Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project FY18 Annual Review
This is a redacted version of the 2018 annual report presented to NASA shareholders for general release.
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This is a redacted version of the 2018 annual report presented to NASA shareholders for general release.
Public version of the presentation given to the IASP group on the progress for annual year 2019.
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This presentation discusses the results of a recent UAS Integration into the NAS human-in-the-loop simulation. In the study, 16 active UAS pilots flew a UAS through civil airspace and were tasked with maintaining well clear from other aircraft in the area. Pilots performed the task with four different detect and avoid (DAA) traffic displays, each of which varied in the form of guidance it provided to pilots The present findings focus on how the different displays impacted pilots' measured response to scripted conflicts with their aircraft. Measured response is made up of several components, each of which help inform our understanding of the pilots' role in the overall detect and avoid task.
The UAS Integration into the NAS (UASNAS) project is studying the minimum operational performance standards for unmanned aerial system (UAS) detect-and-avoid (DAA) systems in order to operate in the National Airspace System (NAS). The project is executing a series of fast-time simulation, human-in-the-loop experiments, and flight tests in support of this effort. Armstrong Flight Research Center is hosting a VIP Day in conjunction with the UAS-NAS Project's Flight Test 4 activity, and the Ames Project Engineer (or designate) will be presenting a briefing. This briefing will review the data collection and analysis activities for Flight Test 4 within the Separation assurance-Sense-and-avoid Interoperability (SSI) team.
This is a benefit to NASA because of all the networking opportunities as well as sharing information about UAS-NAS within the UAS community. NASA has developed, and is executing, a Cohesive Strategy for UAS Integration
This study examined air traffic controller acceptability ratings based on the effects of differing horizontal miss distances (HMDs) for encounters between UAS and manned aircraft. In a simulation of the Dallas/Fort Worth (DFW) East-side airspace, the CAS-1 experiment at NASA Langley Research Center enlisted fourteen recently retired DFW air traffic controllers to rate well-clear volumes based on differing HMDs that ranged from 0.5 NM to 3.0 NM. The controllers were tasked with rating these HMDs from "too small" to "too excessive" on a defined, 1-5, scale and whether these distances caused any disruptions to the controller and/or to the surrounding traffic flow. Results of the study indicated a clear favoring towards a particular HMD range. Controller workload was also measured. Data from this experiment and subsequent experiments will play a crucial role in the FAA's establishment of rules, regulations, and procedures to safely and efficiently integrate UAS into the NAS.
Previously, we showed that air traffic controllers (ATCos) rated UAS pilot verbal response latencies as acceptable when a 1.5 s delay was added to the UAS pilot responses, but a 5 s delay was rated as mostly unacceptable. In the present study we determined whether a 1.5 s added delay in the UAS pilots' verbal communications would affect ATCos interactions with UAS and other conventional aircraft when the number and speed of the UAS were manipulated. Eight radar-certified ATCos participated in this simulation. The ATCos managed a medium altitude sector containing arrival aircraft, en route aircraft, and one to four UAS. The UAS were conducting a surveillance mission and flew at either a "slow" or "fast" speed. We measured both UAS and conventional pilots' verbal communication latencies, and obtained ATCos' acceptability ratings for these latencies. Although the UAS pilot response latencies were longer than those of conventional pilots, the ATCos rated UAS pilot verbal communication latencies to be as acceptable as those of conventional pilots. Because the overall traffic load within the sector was held constant, ATCos only performed slightly worse when multiple UAS were in their sector compared to when only one UAS was in the sector. Implications of these findings for UAS integration in the NAS are discussed.
Informational briefing on NASA activities related to the UAS integration in the NAS project.
A need exists to safely integrate Unmanned Aircraft Systems (UAS) into the United States' National Airspace System. Replacing manned aircraft's see-and-avoid capability in the absence of an onboard pilot is one of the key challenges associated with safe integration. Sense-and-avoid (SAA) systems will have to achieve yet-to-be-determined required separation distances for a wide range of encounters. They will also need to account for the maneuver performance of the UAS they are paired with. The work described in this paper is aimed at developing an understanding of the trade space between UAS maneuver performance and SAA system performance requirements, focusing on a descent avoidance maneuver. An assessment of current manned and unmanned aircraft performance was used to establish potential UAS performance test matrix bounds. Then, near-term UAS integration work was used to narrow down the scope. A simulator was developed with sufficient fidelity to assess SAA system performance requirements. The simulator generates closest-point-of-approach (CPA) data from the wide range of UAS performance models maneuvering against a single intruder with various encounter geometries. Initial attempts to model the results made it clear that developing maneuver performance groups is required. Discussion of the performance groups developed and how to know in which group an aircraft belongs for a given flight condition and encounter is included. The groups are airplane, flight condition, and encounter specific, rather than airplane-only specific. Results and methodology for developing UAS maneuver performance requirements are presented for a descent avoidance maneuver. Results for the descent maneuver indicate that a minimum specific excess power magnitude can assure a minimum CPA for a given time-to-go prediction. However, smaller amounts of specific excess power may achieve or exceed the same CPA if the UAS has sufficient speed to trade for altitude. The results of this study will support UAS maneuver performance requirements development for integrating UAS in the NAS. The methods described are being used to help RTCA Special Committee 228 develop requirements.
Unmanned aircraft will equip with a detect-and-avoid (DAA) system that enables them to comply with the requirement to "see and avoid" other aircraft, an important layer in the overall set of procedural, strategic and tactical separation methods designed to prevent mid-air collisions. This paper describes a capability called Java Architecture for Detect and Avoid Extensibility and Modeling (JADEM), developed to prototype and help evaluate various DAA technological requirements by providing a flexible and extensible software platform that models all major detect-and-avoid functions. Figure 1 illustrates JADEM's architecture. The surveillance module can be actual equipment on the unmanned aircraft or simulators that model the process by which sensors on-board detect other aircraft and provide track data to the traffic display. The track evaluation function evaluates each detected aircraft and decides whether to provide an alert to the pilot and its severity. Guidance is a combination of intruder track information, alerting, and avoidance/advisory algorithms behind the tools shown on the traffic display to aid the pilot in determining a maneuver to avoid a loss of well clear. All these functions are designed with a common interface and configurable implementation, which is critical in exploring DAA requirements. To date, JADEM has been utilized in three computer simulations of the National Airspace System, three pilot-in-the-loop experiments using a total of 37 professional UAS pilots, and two flight tests using NASA's Predator-B unmanned aircraft, named Ikhana. The data collected has directly informed the quantitative separation standard for "well clear", safety case, requirements development, and the operational environment for the DAA minimum operational performance standards. This work was performed by the Separation Assurance/Sense and Avoid Interoperability team under NASA's UAS Integration in the NAS project.
Java Architecture for Detect-And-Avoid (DAA) Extensibility and Modeling (JADEM) was developed at NASA Ames Research Center as a research and modeling tool for Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS). UAS will be required to have DAA systems in order to fulfill the regulatory requirement to remain well clear'' of other traffic. JADEM supports research on technological requirements and Minimum Operational Performance Standards (MOPS) for UAS DAA systems by providing a flexible and extensible software platform that includes models and algorithms for all major DAA functions. This paper describes one of these algorithms, the Generic Resolution Advisor and Conflict Evaluator (GRACE). GRACE supports two core DAA functions: threat evaluation and guidance. GRACE is generic in the sense that it is designed to work with any aircraft or sensor type (both cooperative and non-cooperative), and to be used in various applications and DAA guidance concepts, thus supporting evolving MOPS requirements and research. GRACE combines flexibility, robustness, and computational efficiency. It has modest memory requirements and can handle multiple cooperative and noncooperative intruders. GRACE has been used as a core JADEM component in several real-time and fast-time experiments, including human-in-the-loop simulations and live flight tests.
This presentation covers the primary results from a recently completed human-in-the-loop (HITL) simulation conducted as part of the UAS (Unmanned Aircraft System) integration into the NAS (National Airspace System) project. The HITL examined the impact of multiple (simultaneous) UAS control while performing a demanding mission task and managing scripted conflicts. The scripted conflicts were designed to trigger the detect-and-avoid (DAA) system. This was the first time the DAA system as designed as part of the UAS-NAS project has been applied to multi-UAS control. The second part of the presentation briefly summarizes the takeaways from two workshops held on human-automation interaction considerations for UAS integration. NASA co-hosted and participated in both workshops.
This presentation covers the primary results from a recently completed human-in-the-loop (HITL) simulation conducted as part of the UAS (Unmanned Aircraft Systems) integration into the NAS (National Airspace System) project. The HITL examined the impact of multiple (simultaneous) UAS control while performing a demanding mission task and managing scripted conflicts. The scripted conflicts were designed to trigger the detect-and-avoid (DAA) system. This was the first time the DAA system as designed as part of the UAS-NAS project has been applied to multi-UAS control. The second part of the presentation briefly summarizes the takeaways from two workshops held on human-automation interaction considerations for UAS integration. NASA co-hosted and participated in both workshops.
A well-clear volume is a key component of NASA's Separation Assurance concept for the integration of UAS in the NAS. This paper proposes a mathematical definition of the well-clear volume that uses, in addition to distance thresholds, a time threshold based on time to entry point (TEP). The mathematical model that results from this definition is more conservative than other candidate definitions of the wellclear volume that are based on range over closure rate and time to closest point of approach.
This paper describes a Detect and Avoid (DAA) concept for integration of UAS into the NAS developed by the National Aeronautics and Space Administration (NASA) and provides results from recent human-in-the-loop experiments performed to investigate interoperability and acceptability issues associated with these vehicles and operations. The series of experiments was designed to incrementally assess critical elements of the new concept and the enabling technologies that will be required.