In January last year, a Japanese car ferry, the Soleil, became the first large vessel to navigate without human intervention. The 220-metre-long ship automatically berthed and unberthed, turned, reversed and steered itself for 240 kilometres across the Iyonada Sea from Shinmoji in northern Kyushu — manoeuvres that even skilled human operators find challenging.

It is early days, but ships are increasingly deploying sensors and artificial-intelligence (AI) systems to navigate, steer and avoid collisions. As with cars, such advances should improve safety, increase efficiency and — along with cleaner fuels and engines — reduce environmental impacts.

This is crucial: 80% of global trade (around 11 billion tonnes) is transported by sea each year¹. In 2018, shipping generated around 3% (about 1,000 million tonnes) of global carbon dioxide emissions². The International Maritime Organization (IMO) has committed to halving the industry’s greenhouse-gas emissions by 2050.

Seafaring is risky and workers are in short supply. Inefficiencies and congestion at ports add delays and costs, as do accidents, such as the grounding of the container ship Ever Given in the Suez canal for six days in March 2021. Streamlining passage through locks, reducing energy consumption and negotiating manoeuvres to avoid collisions would enable safer and more optimal use of waterways.

Some small, fully autonomous boats, typically less than 10 metres long, are already in operation for specialist tasks such as monitoring water quality and infrastructure in the open sea, or as test beds for the technology. But the next couple of years will see a sea change, with the first larger ‘maritime autonomous surface ships’ planned to start commercial operation.

Pilot projects include the Norwegian container ship Yara Birkeland, an 80-metre-long vessel that, by 2024, is expected to convey fertilizer autonomously and with zero emissions from a manufacturing plant to an export port. In China, a 120-metre-long electric container ship called Zhi Fei has been demonstrated shuttling under remote (and sometimes autonomous) control between two ports in Shandong province.

In a decade, automated vessels might interact with one another. For instance, the Vessel Train, a pilot project funded by the European Union and coordinated by the Netherlands Maritime Technology Foundation in Rotterdam, uses a crewed lead vessel to head a convoy of smaller, automated ones that can access small waterways around ports efficiently. Ultimately, fleets of self-steering ships or boats might be managed from maritime traffic-control centres located on shore.

But if autonomous vessels are to fulfil their promise, much remains to be done — and soon. More than 50,000 merchant ships trade internationally, under the flags of some 150 nations. A large, high-tech vessel can cost US$200 million to build, and can operate for decades. Ships are complex technically. They need to work in busy shipping lanes, ports and rough open seas.

Combining maritime systems is daunting — from radar, satellites and GPS, cameras and sensors, to image recognition, data analytics and machine-learning algorithms. And autonomous ships need to be plugged into a broader ecosystem of maritime technologies, including interactions between ships and with cargo handlers, equipment, pilots, traffic services and ports.

Here, we highlight research gaps in six key areas.

Understand the challenges at different levels of autonomy

The roll-out of increasing levels of autonomy needs to be managed to assure safety and to allow regulation to keep up. Operational guidelines are needed for vessels in the four classes of autonomy defined by the IMO.

The first challenge is to add sensors and algorithms based on AI and deep learning to the autopilot systems that are currently used on some crewed ships and boats — classed as IMO autonomy level one. Obstacles such as small boats, debris, swimmers and riverbanks do not appear on radar or on the global ‘automatic identification system’ (AIS) that tracks maritime traffic. Visual and thermal cameras and lasers would give a captain a better view of what is around, helping to avoid collisions, assess risks and plan routes — tasks that are now done manually. But to do that, researchers need to overcome limitations to sensor systems — for instance, that some smaller obstacles can be indistinguishable from waves.

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