Maritime traffic in winter in the Baltic Sea (particularly the northern part) is challenged by heavy ice formation. Icebreaker ships that can provide assistance are a limited resource that needs to be shared among all ships. Decision-making for winter navigation systems thus involves monitoring several parameters at both operational and system levels, including multiple stochastic parameters.
This work presented an integration of ice characteristics, operational-level details of ships, and system-level details such as traffic flows and icebreaker scheduling through a simulation framework.
The simulation model offers a platform to combine information from different sources: ice conditions, traffic flows, resource availability, and operating strategies. The model has been implemented using the AnyLogic software, with additional functionalities coded in Java.
The model captured ice navigation in detail, including convoy operations, where an icebreaker may assist a group of vessels together. The vessels followed the icebreaker, one behind the other, and the convoy moved together at a common speed.
This work presented a simulation-based framework for evaluating the impact of ice variation on maritime traffic. A case study focused on the Bay of Bothnia in the Baltic Sea Region was chosen to demonstrate the model. The model used a multi-level environment to capture ice information along with geographical coordinates and Automatic Identification System data for vessel trips.
The vessels and icebreakers in the system were modeled as agents whose behaviors were governed by statecharts. Using the simulation model to vary the ice conditions, the effects of ice levels on the winter navigation system were quantitatively captured through carefully designed experiments.
The model provided a bird’s-eye view of the winter navigation system and allowed for testing what-if scenarios, addressing important decisions about icebreaker availability in the future. The framework has been designed to be easy to use for stakeholders. The system behaviors have been modeled with inputs from experienced mariners and traffic controllers.