Improving a railway timetable by implementing technologies for increased automation

The capacity of many railway networks in Europe is highly utilized, but planning norms such as headways and buffer times in the timetable are already optimized given the available infrastructure. Thus, planning norms in busy networks can only be further decreased by implementing new technologies for increased automation, including Driver Controlled Operation, European Rail Traffic Management Systems, Automatic Train Operation, and Traffic Management Systems. Implementing all these technologies directly on a national level would be too complex and would require high investments. Furthermore, since the technologies are relatively new, there is the need to assess their implementation on different corridors and rolling stock based on their effect on the timetable, before deploying them nationally. To address this challenge, we propose a novel railway timetable optimization model that extends the periodic event scheduling problem by allowing the implementation of planning norm decreasing technologies under a budget constraint. Specifically, the model can choose what technologies to implement on what corridors and train series such that the optimized timetable benefits the most. Numerical experiments on single-line and regional railway networks in the Netherlands provide insights into the effectiveness of different technologies, the identification of specific corridors and train series for implementation, and reveal that relatively small investments (15-20% of the total) can lead to 60% of the potential timetable improvements. The proposed model can thus be used as a decision support tool for railway operators and infrastructure managers to prioritize the implementation of technologies and their locations in a railway network.