This paper presents DAIDALUS (Detect and Avoid Alerting Logic for Unmanned Systems), a reference implementation of a detect and avoid concept intended to support the integration of Unmanned Aircraft Systems into civil airspace. DAIDALUS consists of self-separation and alerting algorithms that provide situational awareness to UAS remote pilots. These algorithms have been formally specified in a mathematical notation and verified for correctness in an interactive theorem prover. The software implementation has been verified against the formal models and validated against multiple stressing cases jointly developed by the
The FAA-sponsored Sense and Avoid Workshop for Unmanned Aircraft Systems (UAS) defines the concept of sense and avoid for remote pilots as "the capability of a UAS to remain well clear from and avoid collisions with other airborne traffic." Hence, a rigorous definition of well clear is fundamental to any separation assurance concept for the integration of UAS into civil airspace. This paper presents a family of well-clear boundary models based on the TCAS II Resolution Advisory logic. For these models, algorithms that predict well-clear violations along aircraft current trajectories are provided. These algorithms are analogous to conflict detection algorithms but instead of predicting loss of separation, they predict whether well-clear violations will occur during a given lookahead time interval. Analytical techniques are used to study the properties and relationships satisfied by the models.
As the technological and operational capabilities of unmanned aircraft systems (UAS) have grown, so too have international efforts to integrate UAS into civil airspace. However, one of the major concerns that must be addressed in realizing this integration is that of safety. For example, UAS lack an on-board pilot to comply with the legal requirement that pilots see and avoid other aircraft. This requirement has motivated the development of a detect and avoid (DAA) capability for UAS that provides situational awareness and maneuver guidance to UAS operators to aid them in avoiding and remaining well clear of other aircraft in the airspace. The NASA Langley Research Center Formal Methods group has played a fundamental role in the development of this capability. This article gives a selected survey of the formal methods work conducted in support of the development of a DAA concept for UAS. This work includes specification of low-level and high-level functional requirements, formal verification of algorithms, and rigorous validation of software implementations.
A fundamental requirement for the integration of unmanned aircraft into civil airspace is the capability of aircraft to remain well clear of each other and avoid collisions. This requirement has led to a broad recognition of the need for an unambiguous, formal definition of well clear. It is further recognized that any such definition must be interoperable with existing airborne collision avoidance systems (ACAS). A particular class of well-clear definitions uses logic checks of independent distance thresholds as well as independent time thresholds in the vertical and horizontal dimensions to determine if a wellclear violation is predicted to occur within a given time interval. Existing ACAS systems also use independent distance thresholds, however a common time threshold is used for the vertical and horizontal logic checks. The main contribution of this paper is the characterization of the effects of the decoupled vertical time threshold on a well-clear definition in terms of (1) time to wellclear violation, and (2) interoperability with existing ACAS. The paper provides governing equations for both metrics and includes simulation results to illustrate the relationships. In this paper, interoperability implies that the time of well-clear violation is strictly less than the time a resolution advisory is issued by ACAS. The encounter geometries under consideration in this paper are initially well clear and consist of constant-velocity trajectories resulting in near-mid-air collisions.
Experimental plan for the evaluation of the UAS integration concept Mathematical Model for Well-Clear WC definition implemented in the DAA prototype capability known as Stratway+ , now renamed as Detect and Avoid Alerting Logic for Unmanned Systems (DAIDALUS) Bands-based SS pilot maneuver guidance developed HITL simulation lab to support the CAS series of experiments developed May 2014 HITL Controller Acceptability Study 1 (CAS 1) July 2014 HITL Controller Acceptability Study 2 (CAS 2) Dec 2014 General Atomics -FAA-NASA Flight Test DAIDALUS algorithm tested in flight providing SS maneuver guidance to the pilot-in-command.
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