In the field of advanced driver assistance systems, researchers and developers make great efforts to reduce drivers' workload and to keep it on an ideal level respectively. In the course of these efforts the physiological detection of workload, also in commercial vehicles, is coming more and more to the fore. A total of 44 driving situations have been identified in an exploratory survey of truck drivers which are relevant for the resulting driver workload. This includes various driving situations as well as driving maneuvers and traffic situations, such as high traffic density or different weather conditions. With regard to objectively measurable parameters, these 44 situations were examined in a study with 37 professional truck drivers in the dynamic truck driving simulator of the Institute of Automotive Technology. In addition to the changes in pupil dilation the electrodermal activity and a subjective assessment based on the Rating Scale of Mental Effort (RSME) were used in order to detect the mental workload. The results were validated in a field trial subsequent to this driving simulator study. At the selection of the test course, particular attention was paid to a high degree of similarities between real-world and simulated roadway sections. The evaluation of the electrodermal activity measured in the real traffic study as an indicator for mental workload revealed the following. The most demanding activity during the performed study was making phone calls, whereby the participants were confronted with a planning task. Paying attention to an accessing car was also a high demanding task with anticipatory requirements with respect to the car driver's behavior. Regarding routine tasks such as crossing intersections, the evaluation of electrodermal activity does not lead to statistical differences between the investigated situations. In contrast, a self-report measurement of mental workload conducted in parallel shows sufficient sensitivity and therefore significant differences between the tested maneuvers and environmental conditions. Thus, in order to evaluate everyday driving situations with respect to the mental workload they cause, self-report measures are suggested to be the method of choice. Cognitively high demanding planning or anticipation tasks however can be detected reliably by means of electrodermal activity.