The Future of Aviation: A Paradigm for Unmanned Aviation Systems and Urban Air Mobility
This presentation provides an overview of Unmanned Aircraft Systems Traffic Management (UTM) and the emerging aviation market for urban air mobility.
Mobility↗
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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.
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ASRS for Unmanned Aviation Systems
This presentation provides an overview of NASA's Aviation Safety Reporting System (ASRS) for Unmanned Aviation Systems / drones
Aviation Safety Reporting System↗
Identification of Human Factors in Unmanned Aviation Via Pilot Incident Reports
There is a need for incident data relevant to the operation of civilian unmanned aircraft systems (UAS) in the National Air Space (NAS). Currently, very limited incident and accident data are available from military sources, and the tightly-restricted civilian UAS industry has produced very few incident reports that could shed light on design issues relevant to human factors. An exploratory study is being conducted to examine the feasibility of collecting voluntary critical incident reports from UAS pilots, and using the information to identify areas where human factors guidelines will be of assistance. Experienced UAS pilots are participating in small focus groups in which they are prompted to describe critical incidents that either reveal a system flaw, or highlight a case where the human operator contributed to system resilience or mission success. The de-identified incidents are being analyzed to identify contributing factors, with a focus on design issues that either hindered or assisted the pilot in dealing with the incident. Preliminary findings will be described.
human factors↗
Unmanned Aviation Systems Models of the Radio Communications Links: Study Results - Appendices Annex 2. Volume 1 and Volume 2
This report describes the analysis of communications between the Control Station and an Unmanned Aircraft (UA) flying in the National Airspace System (NAS). This work is based on the RTCA SC-203 Operational Services and Environment Description (OSED). The OSED document seeks to characterize the highly different attributes of all UAs navigating the airspace and define their relationship to airspace users, air traffic services, and operating environments of the NAS. One goal of this report is to lead to the development of Minimum Aviation System Performance Standards for Control and Communications. This report takes the nine scenarios found in the OSED and analyzes the communication links.
Birr, Richard B.↗
Markov Decision Process based Trajectory Planning for UAVs under Uncertain Wind Conditions
In this paper we propose a Markov Decision Process (MDP) algorithm for path-planning of Unmanned Aviation Vehicles (UAVs) under varying wind conditions. Solutions to path-planning for UAVs are becoming increasingly necessary as autonomous UAVs continue to enter commercial and government spaces. Path-planning is inherently challenging, as UAVs needs to account for dynamically changing flying conditions such as weather, obstacle or no-fly zones, degraded vehicle health and off-nominal battery power consumption. Machine learning methods such as Markov Decision Process (MDPs) have the potential to revolutionize how vehicles navigate in such uncertain environments. Previous papers have demonstrated the use of MDPs to optimize UAV path-planning for energy consumption under time-varying wind distribution. In this study, UAV trajectories from a pre-determined waypoint to target cell, will be computed on a 7X7 grid environment by optimizing parameters for mission assurance and safety limits in addition to the energy consumption, and operation time. The UAV navigates the grid by taking actions to move in either of the eight cardinal and intercardinal directions, under constant thrust profile. The next state of the UAV is calculated by considering its action, transition probability, obstacle cells and the wind speed magnitude and direction. Both constant and stochastic wind will be considered in this paper, the parameters being extracted from real wind measurements in proximity to an experimental UAV flight. One of the studies to be demonstrated in this paper is that as the unmanned airspace gets more complex with multiple vehicles and environmental uncertainties, trade-offs between energy consumption, operation time, risk tolerance, and mission assurance needs to be made. Further, MDPs are capable of fast computation of UAV trajectories under varying wind, hence making them suitable for in-flight path planners.
decision-making↗
Secure Network-Centric Aviation Communication (SNAC)
The existing National Airspace System (NAS) communications capabilities are largely unsecured, are not designed for efficient use of spectrum and collectively are not capable of servicing the future needs of the NAS with the inclusion of new operators in Unmanned Aviation Systems (UAS) or On Demand Mobility (ODM). SNAC will provide a ubiquitous secure, network-based communications architecture that will provide new service capabilities and allow for the migration of current communications to SNAC over time. The necessary change in communication technologies to digital domains will allow for the adoption of security mechanisms, sharing of link technologies, large increase in spectrum utilization, new forms of resilience and redundancy and the possibly of spectrum reuse. SNAC consists of a long term open architectural approach with increasingly capable designs used to steer research and development and enable operating capabilities that run in parallel with current NAS systems.
Communications↗
Energy-Optimized Path Planning for Uas in Varying Winds Via Reinforcement Learning
In this paper we propose a reinforcement learning (RL) algorithm for path planning of Unmanned Aviation Vehicles (UAVs) under varying wind conditions. Solutions to UAV path planning problems are becoming increasingly necessary as autonomous UAVs continue to enter commercial and government spaces. Path-planning is inherently challenging, as UAVs need to account for dynamically changing flying conditions such as weather, obstacle or no-fly zones, degraded vehicle health, and off-nominal battery power consumption. Machine learning methods such as reinforcement learning (RL) have the potential to revolutionize how vehicles navigate in such uncertain environments. In this study, we compute UAV trajectories from a pre-determined starting position to a target cell within a 7X7 grid environment by optimizing parameters for mission assurance and safety limits in addition to the energy consumption and operation time. The UAV navigates the grid by taking actions to move in any of the eight cardinal and inter-cardinal directions, under constant thrust profile. The resultant UAV state is sampled from a probability distribution which accounts for the UAV’s action, local wind velocity, and the presence of obstacles or boundaries. As the unmanned airspace gets more complex due to multiple vehicles and environmental uncertainties, trade-offs between energy consumption, operation time, risk tolerance, and mission assurance need to be made. Our Markov Decision Process (MDP) environment model can capture any combination of these in the optimization objective, making it novel compared to other work in the field.
trajectory planning↗
Transportation Network Topologies
The existing U.S. hub-and-spoke air transportation system is reaching saturation. Major aspects of the current system, such as capacity, safety, mobility, customer satisfaction, security, communications, and ecological effects, require improvements. The changing dynamics - increased presence of general aviation, unmanned autonomous vehicles, military aircraft in civil airspace as part of homeland defense - contributes to growing complexity of airspace. The system has proven remarkably resistant to change. NASA Langley Research Center and the National Institute of Aerospace conducted a workshop on Transportation Network Topologies on 9-10 December 2003 in Williamsburg, Virginia. The workshop aimed to examine the feasibility of traditional methods for complex system analysis and design as well as potential novel alternatives in application to transportation systems, identify state-of-the-art models and methods, conduct gap analysis, and thus to lay a foundation for establishing a focused research program in complex systems applied to air transportation.
Alexandrov, Natalia↗
Technologies Advance UAVs for Science, Military
A Space Act Agreement with Goddard Space Flight Center and West Virginia University enabled Aurora Flight Sciences Corporation, of Manassas, Virginia, to develop cost-effective composite manufacturing capabilities and open a facility in West Virginia. The company now employs 160 workers at the plant, tasked with crafting airframe components for the Global Hawk unmanned aerial vehicle (UAV) program. While one third of the company's workforce focuses on Global Hawk production, the rest of the company develops advanced UAV technologies that are redefining traditional approaches to unmanned aviation. Since the company's founding, Aurora s cutting-edge work has been supported with funding from NASA's Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs.
Source record↗
Remotely Piloted Aircraft Systems
Remotely piloted aircraft range from quadcopter “drones” with endurance measured in minutes, to large, long endurance aircraft powered by jet turbine engines. The central message of this chapter is that the further development of unmanned aviation may be held back more by a lack of attention to human factors, than by technological hurdles. This chapter begins with a brief overview of remotely piloted aircraft, follows with a review of their accident record, and then focuses on human factors principles for Remote Pilot Stations (RPS).
remotely piloted aircraft↗
Probability of Obstacle Collision for UAVs in Presence of Wind
For incorporation of unmanned aerial vehicles into the National Airspace, ensuring safety of the airspace including the vehicles, people, and property on the ground is of utmost importance. One of the safety-critical factors for unmanned aviation flights is the risk of deviating from a planned trajectory resulting in a variety of hazards, including potential loss of separation between vehicle and obstacles or unexpected battery energy consumption. Off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts can lead to unacceptable unexpected deviations from the flight trajectory. It is essential to accurately model such effects on the flight trajectory while computing safety thresholds such as minimum separation from surrounding obstacles, available battery resource to complete the mission or determining delay in the expected time of arrival of flights. In this paper, a tool is presented based on Gaussian Process Regression for wind representation over a pre-defined trajectory for fast, yet approximated, in-time evaluation of possible trajectory deviations caused by wind gusts. The deviation in the planned trajectory caused by wind is further simulated utilizing a 6 degrees-of-freedom (DOF) UAV trajectory simulator comprising of a rotorcraft lumped-mass model with LQRI controller. Both steady-state wind and wind gust effects are investigated. The probability of collision with obstacle is computed and demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in the presence of simulated obstacles and wind conditions. Effect of varying wind conditions and varying UAV airspeed is further demonstrated on experimental flights in the presence of wind measured by ground based weather service stations. The proposed approach would eventually benefit timely mitigation of current and future safety-critical events in autonomous systems by enabling risk-informed decision making.
Portia Banerjee↗
Funding and Strategic Alignment Guidance for Infusing Small Business Innovation Research Technology Into Aeronautics Research Mission Directorate Projects at NASA Glenn Research Center for 2015
This document is intended to enable the more effective transition of NASA Glenn Research Center (GRC) SBIR technologies funded by the Small Business Innovation Research (SBIR) program as well as its companion, the Small Business Technology Transfer (STTR) program into NASA Aeronautics Research Mission Directorate (ARMD) projects. Primarily, it is intended to help NASA program and project managers find useful technologies that have undergone extensive research and development (RRD), through Phase II of the SBIR program; however, it can also assist non-NASA agencies and commercial companies in this process. aviation safety, unmanned aircraft, ground and flight test technique, low emissions, quiet performance, rotorcraft
rotorcraft.↗
Flying NASA Unmanned Aircraft: A Pilot's Perspective
Conference presentation sharing aspects of basic human factors engineering applied to aviation and unmanned aircraft systems from the pilot's perspective
Pestana, Mark E.↗
Unmanned Aircraft: A Pilot's Perspective
Conference presentation sharing aspects of basic human factors engineering applied to aviation and unmanned aircraft systems from the pilot's perspective
Pestana, Mark↗
Role of PHM in Autonomous Decision-Making: Aerospace applications
There is an increased need for onboard decision-making capabilities in cyber-physical systems be it in energy, automotive, aviation, space, or other industries as they aim for increased efficiency, resiliency, and mission assurance capabilities. Emerging next-gen technologies such as multi-rover planetary missions, distributed satellites, unmanned ground and aerial vehicle operations and smart grid systems rely on in-time risk assessment and autonomous decision-making. One critical piece of the autonomy puzzle is reliable prediction of system behavior under time-varying and potentially uncertain environmental conditions. Further, if agent states change during operation such as initiation of faults or degradation, reliable diagnostic tools need to be investigated. In this tutorial, we will revise approaches that integrates existing physics-based and data-driven models of agents interacting with probability models of the environment and component operation state. Role of existing PHM methodologies as they feed into decision-making under uncertainty will be studied. Balancing critical trade-offs between high-fidelity prognostic models, prediction time-horizons and the computational requirements for in-time cost-effective decision-making will be discussed through the implementation of surrogate models. Finally, the audience will be introduced to a real-time application of in-time trajectory planning of an unmanned aerial system (UAS) based on its PHM assessments under uncertain and varying wind conditions.
decision-making↗
Outcomes of the 2015 World Radiocommunication Conference for Aeronautical Spectrum and Applications
At the conclusion of a nearly four year study cycle following the closing of the 2012 World Radiocommunication Conference (WRC-12), the 2015 WRC in November of 2015 considered a number of agenda items and issues relevant to systems and spectrum allocations supporting communications, navigation and surveillance for the operation of civil aviation. Among a number of WRC-15 agenda items and issues, the key agenda items affecting civil aviation included: unmanned aircraft systems use of the Fixed Satellite Service for command and control communications; global flight tracking; new allocations to International Mobile Telecommunications (IMT); and protection of the Fixed Satellite Service to support safe operation of aircraft. A number of other agenda items affecting or potentially affecting civil aviation were also addressed by WRC-15. In this paper we describe the outcomes of WRC-15 for these civil aeronautical-relevant issues. We then outline the civil aviation-related agenda items and issues that will be considered at the upcoming 2019 WRC.
air traffic control↗
Autonomous Flight Rules Concept: User Implementation Costs and Strategies
The costs to implement Autonomous Flight Rules (AFR) were examined for estimates in acquisition, installation, training and operations. The user categories were airlines, fractional operators, general aviation and unmanned aircraft systems. Transition strategies to minimize costs while maximizing operational benefits were also analyzed. The primary cost category was found to be the avionics acquisition. Cost ranges for AFR equipment were given to reflect the uncertainty of the certification level for the equipment and the extent of existing compatible avionics in the aircraft to be modified.
Cotton, William B.↗
Initial Approach to Collect Small Unmanned Aircraft System Off-Nominal Operational Situations Data
NASA is developing the Unmanned Aircraft System Traffic Management research platform to safely integrate small unmanned aircraft operations in large-scale at low-altitudes. As a part of this effort, small unmanned aircraft system off-nominal operational situations data collection process has been developed to take lessons learned and to reinforce operational compliance. In this paper, descriptions of variables used for digital data collection and an online report form for collection of observational data from the operators (contextual data) are provided. They are used to collect off-nominal data from the Unmanned Aircraft System Traffic Management National Campaign in 2017. The digital data show that 2 out of 118 campaign operations (1.7%) encountered loss of navigation. Since the campaign aircraft used Global Positioning System for navigation, it is likely that unobstructed view of the sky at the campaign locations contributed to this small number. Also, 4 out of 47 operations (8.5%) encountered loss of communications. A relatively short distance between ground control system and aircraft, ranging from 2300 feet to 4200 feet, likely contributed to this small number. There was no data to identify the loss of communications condition, aircraft received signal strength, for the remaining 71 operations suggesting that some operators may not be monitoring unmanned aircraft communications system performance or monitoring it with different parameters. For the contextual data, due to the low number of total reports during the campaign, no significant trends emerged. This is an initial attempt to collect contextual data from small unmanned aircraft operators about off-nominal situations, and changes will be made to the future data collection to improve the amount and quality of the information.
unmanned aviation systems traffic management (UTM)↗