Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance

Ground Risk Assessment Service Provider (GRASP) Development Effort as a Supplemental Data Service Provider (SDSP) for Urban Unmanned Aircraft System (UAS) Operations

NASAs Unmanned Aircraft System (UAS) Traffic Management (UTM) project aims to enable the integration of new aviation paradigms such as Unmanned Aircraft Systems (UAS) while providing the necessary infrastructure for future concepts such as On-Demand Mobility (ODM) and Urban Air Mobility (UAM) operations in the National Airspace System (NAS). In order to do so, the UTM project has developed an architecture to allow communication among UAS operators, UAS Service Suppliers (USS), Air Navigation Service Providers (ANSP), and the public. As part of this framework, the Supplemental Data Service Providers (SDSP) are envisioned as model and/or data based services that disseminate essential or enhanced information to ensure safe operations within low-altitude airspace. These services include terrain and obstacle data, specialized weather data, surveillance, constraint information, risk monitoring, etc. This paper highlights the development efforts of a non-participant casualty risk assessment SDSP called Ground Risk Assessment Service Provider (GRASP) which assists operators with preflight planning. GRASP is based on the previously introduced UTM Risk Assessment Framework (URAF) and allows UAS operators to simulate and visualize potential non-participant casualty risks associated with their proposed flight. The risk assessment capability also allows operators to revise their flight plans if the casualty risks are determined to be above acceptable thresholds. GRASP is configured to account for future improvements including servicing airborne aircraft as part of NASAs System-Wide Safety (SWS) project

Testing Enabling Technologies for Safe UAS Urban Operations

A set of more than 100 flight operations were conducted at NASA Langley Research Center using small UAS (sUAS) to demonstrate, test, and evaluate a set of technologies and an overarching air-ground system concept aimed at enabling safety. The research vehicle was tracked continuously during nominal traversal of planned flight paths while autonomously operating over moderately populated land. For selected flights, off-nominal risks were introduced, including vehicle-to-vehicle (V2V) encounters. Three contingency maneuvers were demonstrated that provide safe responses. These maneuvers made use of an integrated air/ground platform and two on-board autonomous capabilities. Flight data was monitored and recorded with multiple ground systems and was forwarded in real time to a UAS traffic management (UTM) server for airspace coordination and supervision

Unmanned Aerial Systems for Wildland and Forest Fires

Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

An Innovative Human Machine Interface for UAS Flight Management System

The thesis is relative to the development of an innovative Human Machine Interface for UAS Flight Management System. In particular, touchscreena have been selected as data entry interface. The thesis has been done together at Alenia Aermacch

Cyberinfrastructure for Airborne Sensor Webs

Since 2004 the NASA Airborne Science Program has been prototyping and using infrastructure that enables researchers to interact with each other and with their instruments via network communications. This infrastructure uses satellite links and an evolving suite of applications and services that leverage open-source software. The use of these tools has increased near-real-time situational awareness during field operations, resulting in productivity improvements and the collection of better data. This paper describes the high-level system architecture and major components, with example highlights from the use of the infrastructure. The paper concludes with a discussion of ongoing efforts to transition to operational status

Flying Unmanned Aircraft: A Pilot's Perspective

The National Aeronautics and Space Administration (NASA) is pioneering various Unmanned Aircraft System (UAS) technologies and procedures which may enable routine access to the National Airspace System (NAS), with an aim for Next Gen NAS. These tools will aid in the development of technologies and integrated capabilities that will enable high value missions for science, security, and defense, and open the door to low-cost, extreme-duration, stratospheric flight. A century of aviation evolution has resulted in accepted standards and best practices in the design of human-machine interfaces, the displays and controls of which serve to optimize safe and efficient flight operations and situational awareness. The current proliferation of non-standard, aircraft-specific flight crew interfaces in UAS, coupled with the inherent limitations of operating UAS without in-situ sensory input and feedback (aural, visual, and vestibular cues), has increased the risk of mishaps associated with the design of the "cockpit." The examples of current non- or sub- standard design features range from "annoying" and "inefficient", to those that are difficult to manipulate or interpret in a timely manner, as well as to those that are "burdensome" and "unsafe." A concerted effort is required to establish best practices and standards for the human-machine interfaces, for the pilot as well as the air traffic controller. In addition, roles, responsibilities, knowledge, and skill sets are subject to redefining the terms, "pilot" and "air traffic controller", with respect to operating UAS, especially in the Next-Gen NAS. The knowledge, skill sets, training, and qualification standards for UAS operations must be established, and reflect the aircraft-specific human-machine interfaces and control methods. NASA s recent experiences flying its MQ-9 Ikhana in the NAS for extended duration, has enabled both NASA and the FAA to realize the full potential for UAS, as well as understand the implications of current limitations. Ikhana is a Predator-B/Reaper UAS, built by General Atomics, Aeronautical Systems, Inc., and modified for research. Since 2007, the aircraft has been flown seasonally with a wing-mounted pod containing an infrared scanner, utilized to provide real-time wildfire geo-location data to various fire-fighting agencies in the western U.S. The multi-agency effort included an extensive process to obtain flight clearance from the FAA to operate under special provisions, given that UAS in general do not fully comply with current airspace regulations (e.g. sense-and-avoid requirements)

Spatial Data Performance Test of Mid-cost UAS with Direct Georeferencing

Recent development of lightweight and small size multi-frequency GNSS receivers allows determination of the precise position of the moving platform and spatial data acquisition without the need for setting up and measuring of ground control points. The main advantage of this approach is a higher operational capacity with reduced time and cost of field measurement. This relates to fieldwork in inaccessible areas with demanding terrain configuration. In this paper development and use of a UAS with direct georeferencing of camera sensor for spatial data acquisition is described, and the possibility of 3D scene reconstruction based on the precise position of the camera with predetermined interior parameters is examined. Modern computer vision-based SfM photogrammetry algorithms are used for determining attitude parameters and reconstruction of the scene. For that purpose, several tests on two different test fields were performed using various system parameters for collecting and analysis of several spatial data sets. The presented results demonstrate a satisfactory accuracy (3.1 cm planar and 6.4 cm spatial) of the system for various applications in geodesy