Single-phase brushless fan motor is investigated in this thesis and is fabricated by UMC 0.5 m double-poly, triple-metal, N-Well CMOS process for notebook micro fan motor applications. H-bridge and embedded power mos architecture are used in implemented driver circuit, and an external capacitor is needed for pulse width modulation speed control. A comparator with hysteresis and digital lock detection and auto self-restart function are also implemented in this thesis. Besides, in order to prevent the rush current in output stage, the switch operation of power mos transistors are controlled individually.

Remote control service on the internet has found many applications such as remote teaching service and industry applications. Our research is not like the traditional method which sends image frames to network users. Instead, we only send the mouse and keyboard message. Our research is composed of two techniques: one is to connect computer¡¦s mouse and keyboard message with virtual device driver, and the other is to provide network function and interface with Win32 application. The accomplishment of virtual device driver is achieved by VxD and Win32 API. We compare our method with other traditional methods in both local network and 56K Modem to test the possibility of remote teaching service. The transmission amount is reduced significantly by our method. Also, the remote teaching service using our method has been successfully performed at 56K modem network environment without the delay phenomenon as shown in the test by the traditional method.

The need to see traffic signs at night has led to the development of increasingly brighter retroreflective sign sheeting. The impact of this increased brightness has been shown to increase the legibility distance of the sign, but at what cost? With brighter signs being visible from farther away, there is an increased opportunity for the driver to look at the sign. This thesis assesses the impact of sign brightness on the nighttime driver’s sign viewing behavior; such as the number of glances and the total glance duration directed at the sign. Eye-tracking technology has been used to follow the nighttime driver’s eye movements through tasks based on sign usage. The six signs used for the analysis are classified in three relative brightness categories of bright, medium, and dim on a closed course and on a public road. Data relating to the beginning and end of each glance were recorded as well as the distance at which the sign became legible to the driver. Comparisons were made between the three brightness levels for the number of glances, total glance duration, and legibility distance of the sign. Further analysis was conducted to determine the effect of the testing environment on a driver’s sign viewing behavior by comparing the results from the closed course with those from the open road. The data for this thesis show varying results between the two courses with more defined differences based on luminance for the open road. The results of this thesis indicate that drivers do not consistently change the number of times they look at a sign or the amount of time dedicated to a sign based on its brightness. During real world driving scenarios, the brightest sign resulted in the longest legibility distance and the lowest total glance duration, indicating an increased efficiency reading the sign by the driver. Typically, a sign with a longer total glance duration had a shorter legibility distance. Comparisons between the closed and open courses revealed that open road driving resulted in a longer total glance duration and a shorter legibility distance.

This thesis attempted to provide a detailed theoretical understanding of the effects of task-induced fatigue on simulated driving performance. Previous research has shown that duration of driving has only a weak effect on driving performance. A series of studies were conducted to examine how fatigue effects interact with task demands, and to explore the psychological changes associated with fatigue. The research also explored links between fatigue and stress in terms of their affective reactions and the coping mechanisms which are central to them. The first phase of the research consisted of a series of simulated studies of fatigue. The first study developed an experimental paradigm to examine both task-specific and aftereffects of fatigue on driving performance. The findings showed that fatigue effects interacted with task demands such that drivers' lateral control of the vehicle and trajectory were impaired during low demand rather than in high demand driving episodes. The study also showed that the fatigue state is a multidimensional state which is principally characterised by a reduction in motivation. The second and third studies attempted to explore the role of motivational mechanisms in fatigue-related impairments. This phase of the research showed that impairments in low demand driving conditions may be reduced by enhancing the driver's motivational state. The fourth study explored the development of subjective fatigue in two types of task-induced fatigue. The study showed that there is a dissociation between subjective and objective fatigue. The second phase of the research examined the links between stress and fatigue in simulated and real-life driving environments. The studies showed that stress and fatigue are similar states but there are particular features which make them distinct states. The results from simulated and real-life driving environments showed a high degree of consistency.

Driver fatigue is responsible for up to 30% of fatal car accidents. This issue has been addressed by many scholars in order to save thousands of lives and reduce many costs. The goal of this work is to reduce the number of car accidents caused by mental fatigue or drowsiness. In order to achieve this goal, we propose a personalized Bayesian Network (BN) to detect driver’s fatigue. The detection of driver fatigue is enhanced by combining data that reflects the driver’s performance with context-aware information. The parameters of the system are the angular velocity of the steering wheel, the pressure applied to the gas and brake pedals, the grip force on the steering wheel, weather conditions, current traffic, and time of day. The aforementioned parameters of the network are updated on a regular basis, which makes fatigue detection more reliable. Besides, these parameters allow the system to detect a driver’s fatigue through driving performance which is both individualized and context aware. In our experiment, subjects drove a driving simulator game during six sessions, for a total of one hour. After each session, every subject used the Karolinska Sleepiness Scale (KSS) to rate her fatigue’s level. The system was trained on the data collected separately from each user, allowing BN to be personalized for each subject. The proposed system showed an average accuracy of 96%, and ability to overcome the issue of individual differences and uncertainties which are involved in fatigue detection process.

Thesis (Ph. D.)--Illinois State University, 1976. / Title from title page screen, viewed Nov. 22, 2004. Dissertation Committee: Charles Edwards (chair), G. Alan Hickrod, Laurance Quane, Clayton Thomas, Joe Talkington. Includes bibliographical references (leaves 139-149) and abstract. Also available in print.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1969. / Typescript. Vita. Description based on print version record. Includes bibliographical references.

This thesis documents new research into the modelling of driver vision and the integration of a new vision model into a microscopic traffic simulation tool. It is proposed and demonstrated that modelling of driver vision enhances the realism of simulated driver decision-making and behaviour, in turn, leading to improved simulation of driver interactions and traffic flow. Driving and traffic related research has traditionally fallen into the three distinct areas of driver psychology, traffic and highway engineering and vehicle dynamics, with modelling or experimentation in any of these areas supported by significant approximation in the others. In contrast to this, the vision research discussed here has been carried out in a context that aims to integrate all of these areas equally. This has been realised through the implementation of a new modelling environment, Synthetic Driving SIMulation, SD-SIM.

Driver fatigue is responsible for up to 30% of fatal car accidents. This issue has been addressed by many scholars in order to save thousands of lives and reduce many costs. The goal of this work is to reduce the number of car accidents caused by mental fatigue or drowsiness. In order to achieve this goal, we propose a personalized Bayesian Network (BN) to detect driver’s fatigue. The detection of driver fatigue is enhanced by combining data that reflects the driver’s performance with context-aware information. The parameters of the system are the angular velocity of the steering wheel, the pressure applied to the gas and brake pedals, the grip force on the steering wheel, weather conditions, current traffic, and time of day. The aforementioned parameters of the network are updated on a regular basis, which makes fatigue detection more reliable. Besides, these parameters allow the system to detect a driver’s fatigue through driving performance which is both individualized and context aware. In our experiment, subjects drove a driving simulator game during six sessions, for a total of one hour. After each session, every subject used the Karolinska Sleepiness Scale (KSS) to rate her fatigue’s level. The system was trained on the data collected separately from each user, allowing BN to be personalized for each subject. The proposed system showed an average accuracy of 96%, and ability to overcome the issue of individual differences and uncertainties which are involved in fatigue detection process.

This report is the result of a master thesis performed at MacGREGOR (SWE) AB (Crane Division), Örnsköldsvik. MacGREGOR (SWE) AB (Crane Division) is the world’s leading marine cargo crane supplier with cranes designed for operation in harbor and sheltered water environments. The project aimed to identify and investigate needs and problem areas in the crane cabin with the purpose to design an ergonomic and user-friendly driver environment. Besides ergonomics and user interaction, sturdiness, comfort and safety have been keywords throughout the project. It has not been possible to observe drivers at work because of the world wide location of the cranes. Therefore needs and problem areas were identified through interviews with personnel at MacGREGOR (SWE) AB (Crane Division) and analysis through different methods and softwares such as I- deas, Jack and RULA. The project group has also been given the opportunity to drive a crane and observe the relations between regulators, indicators and driver. To investigate new solutions and designs, competitors and related technologies were thoroughly analyzed. Four concepts were created after the design specification was established. To see how well the concepts fulfilled the identified needs they were evaluated in a merit calculation table. Concept 1 “Rotate all” and concept 4 “Office chair” were then compared in a weak-point analysis. After consultation with the instructors at MacGREGOR (SWE) AB (Crane Division) it was decided that “Rotate all” was to be further developed. The final solution is a combination of new ideas and ideas from the four concepts in the concept design phase. Aspects considering function and form have been carefully thought out using theoretical guidelines in ergonomics, semiotics and gestalts. The new crane cabin emphasizes quality and a feeling for the company through colors, shape and placement. The new crane cabin is based on an adjustable interior suited for drivers between the 5th and 95th percentile. A major improvement is the rotating chair with integrated control levers on the armrests. The indicators and regulators are separated and now placed on the walls. The visual field is improved with a larger front window and a tilted floor window. / <p>Validerat; 20101217 (root)</p>