Alessandro Gardi

Cognitive Human-Machine Interfaces and Interactions for Unmanned Aircraft

This paper presents the concept of Cognitive Human-Machine Interfaces and Interactions (CHMI2) for Unmanned Aircraft System (UAS) Ground Control Stations (GCS). CHMI2 represents a new approach to aviation human factors engineering that introduces adaptive functionalities in the design of operators’ command, control and display functions. A CHMI2 system assesses human cognitive states based on measurement of key psycho-physiological observables. The cognitive states are used to predict and enhance operator performance in the accomplishment of aviation tasks, with the objective of improving the efficiency and effectiveness of the overall human-machine teaming. The CHMI2 system presented in this paper employs a four-layer architecture comprising sensing, extraction, classification and adaptation functionalities. An overview of each layer is provided along with the layer’s metrics, algorithms and functions. Two relevant case studies are presented to illustrate the interactions between the different layers, and the conceptual design of the associated display formats is described. The results indicate that specific eye tracking variables provide discrimination between different modes of control. Furthermore, results indicate that the higher levels of automation supported by the CHMI2 are beneficial in Separation Assurance and Collision Avoidance (SA&CA) scenarios involving low-detectability obstacles and stringent time constraints to implement recovery manoeuvres. These preliminary results highlight that the introduction of CHMI2 functionalities in future UAS can significantly reduce reaction time and enhance operational effectiveness of unmanned aircraft response to collision and loss of separation events, as well as improve the overall safety and efficiency of operations.

A Unified Analytical Framework for Aircraft Separation Assurance and UAS Sense-and-Avoid

A novel analytical framework is presented addressing the need for a unified approach to aircraft separation assurance and Unmanned Aircraft System (UAS) Sense-and-Avoid (SAA). A brief review of the state-of-research in Separation Assurance and Collision Avoidance (SA&CA) technologies is included to highlight the benefits offered by the unified approach. In this approach, the employment of Adaptive Boolean Decision Logics (ABDL) allows automated selection of sensors/systems including passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance – Broadcast (ADS-B). This system performance based selection approach supports trusted autonomous operations during all flight phases. After describing a SA&CA reference architecture, the mathematical models employed in the unified approach to compute the overall uncertainty volume in the airspace surrounding an intruder/obstacle are described. The algorithms support the translation of navigation errors affecting the host aircraft platform and tracking errors affecting the intruder sensor measurements to unified range and bearing uncertainty descriptors. Simulation case studies are presented to evaluate the performance of the unified approach on a representative UAS host platform and a number of intruder platforms in both cooperative and non-cooperative scenarios. The results confirm the validity of the proposed unified methodology in providing a pathway for certification of SA&CA systems. The significance of this approach is also discussed in the Communication, Navigation and Surveillance/Air Traffic Management and Avionics (CNS + A) context, with a focus on the evolving UAS Traffic Management (UTM) requirements.

Descent 4D trajectory optimisation for curved GNSS approaches

This paper describes the 4-Dimensional Trajectory (4DT) optimisation algorithm implemented to avoid a variety Global Navigation Satellite System (GNSS) signal degradations predicted by Avionics Based Integrity Augmentation system (ABIA). The paper focusses on descent and initial curved GNSS approach phases in a dense Terminal Manoeuvring Area (TMA) scenario, with multiple aircraft converging on the same short and curved final GNSS approach leg. The reference platform for this study is the Javelin Remotely Piloted Aircraft System (RPAS). The 4DT optimisation algorithm implements three degrees-of-freedom aircraft dynamics models as well as suitable GNSS satellite visibility models based on Global Positioning System (GPS) constellation ephemeris data. Direct transcription methods of the global orthogonal (pseudospectral) collocation family are implemented, generating optimal high-integrity trajectories for curved GNSS approaches in real-time. The optimal trajectories calculated by the pseudospectral method are subsequently processed by control input smoothing and manoeuvre identification algorithms to translate the mathematical optimum into a pilot- /autopilot-flyable and concisely described 4DT intent. The characteristics of the proposed 4DT optimisation algorithm are evaluated in representative simulation case studies targeting short and curved GNSS approaches in dense TMA conditions, showing very satisfactory performance.

A unified approach to separation assurance and Collision Avoidance for UAS operations and traffic management

A unified approach to cooperative and non- cooperative Separation Assurance and Collision Avoidance (SA&CA) is presented addressing the technical and regulatory challenges of Unmanned Aircraft Systems (UAS) integration into all classes of airspace. Additionally, the emerging UAS Traffic Management (UTM) system requirements are captured and addressed in this novel unified framework. Uncertainties in navigation and tracking error measurements associated to each manned/unmanned platform (as seen by all other conflicting platforms) are combined statistically to generate avoidance volumes in the airspace. The unified approach to SA&CA provides the required tools to generate uncertainty volumes at discrete time intervals as a function of traffic relative dynamics and thus supports the generation of dynamic geo-fences and multiplatform UTM system implementation. Case studies are presented for evaluating the feasibility of the approach in an urban environment. In this approach, real-time and off-line determination of the UAS safe-to-fly envelope is performed based on the installed avionics sensors and on the own/intruder platform dynamics. Additionally, the required sensors are identified for the UAS to safely fly a certain predefined envelope supporting the development of the SA&CA system certification case and thus providing a pathway to certification.

Acoustic Sensors for Air and Surface Navigation Applications

This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors used for a variety of navigation and guidance applications on air and surface vehicles. In particular, this paper focuses on echolocation, which is widely utilized in nature by certain mammals (e.g., cetaceans and bats). Although acoustic sensors have been extensively adopted in various engineering applications, their use in navigation and guidance systems is yet to be fully exploited. This technology has clear potential for applications in air and surface navigation/guidance for intelligent transport systems (ITS), especially considering air and surface operations indoors and in other environments where satellite positioning is not available. Propagation of sound in the atmosphere is discussed in detail, with all potential attenuation sources taken into account. The errors introduced in echolocation measurements due to Doppler, multipath and atmospheric effects are discussed, and an uncertainty analysis method is presented for ranging error budget prediction in acoustic navigation applications. Considering the design challenges associated with monostatic and multi-static sensor implementations and looking at the performance predictions for different possible configurations, acoustic sensors show clear promises in navigation, proximity sensing, as well as obstacle detection and tracking. The integration of acoustic sensors in multi-sensor navigation systems is also considered towards the end of the paper and a low Size, Weight and Power, and Cost (SWaP-C) sensor integration architecture is presented for possible introduction in air and surface navigation systems.

Real-Time UAS Guidance for Continuous Curved GNSS Approaches

This paper presents new efficient guidance algorithms allowing Unmanned Aircraft Systems (UAS) to avoid a variety of Global Navigation Satellite System (GNSS) continuity and integrity performance threats detected by an Aircraft Based Augmentation System (ABAS). In particular, the UAS guidance problem is formulated as an optimal control-based Multi-Objective Trajectory Optimization (MOTO) problem subject to suitable dynamic and geometric constraints. Direct transcription methods of the global orthogonal collocation (pseudospectral) family are exploited for the solution of the MOTO problem, generating optimal trajectories for curved GNSS approaches in real-time. Three degrees-of-freedom aircraft dynamics models and suitable GNSS satellite visibility models based on Global Positioning System (GPS) constellation ephemeris data are utilised in the MOTO solution algorithm. The performance of the proposed MOTO algorithm is evaluated in representative simulation case studies adopting the JAVELIN UAS as the reference platform. The paper focusses on descent and initial curved GNSS approach phases in a Terminal Maneuvering Area (TMA) scenario, where multiple manned/unmanned aircraft converge on the same short and curved final GNSS approach leg. The results show that the adoption of MOTO based on pseudospectral methods allows an efficient exploitation of ABAS model-predictive augmentation features in online GNSS guidance tasks, supporting the calculation of suitable arrival trajectories in 7 to 16 s using a normal PC.

Benefits and challenges of liquid hydrogen fuels in commercial aviation

This paper aims to highlight the opportunities and challenges associated with the adoption of hydrogen fuels in aviation. An overview of the environmental and economic benefits and technological challenges is presented. A simplified model is subsequently introduced to estimate the benefits of liquid hydrogen fuels in aircraft of conventional configurations, encompassing changes in volume, weights and environmental impacts. This paper concludes that hydrogen in cryogenic liquid form demonstrates great potential to become a highly sustainable commercial aviation fuel with lower emissions and less fuel mass for a given range, resulting in better economies. The presented numerical case study highlights that despite the worsened aerodynamic and structural characteristics, a take-off weight saving of more than 11% (small regional jet) and up to 25% (large wide-body aircraft) can be achieved when considering a liquid hydrogen retrofit of current generation jetliners. Unfortunately, the volume required by integral tanks prevents the translation of this weight saving in additional payload, but remarkable economic savings can be obtained. However, the implementation of this technology comes with many technical challenges, including the development of sustainable production, storage and delivery systems that shall not dilute the environmental benefits as well as widespread uptake to ensure financial sustainability.