In this study an ecosystemic and social constructionist approach is used to understand the meanings and perceptions held by working mothers in relation to their experiences with the childcare and organisation settings. These meanings are described in terms of the influence of wider social discourses, personal epistemological assumptions, tacit knowledge, past experiences and current contexts. The working mothers, together with the researcher, form a linguistic system in which meanings about motherhood, employer-support and childcare arrangements are co-constructed and shared. The relationships between the working mothers and the researcher are not only observed within a linguistic context, but also within the ecosystemic view of mutual reciprocity, self-referentiality and double description. A qualitative and naturalistic research methodology is followed to describe the emergent design and the grounded theory. Based on the qualitative paradigm, the conclusions drawn at the end of the study are idiographic and reflective. / Psychology / M.A.(Clinical Psychology)

The development of Advanced Driver Assistance Systems and autonomous driving is one of the main research fields in the area of vehicle development today. Initially the research in this area focused on analyzing and predicting driving maneuvers on highways. Nowadays, a vast amount of research focuses on urban areas as well. Driving maneuvers in urban areas are more complex and therefore more difficult to predict than driving maneuvers on highways. The goals of predicting and understanding driving maneuvers are to reduce accidents, to improve traffic density, and to develop reliable algorithms for autonomous driving. Driving behavior during different driving maneuvers such as turning at intersections, emergency braking or lane changes are analyzed. This thesis focuses on the driving behavior around lane changes and thus the prediction of lane changes in the urban area is applied with an Echo State Network. First, existing methods with a special focus on input variables and results were evaluated to derive input variables with regard to lane change and no lane change sequences. The data for this first analyses were obtained from a naturalistic driving study. Based on theses results the final set of variables (steering angle, turn signal and gazes to the left and right) was chosen for further computations. The parameters of the Echo State Network were then optimized using the data of the naturalistic driving study and the final set of variables. Finally, left and right lane changes were predicted. Furthermore, the Echo State Network was compared to a feedforward neural network. The Echo State Network could predict left and right lane changes more successful than the feedforward neural network. / Fahrerassistenzsysteme und Algorithmen zum autonomen Fahren stellen ein aktuelles Forschungsfeld im Bereich der Fahrzeugentwicklung dar. Am Anfang wurden vor allem Fahrmanöver auf der Autobahn analysiert und vorhergesagt, mittlerweile hat sich das Forschungsfeld auch auf den urbanen Verkehr ausgeweitet. Fahrmanöver im urbanen Raum sind komplexer als Fahrmanöver auf Autobahnen und daher schwieriger vorherzusagen. Ziele für die Vorhersage von Fahrmanövern sind die Reduzierung von Verkehrsunfällen, die Verbesserung des Verkehrsflusses und die Entwicklung von zuverlässigen Algorithmen für das autonome Fahren. Um diese Ziele zu erreichen, wird das Fahrverhalten bei unterschiedlichen Fahrmanövern analysiert, wie z.B. beim Abbiegevorgang an Kreuzungen, bei der Notbremsung oder beim Spurwechsel. In dieser Arbeit wird der Spurwechsel im urbanen Straßenverkehr mit einem Echo State Network vorhergesagt. Zuerst wurden existierende Methoden zur Spurwechselvorhersage bezogen auf die Eingaben und die Ergebnisse bewertet, um danach die spurwechselbezogenen Variableneigenschaften bezüglich Spurwechsel- und Nicht-Spurwechselsequenzen zu analysieren. Die Daten, die Basis für diese ersten Untersuchungen waren, stammen aus einer Realfahrstudie. Basierend auf diesen Resultaten wurden die finalen Variablen (Lenkwinkel, Blinker und Blickrichtung) für weitere Berechnungen ausgewählt. Mit den Daten aus der Realfahrstudie und den finalen Variablen wurden die Parameter des Echo State Networks optimiert und letztendlich wurden linke und rechte Spurwechsel vorhergesagt. Zusätzlich wurde das Echo State Network mit einem vorwärtsgerichteten neuronalen Netz verglichen. Das Echo State Network konnte linke und rechte Spurwechsel erfolgreicher vorhersagen als das vorwärtsgerichtete neuronale Netz.

Since the turn of the millennium, a large number of computational models of visual salience have been put forward. How best to evaluate a given model's ability to predict where human observers fixate in images of real-world scenes remains an open research question. Assessing the role of spatial biases is a challenging issue; this is particularly true when we consider the tendency for high-salience items to appear in the image center, combined with a tendency to look straight ahead (“central bias”). This problem is further exacerbated in the context of model comparisons, because some—but not all—models implicitly or explicitly incorporate a center preference to improve performance. To address this and other issues, we propose to combine a-priori parcellation of scenes with generalized linear mixed models (GLMM), building upon previous work. With this method, we can explicitly model the central bias of fixation by including a central-bias predictor in the GLMM. A second predictor captures how well the saliency model predicts human fixations, above and beyond the central bias. By-subject and by-item random effects account for individual differences and differences across scene items, respectively. Moreover, we can directly assess whether a given saliency model performs significantly better than others. In this article, we describe the data processing steps required by our analysis approach. In addition, we demonstrate the GLMM analyses by evaluating the performance of different saliency models on a new eye-tracking corpus. To facilitate the application of our method, we make the open-source Python toolbox “GridFix” available.

Indiana University-Purdue University Indianapolis (IUPUI) / Pedestrian and vehicle interaction analysis in a naturalistic driving environment can provide useful information for designing vehicle-pedestrian crash warning/mitigation systems. Many researchers have used crash data to understand and study pedestrian behaviors and interactions between vehicles and pedestrian during crash. However, crash data may not provide detailed pedestrian-vehicle interaction information for us. In this thesis, we designed an automatic pedestrian tracking and status analysis method to process and study pedestrian and vehicle interactions. The proposed pedestrian tracking and status analysis method includes pedestrian detection, pedestrian tracking and pedestrian status analysis modules. The main contributions of this thesis are: we designed a new pedestrian tracking method by learning the pedestrian appearance and also their motion pattern. We designed a pedestrian status estimation method by using our tracking results and thus helped estimate the possibility of collision. Our preliminary experiment results using naturalistic driving data showed promising results.

Technology pervades our daily living, and is increasingly integrated into the vehicle – directly affecting driving. On the one hand technology such as cell phones provoke driver distraction and inattention, whereas, on the other hand, Advanced Driver Assistance Systems (ADAS) support the driver in the driving task. The question is, can a driver successfully adapt to the ever growing technological advancements? Thus, this thesis aimed at improving safe driver behaviour by understanding the underlying psychological mechanisms that influence behavioural change. Previous research on ADAS and human attention was reviewed in the context of driver behavioural adaptation. Empirical data from multiple data sources such as driving performance data, visual behaviour data, video footage, and subjective data were analyzed to evaluate two ADAS (a brake-capacity forward collision warning system, B-FCW, and a Visual Distraction Alert System, VDA-System). Results from a field operational test (EuroFOT) showed that brake-capacity forward collision warnings lead to immediate attention allocation toward the roadway and drivers hit the brake, yet change their initial response later on by directing their eyes toward the warning source in the instrument cluster. A similar phenomenon of drivers changing initial behaviour was found in a driving simulator study assessing a Visual Distraction Alert System. Analysis showed that a Visual Distraction Alert System successfully assists drivers in redirecting attention to the relevant aspects of the driving task and significantly improves driving performance. The effects are discussed with regard to behavioural adaptation, calibration and system acceptance. Based on these findings a novel assessment for human-machine-interaction (HMI) of ADAS was introduced. Based on the contribution of this thesis and previous best-practices, a holistic safety management model on accident prevention strategies (before, during and after driving) was developed. The DO-IT BEST Feedback Model is a comprehensive feedback strategy including driver feedback at various time scales and therefore is expected to provide an added benefit for distraction and inattention prevention. The central contributions of this work are to advance research in the field of traffic psychology in the context of attention allocation strategies, and to improve the ability to design future safety systems with the human factor in focus. The thesis consists of the introduction of the conducted research, six publications in full text and a comprehensive conclusion of the publications. In brief this thesis intends to improve safe driver behaviour by understanding the underlying psychological mechanisms that influence behavioral change, thereby resulting in more attention allocation to the forward roadway, and improved vehicle control.:Abstract i Zusammenfassung iii List of included publications v Acknowledgements vii Previously published work ix Table of contents xi Preface xii 1 Chapter 1 Introduction 1 1.1 Outline 1 1.2 Objectives 2 1.3 Background 8 1.3.1 Behavioural adaption to ADAS 8 1.3.2 Driver distraction and inattention 9 2 Chapter 2 Paper I 23 3 Chapter 3 Paper II 47 4 Chapter 4 Paper III 61 5 Chapter 5 Paper IV 91 6 Chapter 6 Paper V 117 7 Chapter 7 Paper VI 143 8 Chapter 8 Conclusions and discussion 161 8.1. Contributions 161 8.2. Implications 171 8.3. Limitations and research needs 173 9 References 177 Curriculum Vitae 199 Eidesstattliche Erklärung 201 / Technologie durchdringt unser tägliches Leben und ist zunehmend integriert in Fahrzeuge – das Resultat sind veränderte Anforderungen an Fahrzeugführer. Einerseits besteht die Gefahr, dass er durch die Bedienung innovativer Technologien (z.B. Mobiltelefone) unachtsam wird und visuell abgelenkt ist, andererseits kann die Nutzung von Fahrerassistenzsystemen die den Fahrer bei der Fahraufgabe unterstützten einen wertvollen Beitrag zur Fahrsicherheit bieten. Die steigende Aktualität beider Problematiken wirft die Frage auf: "Kann der Fahrer sich erfolgreich dem ständig wachsenden technologischen Fortschritt anpassen?" Das Ziel der vorliegenden Arbeit ist der Erkenntnisgewinn zur Verbesserung des Fahrverhaltens indem der Verhaltensänderungen zugrunde liegende psychologische Mechanismen untersucht werden. Eine Vielzahl an Literatur zu Fahrerassistenzsystemen und Aufmerksamkeitsverteilung wurde vor dem Hintergrund von Verhaltensanpassung der Fahrer recherchiert. Daten mehrerer empirischer Quellen, z. B. Fahrverhalten, Blickbewegungen, Videomitschnitte und subjektive Daten dienten zur Datenauswertung zweier Fahrerassistenzsysteme. Im Rahmen einer Feldstudie zeigte sich, dass Bremskapazitäts-Kollisionswarnungen zur sofortigen visuellen Aufmerksamkeitsverteilung zur Fahrbahn und zum Bremsen führen, Fahrer allerdings ihre Reaktion anpassen indem sie zur Warnanzeige im Kombinationsinstrument schauen. Ein anderes Phänomen der Verhaltensanpassung wurde in einer Fahrsimulatorstudie zur Untersuchung eines Ablenkungswarnsystems, das dabei hilft die Blicke von Autofahrern stets auf die Straße zu lenken, gefunden. Diese Ergebnisse weisen nach, dass solch ein System unterstützt achtsamer zu sein und sicherer zu fahren. Die vorliegenden Befunde wurden im Zusammenhang zu Vorbefunden zur Verhaltensanpassung zu Fahrerassistenzsystemen, Fahrerkalibrierung und Akzeptanz von Technik diskutiert. Basierend auf den gewonnenen Erkenntnissen wurde ein neues Vorgehen zur Untersuchung von Mensch- Maschine-Interaktion eingeführt. Aufbauend auf den Resultaten der vorliegenden Arbeit wurde ein ganzheitliches Modell zur Fahrsicherheit und -management, das DO-IT BEST Feedback Modell, entwickelt. Das Modell bezieht sich auf multitemporale Fahrer-Feedbackstrategien und soll somit einen entscheidenen Beitrag zur Verkehrssicherheit und dem Umgang mit Fahrerunaufmerksamkeit leisten. Die zentralen Beiträge dieser Arbeit sind die Gewinnung neuer Erkenntnisse in den Bereichen der Angewandten Psychologie und der Verkehrspsychologie in den Kontexten der Aufmerksamkeitsverteilung und der Verbesserung der Gestaltung von Fahrerassistenzsystemen fokusierend auf den Bediener. Die Dissertation besteht aus einem Einleitungsteil, drei empirischen Beiträgen sowie drei Buchkapiteln und einer abschliessenden Zusammenfassung.:Abstract i Zusammenfassung iii List of included publications v Acknowledgements vii Previously published work ix Table of contents xi Preface xii 1 Chapter 1 Introduction 1 1.1 Outline 1 1.2 Objectives 2 1.3 Background 8 1.3.1 Behavioural adaption to ADAS 8 1.3.2 Driver distraction and inattention 9 2 Chapter 2 Paper I 23 3 Chapter 3 Paper II 47 4 Chapter 4 Paper III 61 5 Chapter 5 Paper IV 91 6 Chapter 6 Paper V 117 7 Chapter 7 Paper VI 143 8 Chapter 8 Conclusions and discussion 161 8.1. Contributions 161 8.2. Implications 171 8.3. Limitations and research needs 173 9 References 177 Curriculum Vitae 199 Eidesstattliche Erklärung 201

The development of driver assistance and automated vehicle control is in process and finds its way more and more into urban traffic environments. Here, the complexity of traffic situations is highly challenging and requires system approaches to comprehend such situations. The key element is the process of situation assessment to identify critical situations in advance and derive adequate warning and intervention strategies. This thesis introduces a system approach to establish a situation assessment process with the focus on the prediction of the driver intention. The system design is based on the Situation Awareness model by Endsley. Further, a prediction algorithm is created using Hidden Markov Models. To define the parameters of the models, an existing database is used and previously analyzed to identify reasonable variables that indicate an intended driving direction while approaching the intersection. Here, vehicle dynamics are used instead of driver inputs to enable a further extension of the prediction, i.e.\\ to predict the driving intention of other vehicles detected by sensors. High prediction rates at temporal distances of several seconds before entering the intersection are accomplished. The prediction is integrated in a system for situation assessment including an intersection model. A Matlab tool is created with an interface to the vehicle CAN bus and the intersection modeling which uses digital map data to establish a representation of the intersection. To identify differences and similarities in the process of approaching an intersection dependent on the intersection shape and regulation, a naturalistic driving study is conducted. Here, the distance to the intersection and velocity is observed on driver inputs related to the upcoming intersection (leaving the gas pedal, pushing the brake, using the turn signal). The findings are used to determine separate prediction models dependent on shape and regulation of the upcoming intersection. The system runs in real-time and is tested in a real traffic environment.:Contents List of Figures Acronyms 1 Introduction 1.1 Motivation 1.2 Outline 2 Fundamentals 2.1 Traffic Intersections 2.2 Situation Assessment 2.3 Prediction of Driver Intention 2.3.1 Methods Overview 2.3.2 Hidden Markov Models 2.4 Localization 3 Driving Behavior 3.1 Data Analysis 3.1.1 Data selection and processing 3.1.2 Results 3.1.3 Conclusion 3.2 Naturalistic Driving Study 3.2.1 Background 3.2.2 Methods 3.2.3 Results 3.2.4 Discussion and Conclusion 4 Prediction Algorithm 4.1 Framework 4.2 Input data 4.3 Evaluation 4.4 Validation 4.5 Conclusion 5 System Approach 5.1 Sensing 5.2 Situation analysis 5.3 Prediction 5.3.1 Implementation 5.3.2 Graphical User Interface (GUI) 5.3.3 Testing and Outlook 6 Conclusion and Outlook Bibliography / Die Entwicklung von Fahrerassistenz und automatisiertem Fahren ist in vollem Gange und entwickelt sich zunehmend in Richtung urbanen Verkehrsraum. Hier stellen besonders komplexe Verkehrssituationen sowohl für den Fahrer als auch für Assistenzsysteme eine Herausforderung dar. Zur Bewältigung dieser Situationen sind neue Systemansätze notwendig, die eine Situationsanalyse und -bewertung beinhalten. Dieser Prozess der Situationseinschätzung ist der Schlüssel zum Erkennen von kritischen Situationen und daraus abgeleiteten Warnungs- und Eingriffsstrategien. Diese Arbeit stellt einen Systemansatz vor, welcher den Prozess der Situationseinschätzung abbildet mit einem Fokus auf die Prädiktion der Fahrerintention. Das Systemdesign basiert dabei auf dem Situation Awareness Model von Endsley. Der Prädiktionsalgorithmus ist mit Hilfe von Hidden Markov Modellen umgesetzt. Zur Bestimmung der Modellparameter wurde eine existierende Datenbasis genutzt und zur Bestimmung von relevanten Variablen für die Prädiktion der Fahrtrichtung während der Kreuzungsannäherung analysiert. Dabei wurden Daten zur Fahrdynamik ausgewählt anstelle von Fahrereingaben um die Prädiktion später auf externe Fahrzeuge mittels Sensorinformationen zu erweitern. Es wurden hohe Prädiktionsraten bei zeitlichen Abständen von mehreren Sekunden bis zum Kreuzungseintritt erzielt. Die Prädiktion wurde in das System zur Situationseinschätzung integriert. Weiterhin beinhaltet das System eine statische Kreuzungsmodellierung. Dabei werden digitale Kartendaten genutzt um eine Repräsentation der Kreuzung und ihrer statischen Attribute zu erzeugen und die der Kreuzungsform entsprechenden Prädiktionsmodelle auszuwählen. Das Gesamtsystem ist als Matlab Tool mit einer Schnittstelle zum CAN Bus implementiert. Weiterhin wurde eine Fahrstudie zum natürlichen Fahrverhalten durchgeführt um mögliche Unterschiede und Gemeinsamkeiten bei der Annäherung an Kreuzungen in Abhängigkeit der Form und Regulierung zu identifizieren. Hierbei wurde die Distanz zur Kreuzung und die Geschwindigkeit bei Fahrereingaben im Bezug zur folgenden Kreuzung gemessen (Gaspedalverlassen, Bremspedalbetätigung, Blinkeraktivierung). Die Ergebnisse der Studie wurden genutzt um die Notwendigkeit verschiedener Prädiktionsmodelle in Abhängigkeit von Form der Kreuzung zu bestimmen. Das System läuft in Echtzeit und wurde im realen Straßenverkehr getestet.:Contents List of Figures Acronyms 1 Introduction 1.1 Motivation 1.2 Outline 2 Fundamentals 2.1 Traffic Intersections 2.2 Situation Assessment 2.3 Prediction of Driver Intention 2.3.1 Methods Overview 2.3.2 Hidden Markov Models 2.4 Localization 3 Driving Behavior 3.1 Data Analysis 3.1.1 Data selection and processing 3.1.2 Results 3.1.3 Conclusion 3.2 Naturalistic Driving Study 3.2.1 Background 3.2.2 Methods 3.2.3 Results 3.2.4 Discussion and Conclusion 4 Prediction Algorithm 4.1 Framework 4.2 Input data 4.3 Evaluation 4.4 Validation 4.5 Conclusion 5 System Approach 5.1 Sensing 5.2 Situation analysis 5.3 Prediction 5.3.1 Implementation 5.3.2 Graphical User Interface (GUI) 5.3.3 Testing and Outlook 6 Conclusion and Outlook Bibliography

This dissertation set out to understand the decision processes used by decision makers in adversarial environment by setting up an adversarial decision making microworld, as an experimental platform, using a real time strategy (RTS) game called Rise of Nations (RON). The specific objectives of this dissertation were: 1.Contribute to the validation of recognition-primed decision (RPD) model in a simulated adversarial environment; 2.Explore the roles of common-sense strategies in decision making in the adversarial environment; and 3.Test the effectiveness of training recommendations based on the RPD model. Three related experimental studies were setup to investigate each of the objectives. Study 1 found that RPD model was partly valid where RPD processes were prevalently used but other decision processes were also important in an adversarial environment. A new decision model (ConPAD model) was proposed to capture the nature of decision making in the adversarial environment. It was also found that cognitive abilities might have some effects on the types of decision processes used by the decision makers. Study 2 found that common-sense strategies were prevalent in the adversarial environment where the participants were able to use all but one of the warfare related strategies extracted from literature without teaching them. The strategy familiarization training was not found to significantly improve decision making but showed that common-sense strategies were prevalent and simple familiarization training was not sufficient to produce differences in strategy usage and performances from the novice participants. Study 3 also found that RPD based training (cue-recognition and decision skill training) were not significant in producing better performance although subjective feedback found such training to be useful. However, the participants with RPD based training conditions were able to perform on the same level as the expert participants bridging the gap between novices and experts. Based on the findings, it was recommended that decision training should involve not just RPD based training, but comparisons of attributes as well. A more interactive training combining common-sense strategies, cue-recognition and decision skill training might be more useful. More theoretical experimentation would be required to validate the new decision model proposed in this dissertation. / Ph. D.

Mgr. Tomáš Vokáč Engaged Drama of Everyday Life (Socially Engaged French Drama of the late 19th and 20th Century) Abstract This thesis describes the fundamental ontological change in the character of the French drama of the 19th and 20th century which became the basis for the modern French drama of the 20th century. The thesis is based on the analysis of the selected plays with the focus on socially engaged and socio-critical themes. This thesis defines the basic line of development of the socially engaged drama that begins with the work of naturalistic writers Émile Zola and the Goncourt brothers, continues in the form of Henry Becque's playwrights and the authors grouped around Andre Antoine's Théâtre Libre, especially Jean Jullien and his theory of "live theatre", and results in the definition of Eugène Brieux's, François de Curel's and partly Octava Mirbeaua's drama. The opposite character of French theatre and drama at the turn of the 19th and 20th century is described as the counterpart to this line. The thesis provides comparison with the contemporary influences of commercial and subsidized theatres, refers to the symbolist theatre and to the work of late Parnassians. It also closely describes Neo- Romanticism Drama in verse represented by the works of Edmond Rostand, Jean Richepina and, partially,...

La méthodologie de l’évaluation en psychothérapie s’est longtemps limitée aux résultats issus d’essais cliniques comparatifs de groupes. L’objectif, engagé dans les années 2000, de comprendre ce qui cause son efficacité a engagé un renouvellement méthodologique. Son application concrète est peu documentée. La première partie présente, à partir d’une revue de la littérature centrée sur l’introduction de la recherche sur le processus associée aux résultats, comment le paradigme interactionnel multifactoriel de la psychothérapie a stimulé le développement de méthodes adaptées à la complexité et à l’observation en conditions naturelles. La seconde partie introduit autour de cinq axes principaux les questions méthodologiques générales et spécifiques de cette nouvelle orientation : 1. une épistémologie interactionnelle et transactionnelle ; 2. Un recentrage sur les études mixtes intensives de cas ; 3. Une investigation clinique et théorique multifocale des processus et mécanismes de changement ; 4. une forte relation clinicien-chercheur ; 5. une approche statistique innovante. La troisième partie expose l’expérience et les questions soulevées par la mise en œuvre de ce programme dans le cadre d’un réseau de recherche clinique centré sur les pratiques, du recueil des données jusqu’à l’analyse des processus et mécanismes de changement, et les résultats qui en sont issus. La quatrième partie présente une revue détaillée de la littérature. Ce travail devrait favoriser les collaborations avec les disciplines connexes et l’efficience des traitements par une meilleure connaissance des conditions et des mécanismes de changement associée au développement d’une base de données issue d’études de cas. / The methodology of assessment in psychotherapy has long been limited to results from comparative group clinical trials. The objective, expressed in the 2000s, to understand what is causing its effectiveness has involved a methodological renewal. Its concrete application is poorly documented. The first part presents, from a review of the literature focusing on the introduction of research on the process associated with outcomes, how the multifactorial interactional paradigm of psychotherapy has stimulated the development of methods adapted to the complexity and observation in natural conditions. The second part introduces the general and specific methodological questions of this new orientation around five main axes: 1. an interactional and transactional epistemology; 2. A refocusing on intensive mixed case studies; 3. A multifocal clinical and theoretical investigation of the processes and mechanisms of change; 4. a strong clinical-researcher relationship; 5. an innovative statistical approach. The third part presents the experience and issues raised by the implementation of this program as part of a practice-oriented clinical research network, from data collection to analysis of processes and mechanisms of change, and results. The fourth part presents a detailed review of the literature. This work should foster collaborations with related disciplines and treatment efficiency through a better understanding of the conditions and mechanisms of change associated with the development of a case study database.

System dynamics modelling has been used for around 40 years to address complex, systemic, dynamic problems, those often described as wicked. But, system dynamics modelling is not an exact science and arguments about the most suitable techniques to use in which circumstances, continues. The nature of these wicked problems is investigated through a series of case studies where poor situational awareness among stakeholders was identified. This was found to be an underlying cause for management failure, suggesting need for better ways of recognising and managing wicked problem situations. Human cognition is considered both as a limitation and enabler to decision-making in wicked problem environments. Naturalistic and deliberate decision-making are reviewed. The thesis identifies the need for integration of qualitative and quantitative techniques. Case study results and a review of the literature led to identification of a set of principles of method to be applied in an integrated framework, the aim being to develop an improved way of addressing wicked problems. These principles were applied to a series of cases in an action research setting. However, organisational and political barriers were encountered. This limited the exploitation and investigation of cases to varying degrees. In response to a need identified in the literature review and the case studies, a tool is designed to facilitate analysis of multi-factorial, non-linear causality. This unique tool and its use to assist in problem conceptualisation, and as an aid to testing alternate strategies, are demonstrated. Further investigation is needed in relation to the veracity of combining causal influences using this tool and system dynamics, broadly. System dynamics modelling was found to have utility needed to support analysis of wicked problems. However, failure in a particular modelling project occurred when it was found necessary to rely on human judgement in estimating values to be input into the models. This was found to be problematic and unacceptably risky for sponsors of the modelling effort. Finally, this work has also identified that further study is required into: the use of human judgement in decision-making and the validity of system dynamics models that rely on the quantification of human judgement.