At present, an ÖBB dispatcher still has to manually assign empty freight wagons to requests from clients. The aim of the project “Partially Automated Empty Wagon Dispatching” is to support this process with software that suggests optimal utilisation. The research forms part of the TARO project, with which ÖBB aims to leverage automation and digitalisation to increase its capacities, boost productivity and thereby ensure high quality.
The rail system represents one of the most climate-friendly modes of transport. However, even within this system, there is scope for a more efficient use of resources. One of the areas affected by this is freight transport, with too many trains travelling through Austria empty. “We need to optimise the capacity utilisation. The aim of our project is to achieve a better allocation of requests to the available empty wagons. We want to ensure that fewer empty kilometres are travelled by rail”, as Philipp Hungerländer explains. He heads the project at the Department of Mathematics at the University of Klagenfurt. The project partners are the Rail Cargo Group of the Austrian Federal Railways and the software development company Anexia.
In order to meet the project objective, researchers conducted a comprehensive analysis of the prevailing situation. “Based on this, we carried out the mathematical modelling, which we can use to propose an optimal workload for each specific scenario,” Philipp Hungerländer elaborates. Solutions are calculated with the help of a software package, which then suggests the most efficient utilisation and allocations to the dispatchers.
For the railways, which play a major role in climate protection as an alternative to road transport, this should yield several advantages in terms of competitiveness: Higher capacity utilisation and lower costs are key. It is also important to simplify the dispatchers’ job by means of partial automation.
The research project commenced in 2020 and will be completed by the end of 2023. It is part of the TARO (Towards Automated Railway Operation) project and is funded by the Austrian Research Promotion Agency FFG.