Autonomous aircraft operations using RTCA guidelines for airborne conflict management

Abstract

A human-in-the-loop experiment was performed at the NASA Langley Research Center to study the feasibility of DAG-TM autonomous aircraft operations in highly constrained airspace. The airspace was constrained by a pair of special-use airspace (SUA) regions on either side of the pilot's planned route. Traffic flow management (TFM) constraints were imposed as a required time of arrival and crossing altitude at an en route fix. Key guidelines from the RTCA Airborne Conflict Management (ACM) concept were applied to autonomous aircraft operations for this experiment. These concepts included the RTCA ACM definitions of distinct conflict detection and collision avoidance zones, and the use of a graded system of conflict alerts for the flight crew.Three studies were conducted in the course of the experiment. The first study investigated the effect of hazard proximity upon pilot ability to meet constraints and solve conflict situations. The second study investigated pilot use of the airborne tools when faced with an unexpected loss of separation (LOS). The third study explored pilot interactions in an over-constrained conflict situation, with and without priority rules dictating who should move first.Detailed results from these studies were presented at the 5 th USA/Europe Air Traffic Management R&D Seminar (ATM2003). This overview paper focuses on the integration of the RTCA ACM concept into autonomous aircraft operations in highly constrained situations, and provides an overview of the results presented at the ATM2003 seminar. These results, together with previously reported studies, continue to support the feasibility of autonomous aircraft operations.

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“…16 In order to provide such alerting in a concise and clear manner, alert levels are assigned to each conflict for later use in prioritization and filtering. The rule set containing the logic for assigning these levels is defined in an alerting scheme, which may be tailored to the experiment at hand.…”

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“…However, in order to respond to a growing market's demand and operate in the US National Airspace System (NAS), UAVs require the Certificate of Authorization from the Federal Aviation Administration (FAA) [1], [2]. Typically, the practice in rotary wing UAV flight control is to linearize the aircraft dynamics about different trim conditions and use gain scheduled linear control techniques to control the helicopter during different flight conditions.…”

An eye-hand movement Model for traffic complexity evaluation and monitoring enhancement for air traffic controllers

“…Spacing Tool (FAST) and the Descent Advisor (DA) [11,12], that seek to detect conflicts way in advance for better decision making, automate take-off and landing procedures with increased runway capacity and flight efficiency. Hence, it has been postulated that future ATCO tasks would likely be dedicated more towards monitoring and exogenous activities presented on monitor displays with lesser communication with the flight crew under regular circumstances [2,13,14]. Effective and efficient translation and interpretation of data on the screen display would therefore be of paramount importance [15].…”

“…Otherwise, the polygons are either coplanar or they are not parallel and split by the plane of the other polygon. If the polygons are coplanar, the potential separating direction vectors are those in the common plane, which are perpendicular to the edges, given by (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14). Subsequently, if the polygons are not parallel and divided by the plane of the other polygon, the potential separating direction vectors are those perpendicular to the touching edges, given by (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15).…”

“…The speed of the slower Aircraft Y and R are also varied, where the speed of Aircraft R is 1.14 times faster than Aircraft Y. Their respective input parameters, which were flight information extracted directly from the radar screen, can be seen in Table 4.8, serving as the input into the CAL time profile, as described in equation (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16). Using these input parameters, the CAL-SAT model is able to predict that a full overlap exists both vertically and laterally, having a peak score of (CAL overall ) effective = 3, for both aircraft pairs, X and Y, Q and R respectively.…”