High performance computing simulator for the performance assessment of trajectory based operations

High performance computing (HPC), both at hardware and software level, has demonstrated significant improve- ments in processing large datasets in a timely manner. However, HPC in the field of air traffic management (ATM) can be much more than only a time reducing tool. It could also be used to build an ATM simulator in which distributed scenarios where decentralized elements (airspace users) interact through a centralized manager in order to generate a trajectory-optimized conflict-free scenario. In this work, we introduce an early prototype of an ATM simulator, focusing on air traffic flow management at strategic, pre-tactical and tactical levels, which allows the calculation of safety and efficiency indicators for optimized trajectories, both at individual and network level. The software architecture of the simulator, relying on a HPC cluster of computers, has been preliminary tested with a set of flights whose trajectory vertical profiles have been optimized according to two different concepts of operations: conventional cruise operations (i.e. flying at constant altitudes and according to the flight levels scheme rules) and continuous climb cruise operations (i.e., optimizing the trajectories with no vertical constraints). The novel ATM simulator has been tested to show preliminary benchmarking results between these two concepts of operations. The simulator here presented can contribute as a testbed to evaluate the potential benefits of future Trajectory Based Operations and to understand the complex relationships among the different ATM key performance areasPeer ReviewedPostprint (published version

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

Synchronization of autonomous objects in discrete event simulation

Autonomous objects in event-driven discrete event simulation offer the potential to combine the freedom of unrestricted movement and positional accuracy through Euclidean space of time-driven models with the computational efficiency of event-driven simulation. The principal challenge to autonomous object implementation is object synchronization. The concept of a spatial blackboard is offered as a potential methodology for synchronization. The issues facing implementation of a spatial blackboard are outlined and discussed

Human Computer Interactions in Next-Generation of Aircraft Smart Navigation Management Systems: Task Analysis and Architecture under an Agent-Oriented Methodological Approach

The limited efficiency of current air traffic systems will require a next-generation of Smart Air Traffic System (SATS) that relies on current technological advances. This challenge means a transition toward a new navigation and air-traffic procedures paradigm, where pilots and air traffic controllers perform and coordinate their activities according to new roles and technological supports. The design of new Human-Computer Interactions (HCI) for performing these activities is a key element of SATS. However efforts for developing such tools need to be inspired on a parallel characterization of hypothetical air traffic scenarios compatible with current ones. This paper is focused on airborne HCI into SATS where cockpit inputs came from aircraft navigation systems, surrounding traffic situation, controllers' indications, etc. So the HCI is intended to enhance situation awareness and decision-making through pilot cockpit. This work approach considers SATS as a system distributed on a large-scale with uncertainty in a dynamic environment. Therefore, a multi-agent systems based approach is well suited for modeling such an environment. We demonstrate that current methodologies for designing multi-agent systems are a useful tool to characterize HCI. We specifically illustrate how the selected methodological approach provides enough guidelines to obtain a cockpit HCI design that complies with future SATS specifications.This work was supported in part by Projects MINECO TEC2011-28626-C02-01/02, by program CENIT-ATLANTIDA (cofinanced by Indra and Boeing R&TE), and by ULPGC Precompetitive Research Project (ULPGC Own Program).Publicad

Management by Trajectory: Trajectory Management Study Report

In order to realize the full potential of the Next Generation Air Transportation System (NextGen), improved management along planned trajectories between air navigation service providers (ANSPs) and system users (e.g., pilots and airline dispatchers) is needed. Future automation improvements and increased data communications between aircraft and ground automation would make the concept of Management by Trajectory (MBT) possible

Symbolic representation of scenarios in Bologna airport on virtual reality concept

This paper is a part of a big Project named Retina Project, which is focused in reduce the workload of an ATCO. It uses the last technological advances as Virtual Reality concept. The work has consisted in studying the different awareness situations that happens daily in Bologna Airport. It has been analysed one scenario with good visibility where the sun predominates and two other scenarios with poor visibility where the rain and the fog dominate. Due to the study of visibility in the three scenarios computed, the conclusion obtained is that the overlay must be shown with a constant dimension regardless the position of the aircraft to be readable by the ATC and also, the frame and the flight strip should be coloured in a showy colour (like red) for a better control by the ATCO

Analysis of Automated Aircraft Conflict Resolution and Weather Avoidance

This paper describes an analysis of using trajectory-based automation to resolve both aircraft and weather constraints for near-term air traffic management decision making. The auto resolution algorithm developed and tested at NASA-Ames to resolve aircraft to aircraft conflicts has been modified to mitigate convective weather constraints. Modifications include adding information about the size of a gap between weather constraints to the routing solution. Routes that traverse gaps that are smaller than a specific size are not used. An evaluation of the performance of the modified autoresolver to resolve both conflicts with aircraft and weather was performed. Integration with the Center-TRACON Traffic Management System was completed to evaluate the effect of weather routing on schedule delays

AMANDA V3: Toward a Common Workspace between Air Traffic Controllers

International audienceThis paper presents the different tools developed in the LAMIH, in optics to assist air traffic controllers in their tasks, to decrease their workloads, and to enable them to support the ceaseless increase of the traffic. Common philosophy to all these tools is to preserve the controllers in the loop: we do not try to develop tools entirely automatic. The platform AMANDA V2 made it possible to set up and to evaluate a common workspace, which allows the two controllers of a sector to cooperate and to share the same representation of their traffic and conflicts. This space maintains common situation awareness. This tool was very appreciated by professional controllers and we now wish to extend this principle to the cooperation between two planning controllers of two adjacent sectors. It is what we present in this paper which begins with a presentation of the ATC then a point on the platforms of the laboratory and particularly AMANDA V2, to conclude with the objectives of AMANDA V3

Trajectory Specification Language for Air Traffic Control

Trajectory Specification is a method of specifying aircraft trajectories with tolerances such that the position at any instant in time is constrained to a precisely defined bounding space. The bounding space at any instant in time is defined by tolerances relative to a reference trajectory that specifies position as a function of time. The tolerances are dynamic and are based on the aircraft navigation capabilities and the traffic situation. This paper proposes a standard Trajectory Specification Language (TSL) based on the Extensible Markup Language (XML) to represent these specifications and to communicate them by datalink. The language can be used to downlink trajectory requests from air to ground and to uplink trajectory assignments from ground to air. The XML format can be converted to binary for operational use, if necessary, using Efficient XML Interchange (EXI) or Abstract Syntax Notation (ASN.1)

Enhancing Trajectory-Based Operations for UAVs through Hexagonal Grid Indexing: A Step towards 4D Integration of UTM and ATM

Aviation is expected to face a surge in the number of manned aircraft and drones in the coming years, making it necessary to integrate Unmanned Aircraft System Traffic Management (UTM) into Air Traffic Management (ATM) to ensure safe and efficient operations. This research proposes a novel hexagonal grid-based 4D trajectory representation framework for unmanned aerial vehicle (UAV) traffic management that overcomes the limitations of existing square/cubic trajectory representation methods. The proposed model employs a hierarchical indexing structure using hexagonal cells, enabling efficient ground based strategic conflict detection and conflict free 4D trajectory planning. Additionally, the use of Hexagonal Discrete Global Grid Systems provides a more accurate representation of UAV trajectories, improved sampling efficiency and higher angular resolution. The proposed approach can be used for predeparture conflict free 4D trajectory planning, reducing computational complexity and memory requirements while improving the accuracy of strategic trajectory conflict detection. The proposed framework can also be extended for air traffic flow management trajectory planning, Air Traffic Control (ATC) workload measurement, sector capacity estimation, dynamics airspace sectorization using hexagonal sectors and traffic density calculation, contributing to the development of an efficient UTM system, and facilitating the integration of UAVs into the national airspace system with AT