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Upchurch, Jason

Publications and source records attributed to Upchurch, Jason.

Unmanned Aircraft Systems in the National Airspace System: A Formal Methods Perspective

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.

Munoz, Cesar A.

Human-In-The-Loop Experimental Research for Detect and Avoid

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.

Consiglio, Maria

DAIDALUS: Detect and Avoid Alerting Logic for Unmanned Systems

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 US Air Force Research Laboratory, MIT Lincoln Laboratory, and NASA. The DAIDALUS reference implementation is currently under consideration for inclusion in the appendices to the Minimum Operational Performance Standards for Unmanned Aircraft Systems presently being developed by RTCA Special Committee 228.

Munoz, Cesar

A Family of Well-Clear Boundary Models for the Integration of UAS in the NAS

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.

Munoz, Cesar A.