Stena Line Launches AI Study on Board Stena Scandinavica

Stena Line's Head of AI Lars Carlsson and Senior Master Jan Sjöström discussing the new AI-model onboard Stena ScandinavicaImage Courtesy: Stena Line

Ferry operator Stena Line is running a pilot study with artificial intelligence technology implemented on board vessels in an effort to reduce fuel consumption and minimise environmental impact.

In close collaboration with the technology company Hitachi, an AI-model is being developed that will help predict the most fuel-efficient way to operate a certain vessel on a specific route. The model will be a support for the captain and officers on board, and if successful it will contribute to Stena Line’s sustainability target to reduce fuel consumption by 2.5% annually.

“The model simulates many different scenarios before suggesting the most optimal route and performance setup. With the help of AI we are able to consider a number of variables, such as currents, weather conditions, shallow water and speed through water, in various combinations which would be impossible to do manually,” Lars Carlsson, Head of AI at Stena Line, said.

The model is still under development and it would not be possible to take it further without a committed captain and crew. The first pilot study is taking place on Stena Scandinavica, under the supervision of Senior Master Jan Sjöström who has been working with fuel optimisation at Stena Line for the last 40 years.

“Since we are helping the AI to evolve, we might be assisting the AI more than we are at the moment, but it is a very exciting and rewarding process. We’ve been making adjustments to the model after each trip for about four weeks and it is amazing to see how quickly it is learning,” Jan Sjöström, Senior Master at Stena Scandinavica, said.

Stena Line has an overall goal that the whole company should be assisted by AI in 2021 and the pilot study on Stena Scandinavica, on the Gothenburg – Kiel route, is the first of several studies regarding AI-assisted ferry trips within the fleet this year. At the end of the year there will be an evaluation of the project, before deciding how to continue with AI-assistance on the company’s 38 ships.

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