The project of enhancing traffic safety is a continuous effort that will not cease in its aspirations. In fact, as technology evolves and additional digital artifacts are implemented into our cars, the attention to traffic safety becomes even more important. Driving a car through urban and rural environments is a cognitively challenging task that especially tax attentional resources, and as more artifacts compete for our attention during driving, the adherence to traffic safety is vital. Thus, factors that influence driving ability, such as sleep, nutrition and – perhaps - emotions are of great interest. An earlier study by Bulmash et al. (2006) hypothesized that individuals with Major Depressive Disorder would perform worse than controls in a study using a driving simulator; their hypothesis was confirmed. The purpose of this thesis is to investigate whether dysphoric individuals show reduced driving performance relative to controls. The notion of dysphoria refers to mild depression in a non-clinical sense. This was investigated using a driving simulator that measured Lateral Positioning (Standard Deviation of Lateral Position - SDLP) on the road, Brake Reaction Time (BRT) and performance on a secondary task (Peripheral Detection Task - PDT). Dysphoric individuals were identified using the Major Depression Inventory (MDI). The hypothesis was partly confirmed, as dysphoric individuals did indeed show more variable positioning on the road. However, performance differences on PDT and BRT were not significant. The results indicate that the negative influence of mood on driving ability is not a discrete phenomenon primarily manifested in individuals with clinical depression, but is rather a continuous phenomenon. The results should be of special interest to clinicians that evaluate individuals with depressive tendencies, as well as the academic community in general since the insights into the impact of emotions on cognitive performance are inconclusive and still not clearly understood. These results might also be of interest in other domains of high complexity, where human performance is of great importance, such as Command and Control, nuclear power plants and control rooms in general.