Evaluation of remain well clear and collision avoidance for drones

One of the cornerstones that should enable inserting unmanned aircraft into the airspace is the development of Detect and Avoid (DAA) systems. DAA systems will improve the Remote Pilot (RP) situational awareness by means of electronic conspicuity devices, providing them with the necessary means to Remain Well Clear (RWC) from other traffic and, if necessary, avoid Mid-Air collisions (MAC). DAA systems will compensate for the loss of a pilot on board, which drastically reduces the capacity to keep a safe separation from traffic, making current Rules of the Air very challenging to achieve. Given the growing popularity of drone operations for commercial and recreational purposes, new standards should include them in the not-too-distant future. Since current DAA standards and algorithms (DO-365 and ED-258) are being developed targeting large, mostly military Remotely Piloted Aircraft Systems (RPAS), this project proposes a new set of detection volumes and alert thresholds for U-Space users according to an aircraft type classification. This will allow adapting the existing DAA algorithms to small drones, complying with the new European framework of services and applications for drones (U-Space). Because testing new safety nets (such as new DAA algorithms) on real aircraft would be dangerous and inadequate, radar reports and computer-based simulations allow for a risk-free and faster evaluation of safety net performances. Due to the current lack of real drone radar tracks, this project has developed a multi-rotor drone encounter generator tool (called DEG). This software is able to generate a large number of synthetic pairwise quadcopter drone conflict tracks, simulating the instant prior to a MAC. The way trajectories are generated by DEG strongly depends on the type of operation being flown (inspection/surveillance flights and logistic flights) and the aircraft type (including a DJI F450 and a faster version called DJI F450 FAST). The results of this project include a drone conflict trajectory example generated with DEG and an investigation of the performance and effectiveness of the DEG tool using a tailored existing DAA algorithm (DAIDALUS).Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructur

An Airspace Simulator for Separation Management Research

Air Traffic Management (ATM) systems are undergoing a period of major transformation and modernisation, requiring and enabling new separation management (SM) methods. Many novel SM functions, roles and concepts are being explored using ATM simulators. Commercial simulators are capable, high-fidelity tools, but tend to be complex and inaccessible. The Airspace Simulator is a fast-time, discrete event simulator originally designed for exploratory ATM research. This thesis describes the redevelopment of the Airspace Simulator into a simulation platform better suited for researching and evaluating SM in future airspace. The Airspace Simulator-II has the advantage of new functionality and greater fidelity, while remaining high-speed, accessible and readily adaptable. The simulator models FMS-like spherical earth navigation and autopilot flight control with an average cross track error of 0.05 nmi for waypoint-defined routes in variable wind-fields. Trajectories are computed using the BADA v3.8 tabulated database to model the performance of 318 aircraft types. The simulator was demonstrated with up to 4000 total aircraft, and trajectories for 300 simultaneous aircraft were computed over 900 times faster than real-time. Datalink and radio-telephony communications are modelled between the air traffic and ATM systems. Surveillance is provided through ADS-B-like broadcasts, and an algorithm was developed to automatically merge instructions from conflict resolution systems with existing flight plans. Alternate communication, navigation, and separation modes were designed to permit the study of mixed-mode operations. Errors due to wind, navigational wander, communication latencies, and localised information states are modelled to facilitate research into the robustness of SM systems. The simulator incorporates a traffic visualisation tool and was networked to conflict detection and resolution software through a TCP/IP connection. A scenario generator was designed to automatically prepare flight plans for a large variety of two-aircraft encounters to support stochastic SM experiments. The simulator, scenario generator, and resolver were used for the preliminary analysis of a novel concept for automated SM over radio-telephony using progressive track angle vectoring

Full Automation of Air Traffic Management in High Complexity Airspace

The thesis is that automation of en-route Air Traffic Management in high complexity airspace can be achieved with a combination of automated tactic planning in a look-ahead time horizon of up to two hours complemented with automated tactic conflict resolution functions. The literature review reveals that no significant results have yet been obtained and that full automation could be approached with a complementary integration of automated tactic resolutions AND planning. The focus shifts to ‘planning for capacity’ and ‘planning for resolution’ and also – but not only – for ‘resolution’. The work encompasses a theoretical part on planning, and several small scale studies of empirical, mathematical or simulated nature. The theoretical part of the thesis on planning under uncertainties attempts to conceive a theoretical model which abstracts specificities of planning in Air Traffic Management into a generic planning model. The resulting abstract model treats entities like the planner, the strategy, the plan and the actions, always considering the impact of uncertainties. The work innovates in specifying many links from the theory to the application in planning of air traffic management, and especially the new fields of tactical capacity management. The second main part of the thesis comprises smaller self-containing works on different aspects of the concept grouped into a section on complexity, another on tactic planning actions, and the last on planners. The produced studies are about empirical measures of conflicts and conflict densities to get a better understanding of the complexity of air traffic; studies on traffic organisation using tactical manoeuvres like speed control, lateral offset and tactical direct using fast time simulation; and studies on airspace design like sector optimisation, dynamic sectorisation and its optimisation using optimisation techniques. In conclusion it is believed that this work will contribute to further automation attempts especially by its innovative focus which is on planning, base on a theory of planning, and its findings already influence newer developments

A causal model to analyze aircraft collision avoidance deadlock scenarios

[Abstract] Continuous increase in the traffic density over the certain en-route sectors provokes many situations in which a loss of separation minima (SM) between two aircraft occurs. Although, this loss is predicted well in advance, giving a proper look-ahead time (LAT) for a detection function, the resolution of such an event may lead to a new conflict situation due to dynamics of surrounding traffic aircraft. A multiagent system framework can deal with these cases. This work presents three different complexity indicators that can be used to shape the social behavior of the agents. Simulation results show that the proposed indicators can suggest drastically different nature of the same ecosystem, therefore further investigation of the correlation of the proposed indicators to the actual complexity is necessary.Ministerio de Economía y Competitividad; TIN2014-56919-C3-1-

Cooperative and non-cooperative sense-and-avoid in the CNS+A context: a unified methodology

A unified approach to cooperative and noncooperative Sense-and-Avoid (SAA) is presented that addresses the technical and regulatory challenges of Unmanned Aircraft Systems (UAS) integration into nonsegregated airspace. In this paper, state-of-the-art sensor/system technologies for cooperative and noncooperative SAA are reviewed and a reference system architecture is presented. 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) system is performed based on Boolean Decision Logics (BDL) to support trusted autonomous operations during all flight phases. The BDL adoption allows for a dynamic reconfiguration of the SAA architecture, based on the current error estimates of navigation and tracking sensors/systems. The significance of this approach is discussed in the Communication, Navigation and Surveillance/Air Traffic Management and Avionics (CNS+A) context, with a focus on avionics and ATM certification requirements. Additionally, the mathematical models employed in the SAA Unified Method (SUM) to compute the overall uncertainty volume in the airspace surrounding an intruder/obstacle are described. In the presented methodology, navigation and tracking errors affecting the host UAS platform and intruder sensor measurements are translated 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. The results confirm the validity of the proposed unified methodology providing a pathway for certification of SAA systems that typically employ a suite of non-cooperative sensors and/or cooperative systems

Visual flight rules-based collision avoidance systems for UAV flying in civil aerospace

The operation of Unmanned Aerial Vehicles (UAVs) in civil airspace is restricted by the aviation authorities, which require full compliance with regulations that apply for manned aircraft. This paper proposes control algorithms for a collision avoidance system that can be used as an advisory system or a guidance system for UAVs that are flying in civil airspace under visual flight rules. A decision-making system for collision avoidance is developed based on the rules of the air. The proposed architecture of the decision-making system is engineered to be implementable in both manned aircraft and UAVs to perform different tasks ranging from collision detection to a safe avoidance manoeuvre initiation. Avoidance manoeuvres that are compliant with the rules of the air are proposed based on pilot suggestions for a subset of possible collision scenarios. The proposed avoidance manoeuvres are parameterized using a geometric approach. An optimal collision avoidance algorithm is developed for real-time local trajectory planning. Essentially, a finite-horizon optimal control problem is periodically solved in real-time hence updating the aircraft trajectory to avoid obstacles and track a predefined trajectory. The optimal control problem is formulated in output space, and parameterized by using B-splines. Then the optimal designed outputs are mapped into control inputs of the system by using the inverse dynamics of a fixed wing aircraft

Design and preliminary pilot assessment of a directive runway conflict alerting and resolution system

The work described in this paper was carried out collaboratively between the Department of Electronic Systems Engineering of the University of Malta and Cranfield University’s Department of Aerospace Engineering and Department of Systems Engineering and Human Factors as part of the FLYSAFE project, funded under EC Framework Programme 6 (AIP4-CT-2005-516167).As runway incursions continue to occur, a radical change is required in the technique used for runway conflict mitigation. This paper presents the concept of an airborne runway conflict alerting and resolution system that generates directive alerts to the crew in order to instruct them on the action that should be taken to resolve the conflict. The system proposed utilises aircraft performance calculations to evaluate the viability of potential escape manoeuvres that could avert a collision as the basis of directing the crew into taking the safest action. A preliminary pilot assessment of the directive alerting philosophy has been carried out to qualitatively assess crew acceptance of this novel alerting philosophy in runway conflict mitigation.peer-reviewe

EEG-based cognitive control behaviour assessment: an ecological study with professional air traffic controllers

Several models defining different types of cognitive human behaviour are available. For this work, we have selected the Skill, Rule and Knowledge (SRK) model proposed by Rasmussen in 1983. This model is currently broadly used in safety critical domains, such as the aviation. Nowadays, there are no tools able to assess at which level of cognitive control the operator is dealing with the considered task, that is if he/she is performing the task as an automated routine (skill level), as procedures-based activity (rule level), or as a problem-solving process (knowledge level). Several studies tried to model the SRK behaviours from a Human Factor perspective. Despite such studies, there are no evidences in which such behaviours have been evaluated from a neurophysiological point of view, for example, by considering brain activity variations across the different SRK levels. Therefore, the proposed study aimed to investigate the use of neurophysiological signals to assess the cognitive control behaviours accordingly to the SRK taxonomy. The results of the study, performed on 37 professional Air Traffic Controllers, demonstrated that specific brain features could characterize and discriminate the different SRK levels, therefore enabling an objective assessment of the degree of cognitive control behaviours in realistic setting