<p> Driving is a complicated task that requires the coordination of visual and sensory-motor skills. Unsafe driving behavior and accidents can happen regardless of the level of drivers&rsquo; experience. The main cause of the most of these accidents is human error. Emotions influence the way drivers process and react to internal or environmental factors. Specifically, anger elicited either from traffic or personal issues, is a serious threat on the road. Therefore, having an affective intelligent system in the car that can estimate drivers&rsquo; anger and respond to it appropriately can help drivers adapt to moment to-moment changes in driving situations. To this end, the present dissertation uses an integrated approach to monitoring drivers&rsquo; affective states in various driving contexts to address the question: &ldquo;What types of music can mitigate the effects of anger on driving performance?&rdquo; Three sources of information (behavioral, physiological, and subjective data) were considered in two experiments. In Experiment 1, three groups of participants were compared based on their emotional reactions and driving behaviors. Results showed that angry drivers who did not listen to music had riskier driving behavior than emotion neutral drivers. Results from heart rate, oxygenation level in prefrontal cortex, and self report questionnaires showed that music could help angry drivers react at the similar level to emotion-neutral drivers both internally and behaviorally. In Experiment 2, types of music emotion and familiarity of music were addressed to identify what kind of music an in-vehicle auditory system should play when it recognizes drivers&rsquo; anger. Results showed that different kinds of music did not effect driving performance. However, drivers experienced less frustration and effort when listening to music in general and less viii frustration when listening to self-selected music specifically. Regarding personality characteristics, drivers who had anger-expression out style had riskier driving behavior just as in Experiment 1. In conclusion, this research showed the benefits of music as a possible strategy to help angry drivers. In addition, important patterns were uncovered relating to assessing driver anger for possible affective intelligent systems in cars.</p><p>

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Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (M. A.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Continual increase in transport demand and uneven road capacity results in chaotic traffic congestion, brings with it high levels of air pollution, an elevated number of accidents, and an insatiable demand for oil to satisfy the motorized vehicles on roads. The dualmode transportation system is a transformational solution to address all of these problems simultaneously. This project will quantify the amount of energy needed to electrify a portion of the actual ground transportation (personal vehicle and freight) in a specific electric region grid and analyze the impact that it represents. A model that gives a close approximation of the electric energy demand that would be generated by converting existing traffic data into electricity demand was developed. This model allows for sensitivity testing of all conversion factors, data variation and variations in the different types of propulsion technology that may be used in the new system. Results show that inclusion of the new transportation system into the electric grid of Texas will not require significantly more energy than the current available resource.

Continual increase in transport demand and uneven road capacity results in chaotic traffic congestion, brings with it high levels of air pollution, an elevated number of accidents, and an insatiable demand for oil to satisfy the motorized vehicles on roads. The dualmode transportation system is a transformational solution to address all of these problems simultaneously. This project will quantify the amount of energy needed to electrify a portion of the actual ground transportation (personal vehicle and freight) in a specific electric region grid and analyze the impact that it represents. A model that gives a close approximation of the electric energy demand that would be generated by converting existing traffic data into electricity demand was developed. This model allows for sensitivity testing of all conversion factors, data variation and variations in the different types of propulsion technology that may be used in the new system. Results show that inclusion of the new transportation system into the electric grid of Texas will not require significantly more energy than the current available resource.

Thesis (Ph. D.)--University of Texas at Austin, 2003. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (M.P.A.)--University of Hong Kong, 2001. / Includes bibliographical references.

Thesis (M.A.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 123-129).