A research report submitted to the Faculty of Humanities, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Arts (Organisational Psychology), 2017 / The aim of the present study was to utilise a mixed methods design as a means of investigating the relation between job demands, job resources, safety, and burnout in Air Traffic Management (ATM) technicians. It was also of interest to determine participants’ perspectives on the job demands and resources that may be present in their occupational environment, their participation in safety behaviours, and their perceptions regarding their work and safety performance. Non-probability, convenience sampling was employed to acquire the participants of the present research study. Participants included 33 ATM technicians (50.77% response rate) who took part in the quantitative component of the research study and 14 ATM who took part in the interview process. Participants’ ages ranged from 27 to 55 years (M = 38.91; SD = 8.76) and 90.1% were male (n = 30). Jackson and Rothmann’s (2005) original Job Demands-Resources Scale was used for the assessment of the job demands and resources sixteen items were also added to the original JDRS scale. Sixteen items were added to incorporate the possible job resources and demands experienced by ATM technicians, which were separated into the following sub-scales: shifts, weather conditions, travel, and equipment. Schaufeli, Leiter, Maslach, and Jackson’s (1996) Maslach Burnout Inventory-General Survey (MBIGS) was used to assess ATM technicians’ burnout. Safety behaviours were assessed through the integration of items found within two safety behaviour scales developed by Neal and Griffin (2006) and Hofmann and Morgeson (1999). A semi-structured interview process consisting of open-ended questions was used to discuss the following issues: job tasks, job demands, job resources, burnout, job safety, work-family spillover, and job performance. The findings depicted a weak, positive correlation between the perception of job demands and the experience of burnout (r = .376, p < .05) and a weak, negative correlation between the perception of job resources and the experience of burnout (r = -.383, p < .05). Job resources significantly predicted the experience of burnout (β = -.494, p = .002), as did job demands (β = .489, p = .003). A moderate, positive correlation between the perception of job resources and safety behaviours was obtained (r = .514, p < .01). The participants’ perceptions of job resources explained 26.5% of the variance in safety behaviours, (R2= .265, F(1, 31) = 11.16, p < 0.05. ATM technicians took part in the following safety behaviours: they consistently communicated with both management and air traffic controllers as a way of knowing exactly what the problem is before they went to a site, they took part in training programs as a means of keeping up to date with the latest technological knowledge, attended safety meetings, always communicated with management on how to increase safety, and made sure that a first aid kit was always available. ATM technician’s safety and performance appeared to be heavily influenced by their own personal understanding of the occupation’s risks, the weather conditions that take place on each specific site, the safety equipment that is worn, the knowledge of the possible repercussions that may arise from making any mistakes, and their own individual mood or disposition. / XL2018

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In recent years, unmanned aerial vehicles (UAVs) have become a dominant force in the aerospace industry. Recent technological developments have moved these aircraft from remote operation roles to more active response missions. Of particular interest is the possibility of applying UAVs toward solving complex problems in long-endurance missions. Under that belief, the feasibility of utilizing UAVs for wildfire detection and response was investigated in a partnership that included NASA’s Aeronautics Research Mission Directorate and Science Mission Directorate, and the United States Forest Service. Under NASA’s Intelligent Mission Management (IMM) project, research was conducted to develop a mission architecture that would enable use of a high altitude UAV to search for reported wildfires with a separate low altitude UAV supporting ground assets. This research proposes a “straw man” concept incorporating both a High Altitude Long Endurance (HALE) UAV and a Low Altitude Short Endurance (LASE) UAV in a loosely coupled, low cost solution tailored towards wildfire response. This report identifies the communications architecture, algorithms, and required system configuration that meets the outlined goals of the IMM project by mitigating wildfires and addressing the United States Forest Service immediate needs. The end product is a defined parent-child framework capable of meeting all wildfire mission goals. The concept has been implemented in simulation, the results of which are presented in this report.

No description available.

We develop and evaluate two significant modeling concepts within the context of a large-scale Airspace Planning and Collaborative Decision-Making Model (APCDM) and, thereby, enhance its current functionality in support of both strategic and tactical level flight assessments. The first major concept is a new severe weather-modeling paradigm that can be used to assess existing tactical en route flight plan strategies such as the Flight Management System (FMS) as well as to provide rerouting strategies. The second major concept concerns modeling the mediated bartering of slot exchanges involving airline trade offers for arrival/departure slots at an arrival airport that is affected by the Ground Delay Program (GDP), while simultaneously considering issues related to sector workloads, airspace conflicts, as well as overall equity concerns among the airlines. This research effort is part of an $11.5B, 10-year, Federal Aviation Administration (FAA)-sponsored program to increase the U.S. National Airspace (NAS) capacity by 30 percent by the year 2010. Our innovative contributions of this research with respect to the severe weather rerouting include (a) the concept of "Probability-Nets" and the development of discretized representations of various weather phenomena that affect aviation operations; (b) the integration of readily accessible severe weather probabilities from existing weather forecast data provided by the National Weather Service (NWS); (c) the generation of flight plans that circumvent severe weather phenomena with specified probability levels, and (d) a probabilistic delay assessment methodology for evaluating planned flight routes that might encounter potentially disruptive weather along its trajectory. Given a fixed set of reporting stations from the CONUS Model Output Statistics (MOS), we begin by constructing weather-specific probability-nets that are dynamic with respect to time and space. Essential to the construction of the probability-nets are the point-by-point forecast probabilities associated with MOS reporting sites throughout the United States. Connections between the MOS reporting sites form the strands within the probability-nets, and are constructed based upon a user-defined adjacency threshold, which is defined as the maximum allowable great circle distance between any such pair of sites. When a flight plan traverses through a probability-net, we extract probability data corresponding to the points where the flight plan and the probability-net strand(s) intersect. The ability to quickly extract this trajectory-related probability data is critical to our weather-based rerouting concepts and the derived expected delay and related cost computations in support of the decision-making process. Next, we consider the superimposition of a flight-trajectory-grid network upon the probability-nets. Using the U.S. Navigational Aids (Navaids) as the network nodes, we develop an approach to generate flight plans that can circumvent severe weather phenomena with specified probability levels based on determining restricted, time-dependent shortest paths between the origin and destination airports. By generating alternative flight plans pertaining to specified threshold strand probabilities, we prescribe a methodology for computing appropriate expected weather delays and related disruption factors for inclusion within the APCDM model. We conclude our severe weather-modeling research by conducting an economic benefit analysis using a k-means clustering mechanism in concert with our delay assessment methodology in order to evaluate delay costs and system disruptions associated with variations in probability-net refinement-based information. As a flight passes through the probability-net(s), we can generate a probability-footprint that acts as a record of the strand intersections and the associated probabilities from origin to destination. A flight plan's probability-footprint will differ for each level of data refinement, from whence we construct route-dependent scenarios and, subsequently, compute expected weather delay costs for each scenario for comparative purposes. Our second major contribution is the development of a novel slot-exchange modeling concept within the APCDM model that incorporates various practical issues pertaining to the Ground Delay Program (GDP), a principal feature in the FAA's adoption of the Collaborative Decision-Making (CDM) paradigm. The key ideas introduced here include innovative model formulations and several new equity concepts that examine the impact of "at-least, at-most" trade offers on the entire mix of resulting flight plans from respective origins to destinations, while focusing on achieving defined measures of "fairness" with respect to the selected slot exchanges. The idea is to permit airlines to barter assigned slots at airports affected by the Ground Delay Program to their mutual advantage, with the FAA acting as a mediator, while being cognizant of the overall effect of the resulting mix of flight plans on air traffic control sector workloads, collision risk and safety, and equity considerations. We start by developing two separate slot-exchange approaches. The first consists of an external approach in which we formulate a model for generating a set of package-deals, where each package-deal represents a potential slot-exchange solution. These package-deals are then embedded within the APCDM model. We further tighten the model representation using maximal clique cover-based cuts that relate to the joint compatibility among the individual package-deals. The second approach significantly improves the overall model efficiency by automatically generating package-deals as required within the APCDM model itself. The model output prescribes a set of equitable flight plans based on admissible trades and exchanges of assigned slots, which are in addition conformant with sector workload capabilities and conflict risk restrictions. The net reduction in passenger-minutes of delay for each airline is the primary metric used to assess and compare model solutions. Appropriate constraints are included in the model to ensure that the generated slot exchanges induce nonnegative values of this realized net reduction for each airline. In keeping with the spirit of the FAA's CDM initiative, we next propose four alternative equity methods that are predicated on different specified performance ratios and related efficiency functions. These four methods respectively address equity with respect to slot-exchange-related measures such as total average delay, net delay savings, proportion of acceptable moves, and suitable value function realizations. For our computational experiments, we constructed several scenarios using real data obtained from the FAA based on the Enhanced Traffic Management System (ETMS) flight information pertaining to the Miami and Jacksonville Air Route Traffic Control Centers (ARTCC). Through our experimentation, we provide insights into the effect of the different proposed modeling concepts and study the sensitivity with respect to certain key parameters. In particular, we compare the alternative proposed equity formulations by evaluating their corresponding slot-exchange solutions with respect to the net reduction in passenger-minutes of delay for each airline. Additionally, we evaluate and compare the computational-effort performance, under both time limits and optimality thresholds, for each equity method in order to assess the efficiency of the model. The four slot-exchange-based equity formulations, in conjunction with the internal slot-exchange mechanisms, demonstrate significant net savings in computational effort ranging from 25% to 86% over the original APCDM model equity formulation. The model has been implemented using Microsoft Visual C++ and evaluated using a C++ interface with CPLEX 9.0. The overall results indicate that the proposed modeling concepts offer viable tools that can be used by the FAA in a timely fashion for both tactical purposes, as well as for exploring various strategic issues such as air traffic control policy evaluations; dynamic airspace resectorization strategies as a function of severe weather probabilities; and flight plan generation in response to various disruption scenarios. / Ph. D.

We develop a detailed, large-scale, airspace planning and collaborative decision-making model (APCDM), that is part of an $11.5B, 10-year, Federal Aviation Administration (FAA)-sponsored effort to increase U.S. National Airspace (NAS) capacity by 30 percent. Given a set of flights that must be scheduled during some planning horizon, we use a mixed-integer programming formulation to select a set of flight plans from among alternatives subject to flight safety, air traffic control workload, and airline equity constraints. Novel contributions of this research include three-dimensional probabilistic conflict analyses, the derivation of valid inequalities to tighten the conflict safety representation constraints, the development of workload metrics based on average (and its variance from) peak load measures, and the consideration of equity among airline carriers in absorbing the costs related to re-routing, delays, and cancellations. We also propose an improved set of flight plan cost factors for representing system costs and investigating fairness issues by addressing flight dependencies occurring in hubbed operations, as well as market factors such as schedule convenience, reliability, and the timeliness of connections. The APCDM model has potential use for both tactical and strategic applications, such as air traffic control in response to severe weather phenomenon or spacecraft launches, FAA policy evaluation, Homeland Defense contingency planning, and military air campaign planning. The model is tested to consider various airspace restriction scenarios imposed by dynamic severe weather systems and space launch Special Use Airspace (SUA) impositions. The results from this model can also serve to augment the FAA's National Playbook of standardized flight profiles in different disruption-prone regions of the National Airspace. / Ph. D.

The Multiple Remote Tower Center concept (mRTC) is a cutting edge project which allows one air traffic control officer (ATCO) to be in charge of multiple remotely situated airports simultaneously. When implemented, it will revolutionise how air traffic is managed at smaller airports and allow for increased efficiency and decreased operational costs. Consequently, at the time of writing a lot of effort is going into evaluating this new way of air traffic management from a safety perspective. Air traffic management has been defined as an issue maintaining situational awareness and exercising control. This thesis aims to investigate how the phenomenon target fascination affects the ATCOs ability to exercise control over its controlled airspace and maintain its situation awareness. It does so by creating a baseline scenario of work in a mRTC, and then comparing the ATCOs performance in the baseline scenario with its performance in the same corresponding scenario, but with elements of target fascination introduced. The differences in the scenarios are analysed using the Contextual Control Model, the Extended Control Model and a holistic framework for studying situation awareness. The analysis shows that target fascination does affect the ATCOs ability to maintain control, but not radically so, and only for a short period of time. The target fascination forces the ATCO to rely on information in the immediate environment to a higher degree than during regular work, as opposed to making decisions based on a holistic understanding of the situation and high level goals. However, once the understanding of the situation have been re-established, the level of control quickly returns to normal levels. Situation awareness is thus a key concept in maintaining control. The situation awareness analysis show that target fascination affects situation awareness by causing the ATCOs understanding of the situation to become outdated without the ATCOs knowledge. Because of this, there may be developments in the situation that the ATCO is not aware of, which hinders it from acting as it normally would. In some cases an intervention from an external actor or element may be necessary to break the fascination and re-establish the ATCOs understanding for the situation. As soon as the fascination is broken, the ATCO quickly takes steps to re-establish its situation awareness and return to normal operations.

Η τεχνολογία της αναγνώρισης και παρακολούθησης αεροσκαφών βρίσκει ποικίλες εφαρμογές σε όλους τους τομείς της αεροναυσιπλοΐας, πολιτικούς και στρατιωτικούς, από τον έλεγχο και τη ρύθμιση της εναέριας κυκλοφορίας σε πολιτικά αεροδρόμια έως το χειρισμό και την καθοδήγηση αντιαεροπορικών όπλων για στρατιωτικούς σκοπούς (π.χ. το σύστημα TAS του αντιαεροπορικού συστήματος MIM-23B Hawk). Έως σήμερα, γνωστές μέθοδοι υλοποίησης αποτελούν οι ραδιοεντοπιστές (radar), οι υπέρυθρες και οι θερμικές κάμερες, τα οποία είναι εγκατεστημένα σε επίγειους σταθμούς, σε κινούμενες μονάδες και σε αεροσκάφη. Το σύστημα που δημιουργήθηκε και θα παρουσιαστεί στην παρούσα διπλωματική εργασία αποτελεί μια εναλλακτική μέθοδο υλοποίησης της αναγνώρισης και της παρακολούθησης ιπτάμενων αντικειμένων, που εκμεταλλεύεται το οπτικό φάσμα με τη χρήση μιας οπτικής κάμερας ενσωματωμένης σε ένα σερβοκινητήρα. Σε σημεία όπου είναι δύσκολο να εφαρμοσθεί κάποια άλλη τεχνολογία ή σε σημεία που δεν καλύπτονται από άλλες συσκευές ανίχνευσης (π.χ. radar), η συσκευή μας προσφέρει όμοιες υπηρεσίες και συμπληρώνει πιθανά χάσματα ακάλυπτων περιοχών. Συγκεκριμένα, μέσω του λογισμικού που έχει αναπτυχθεί, όταν κάποιος στόχος (αεροσκάφος) εισέλθει στο οπτικό πεδίο της κάμερας, ανιχνεύεται και αναγνωρίζεται. Στη συνέχεια ο σερβοκινητήρας παρακολουθεί τον στόχο τροφοδοτούμενος με δεδομένα της θέσης και της ταχύτητάς του, ενώ βρίσκεται σε συνεχή επικοινωνία με την κάμερα. Όλα τα παραπάνω έχουν αναπτυχθεί ώστε να λειτουργούν σε συνθήκες πραγματικού χρόνου. Παρά την απουσία μιας θεωρητικής παρουσίασης ή μιας ολοκληρωμένης λύσης οπτικής αναγνώρισης και παρακολούθησης αεροσκαφών, η αναζήτηση και μελέτη της διεθνούς βιβλιογραφίας μας έδωσε το θεωρητικό υπόβαθρο για την κατανόηση του προβλήματος και ταυτόχρονα τη δυνατότητα να συνδυάσουμε τεχνικές και μεθόδους για την επίτευξη του στόχου μας. Για την επιτυχή αναγνώριση και παρακολούθηση των στόχων δημιουργήθηκαν διάφορα μοντέλα προσομοίωσης για τον έλεγχο της συμπεριφοράς μεμονομένων χαρακτηριστικών. Συγκεκριμένα, στο υποσύστημα της αναγνώρισης του στόχου μοντελοποιήθηκε αρχικά μια μέθοδος εξαγωγής της θέσης βασισμένη στο χρώμα του στόχου σε περιβάλλον Matlab/Simulink. Στη συνέχεια η ίδια μέθοδος μεταφέρθηκε σε περιβάλλον LabVIEW για να εμπλουτισθεί με διάφορες άλλες μεθόδους βασισμένες σε ένα σύνολο από χαρακτηριστικά που θα αναλυθούν στη συνέχεια. Το τελικό μοντέλο αποτελεί συνδυασμό των μεθόδων του αθροίσματος απολύτων διαφορών, της οπτικής ροής, της εξαγωγής χρωματικών και σχηματικών χαρακτηριστικών, της κανονικοποιημένης εττεροσυσχέτισης και άλλων λογικών μεθόδων και βελτιστοποιήσεων τους. Για την επίτευξη μιας επιτυχυμένης παρακολούθησης ενός “κλειδωμένου” στόχου, δοκιμάστηκαν και έγιναν πολλές προσομοιώσεις με διαφορετικούς τύπους ελεγκτών. Συγκεκριμένα η δυναμική του μοντέλου που δημιουργήθηκε, εξαρτάται από ένα συνδυασμό ελεγκτών θέσεως, ταχύτητας και άλλων παραμέτρων. Αυτά εξασφαλίζουν ένα ευσταθές και γραμμικοποιημένο σύστημα παρακολούθησης, ικανό να παρακολουθήσει οποιοδήποτε στόχο με τη προϋπόθεση ότι τα χαρακτηριστικά του στόχου καθώς και η κατάστασή του (θέση, ταχύτητα κτλ.), ικανοποιούν τις απαιτήσεις του αλγορίθμου αναγνώρισης και είναι μέσα στις εργοστασιακές δυνατότητες του συστήματος. Το μοντέλο αυτό αναπτύχθηκε και υλοποιήθηκε σε περιβάλλον LabVIEW, όπως και οι μετρήσεις και προσομοιώσεις που έγιναν πάνω σε αυτό. Όλες οι παραπάνω μέθοδοι συνεργάζονται και είναι ικανοί να δώσουν ακριβή αποτελέσματα θέσης πραγματικών στόχων κατά τη διάρκεια της ημέρας ακόμα και κάτω από δύσκολες συνθήκες (όπως συννεφιά, χαμηλή φωτεινότητα, παρεμβολή αντικειμένων) σε πραγματικό χρόνο. Η ακραία μεταβολή των περιβαλλοντικών συνθηκών θα επηρρέαζε οποιοδήποτε οπτικό σύστημα, συνεπώς και το παρόν. Περιγραφή των παραγόντων που επηρρεάζουν το σύστημά μας θα γίνει στη συνέχεια. / The technology of aircraft recognition and tracking applies in various applications in all areas of air navigation, civil and military, from air traffic control and regulation at civilian airports to anti-aircraft weapon handling and guidance for military purposes (e.g the TAS system of MIM-23B Hawk anti-aircraft system). To date, known methods of implementation are the radar, infrared and thermal cameras, which are installed at ground stations, in moving plants and aircrafts. The system that was created and is presented in this thesis is an alternative implementation of identifying and tracking flying objects, which operates in the optical spectrum using an optical camera built into a servomotor (pan-tilt unit – PTU). In regions where is difficult for one technology to be applied or in areas that are not covered by other detection devices (e.g. radar), our device offers similar services and complements potential gaps that arise by uncovered areas. Specifically, through the software we developed, when a target (aircraft) enters the field of view of our camera, it is detected and identified. Then the PTU, fed with data of target position and velocity, tracks the aircraft while keeps in constant communication with the camera. All the above have been developed to operate in real time. Despite the lack of a theoretical presentation or a complete solution of optical aircraft recognition and tracking, search and study of literature has given us the theoretical background for understanding the problem and making it possible to combine techniques and methods to achieve our goal. For the successful identification and monitoring of the targets, various simulation models were created to control the behavior of isolated features. Specifically, for the target recognition subsystem a method for extraction of the position based on the color of the target was initially modeled in Matlab/Simulink environment. Then the same method was implemented in LabVIEW to be enriched with several other methods based on a set of features that will be discussed below. The final model is a combination of the sum of absolute differences between two images, the extraction of color and shape profiles, the normalized cross-correlation and other logical methods and their optimizations. In order a successful tracking of a “locked” target to be achieved, there have been many tests and carried out many simulations with different types of controllers. Specifically, the dynamic of the model which was created, depends on a combination of position/velocity controllers and other parameters. These provide a stable and linearized tracking system, capable to follow any target under the condition that the characteristics of the target and its current status (position, speed, etc.) meet the requirements of the recognition algorithm and is within the capabilities of the system. The model was developed and implemented in the LabVIEW environment, as well as measurements and simulations were carried out in it. All these methods work and are able to give accurate results of the position of real targets during the day, even under difficult circumstances (such as clouds, decreased sky brightness etc) in real time. The extreme variation of environmental conditions would affect any optical system and hence could affect ours as well. Description of the factors that affect our system will be presented.

This thesis addresses the problems of collision avoidance and coalition formation of multiple UAVs in high density traffic environments, proposes simple and efficient algorithms as solutions, and discusses their applications in multiple UAV missions. First, the problem of collision avoidance among UAVs is considered and deconfliction algorithms are proposed. The efficacy of the proposed algorithms is tested using simulations involving random flights in high density traffic. Further, the proposed collision avoidance algorithms are implemented using realistic six degree of freedom UAV models. The studies in this thesis show that implementation of the proposed collision avoidance algorithms leads to a safer and efficient operational airspace occupied by multiple UAVs. Next, coalition formation in a search and prosecute mission involving a large number of UAVs and targets is considered. This problem is shown to be NP-hard and a sub-optimal but polynomial time coalition formation strategy is proposed. Simulations are carried out to show that this coalition formation algorithm works well. The coalition formation algorithm is then extended to handle situations where the UAVs have limited communication ranges. Finally, this thesis considers some multiple UAV missions that require the application of collision avoidance and coalition formation techniques. The problem of multiple UAV rendezvous is tackled by using (i) a consensus among the UAVs to attain rendezvous and (ii) the collision avoidance algorithm previously developed for safety. The thesis also considers a search and prosecute mission where the UAVs also have to avoid collisions among one another. In summary, the main contributions of this thesis include (a) novel collision avoidance algorithms, which are conceptually simple and easy to implement, for resolving path conflicts – both planar and three dimensional – in a high density traffic airspace with UAVs in free flight and (b) efficient coalition formation algorithms for search and prosecute task with large number of UAVs and targets where UAVs have limited communication ranges and targets are maneuvering. Simulations to evaluate the performance of algorithms based on these concepts to carry out realistic tasks by UAV swarms are also given.