The goal of this research is a better understanding of driving behavior on a global scale. This thesis analyzes global fleet data to gain insight into the trip driving behavior of a fleet. The detailed analysis of the distributions of the trip parameters provides insight into the trip driving behavior in different regions. The focus of this work was the variation of the trip parameters distance traveled, travel time and average speed in different regions. Through a comprehensive analysis, not only differences and similarities in the distributions of these parameters could be identified, but also a grouping of countries according to similarities in the distributions could be found. These groupings are intended to give an indication of which factors influence driving behavior in similar regions. The study of traffic parameters in different countries, cities and on different days also provides insight into global traffic patterns and trends. Furthermore, the question of suitable distribution functions for modeling the trip parameters of the vehicle fleet is the subject of the study. It was investigated which distribution functions for distance, travel time and average speed are already known and how they can be adapted to real measured data. This step not only enables a realistic representation of the trip parameters, but also opens up the possibility of creating scenarios and forecasts for the future. However, these large-scale data do not allow detailed conclusions to be drawn about local traffic dynamics, in particular specific driving maneuvers such as merging behavior on highways or interactions between vehicles.To investigate these microscopic aspects of traffic flow, drone images were also analyzed.These high-resolution aerial images allow precise recording of vehicle movements, time gaps between vehicles, and lane change strategies, and show how individual vehicles behave in complex traffic situations. These were analyzed in detail, with particular attention paid to possible differences in the frequency of use of lane change positions.The results showed which areas of the highway entrance are preferentially used by drivers to change lanes.Another focus was the analysis of time gaps between vehicles in the merging lane during the merging process.It was investigated how these time gaps vary in the area of the merging process and what role they play for the merging behavior. The findings revealed the distribution of time gaps during the merging process and offered insights into their impact on the merging behavior of vehicles. The behavior of vehicles entering the main carriageway was analyzed to understand how merging affects speed profiles.Our findings indicate that the speeds of already-driving cars adapt to merging processes by newly arriving vehicles, causing a temporary increase in speed variance on the main carriageway. Both decelerations and accelerations due to merging occur, enabling this adaptation. Overall, the analysis of drone data provides important insights into merging behavior, time gaps, and speed profiles at freeway entrances.     «

The goal of this research is a better understanding of driving behavior on a global scale. This thesis analyzes global fleet data to gain insight into the trip driving behavior of a fleet. The detailed analysis of the distributions of the trip parameters provides insight into the trip driving behavior in different regions. The focus of this work was the variation of the trip parameters distance traveled, travel time and average speed in different regions. Through a comprehensive analysis, not on...     »