DNV, partners launch autonomous safety project

(OSLO, Norway) — At the Nor-Shipping trade fair Tuesday, DNV, Kongsberg Maritime, Kongsberg Seatex, Basto Fosen and NTNU announced the launch of the new SAFE Maritime Autonomous Technology (SAFEMATE) project. The project will work on improving and assessing the safety and efficiency of autonomous navigation systems and deploy a pilot on an operational ferry, Basto VI.

The promise of automating more functions in shipping shows great potential, and interest continues to grow throughout the industry as more projects are developed. For autonomous navigation, in particular, the technologies that support object detection and collision avoidance have the potential to enhance safety and efficiency across the whole industry.

The SAFEMATE project will focus on routing and collision avoidance, to create a system that is able to detect threats and obstacles in the marine environment, interpret this information, and communicate a solution to an onboard operator. The system will be tested though the use of simulators and with human operators in the loop and then will be deployed in full-scale trials on Basto VI, the Basto Fosen ferry that operates between Moss and Horten, Norway.

The SAFEMATE project will pilot an automated navigation decision support system on the Basto VI ferry. Torghatten AS photo

For these technologies to be widely adopted, the systems not only need to be developed, but tools and processes that assess and assure their safe function must be in place. The SAFEMATE project is designed to cover both of these aspects and test automated systems to assist navigation, while keeping an operator in the loop.

“For DNV, our focus is on building trust in complex software-controlled systems through testing and verification,” said Pierre Sames, group research and development director at DNV. “Modern vessels are already complex automated systems, but building in autonomous decision support capability, increases this complexity immensely. This is why it’s vital to develop a framework comprising processes and tools that can assess the safety performance of these systems both in the design stage and throughout operations. As these systems include machine learning modules, they require a new approach to safety assessment and verification.”

“We are delighted to see safety in maritime navigation at the core in the SAFEMATE project, with backing from leading industrial players and academia,” said Borre Flaglien, director of bridge systems at Kongsberg Maritime. “Kongsberg will through this project build on its strong position in autonomy enabled technology and provide automated advisory to manned vessels. Our bridge control system will double as a digital crewmember, warning of dangerous situations (including collisions) and advise on a preferred deviation maneuver.”

“The SAFEMATE project is an important step forward for us in Torghatten and a continuance of the good work we have been doing on the topic of autonomy,” said Jan-Egil Wagnild, CTO at Torghatten AS. “The technology and processes developed in the project are a few of many pieces in the puzzle when working on increased safety, energy efficiency and the enablement of integrated operations. Together with strong industry players in the project we believe that the project will answer a lot of key questions and provide us with valuable learnings.”

“The SAFEMATE project is key to further developing the Kongsberg Situational Awareness solution,” said Henrik Foss, product manager, Kongsberg Seatex AS. “The project focuses on exploiting technology brought forward for autonomous vessels, and how we can adapt this to increase safety and efficiency in the current bridge solutions. The SAFEMATE project enables us to work closely with users on integrating navigational decision support into the bridge in the best manner possible and with class on assurance frameworks which are essential for delivering these kinds of systems.”

SAFEMATE has been partially funded by the Research Counsel of Norway (RCN) through the MAROFF-2 program.


By Rich Miller