Passenger numbers in rail transportation and the need for transportation of goods hasbeen rising over the last years. After a breakdown during the years of the pandemicthe need for transportation on rail has almost recovered and numbers are rising again.Additionally, the carbon footprint for transportation becomes more important in thecontext of the climate crisis. The rail infrastructure in Germany has therefore cometo its limits on many stretches, having problems to fit the rising demand. As theconstruction of new infrastructure is taking a lot of time and resources, digital solutionsshould help to increase the capacity on the existing infrastructure and prevent bottlenecks. This thesis is therefore looking at the influences of the individual train driverson capacity and how an Automatic Train Operation system (ATO) in combination withthe new European Rail Traffic Management System (ERTMS) can help to increase thecapacity. For this purpose, the central part of the S-Bahn Stuttgart network was chosenas a case study as it is one of the lines currently already running over capacity, in needfor an upgrade.

To show the effects of the train driver and its individual behaviour on the capacitya runtime model was written in MATLAB. The model calculates the train dynamicsand running times based on the properties of the vehicle and the infrastructure.Furthermore, it can calculate the braking curves for the ERTMS/ETCS system, whichare then used for the braking of the train in the model. Based on the input parameters,the model calculates a journey operated by an ATO or a driver operated train along theinfrastructure. It can also handle several trains of different operational modes to followeach other and create a timetable for all of them. To validate the results an existing toolfor modelling capacity, RailSys has been used, a software designed for the constructionand simulation of timetables. Additionally, the braking curves calculated by the modelwere compared to the reference tool provided by ERA.

The results show that the automatic operation leads to shorter travel times and a morehomogenous operation in all cases. The behaviour of the trains operated by an ATOsystem is predictable and does not change between the different departure. This saveson average over 14 seconds per departure for the almost 10-kilometre-long stretchalong the line in Stuttgart. This is due to the differences in the braking behaviour of thetrains with a train driver. Additionally, a shorter headway because of shorter reactiontimes allows for more trains to be operated per hour. With conventional operation bya driver, the limit of the infrastructure is 25 trains per hour. With an ATO this can beincreased to 28 trains per hour. The RailSys model shows travel times which are evena little shorter. The running time distribution between the stations is similar and showa more optimistic result for the ATO. All results are without buffer times, which areimportant for a stable operation.

In general, it can be concluded, that the automation in railway traffic can lead toa higher capacity, which is beneficial for crowded infrastructure. This additionalcapacity can be used for the operation of additional services or to increase timetablestability. The options for improvement are limited though and cannot replace theconstruction of new infrastructure and other improvements entirely. The effects of thecombination of a restructuring of the block division in combination with ATO and/ora traffic management system show potential as well as improvements in dwell time, asthe stopping time decreases the capacity significantly.