Modeling the Impact of Digitalization on Railway Capacity
Mobility Initiative Project
Digitalization offers a valuable opportunity to increase railway capacity efficiently. Railways face rising demand, but expanding infrastructure is often infeasible due to space, cost, and planning constraints. Instead, digitalization enables better use of existing infrastructure through real-time train control, adaptive scheduling, and intelligent traffic management. Technologies like ETCS, moving-block systems, and automated decision support systems improve efficiency while ensuring safety and reliability.
However, existing capacity evaluation methods do not fully capture digitalization’s potential. Based on UIC 406, traditional railway assessment relies on blocking-time deterministic models, assuming fixed schedules and predefined track allocations. These models fail to account for stochastic influences, such as disruptions, driver variability, and fluctuating demand, which are critical for assessing real- world railway performance.
The key challenge is evaluating digitalization holistically across different railway contexts. While extensive research exists on individual technologies, most studies focus on isolated case studies. There is no established framework to assess digital strategies across railway networks, nor to quantify their interactions and uncertainties. This lack of integration makes it difficult for infrastructure managers to compare investments and maximize returns.
This project bridges this gap by developing a scalable, probabilistic framework to assess digital railway capacity. We integrate dynamic modelling techniques to quantify digitalization’s impact under real- world uncertainties. Key performance metrics will evaluate planned vs. realized capacity, enabling systematic comparison of digital investment strategies. In collaboration with SBB and Siemens, it will align theoretical capacity gains with practical railway operations, ensuring digital solutions are validated in real-world conditions.
The project delivers a decision-support framework to help railway operators prioritize digital investments efficiently. It will unlock untapped railway capacity without costly infrastructure expansion by shifting from static, deterministic models to dynamic, data-driven approaches. The findings will provide actionable insights for policymakers and operators, leading to higher efficiency, more reliable operations, and a more sustainable railway system.
