No description available.

No description available.

<p>This thesis suggests that new tools and technology can be used for production of relevant data and insights from the study of human performance in simulator and field experiments. It examines some of the theoretical perspectives behind data collection and human performance assessment, and argues for a high resemblance of the real world and use of subject matter expertise in simulator studies. A model is proposed, suggesting that human performance measurement should be tightly coupled to the topic of study and have a close connection to the time line. This coupling requires new techniques for continuous data collection, and eye movement tracking has been identified as a promising basis for this type of measures.</p><p>One way of improving realism is to create virtual environments allowing for controlling more of the environment surrounding the test subjects. New application areas for virtual environments are discussed for use in control room and field studies.</p><p>The combination of wearable computing, virtual and augmented (the use of computers to overlay virtual information onto the real world) reality provides many new possibilities to present information to operators. In two experiments, virtual and augmented reality techniques were used to visualise radiation fields for operators in a contaminated nuclear environment. This way the operators could train for and execute their tasks in a way that minimised radiation exposure to the individual operator. Both experiments were successful in proving the concept of radiation visualisation.</p><p>Virtual environments allow for early end-user feedback in the design and refurbishment of control room man-machine interfaces. The practical usability of VR in the control room setting was tested in two control room design experiments. The results show that with the right tools for solving the tasks under test, even desktop presentations of the virtual environment can provide sufficient resemblance of the real world.</p><p>Computerised data collection was identified as a key factor for efficient data handling in simulator and field experiments. An Internet based questionnaire system was specified and implemented in parallel with the experimental work, and functionality was developed to fulfil the special needs of each new experimental setting. The result is a computer platform independent system capable of handling most types of data and test situations for data collection by Internet or local computer networks.</p>

<p>The primary aim of this thesis is to highlight the most important features of driving and to describe the models that have attempted to conceptualise these features. The discussion focuses on the concept of "safety margin." The concept is elaborated upon in an effort to enhance its usefulness as an empirical tool in traffic research. In this study, safety margin is defined as a threshold value that informs the driver when to undertake an action to minimise the risk of a car accident. Three separate studies of various driver behaviours are presented as illustrations of how this view can be applied in a real highway traffic setting. One study (Study I), consisting of three independent but related experiments, examines car following; a second study (Study II) explores gap acceptance at a T-crossing; and a third study (Study III) investigates drivers’ braking decisions.</p><p>The overall findings of the present studies suggest that it is valid to model driver behaviour as a concern related to the control of safety margins. It was shown that the driver controls time-distance dynamics to leading and following cars when driving in a queue. A bias in the drivers’ impressions of distances to leading and following vehicles that has safety promoting implications was also found. There was no evidence for the hypothesised use of the limit for dissolution of time-distance to oncoming vehicles for merging decisions at a T-junction. Drivers’ rules for establishing braking decisions were successfully assessed in a field study using linear regression. </p>

The primary aim of this thesis is to highlight the most important features of driving and to describe the models that have attempted to conceptualise these features. The discussion focuses on the concept of "safety margin." The concept is elaborated upon in an effort to enhance its usefulness as an empirical tool in traffic research. In this study, safety margin is defined as a threshold value that informs the driver when to undertake an action to minimise the risk of a car accident. Three separate studies of various driver behaviours are presented as illustrations of how this view can be applied in a real highway traffic setting. One study (Study I), consisting of three independent but related experiments, examines car following; a second study (Study II) explores gap acceptance at a T-crossing; and a third study (Study III) investigates drivers’ braking decisions. The overall findings of the present studies suggest that it is valid to model driver behaviour as a concern related to the control of safety margins. It was shown that the driver controls time-distance dynamics to leading and following cars when driving in a queue. A bias in the drivers’ impressions of distances to leading and following vehicles that has safety promoting implications was also found. There was no evidence for the hypothesised use of the limit for dissolution of time-distance to oncoming vehicles for merging decisions at a T-junction. Drivers’ rules for establishing braking decisions were successfully assessed in a field study using linear regression.

This thesis suggests that new tools and technology can be used for production of relevant data and insights from the study of human performance in simulator and field experiments. It examines some of the theoretical perspectives behind data collection and human performance assessment, and argues for a high resemblance of the real world and use of subject matter expertise in simulator studies. A model is proposed, suggesting that human performance measurement should be tightly coupled to the topic of study and have a close connection to the time line. This coupling requires new techniques for continuous data collection, and eye movement tracking has been identified as a promising basis for this type of measures. One way of improving realism is to create virtual environments allowing for controlling more of the environment surrounding the test subjects. New application areas for virtual environments are discussed for use in control room and field studies. The combination of wearable computing, virtual and augmented (the use of computers to overlay virtual information onto the real world) reality provides many new possibilities to present information to operators. In two experiments, virtual and augmented reality techniques were used to visualise radiation fields for operators in a contaminated nuclear environment. This way the operators could train for and execute their tasks in a way that minimised radiation exposure to the individual operator. Both experiments were successful in proving the concept of radiation visualisation. Virtual environments allow for early end-user feedback in the design and refurbishment of control room man-machine interfaces. The practical usability of VR in the control room setting was tested in two control room design experiments. The results show that with the right tools for solving the tasks under test, even desktop presentations of the virtual environment can provide sufficient resemblance of the real world. Computerised data collection was identified as a key factor for efficient data handling in simulator and field experiments. An Internet based questionnaire system was specified and implemented in parallel with the experimental work, and functionality was developed to fulfil the special needs of each new experimental setting. The result is a computer platform independent system capable of handling most types of data and test situations for data collection by Internet or local computer networks.

The aim of the studies was to predict individual traffic accident involvement by the quantification of driving style in terms of speed changes, using bus drivers as subjects. An accident database was constructed from the archives of the bus company whose drivers were used as subjects. The dependent variable was also discussed regarding whether responsibility for crashes should be included, and what time period to use for optimal prediction. A new theory was constructed about how accidents are caused by driver behavior, more specifically the control movements of the driver, i.e. all actions taken which influence the relative motion of the vehicle in a level plane when v&gt;0. This theory states that all traffic safety related behavior can be measured as celerations (change of speed of the vehicle in any direction of a level plane) and summed. This theoretical total sum is a measure of a person's liability to cause accidents over the same time period within a homogenous traffic environment and a similarly homogenous driving population. Empirically, the theory predicts a positive correlation between mean driver celeration behavior and accident record. The theory was tested in three empirical studies. The first tested equipment and methods, the second studied the question whether driver celeration behavior is stable over time. Celeration behavior turned out to be rather variable between days, and repeated measurements were therefore needed to stabilize the measure. In the third study, a much larger amount of data brought out correlations of sizes sufficient to lend some credibility to the theory. However, the predictive power did not extend beyond two years of time. The reported results would seem to imply that the celeration variable can predict accident involvement (at least for bus drivers), and is practical to use, as it is easily and objectively measured and semi-stable over time.

No description available.

<p>In cognitive behavioral therapy (CBT), the definition of mental illness is associated with the level of functionality of the patient. The level of functionality is in turn related to present norms about illness in society, which can be put in relation to the existing norms in the society. In addition, the latter are discussed in relation to social constructivism theory. Here, Fromm and Marcuse are the most important theorists. On the basis of interviews with four patients in CBT, the aim of this study was to examine how the patients’ notions of mental illness and their problem definitions differed from the therapists’ view, and if the functionality focus was of any significance for the patients’ experiences of CBT. In the results, it is noticeable that the interviewees’ notion of mental illness affected the therapy outcome. Thus, the present study illustrates the importance of discussing what definition of mental illness is applied – not just in clinical cases, but also in a social context – and why.</p>

<p>Syftet med denna studie var att undersöka vilka situationer som vanligen orsakar ilska hos vuxna individer, och att ur dessa försöka härleda vilka faktorer som i dessa situationer orsakat ilskan. Genom en enkätundersökning fick 55 psykologistudenter vardera beskriva två situationer som gjort dem arga, samt vad det var som gjort dem arga. På detta material utfördes en induktiv tematisk analys, vilket visade på fem olika huvudorsaker till ilska. Dessa var: Hot mot ens (eller signifikant annans) välbefinnande; Normbrytande beteende och orättvisa; Bristande kontroll över relevant situation samt förhindrelse att uppnå mål; Ens förväntningar bryts till det negativa; Negativa tillstånd. I en vidare diskussion behandlas att dessa teman förefaller passa väl in i ett evolutionistiskt synsätt på emotioner. Ilska förefaller vara en handlingsmotiverande emotion som huvudsakligen fyller funktionen som mobiliserande kraft gentemot negativa utvecklingar.</p>