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In today's technology based society the rapid proliferation of new machines and systems that would have been undreamed of only a few short years ago has become a way of life. Developments and advances especially in the areas of digital electronics and micro-circuitry have spawned subsequent technology based improvements in transportation, communications, entertainment, automation, the armed forces, and many other areas that would not have been possible otherwise. This rapid "explosion" of new capabilities and ways of performing tasks has been motivated as often as not by the philosophy that if it is possible to make something better or work faster or be more cost effective or operate over greater distances then it must inherently be good for the human operator. Taken further, these improvements typically are envisioned to consequently produce a more efficient operating system where the human operator is an integral component. The formal concept of human-system interface design has only emerged this century as a recognized academic discipline, however, the practice of developing ideas and concepts for systems containing human operators has been in existence since humans started experiencing cognitive thought. An example of a human system interface technology for communication and dissemination of written information that has evolved over centuries of trial and error development, is the book. It is no accident that the form and shape of the book of today is as it is. This is because it is a shape and form readily usable by human physiology whose optimal configuration was determined by centuries of effort and revision. This slow evolution was mirrored by a rate of technical evolution in printing and elsewhere that allowed new advances to be experimented with as part of the overall use requirement and need for the existence of the printed word and some way to contain it. Today, however, technology is advancing at such a rapid rate that evolutionary use requirements have no chance to develop along side the fast pace of technical progress. One result of this recognition is the establishment of disciplines like human factors engineering that have stated purposes and goals of systematic determination of good and bad human system interface designs. However, other results of this phenomenon are systems that get developed and placed into public use simply because new technology allowed them to be made. This development can proceed without a full appreciation of how the system might be used and, perhaps even more significantly, what impact the use of this new system might have on the operator within it. The U.S. Army has a term for this type of activity. It is called "stove-piped development". The implication of this term is that a system gets developed in isolation where the developers are only looking "up" and not "around". They are thus concerned only with how this system may work or be used for its own singular purposes as opposed to how it might be used in the larger community of existing systems and interfaces or, even more importantly, in the larger community of other new systems in concurrent development. Some of the impacts for the Army from this mode of system development are communication systems that work exactly as designed but are unable to interface to other communications systems in other domains for battlefield wide communications capabilities. Having communications systems that cannot communicate with each other is a distinct problem in its own right. However, when developments in one industry produce products that humans use or attempt to use with products from totally separate developments or industries, the Army concept of product development resulting from stove-piped design visions can have significant implication on the operation of each system and the human operator attempting to use it. There are many examples that would illustrate the above concept, however, one that will be explored here is the Army effort to study, understand, and optimize its command and control (C2) operations. This effort is at the heart of a change in the operational paradigm in C2 Tactical Operations Centers (TOCs) that the Army is now undergoing. For the 50 years since World War II the nature, organization, and mode of the operation of command organizations within the Army has remained virtually unchanged. Staffs have been organized on a basic four section structure and TOCs generally only operate in a totally static mode with the amount of time required to move them to keep up with a mobile battlefield going up almost exponentially from lower to higher command levels. However, current initiatives are changing all that and while new vehicles and hardware systems address individual components of the command structures to improve their operations, these initiatives do not necessarily provide the environment in which the human operator component of the overall system can function in a more effective manner. This dissertation examines C2 from a system level viewpoint using a new paradigm for systematically examining the way TOCs operate and then translating those observations into validated computer simulations using a methodological framework. This paradigm is called COmputer Modeling Paradigm And Simulation of Systems (COMPASS). COMPASS provides the ability to model TOC operations in a way that not only includes the individuals, work groups and teams in it, but also all of the other hardware and software systems and subsystems and human-system interfaces that comprise it as well as the facilities and environmental conditions that surround it. Most of the current literature and research in this area focuses on the concept of C2 itself and its follow-on activities of command, control, communications (C3), command, control, communications, and computers (C4), and command, control, communications, computers and intelligence (C4I). This focus tends to address the activities involved with the human processes within the overall system such as individual and team performance and the commander's decision-making process. While the literature acknowledges the existence of the command and control system (C2S), little effort has been expended to quantify and analyze C2Ss from a systemic viewpoint. A C2S is defined as the facilities, equipment, communications, procedures, and personnel necessary to support the commander (i.e., the primary decision maker within the system) for conducting the activities of planning, directing, and controlling the battlefield within the sector of operations applicable to the system. The research in this dissertation is in two phases. The overall project incorporates sequential experimentation procedures that build on successive TOC observation events to generate an evolving data store that supports the two phases of the project. Phase I consists of the observation of heavy maneuver battalion and brigade TOCs during peacetime exercises. The term "heavy maneuver" is used to connotate main battle forces such as armored and mechanized infantry units supported by artillery, air defense, close air, engineer, and other so called combat support elements. This type of unit comprises the main battle forces on the battlefield. It is used to refer to what is called the conventional force structure. These observations are conducted using naturalistic observation techniques of the visible functioning of activities within the TOC and are augmented by automatic data collection of such things as analog and digital message traffic, combat reports generated by the computer simulations supporting the wargame exercise, and video and audio recordings where appropriate and available. Visible activities within the TOC include primarily the human operator functions such as message handling activities, decision-making processes and timing, coordination activities, and span of control over the battlefield. They also include environmental conditions, functional status of computer and communications systems, and levels of message traffic flows. These observations are further augmented by observer estimations of such indicators as perceived level of stress, excitement, and level of attention to the mission of the TOC personnel. In other words, every visible and available component of the C2S within the TOC is recorded for analysis. No a priori attempt is made to evaluate the potential significance of each of the activities as their contribution may be so subtle as to only be ascertainable through statistical analysis. Each of these performance activities becomes an independent variable (IV) within the data that is compared against dependent variables (DV) identified according to the mission functions of the TOC. The DVs for the C2S are performance measures that are critical combat tasks performed by the system. Examples of critical combat tasks are "attacking to seize an objective", "seizure of key terrain", and "river crossings'. A list of expected critical combat tasks has been prepared from the literature and subject matter expert (SME) input. After the exercise is over, the success of these critical tasks attempted by the C2S during the wargame are established through evaluator assessments, if available, and/or TOC staff self analysis and reporting as presented during after action reviews. The second part of Phase I includes datamining procedures, including neural networks, used in a constrained format to analyze the data. The term constrained means that the identification of the outputs/DV is known. The process was to identify those IV that significantly contribute to the constrained DV. A neural network is then constructed where each IV forms an input node and each DV forms an output node. One layer of hidden nodes is used to complete the network. The number of hidden nodes and layers is determined through iterative analysis of the network. The completed network is then trained to replicate the output conditions through iterative epoch executions. The network is then pruned to remove input nodes that do not contribute significantly to the output condition. Once the neural network tree is pruned through iterative executions of the neural network, the resulting branches are used to develop algorithmic descriptors of the system in the form of regression like expressions. For Phase II these algorithmic expressions are incorporated into the CoHOST discrete event computer simulation model of the C2S. The programming environment is the commercial programming language Micro Saintä running on a PC microcomputer. An interrogation approach was developed to query these algorithms within the computer simulation to determine if they allow the simulation to reflect the activities observed in the real TOC to within an acceptable degree of accuracy. The purpose of this dissertation is to introduce the COMPASS concept that is a paradigm for developing techniques and procedures to translate as much of the performance of the entire TOC system as possible to an existing computer simulation that would be suitable for analyses of future system configurations. The approach consists of the following steps: • Naturalistic observation of the real system using ethnographic techniques. • Data analysis using datamining techniques such as neural networks. • Development of mathematical models of TOC performance activities. • Integration of the mathematical into the CoHOST computer simulation. • Interrogation of the computer simulation. • Assessment of the level of accuracy of the computer simulation. • Validation of the process as a viable system simulation approach. / Ph. D.

The driving risk of novice teenagers is the highest during the initial period after licensure but decreases rapidly. This dissertation develops recurrent-event change-point models to detect the time when driving risk decreases significantly for novice teenager drivers. The dissertation consists of three major parts: the first part applies recurrent-event change-point models with identical change-points for all subjects; the second part proposes models to allow change-points to vary among drivers by a hierarchical Bayesian finite mixture model; the third part develops a non-parametric Bayesian model with a Dirichlet process prior. In the first part, two recurrent-event change-point models to detect the time of change in driving risks are developed. The models are based on a non-homogeneous Poisson process with piecewise constant intensity functions. It is shown that the change-points only occur at the event times and the maximum likelihood estimators are consistent. The proposed models are applied to the Naturalistic Teenage Driving Study, which continuously recorded textit{in situ} driving behaviour of 42 novice teenage drivers for the first 18 months after licensure using sophisticated in-vehicle instrumentation. The results indicate that crash and near-crash rate decreases significantly after 73 hours of independent driving after licensure. The models in part one assume identical change-points for all drivers. However, several studies showed that different patterns of risk change over time might exist among the teenagers, which implies that the change-points might not be identical among drivers. In the second part, change-points are allowed to vary among drivers by a hierarchical Bayesian finite mixture model, considering that clusters exist among the teenagers. The prior for mixture proportions is a Dirichlet distribution and a Markov chain Monte Carlo algorithm is developed to sample from the posterior distributions. DIC is used to determine the best number of clusters. Based on the simulation study, the model gives fine results under different scenarios. For the Naturalist Teenage Driving Study data, three clusters exist among the teenagers: the change-points are 52.30, 108.99 and 150.20 hours of driving after first licensure correspondingly for the three clusters; the intensity rates increase for the first cluster while decrease for other two clusters; the change-point of the first cluster is the earliest and the average intensity rate is the highest. In the second part, model selection is conducted to determine the number of clusters. An alternative is the Bayesian non-parametric approach. In the third part, a Dirichlet process Mixture Model is proposed, where the change-points are assigned a Dirichlet process prior. A Markov chain Monte Carlo algorithm is developed to sample from the posterior distributions. Automatic clustering is expected based on change-points without specifying the number of latent clusters. Based on the Dirichlet process mixture model, three clusters exist among the teenage drivers for the Naturalistic Teenage Driving Study. The change-points of the three clusters are 96.31, 163.83, and 279.19 hours. The results provide critical information for safety education, safety countermeasure development, and Graduated Driver Licensing policy making. / Ph. D.

Most of the existing bicycle flow traffic research is limited to characterizing the longitudinal motion of bicyclists based on the assumption that there is no significant differences between the dynamics of a single-file bicycle traffic and the longitudinal motion behavior of cars. This research reparametrizes an existing car-following model to describe bicycle-following and motion behavior. Furthermore, the lack of naturalistic data has limited the validation of this model. This research aims at developing a descriptive model that is capable of capturing the inherent non-lane-based traffic behavior characteristics of bicycle traffic and provides a methodology for extracting naturalistic cycling data from video feeds for use in safety and mobility applications. In this study, The Fadhloun-Rakha (FR) bicycle-following longitudinal motion model was extended through complementing it with a lateral motion strategy; thus allowing for overtaking maneuvers and lateral bicycle movements. For the most part, the following strategy of the FR model remains valid for modeling the longitudinal motion of bicycles except for the activation conditions of the collision avoidance strategy which are modified in order to allow for overtaking when possible. The proposed methodology is innovative in that it makes use of the intersection of certain pre-defined regions around the bicycles to decide on the feasibility of angular motion along with its direction and magnitude. The resulting model is the first point-mass dynamics-based model for the description of the longitudinal and lateral behavior of bicycles in both constrained and unconstrained conditions, and it is the only existing model that is sensitive to the bicyclist physical characteristics and the bicycle and roadway surface conditions given that the used longitudinal logic was previously validated against experimental cycling data. In relation to the development of the naturalistic cycling dataset, the used videos come from a dataset collected in a previous Virginia Tech Transportation Institute study in collaboration with SPIN in which continuous video data at a non-signalized intersection on the Virginia Tech campus was recorded. The research applied computer vision and machine learning techniques to develop a comprehensive framework for the extraction of naturalistic cycling trajectories. In total, this study resulted in the collection and classification of 619 bicycle trajectories based on their type of interactions with other road users. The results confirm the success of the proposed methodology in relation to extracting the locations, speeds, and accelerations of the bicycles with a high precision level. Furthermore, preliminary insights into the acceleration and speed behavior of bicyclists around motorists are determined. / Master of Science / The behavior of bicycle traffic differs from the that of cars. Bicycle traffic flow dynamics is unconstrained in lateral motion and overtaking when compared to car traffic flow. Based on this inherent behavior, existing car-following can only model the longitudinal motion of the bicycle flow traffic and it does not describe the non-lane base traffic that characterizes bicycle traffic dynamics. Furthermore, the existing experimental controlled dataset used for validating bicycle traffic flow models does not capture the naturalistic behavior of cyclists. Therefore, this research aims to develop a descriptive model that is capable of capturing the inherent non-lane-based traffic behavior characteristics of bicycle traffic and provides a methodology for extracting a naturalistic cycling data from a video dataset for use in safety and mobility applications. In this study, the Fadhloun-Rakha (FR) bicycle-following longitudinal motion model was extended through complementing it with a lateral motion strategy; thus allowing for overtaking maneuvers and lateral bicycle movements. For the most part, the following strategy of the FR model remains valid for modeling the longitudinal motion of bicycles except for the activation conditions of the collision avoidance strategy which are modified in order to allow for overtaking when possible. The proposed methodology is innovative in that it makes use of the intersection of certain pre-defined regions around the bicycles to decide on the feasibility of angular motion along with its direction and magnitude. The resulting model is the first point-mass dynamics-based model for the description of the longitudinal and lateral behavior of bicycles in both constrained and unconstrained conditions, and it is the only existing model that is sensitive to the bicyclist physical characteristics and the bicycle and roadway surface conditions given that the used longitudinal logic was previously validated against experimental cycling data. In relation to the development of the naturalistic cycling dataset, the used videos come from a dataset collected in a previous Virginia Tech Transportation Institute study in collaboration with SPIN in which continuous video data at a non-signalized intersection on the Virginia Tech campus was recorded. The research applied computer vision and machine learning techniques to develop a comprehensive framework for the extraction of naturalistic cycling trajectories. In total, this study resulted in the collection and classification of 619 bicycle trajectories based on their type of interactions with other road users. The results confirm the success of the proposed methodology in relation to extracting the locations, speeds, and accelerations of the bicycles with a high precision level. Furthermore, preliminary insights into the acceleration and speed behavior of bicyclists around motorists are determined.

Naturalistic exhibits have become popular among zoo designers as well as zoo visitors. However, one problem associated with naturalistic exhibits is that many times visitors cannot see the animals. The primary purpose of this study was to examine the effect of this lack of visibility on visitor experience. Other goals of this study were 1) to theorize the relationship between visitor experience and exhibit design, 2) to present the implications of this study on current practices in zoo exhibit design, and 3) to provide a series of design recommendations which will enhance current design practices. The results of this study suggest that there is a significant relationship between animal visibility and visitor experience. Most importantly, the results indicate that animal visibility can significantly influence how visitors use the interpretive materials associated with the exhibits. These results are important because a primary zoo objective is visitor education through sign readership. The most valuable contributions made by this study are 1) the theory proposed in this thesis which provides designers a stronger theoretical foundation from which to begin the design of zoo exhibits, 2) the findings provide additional empirical data in identifying qualities of exhibits which stimulate visitors to read, and 3) the findings provide researchers additional evidence concerning what factors of an exhibit are most significant in influencing visitor attitudes. / Master of Landscape Architecture

This dissertation aims to develop statistical methodologies for estimating the effects of time-fixed and time-varying factors in recurrent events modeling context. The research is motivated by the traffic safety research question of evaluating the influence of crash on driving risk and driver behavior. The methodologies developed, however, are general and can be applied to other fields. Four alternative approaches based on various data settings are elaborated and applied to 100-Car Naturalistic Driving Study in the following Chapters. Chapter 1 provides a general introduction and background of each method, with a sketch of 100-Car Naturalistic Driving Study. In Chapter 2, I assessed the impact of crash on driving behavior by comparing the frequency of distraction events in per-defined windows. A count-based approach based on mixed-effect binomial regression models was used. In Chapter 3, I introduced intensity-based recurrent event models by treating number of Safety Critical Incidents and Near Crash over time as a counting process. Recurrent event models fit the natural generation scheme of the data in this study. Four semi-parametric models are explored: Andersen-Gill model, Andersen-Gill model with stratified baseline functions, frailty model, and frailty model with stratified baseline functions. I derived model estimation procedure and and conducted model comparison via simulation and application. The recurrent event models in Chapter 3 are all based on proportional assumption, where effects are constant. However, the change of effects over time is often of primary interest. In Chapter 4, I developed time-varying coefficient model using penalized B-spline function to approximate varying coefficients. Shared frailty terms was used to incorporate correlation within subjects. Inference and statistical test are also provided. Frailty representation was proposed to link time-varying coefficient model with regular frailty model. In Chapter 5, I further extended framework to accommodate multi-type recurrent events with time-varying coefficient. Two types of recurrent-event models were developed. These models incorporate correlation among intensity functions from different type of events by correlated frailty terms. Chapter 6 gives a general review on the contributions of this dissertation and discussion of future research directions. / Ph. D.

Erkenntnisse über das Fahrerleben, also die subjektive Sicht von Fahrern auf Ereignisse im Fahralltag, wurden bisher vor allem retrospektiv gewonnen und sind damit anfällig für mitunter weitreichende Verfälschungen. Diese Dissertation verfolgte den Ansatz, das subjektive Fahrerleben auf alltäglichen Fahrten so situationsnah wie möglich zu erfassen. Ziel der Untersuchung war es, eine breite Datenbasis von subjektiv beanspruchenden Situationen für jüngere und ältere Fahrer zu generieren, um auch unbewusst vorhandene Unterstützungsbedürfnisse zu erfassen und damit eine bedarfsgerechte Entwicklung von Fahrerassistenzsystemen zu unterstützen. Es wurden 40 jüngere (M = 32,35 Jahre; SD = 3,58) und 40 ältere (M = 66,05 Jahre; SD = 4,13) Fahrer, je 20 Männer und Frauen, in ihrem Fahralltag über einen Zeitraum von jeweils 10 Tagen untersucht. Die Probanden hielten für sie relevante Situationen in kurzen Sprachprotokollen während der Fahrt über die Aufnahmefunktion in einem Smartphone fest. Unterstützt wurde die Situationsbetrachtung durch eine Videoaufnahme der Fahrsituation, sowie im Smartphone erfasste Geschwindigkeits-, Beschleunigungsdaten und GPS. Im Versuchszeitraum wurden insgesamt 1074 für die Auswertung relevante Sprachprotokolle während der Fahrt aufgezeichnet. Es ließen sich dabei 301 verschiedene Auslöser für die Aufnahme eines Sprachprotokolls unterscheiden. Ausgehend von den Ergebnissen und den geäußerten Unterstützungswünschen der Probanden wurden fünf verschiedene Unterstützungsbedürfnisse identifiziert, aus denen sich Anforderungen für Fahrerassistenzsysteme und Mensch-Maschine-Schnittstellen ableiten lassen. / Insights into driver experience, i.e. the driver's subjective view on events in everyday driving, have so far been gained mainly retrospectively (e.g. through interviews or online surveys). From a methodic perspective this means that reports and judgment are provided somewhat later after the event and therefore can be biased. In recent years, research in the field of driver-vehicle interaction has increasingly been enriched by natural driving studies (NDS). Since this method captures driving behavior in the natural driving context, it provides very realistic insights into events that drivers experience on a daily basis. So far, however, the focus has been on an objective view of driving behavior and environmental conditions with the aim of capturing parameters that provide an indication of future safety-critical situations. The subjective view of the driver, e.g. which situations he assesses as demanding, was hardly considered. The idea of the dissertation thesis was to capture subjective driver experience and support wishes of drivers in a NDS-like study. The aim of the study was to generate a broad database of subjectively demanding situations for younger and elder drivers, in order to detect unconsciously existing support needs and thus to support the user-centered development of driver assistance systems. Participants were 40 younger (M = 32.35 years, SD = 3.58) and 40 elder (M = 66.05 years, SD = 4.13) drivers, 20 men and 20 women each. Over the period of 10 days they documented each journey by questionnaires before and after each ride. Furthermore a smartphone with a specially programmed application was used as a recording device. Through short speech protocols the participants commented on every relevant driving situation. Considered as relevant - beyond critical events - were all special incidents or situations that were notable for the drivers or in which they wished for support in whatever form. The application also recorded GPS, speed and acceleration data as well as a video of the driving situation during relevant situations. A personal interview took place at the end of each trial period. As a result, a total of 1074 speech protocols were recorded while driving. They showed a very high range of situations that were notable for the participants. A total of 301 different triggers for recording a speech protocol could be distinguished. In addition, the consideration of the verbalized reaction of the drivers in the situations was important. The results were examined with regard to possible differences in age and gender groups. On the basis of the results and the expressed support wishes of the participants, five different support needs were identified, from which requirements for future driver assistance systems and human-machine interfaces can be derived.

The impact of the diagnosis and the reality of being hearing impaired could trigger uncomfortable feelings at different times in the client's life. With the cochlear implant, these feelings will still be a reality, as the implant does not heal the hearing impairment. Psychological interventions could assist the client during this healing process. The process of cochlear implants could also bring other challenges into the client's life. Expectations of quick healing play a major role and should be addressed throughout the process of implantation and rehabilitation. This is another opportunity for the psychologist to intervene. This research shows that the role of the psychologist could be expanded not only to evaluate but also to bring about change. The treatment model gives a logical and workable explanation of how and where the psychologist may intervene in the process of cochlear implantation. This model was tested and adapted by the cochlear implant team at the University of Pretoria over a period of ten years. The model may be used as a template for new teams. Intervening as described in the model presents the opportunity to address various different needs as they occur. The qualitative research design proved to be a fitting method to explore the experiences of the participants from their own viewpoints. The qualitative research is also congruent with a systemic perspective and emphasises social context, multiple perspectives, complexity, recursion and holism. This study aims to develop a complementary psychological treatment programme and create awareness within professionals working with hearing impairment of the complexity of systems. The study shows that one can only understand the behaviour of any given system by tracking changes that occur within that system and its subsystems and by tracking changes between that system and the larger whole. In this study three different therapeutic interventions are used on three different case studies, two children from different age groups and an adult, to accommodate the multiple realities of the different systems. The aim of the study with cochlear implantees and their families is to stimulate new leads and avenues of enquiry that may be used as a basis for further research. / Psychology / Thesis (D.Litt. et Phil. (Psychology))