SchleusenNOK40

At around 100 kilometers, the Kiel Canal (NOK) is one of the busiest waterways in the world. Depending on the port of departure and destination, the distance ships travel between the North Sea and Baltic Sea is reduced by an average of around 250 nautical miles. Their travel time and fuel requirements are reduced accordingly.

When passing through the NOK, the ships must pass through locks. Up to now, the lock masters have only been able to rely on their many years of experience when planning the sequence of locks on the NOK. However, due to constant changes in traffic flows, short-term advance planning is becoming increasingly difficult, as there is no data available on current traffic volumes. Long-term, reliable advance notification of ships does not yet exist.

The project SchleusenNOK40 enables improved lock management through data-based traffic forecasts and knowledge-based planning and optimization processes. A planning and information system was developed for this purpose as part of the project. The aim is to provide better support for lock personnel in their decisions. Waterway users can thus obtain improved information about possible waiting and clearance times at the locks for their own planning.

In developing the system, the project partners relied on the consolidation of comprehensive data sets, such as weather and climate data, navigation and geodata. From this data and with the help of machine learning and stochastic analysis methods, forecasts were created and made available in an adapted form. In addition, a knowledge-based planning tool for optimized lock allocation and scheduling was developed, which incorporates the experience of lock personnel and supports them in lock operation.

“To implement the required functions, we rely on machine learning methods and processes for predicting traffic data as well as problem modelling, solution and optimization approaches from the fields of operations research, constraint programming and artificial intelligence,” says Dr. Armin Wolf, project manager for SchleusenNOK40 at Fraunhofer FOKUS. During the requirements analysis with stakeholders, FOKUS focused on lock planning and scheduling as well as on the necessary predictions of ship travel and arrival times and other data relevant to planning, scheduling and forecasting. In addition to the correct behavior, the quality of the predictions, the lock allocation plans and schedules, but also the reaction behavior in adaptive or interactive planning and scheduling is being investigated and improved.

In addition to Fraunhofer FOKUS, dbh Logistics IT AG and TTS TRIMODE Transport Solutions GmbH were also involved in the project. The project was funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of the mFUND (Modernity Fund) research initiative.