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Autonomous systems

Autonomous systems: Their place in our future

Autonomous systems will make us more productive, efficient and safer

8-minute read

When a huge ship became wedged in the Suez Canal in March 2021, it almost felt like a moment of light relief. In a world grown weary of an endless news cycle focused on the pandemic, there seemed something slightly comical about the situation. But once the initial flurry of amusing memes and talk show quips had subsided, it was clear that there was a serious supply chain crisis brewing—the effects of which continued long after the Ever Given cargo ship was freed. 

The German insurer Allianz claimed at the time that the incident may have cost global trade $6 billion to $10 billion a week, while the business press reported shipping still suffering ramifications a month after the event.

Many see this as a “black swan event”—unusual and unlikely to be repeated—but others suggest that it could accelerate autonomous shipping innovation. Because if an autonomous system had been on board the Ever Given, the situation could have been avoided.

The system would have continuously measured the change in the depth of the canal, calibrated the ship’s proximity to the shore and cross-referenced that against the prevailing wind speed and direction. It would have dynamically changed the ship’s course without human intervention and prevented the incident. According to Mikael Mäkinen, President of Rolls-Royce’s Marine business, “Autonomous shipping is the future of the maritime industry.”

But it’s about more than big boats. Across industries and societies, autonomous systems are going to make lives safer, more productive and more efficient.

What is the socio-economic value of autonomous systems?

Work is already underway to use autonomous systems to help address the early 21st century megatrends—climate change, growing inequality and digitalization—and enable industrial productivity and human wellbeing.

Autonomous systems can be used for multi-sensory industrial IoT tracking. They can run low-carbon public transport and factory production lines and manage efficient power consumption in cities. They can ensure sustainable practices in agriculture and food production and avoid environmentally damaging land use while increasing productivity per hectare. They can also be used to support health and eldercare in countries that have aging populations and fill skills gaps in the digital economy.

Nokia Bell Labs Consulting (BLC) predicts that digital transformation, artificial intelligence (AI) and machine learning (ML) will create new kinds of jobs. The low latency connectivity and high data rate transmission of 5G will allow maximum efficiency and flexibility. In its paper The rise of the new collar worker, BLC says that typical repetitive or dangerous blue-collar roles—for example mining or handling hazardous materials—will either be replaced by machines or machines will allow workers to perform their roles safely. Similarly, some white-collar and specialist roles can be scaled up and made more efficient through AI/ML.

“We call these types of jobs “new-collar” jobs because they combine human and machine skills.”

Bell Labs Consulting

Autonomous systems can also protect governments, companies and citizens against cyberattacks. In May 2021, the DarkSide ransomware attack on the Colonial Pipeline in the southeastern US forced Colonial to shut down its operations and systems managing its pipeline and fuel distribution. This caused supply problems for businesses and consumers and led to panic buying and rising prices in some states. 

Autonomous systems could be used for early incident detection. They can use AI to learn what is normal or unusual for a business without relying on prior knowledge of threats. This means it could identify and defend against never-before-seen threats and mount a response before damage is done.


What is autonomous transportation?

Some of the early use cases for autonomous systems can be seen in other transportation sectors. Semi-autonomous cars are already on the market and autonomous cars are being tested by major car companies, as well as Google, Intel and Uber. 

These systems will have the ability to respond in real-time to changing road and weather conditions and traffic diversions. They’ll monitor and manage the performance of the engine and onboard systems and reroute the vehicle if maintenance is required. When there is a delay, these systems will interact with other systems and ensure a replacement vehicle is ready or a restaurant/accommodation is booked. According to car manufacturer Daimler, by anticipating issues, these systems can make driving safer, more energy-efficient and less stressful. 

“Autonomous driving…will not only enhance safety and comfort, but also provide us with more free time which was previously spent driving.”


Autonomous systems are moving into the realm of public transport as well. The Thales Group is developing autonomous trains and Brussels Airport will have driverless buses. These dynamic, self-learning systems will operate 24/7 and adapt to changes in external conditions to provide fast and safe, low-carbon transport.

Autonomous aircraft are on the cards too, but latency and the way the AI learns are critically important for safety and trust. 

What is autonomous manufacturing?

Manufacturing and logistics are early adopter industries. In supply chain and warehouse processes, the logistics can be automated and adjusted according to production and delivery needs, bringing additional safety and efficiency benefits. When autonomous systems are deployed, predictability and process stability increase; buying, selling and logistics are optimized; error rates decrease; and sorting, picking, and storing times of inventories are minimized. Many of these benefits can already be seen in Nokia’s Conscious Factory in Oulu

A behind-the-scenes look at 5G autonomous systems

As well as ML/AI, 5G is making many scenarios possible, particularly by providing high-speed connectivity on factory floors. 5G 3GPP Release 18 intends to bring down latency to <10 milliseconds and 1 cm accuracy indoor and 10 cm accuracy outdoors. This makes it highly suitable to many of the nascent use cases associated with autonomous systems.

Figure 1. Positioning features for 3GPP Rel-15 to Rel-18 and beyond 

Positioning features for 3GPP Rel-15 to Rel-18 and beyond

5G’s ultra-fast responsiveness makes it easier and safer for automated guided vehicles (AGVs) and other machines and robots to work with each other and with humans. Sensors on AGVs and 5G-enabled devices ensure they don’t interfere with the actions of those around them and, in case of an emergency, wireless full shut-off is effectively instant. This 5G-based, critical manufacturing industry case is on course to be deployed by both Daimler and Bosch. 

In addition to changes to the technology, autonomous systems require changes to business logic and core business processes such as customer relationship, supply and demand management and production and delivery chain management. Developing autonomous systems is complex; it requires technology investments and new thinking in terms of the collaboration and ecosystems.

What’s next for autonomous systems?

Once autonomous systems are determining decisions and actions, the number of parameters increases and the logic, causes and consequences of decision making become more complex. It’s important to understand how to ensure the transparency, safety, legal responsibilities and ethics of machine-based decision making. 

No matter how well we build and program systems, failures will occur. That could mean an autonomous vehicle crashes into a static object or causes an accident or fatalities.

Safety goes hand in hand with legal responsibility. If the car crashes, who is responsible? Is it the human driver, the car manufacturer, the software developer, the AI, or the network connection? When human life is dependent on decisions made by machines, who takes on the insurance risk? These legal responsibilities must be addressed before wide adoption can occur.

This relates to the ethics of AI. If an autonomous system uses learning algorithms to ensure the best outcomes, how do they determine the concepts of “best” or “right”? Responsible usage of technology and data, ethics of AI and share of responsibilities are questions that must be considered. Standards are needed to ensure that different systems can integrate and communicate with each other and add value to each other.

Autonomous systems should only be used for the system they were designed for to avoid misuse and checked to identify negative impacts on individuals or communities. And as the future of work, and humans’ place within it changes, policymakers must ensure that legislation covers machines and the software and algorithms that drive them. Above all, humans must remain in control of and benefit from machines. 

In the longer term, autonomous systems have the potential to help businesses go beyond producing goods and services. The EU has identified an Industry 5.0 research and innovation project that focuses on the shared value business model. The well-being of the worker is at the center of the production process and it uses new technologies, like 5G and other digital technologies, in new jobs while “linking planetary boundaries to business”.

While technological pivots are rarely shaped by one event, perhaps future historians will look back at the Suez blockage as a bellwether for the rise of autonomous systems. Because there’s as seismic shift underway—and communications technology is making it happen.