Railway transportation is one of the major transport modes for industrial goods. Nevertheless, a lack of train drivers can be observed throughout Europe, which slows down the development of this sustainable transport mode. This issue is even supported by the fact that disposition processes are often organized manually, which, in the combination with the complexities of railroad operation, leads to a low productivity and exacerbates the shortage of driving personnel.
Thus, the project WILSON-LEARN aims at developing a machine learning based algorithm for improving the productivity of employees and counteracting the personnel shortage.
The algorithm is developed in cooperation with Menlo79 and will be implemented as well as tested at Havelländische Eisenbahn (HVLE).
This project is part of "Zukunftsbündnis Schiene" and funded by the Bundesministerium für Verkehr und digitale Infrastruktur (BMVI).