The GoTo main goal is to transfer the most recent advances in optimization and machine learning to railway traffic management. We will develop the methodological groundwork for an Optimization-based Traffic Management System (OTMS) that integrates state-of-the-art optimization algorithms and advanced forecasting techniques to tackle the complex scenarios of train dispatching that are found in Norway and the rest of Europe. Expected benefits include improved punctuality, reduced workload for dispatchers, and more efficient utilization of the existing infrastructure. The outcome of this project will be a prototype tool that will be tested in the greater Oslo area. Clearly, all developments for the greater Oslo area can be easily extended to any other railway region found in Norway. Dispatchers at the Oslo control center will be able to visualize the effects of each decision they make, up to few hours in the future. More importantly, the OTMS will automatically suggest them a set of optimized dispatching decisions based on the current train positions and preferences. All in real-time. In addition, we intend to investigate a novel methodology that exploits information gathered by the optimization algorithm of the OTMS with the purpose of identifying bottlenecks in the rail network. This will help steer future investment decisions in infrastructure enhancements. The project will last 3 years, and it will involve three main actors: SINTEF as the project owner and research partner, Bane NOR as the industrial partner and NSB as an end-user (train operator). SINTEF will contribute with its extensive expertise and outstanding research in optimization, machine learning, and train dispatching, in particular. Bane NOR, as the responsible for operating and developing the Norwegian railway network, will provide all the necessary knowledge and support for the prototyping and validation.
Project leader: Carlo Mannino
Category: Teknisk-industrielle institutter
Institution: SINTEF DIGITAL