An Evaluation of Detect and Avoid (DAA) Displays for Unmanned Aircraft Systems: The Effect of Information Level and Display Location on Pilot Performance

Fern, Lisa; Rorie, R. Conrad; Pack, Jessica S.; Shively, Robert J.; Draper, Mark H.

doi:10.2514/6.2015-3327

Cited by 36 publications

(39 citation statements)

References 12 publications

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“…1,2 In the United States, simulation tests as well as flight tests have provided supporting information for defining a DAA Well Clear 1, 3 (DWC) and requirements for the alerting and guidance performance. [4][5][6][7] Prototype DAA algorithms have also been developed to alerting and guidance research. [8][9][10] These developments enabled the RTCA Special Committee 228 (SC-228) to publish the Minimum Operational Performance Standards (MOPS) for DAA systems 11 and air-to-air radar 12 in 2017.…”

Section: Introductionmentioning

confidence: 99%

Well Clear Trade Study for Unmanned Aircraft System Detect And Avoid with Non-Cooperative Aircraft

Cone

Lee

et al. 2018

2018 Aviation Technology, Integration, and Operations Conference

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This paper presents a process for selecting candidate Detect-and-Avoid Well Clear definitions for Unmanned Aircraft Systems and non-cooperative aircraft. The selection is based on considerations of the unmitigated collision risk, maneuver initiation range, and others. Operational assumptions related to low cost, size, weight, and power sensors equipped by the Unmanned Aircraft Systems are applied to set the scope of aircraft performance and drive metrics computation. Four candidate Well Clear definitions, two primary and two secondary, varying from 1500 to 2500 ft in their horizontal miss distance and from 0 to 25 sec in modified tau, are selected for future analyses.

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Section: Introductionmentioning

confidence: 99%

Well Clear Trade Study for Unmanned Aircraft System Detect And Avoid with Non-Cooperative Aircraft

Cone

Lee

et al. 2018

2018 Aviation Technology, Integration, and Operations Conference

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“…The results reported above provide a definitive answer as to the source of the improved pilot performance for the advanced conditions in Fern et al (2015). As shown here, the display conditions that included auto-resolutions (D3 and D4) consistently resulted in the fastest pilot response times, while the displays that lacked the tool (D1 and D2) often led to the slowest pilot responses.…”

Section: Discussionmentioning

confidence: 53%

“…Specifically, Fern et al (2015) reported significantly faster Initial Edit Times, Total Edit Times and Total Response Times when the advanced tools were present. Due to the presence of multiple conflict detection and resolution tools, however, Fern et al (2015) could not report on the cause of the differences in pilot performance.…”

Section: Discussionmentioning

confidence: 95%

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The Impact of Integrated Maneuver Guidance Information on UAS Pilots Performing the Detect and Avoid Task

Rorie

Fern

2015

Proceedings of the Human Factors and Ergonomics Society Annual

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Nine active unmanned aircraft system (UAS) pilots were tasked with flying a simulated UAS in civil airspace and instructed to maintain safe separation (i.e., well clear) from surrounding traffic. Pilots' task of maintaining separation (referred to here as 'Detect-and-Avoid', or DAA) was facilitated by four different traffic displays, each differing in the level of maneuver guidance they presented to the pilot. Pilots were found to spend the least amount of time implementing a maneuver when provided with an integrated form of directive guidance, but were found to subjectively prefer a maneuver guidance tool that allowed them to test self-derived maneuver options and then receive feedback as to that option's predicted safety level. The results of this study are related back to previous research and to the task of identifying the minimum information requirements for UAS pilots performing the DAA task. Limitations and future research are also discussed.

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“…Specific attention has been paid to identifying the traffic display features that minimize pilot response times and the frequency and severity of losses of DAA well clear (LoDWC) [6][7][8][9][10]. The results of these studies informed the development of the Phase 1 DAA MOPS traffic display requirements, which specified a minimum set of information that DAA traffic displays must provide to UAS pilots.…”

Section: Daa Alerting and Guidancementioning

confidence: 99%

An Interoperability Concept for Detect and Avoid and Collision Avoidance Systems: Results from a Human-in-the-Loop Simulation

Rorie

Fern

2018

2018 Aviation Technology, Integration, and Operations Conference

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The integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS) poses a variety of technical challenges to UAS developers and aviation regulators. In response to growing demand for access to civil airspace in the United States, the Federal Aviation Administration (FAA) has produced a roadmap identifying key areas requiring further research and development. One such technical challenge is the development of a "detect and avoid" system (DAA) capable of providing a means of compliance with the "see and avoid" requirement in manned aviation. The purpose of the DAA system is to support the pilot, situated at a ground control station (GCS), in maintaining "DAA well clear" of nearby aircraft through the use of GCS displays and alerts. In addition to its primary function of aiding the pilot in maintaining DAA well clear, the DAA system must also safely interoperate with existing NAS systems and operations, such as the airspace management procedures of air traffic controllers (ATC) and Collision Avoidance (CA) systems currently in use by manned aircraft, namely the Traffic Alert and Collision Avoidance System (TCAS II). It is anticipated that many UAS architectures will integrate both a DAA system and a TCAS II. It is therefore necessary to explicitly study the integration of DAA and TCAS II alerting structures and maneuver guidance formats to ensure that pilots understand the appropriate type and urgency of their response to the various alerts. This paper presents a concept of interoperability for the two systems. The concept was developed with the goal of avoiding any negative impact on the performance level of TCAS II while retaining a DAA system that still effectively enables pilots to maintain DAA well clear. The interoperability concept described in the paper focuses primarily on facilitating the transition from a latestage DAA encounter (where a loss of DAA well clear is imminent) to a TCAS II Corrective Resolution Advisory (RA), which requires pilot compliance within five seconds of its issuance. The interoperability concept was presented to 10 participants (6 active UAS pilots and 4 active commercial pilots) in a medium-fidelity, human-in-the-loop simulation designed to stress different aspects of the DAA and TCAS II systems. Pilots' ability to maintain separation, their rate of compliance and response times using the interoperability concept are reported. Results indicated that pilots exhibited comprehension of, and appropriate prioritization within, the DAA-TCAS II combined alert structure. Pilots demonstrated a high rate of compliance with TCAS II RAs and were also seen to respond to corrective RAs within the five second requirement established for manned aircraft. The DAA system presented under test was also shown to be effective in supporting pilots' ability to maintain DAA well clear in the overwhelming majority of cases in which pilots had sufficient time to respond.

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An Evaluation of Detect and Avoid (DAA) Displays for Unmanned Aircraft Systems: The Effect of Information Level and Display Location on Pilot Performance

Cited by 36 publications

References 12 publications

Well Clear Trade Study for Unmanned Aircraft System Detect And Avoid with Non-Cooperative Aircraft

Well Clear Trade Study for Unmanned Aircraft System Detect And Avoid with Non-Cooperative Aircraft

The Impact of Integrated Maneuver Guidance Information on UAS Pilots Performing the Detect and Avoid Task

An Interoperability Concept for Detect and Avoid and Collision Avoidance Systems: Results from a Human-in-the-Loop Simulation

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