip reliability and transportation utility. Furthermore, acceptance by potential users and regulatory authorities will be challenging without confidence in autonomous systems in developed in less critical, but still challenging applications. A question for the aviation community is how we can best develop practical ease-of-use for aircraft that are sized to carry a small number of passengers (e.g. 1-9) or equivalent cargo. Such development is unlikely to be a single event, but rather a managed, evolutionary process where responsibility and authority transitions from human to automation agents as operational experience is gained with increasingly intelligent systems. This talk presents a technology road map being developed at NASA Langley, as part of an overall strategy to foster ODM, for the development of ease-of-use for ODM aviation.

Goodrich, Ken↗

NASA NTRSDate not supplied

Spacecraft-Initiated Scheduling of Commercial Communications Services

We propose a software framework enabling a spacecraft in Earth orbit to schedule its own access to space communications services via ground stations and relay satellites. All operations are automated, without a human in the loop, allowing for highly responsive service to meet time-varying needs. We describe a modular software architecture allowing the framework to interface with the scheduling systems of several providers - both government and commercial. Specifically, we present the results of an experiment with Amazon Web Services (AWS) Ground Station, an operational commercial service provider. Proposed software executed scheduling of a ground station antenna with minimal lead time (less than 20 minutes before the start of a pass). During the contact AWS cloud infrastructure was used to demodulate, process, and distribute data products from an orbiting satellite. We believe this work demonstrates the framework's ability to interface with additional providers and potential to integrate more complex decision-making in the future to schedule optimal contacts.

Scheduling↗