Trevor Kistan

Next Generation Flight Management System for Real-Time Trajectory Based Operations

This paper presents the concept of operations, architecture and trajectory optimisation algorithms of a Next Generation Flight Management System (NG-FMS). The NG-FMS is developed for Four Dimensional (4D) Intent Based Operations (IBO) in the next generation Communications, Navigation, Surveillance and Air Traffic Management system (CNS+A) context. The NG-FMS, primarily responsible for the aircraft navigation and guidance task, acts as a key enabler for achieving higher level of operational efficiency and mitigating environmental impacts both in manned and unmanned aircraft applications. The NG-FMS is interoperable with the future ground based 4DT Planning, Negotiation and Validation (4-PNV) systems, enabling automated Trajectory/Intent Based Operations (TBO/IBO). After the NG-FMS architecture is presented, the key mathematical models describing the trajectory generation and optimisation modes are introduced. A detailed error analysis is performed and the uncertainties affecting the nominal trajectories are studied to obtain the total NG-FMS error budgets. These are compared with the Required Navigation Performance (RNP) values for the various operational flight tasks considered.

Real-Time Trajectory Optimisation Models for Next Generation Air Traffic Management Systems

This paper presents models and algorithms for real-time 4-Dimensional Flight Trajectory (4DT) operations in the next generation Communications, Navigation, Surveillance/Air Traffic Management (CNS/ATM) systems. In particular, the models are employed for multi-objective optimisation of 4DT intents in ground-based 4DT Planning, Negotiation and Validation (4-PNV) systems and in airborne Next Generation Flight Management Systems (NG-FMS). The assumed timeframe convention for offline and online air traffic operations is introduced and discussed. The adopted formulation of the multi-objective 4DT optimisation problem includes a number of environmental objectives and operational constraints. In particular, the paper describes a real-time multi-objective optimisation algorithm and the generalised expression of cost function adopted for penalties associated with specific airspace volumes, accounting for weather models, condensation trails models and noise models.

4 Dimensional trajectory functionalities for air traffic management systems

The research presented in this paper focuses on the conceptual design of an innovative Air Traffic Management (ATM) system featuring automated 4-Dimensional Trajectory (4DT) Planning, Negotiation and Validation (4-PNV) functionalities to enable Intent Based Operations (IBO). In order to meet the demanding requirements set by national and international organisations for the efficiency and environmental sustainability of air transport operations, a multi-objective 4DT optimization algorithm is introduced that represents the core element of the 4DT planning functionality. The 4-PNV system interacts with airborne avionics also developed for 4DT-IBO such as the Next Generation Flight Management System (NG-FMS) on-board manned aircraft and Next Generation Mission Management System (NG-MMS) for Remotely Piloted Aircraft Systems (RPAS). In this article we focus on the 4-PNV algorithms, and specifically on the multi-objective 4DT optimization algorithm for strategic and tactical online operations. Simulation case studies are carried out to test the key system performance metrics such as 4DT computational time in online tactical Terminal Manoeuvring Area (TMA) operations.

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.

Automated ATM System Enabling 4DT-Based Operations

As part of the current initiatives aimed at enhancing safety, efficiency and environmental sustainability of aviation, a significant improvement in the efficiency of aircraft operations is currently pursued. Innovative Communication, Navigation, Surveillance and Air Traffic Management (CNS/ATM) technologies and operational concepts are being developed to achieve the ambitious goals for efficiency and environmental sustainability set by national and international aviation organizations. These technological and operational innovations will be ultimately enabled by the introduction of novel CNS/ATM and Avionics (CNS+A) systems, featuring higher levels of automation. A core feature of such systems consists in the real-time multi-objective optimization of flight trajectories, incorporating all the operational, economic and environmental aspects of the aircraft mission. This article describes the conceptual design of an innovative ground-based Air Traffic Management (ATM) system featuring automated 4-Dimensional Trajectory (4DT) functionalities. The 4DT planning capability is based on the multi-objective optimization of 4DT intents. After summarizing the concept of operations, the top-level system architecture and the key 4DT optimization modules, we discuss the segmentation algorithm to obtain flyable and concisely described 4DT. Simulation case studies in representative scenarios show that the adopted algorithms generate solutions consistently within the timeframe of online tactical rerouting tasks, meeting the set design requirements.

A novel simulation environment for cognitive human factors engineering research

The simulation environment used in cognitive Human Factors Engineering (HFE) research at RMIT University HFE-Lab is presented in this article. The simulation environment consists of Air Traffic Management (ATM) workstations including Unmanned Aircraft System (UAS) Traffic Management (UTM) features as well as pilot/remote pilot stations, including an immersive research flight simulator. Additional modules are used in cognitive HFE research for collecting and processing psycho-physiological data, and for scenario management. An overview of the simulation environment, including the network, modules and tools is presented. An experimental case study involving eye tracking and cardiorespiratory measures is presented to demonstrate the capabilities of the HFE-Lab as a research tool for cognitive ergonomics and HFE research.

CNS+A capabilities for the integration of unmanned aircraft in controlled airspace

In this paper, the system requirements for the integration of Remotely Piloted Aircraft Systems (RPAS) in controlled airspace regions are discussed. The specificities in terms of Air Traffic Management (ATM) level of service, jurisdiction for deconfliction duties and prevalent traffic characteristics are analysed to support the identification of operational and equipage requirements for RPAS developers. Communication, Navigation, Surveillance, ATM and Avionics (CNS+A) equipment play an essential role in airspace regions characterised by high levels of Air Traffic Services (ATS) and a higher probability of traffic conflicts. A denser route structure and a more frequent occurrence of traffic conflicts mandate high CNS performance, as the deconfliction by ATM crucially relies on accurate and reliable CNS information. Notwithstanding, the reduced jurisdiction of aircraft in deconfliction duties also offers an opportunity to RPAS developers, as it relieves the requirements for on-board expert processing.

4-Dimensional trajectory optimisation algorithm for air traffic management systems

This paper presents Multi Objective Trajectory Optimization (MOTO) algorithms that were developed for integration in state-of-the-art Air Traffic Management (ATM) and Air Traffic Flow Management (ATFM) systems. The MOTO algorithms are conceived for the automation-assisted replanning of 4-Dimensional Trajectories (4DT) when unforeseen perturbations arise at strategic and tactical online operational timeframes. The MOTO algorithms take into account updated weather and neighbouring traffic data, as well as the related forecasts from selected sources. Multiple user-defined operational, economic and environmental objectives can be integrated as necessary. Two different MOTO algorithms are developed for future implementation in ATM systems: an en-route variant and a Terminal Manoeuvring Area (TMA) variant. In particular, the automated optimal 4DT replanning algorithm for en-route airspace operations is restricted to constant flight level to avoid violating the current vertical airspace structure. As such, the complexity of the generated trajectories reduces to 2 dimensions plus time (2D+T), which are optimally represented in the present 2D ATM display formats. Departing traffic operations will also significantly benefit from MOTO-4D by enabling steep/continuous climb operations with optimal throttle, reducing perceived noise and gaseous emissions.

4 Dimensional trajectory functionalities for air traffic management systems: Novel flight management system for improved safety and sustainability in the CNS+A context

Avionic system developers are faced with the challenge of researching and introducing innovative technologies that satisfy the requirements arising from the rapid expansion of global air transport while addressing the growing concerns for environmental sustainability of the aviation sector. As a consequence, novel systems are being developed in the Communication, Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) context. The introduction of dedicated software modules in Next Generation Flight Management Systems (NG-FMS), which are the primary providers of automated navigation and guidance services in manned aircraft and Remotely-Piloted Aircraft Systems (RPAS), has the potential to enable the significant advances brought in by time based operations. In this paper, key elements of the NG-FMS architecture are presented that allow the incorporation of 4-Dimensional Trajectory (4DT) planning and optimisation with inclusion of CNS integrity monitoring and augmentation functions in the overall design. The NG-FMS is designed to be fully interoperable with a future ground based 4DT Planning, Negotiation and Validation (4-PNV) system, enabling automated Trajectory/Intent-Based Operations (TBO/IBO). The mathematical models for 4DT planning are presented and the CNS integrity performance criteria are identified for various mission- and safety-critical tasks. Evaluation of the proposed concepts and methodologies is performed through dedicated simulation test case. The results demonstrate the functional capability of the NG-FMS to generate cost-effective trajectory profiles satisfying operational as well as environmental constraints.

Minimizing the Cost of Weather Cells and Persistent Contrail Formation Region Avoidance Using Multi-Objective Trajectory Optimization in Air Traffic Management

Exhaust heat recovery systems are used to make use of otherwise wasted heat from a car engine. The unique system design described herein utilises thermoelectric generators (TEGs) and heat pipes with its key advantage being it is a passive solid state design. The use of these components creates a few design This paper gives the concepts and mathematically models required for the development of the Multi Objective Trajectory Optimization (MOTO) functionalities to be implemented into the next generation of ATM system. MOTO algorithms are introduced whereby data from various sources are utilized to optimize flight paths for various user defined objectives. The algorithms require digital resources of weather, aircraft data, metrological maps and air traffic. These will be used in conjunction with various mathematical models to compute trajectories that minimize various objectives such as fuel, emissions and operational cost. The automated 4D trajectory computation algorithms are restricted to single flight level to not violate the current layered vertical air route structure for the cruise phase of flight. As such the complexity of the generated trajectories reduces to 2 dimensions plus time (2D+T), which are adequately represented in the radar display, and this improves the ATC Operators familiarity in the tactical trajectory management and deconfliction, as control over vertical separation is maintained. This also permits the ATCO to amend the flight level of an optimized trajectory in the traditional manner if necessary. The constant flight level limitation will theoretically produce a sub-optimal flight path however the computed trajectory will remain more efficient than a straight line as the atmospheric winds are exploited to maximize flight speed while reducing fuel burn and emissions.