A new research project has started: With “KIBA”, we are researching artificial intelligence and discrete loading optimization models for increasing capacity utilization in combined transport together with Prof. Elbert and project manager Yuerui Tang.

The continental combined transport is characterized by a great heterogeneity of the loading unit types and the rail wagons used. Therefore, a valid and optimized allocation between the loading units and the rail wagons according to various target variables is to be determined. In addition to the static-technical characteristics of the semi-trailers, containers and swap bodies (interchangeable containers) in their different designs and rail wagons, variable parameters also play an important role, such as the actual weight and type of load and the timetable.

The project goal: Within the shortest possible time, each request for loading of a loading unit receives a proposal for optimal placement of the loading unit on a deployed wagon set – and this already before

all information is available about which other loading units for the same origin/destination relation will still arrive at the dispatch terminal until departure. Loading optimization is supported by AI and is intended to further advance the capacity control of operators with their extensive networks.

With a planned duration until September 2025, this project is being funded by the German Federal Ministry of Digital Affairs and Transport with up to 2.34 million euros as part of the Innovation Campaign Artificial Intelligence in Mobility. Our Vice President for Research and Young Scientists Prof. Peter Stephan accepted the BMDV's funding certificate from State Secretary Hartmut Höppner at the official handover ceremony in Berlin on November 25, 2022.

Together with our project partners Kombiverkehr KG, Goethe University-Frankfurt, Deutsche Umschlaggesellschaft Schiene-Straße (DUSS) mbH, VTG Rail Europe GmbH, INFORM GmbH and KombiConsult GmbH, we are looking forward to an exciting project full of innovative and future-oriented results.

You can find more information about this project here.