Finland. The lab, among the first of its kind, is designed as a testing environment for remotely controlled, autonomous vessels. Wärtsilä recently delivered a navigation simulator and specific mathematical models for the project. They will be used to carry out simulated testing of remote-controlled vessels that the organisers hope will culminate in a real-world case study.
The smart tug of tomorrow
The benefits of early-stage simulation testing are already being seen in one real-life application – the IntelliTug project, a collaboration between Wärtsilä and Singapore’s leading harbour and terminal towage operator, PSA Marine. The project aims to develop the smart tug of the future by retrofitting Wärtsilä’s smart navigation system on PSA Marine’s harbour tug, PSA Polaris. Through the simulator, the team tested the integration of cutting- edge technologies deployed – including collision avoidance software and system usability – with feedbacks from PSA Marine’s tug masters. The success of the simulations boosted the project team’s confidence to proceed with the next stage of the testing. In March 2020, Wärtsilä and PSA Marine successfully completed initial sea trials for the IntelliTug project.
The smart navigation system, comprised of Wärtsilä’s Dynamic Positioning system, a sensor suite and a newly developed sensor fusion engine, allows the tug master to carry out passage planning while maintaining safe distances from other vessels during autonomous navigation.
The IntelliTug project enhances the tug masters’ capabilities through heightened situational awareness and eases the task of addressing other complex demands they may face.
Alexander Ozersky, Deputy General Manager of Intelligent Systems, Wärtsilä Voyage, explains: “Every system separately was complex, and once you connect them it was going to be even more challenging. We took the decision to try and debug all the pieces in the simulation using the actual control and a mathematical model of the engine. From an engineering perspective, we saved a huge amount of time, making quick mistakes as cheaply and as safely as possible.”
Testing the integration of systems on an autonomous vessel is one thing; providing the systems involved with the intelligence to make decisions in complex marine environments is another challenge entirely. Here, the capability to simulate scenarios is just one building block. Another necessary foundation is the ability for systems to learn from experience.
It is a challenge that Wärtsilä has already addressed in its Advanced Intelligent Manoeuvring (AIM) function, part of its package of artificial intelligence tools. AIM is a track prediction system and anti-collision support tool designed to improve situational awareness and reduce the probability of officer inattention or poor judgement leading to an incident. It anticipates that vessels will move in compliance with collision regulations, but also needs to account for how humans interpret those regulations in various situations.
“Interpretation depends on context,” says Ozersky. “The acceptable distance between vessels is one example. Less than one mile would be unusual in open water but very normal in a harbour.”
Simulation meets machine learning The artificial intelligence for AIM and other products – including Wärtsilä’s Vessel Traffic Services for managing traffic in ports – needs to absorb the habits of local traffic and refine its simulations based on its observation of how vessels actually move. So far, the system has collected data on traffic movements at several ports. With each new set of data, the simulations become more realistic.
This combination of simulation and machine learning will be critical in controlling autonomous vessels. It is already available in decision-support software today and is being trialled in autonomous navigation systems. Before it is let loose on a wider scale, there are many problems to be solved. Among these are the ways in which autonomous vessels interact with other automated systems that do not follow similar protocols – let alone the even less predictable ways in which manned craft may respond to autonomous ships.
Neil Bennett concludes: “Our simulation technologies are providing researchers with a platform to run these studies, and we are constantly being challenged by the need to advance our technology further. We can already do a lot with the technologies we have, and we are evolving products to meet the needs of future autonomous vessel systems.”
Source: Wärtsilä
The Report • September 2020 • Issue 93 | 85
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