The Australian Maritime Safety Authority (AMSA) has banned bulk carrier AGIA SOFIA (IMO 9706786, dwt 82045) from Australian ports for six months, after receiving a complaint via the International Transport Workers’ Federation.
“During the inspection AMSA found evidence that some seafarers on board the ship had not been paid their wages in full since August 2019. The outstanding wages total about AUD $45,000 and constitute a breach of the rights of seafarers as per their employment agreements under the Maritime Labour Convention.”
AMSA Acting General Manager Operations Michael Drake noted it wasn’t the first time this company, Marmaras Navigation Ltd, had been caught underpaying crew in Australian waters.
“In January 2018 AMSA detained another company ship, Koundouros, at Port Walcott for owing its seafarers more than AUD $7500,” Mr Drake said. “Bringing a second ship, Agia Sofia, to Australia with the same breach is inexcusable and has left us with little choice but to ban this ship from Australian ports.”
Mr Drake said seafarers were making enormous sacrifices right now by being away for extended periods of time from their loved ones, just to keep critical global trade moving. “Abusing their most basic rights to be paid for the work they are doing is shameful behaviour on the part of this shipping company,” Mr Drake said.
So you, see, it’s all about seamen and their basic human rights, nothing personal. As usual, bulk carrier was attacked by the authorities after they’ve been tipped off or ordered, by ITF. As usual, culprit – shipowner – can’t speak for himself and explain what’s happening in reality, not in ITF claims. Shipowner is guilty by definition. Now, here’s another side of the story: it may well be so, that the shipowner after his ships are banned from Australian ports, may lose charters and contracts, suffer heavy losses, and with that, become unable to cover crew changes costs, and provide timely wages payments. He may go bankrupt. What will happen to crews, is nobody’s care, definitely not ITF or AMSA. It may well be so (in fact, it is so), that here and there and everywhere throughout the world, shipowners delay wages payments, in order to remain afloat and provide crew changes. It may well be so, that the crews, the employees of this or that owner, understand the situation, and given the enormous challenges owner faces, agree to wait it out.
Each and every case of wage delay or expired contracts, presently, is unique, and is subject to very careful consideration and treatment. Thoughtless and irresponsible detentions and bans, based on ITF claims, may lead in many cases, to tragedies of abandoned ships and crews, in the midst of worldwide “pandemic” insanity.
AMSA cares so much about seamen wellbeing and safety, that recently, it launched an inspection campaign targeting cargo securing arrangements on container ships visiting Australian ports, which will run from August until October. It involves extended port state control (PSC) inspections or stand-alone inspections on vessels that are not currently eligible for PSC inspection. According to AMSA, masters and shipping lines should expect that if a cargo ship visits Australia over this period that the ship will receive an inspection.
Crews which can’t be relieved far beyond their contract dates, with many being aboard for more than a year, now will be targeted for extra inspections.
Authorities live in another world, it seems. Instead of brining to crews as much relief as possible, instead of decrease or total ban of all inspections, they ramp inspections up. AMSA, you know, the crews will soon start intentional sabotaging of all your securing protocols and safety regulations. They don’t care, they have nothing to lose, and they’re on the verge of mass psychological and physical breakdowns.
Once upon a time, I vaguely remember, Australia was considered to be a maritime nation, and a land of free. Together with NZ, UK, USA, Canada. You know what? Soviet Union, in terms of personal freedoms, was in comparison with modern West, a paragon of freedom. Why did you throw away your freedoms with such an appalling ease, guys? What did you get in return? Safety from non-existent “deadly virus”? Total control over everybody and everything? Mass migration? Green idiots and phychos? BLM? ITF? AMSA? UN/WHO/IMO? You didn’t have yet Gestapo, KGB and GULAG, but they’re coming, real soon. Their emergence, indeed, seems to be inevitable.


The EMSA guidance provides recommendations relating to the development of ship and port management plans, as well as the interaction between cruise operations and ports and terminals.

Co-authored with the European Centre for Disease Prevention and Control (ECDC), the EMSA guidance follows the recent publication of EU Healthy Gateways guidance on the resumption of cruise ship operations.

Viewed in tandem, these guidance documents aim to establish a pan-European benchmark for national maritime transport and public health authorities for the future resumption of cruising in Europe.

CLIA and its member lines have been engaged in the development of the guidance, which will help to inform the development of protocols at the national level.

CLIA member lines are also identifying appropriate protocols, based on evolving guidance from health authorities and medical experts, that cover passengers from the time of booking their cruise, to the holiday itself and their safe return home.

Speaking on behalf of CLIA Europe, secretary-general Tom Boardley said: “This guidance from the European Maritime Safety Agency is an important resource for authorities and operators focused on the safe resumption of cruising in Europe.”

Visit emsa.europa.eu for more information.


The “Emerging Technology Opportunities for Maritime Autonomous Ships” report has been added to ResearchAndMarkets.com’s offering.

Advancements in sensor technologies for environmental monitoring, improved navigation, object detection, and collision avoidance, image processing algorithms, and machine vision have created opportunities for marine shipping companies to integrate a wide range of solutions for autonomous vessels.

Sensors are expected to be pivotal in the development of connected and autonomous ships. Apart from devices communicating with each other, future autonomous ships will interact with the environment around, thereby leading to various forms of business opportunities with the collected data.

This research service focuses on capturing emerging technologies enabling autonomous ships, industries best practices and use cases. Growth opportunity assessment was done to assess the pathway of sensor technology development, which will lead to making autonomous ships a reality.

Key questions addressed in the research service:

  • What are the various types of sensor technologies enabling autonomous ships?
  • What are the benefits and applications of the technology?
  • What are the key innovations and who are the innovators impacting autonomous ship development?
  • What are the use case scenarios in the autonomous shipping arena?
  • What is the impact of COVID-19 on autonomous ships?
  • What are future growth opportunities?

Key Topics Covered

1. Executive Summary

1.1 Research Scope

1.2 Research Methodology

1.3 Research Methodology Explained

1.4 Summary of Key Findings

2. Marine Autonomous Ships – An Overview

2.1 Marine Autonomous Ships – A Sneak Preview

2.2 Technologies Encouraging Development of Autonomous Ships

2.3 Satellite Communication and Space-based Sensors Aid in Garnering Information from Above the Ship

2.4 Sensor Fusion, Image Sensors, and UAVs Aid in Environmental Monitoring for Autonomous Ships

2.5 Echosounder, Side-scan Sonar, Forward-looking Sonar, and UUVs Play a Vital Role in Underwater Assessment for Autonomous Ships

3. Assessment of Industry Best Practices and Recent Initiatives

3.1 Strategic Partnership Paves the Way for Development of Autonomous Ship

3.2 International Maritime Organization Aids in the Framework for Marine Autonomous Surface Ships

3.3 Guidelines Lay Out Risk Mitigating Approaches and Autonomous Shipping Concepts

3.4 Regulatory Bodies for Ships Define Degrees of Autonomy

4. Implementation Case Scenario of Autonomous Ships

4.1 Demonstrations of Autonomous Cargo Indicate Reduced Fuel Consumption

4.2 Autonomous Ferry Demonstration Lays the Foundation for Development of Autonomous Ships

4.3 Demonstrations of Autonomous Vessels Indicate the Capabilities of Remotely Operated Marine Vessels to Gather Sea Data

5. Companies to Action

5.1 Stakeholder Initiatives – Rolls Royce Leads Various Initiatives in the Autonomous Ships Arena

5.2 Stakeholder Initiatives – Enabling Technologies for Autonomous Ships

5.3 Stakeholder Ecosystem – Demonstrations and Upcoming Autonomous Ship Projects in 2020

6. Impact of COVID-19 on Autonomous Shipping

6.1 Impact of COVID-19 on the Global Shipping Industry and Advancements in Autonomous Shipping

7. Growth Opportunities of Emerging Technologies for Autonomous Ships

7.1 Growth Opportunities of Autonomous Ships Across Potential Applications

7.2 Growth Opportunity 1: Disruptive Potential of Autonomous Ships

7.3 Growth Opportunity 2: R&D Partnerships of Autonomous Ships

8. Industry Contacts

8.1 Key Industry Contacts

For more information about this report visit https://www.researchandmarkets.com/r/t3m7nt


Autonomous vessel technology company Sea Machines Robotics has announced that it has closed a new $15 million financing round, a major vote of confidence for the Boston-based company, which launched its first products in 2018.

The funding round was heavily backed by Huntington Ingalls Industries (HII), America’s largest military shipbuilding company, as part of an agreement which will also see the companies work in partnership to accelerate HII’s own business deploying self-piloting technologies on unmanned naval vessels.

“This reinforces Sea Machines’ position as the leading developer of autonomous navigation and wireless vessel control systems,” said Michael Johnson, CEO, Sea Machines.

“Our ability to secure significant financing during a challenging economic environment is an indicator of investors’ confidence in our ability to reshape and retool the marine industries with modern-day, advanced technologies. And being selected as technology partner by HII, a leader in every right, further affirms our course in product and market approach.”

“We are entering a phase of growth and universal interest like what was witnessed in the self-driving automotive space starting five years ago, but the difference being that marine self-piloting systems are already operationally deployed. We expect to see broad adoption of autonomous technology on water ahead of that on roads.”

Sea Machines’ autonomous systems can be used to allow remote control of shipboard active domain perception and navigation duties, under the command of a human operator on shore.

To date, the company has already deployed systems on vessels serving a multitude of sectors, including large cargo ships, data-collecting survey boats, oil-spill response craft, and search-and-rescue (SAR), patrol and crew transfer vessels. The company was also selected by Maersk to run a pilot of its AI-based situational awareness technology on board a container ship.

“This investment represents our commitment to advanced innovation and competencies across the unmanned systems market,” said Andy Green, executive vice president and president of technical solutions, HII.

“Sea Machines is making significant strides in the unmanned surface vessel (USV) industry. We want to invest in their growth and continue to form complementary partnerships across this key domain.”

The investment round was led by Accomplice with further participation by Toyota AI Ventures, Brunswick Corp. (through investment partner TechNexus), Geekdom Fund, NextGen Venture Partners, Eniac VC, LaunchCapital and others.

Source: smartmaritimenetwork


In the May 2019 edition of Legalseas, we reflected on the implication of the Court of Appeal decision in the case of Evergreen Marine v Nautical Challenge (Evergreen) when considering the interaction (and interpretation) of the Collision Regulations (COLREGs) (specifically the crossing rule (Rule 15) and narrow channel rule (Rule 9)) in circumstances when they appeared to conflict.In this edition, we consider how the facts in Evergreen demonstrate the challenges faced by those developing autonomous vessels and particularly the algorithm-based navigational systems which will need to interpret the Regulations for the Prevention of Collisions at Sea 1972 (COLREGs). We have used the Evergreen case to consider circumstances where obligations under the COLREGs appear to conflict and speculate how the outcome may have differed if both or either the Ever Smart (the at-fault vessel) and Alexandra I (the inbound vessel) were fully autonomous.

COLREGs and Automation

The regulatory framework governing safe navigation has historically been premised on objective rules interpreted through a human element; for example the “manning” of ships, the “charge of a master,” or taking precautions required by the “ordinary practice of seaman.” Subjective standards are pervasive throughout the UN Law of the Sea Convention 1982, IMO Regulations, domestic shipping legislation, including the Merchant Shipping Act 1995, and civil liability conventions.

The COLREGs are particularly relevant in this regard. Since 1977, seafarers have been obliged to comply with the COLREGs on issues of collision avoidance and, indeed, courts have interpreted the COLREGs when apportioning liability arising from collisions. Being practical rules, having as their primary object the prevention of collisions at sea, the COLREGs provide objective guidance on vessel priority but also necessitate (subjective) deviations from the rules, in accordance with the ordinary practice of seamen if the circumstance requires. By way of example, COLREGs, Rule 2 states, “Nothing in these Rules shall exonerate any vessel, or the owner, master or crew thereof, from the consequences of any neglect to comply with these Rules or of the neglect of any precaution which may be required by the ordinary practice of seamen, or by the special circumstances of the case.” This subjective interpretation of an objective rulebook highlights the inherent challenge in automating deviations from a set of rules, absent a human element.

There has been significant discussion across the shipping industry as to whether unmanned or fully AI-enabled vessels can strictly comply with provisions under the current COLREGs, including on Rule 2 (responsibility), Rule 8 (action to avoid-collision) with regard to the seamanship standard, Rule 5 (look-out), and Rule 18 (responsibilities between vessels) with regard to vessels “under command.”

Various research studies conducted over the course of the past 12 to 18 months have allegedly demonstrated that autonomous vessels can meet (or exceed) the current COLREGs collision avoidance rules. Rolls Royce’s MAXCMAS project (Machine Executable Collision Regulations for Marine Autonomous Systems), in partnership with Lloyd’s Register (amongst others), claim to have developed an algorithm–enabling, AI-based navigational system to effectively enact the COLREGs rules in a manner that is “indistinguishable from good seafarer behaviour,” even in circumstances “when the give-way vessel isn’t taking appropriate action.” The latter will be essential when both autonomous vessels and manned vessels are trying to keep out of the way of one another.

While this article does not seek to address issues of strict compliance, the case of Evergreen demonstrates two issues: (i) that the identity of the “give way” vessel may not always be readily apparent to experienced deck officers; and (ii) that “good seafarer behaviour”, in the context of apportioning liability, is not a fixed standard – it is a product of factual circumstance, interpreted through the (various) rules of the COLREGs, past case law, and the views of expert nautical assessors (the Elder Brethren of Trinity House) post-event. Just as one of the dilemmas facing masters and bridge watch keepers is what to do when faced with a situation where obligations under the COLREGs appear to conflict, those developing autonomous shipping solutions must equally grapple with the same dilemmas; save that they have to program these decisions pre-event in a way that is predictable or the system will have to apply machine learning to be able to comply with the Rules.

In this article we assume that the 1972 COLREGs are applicable to both manned vessels and vessels controlled by AI. The issue of whether an autonomous ship can be programmed to determine whether Section II – Conduct of vessels in sight of one another (Rules 11-18) and Section III – Conduct of vessels in restricted visibility (Rule 19) of Part B – Steering and sailing rules, applies to a developing close quarters situation is an important one but while manned and unmanned ships are sharing the same waterways, then it will be essential that both comply with the same rules. We discuss the issues arising from this assumption at the end of this article.

Below, we have considered whether, on the facts in Evergreen, two autonomous vessels would have been able to avoid a collision. In doing so, we also consider a number of the challenges facing developers of maritime AI solutions from a collision liability perspective.

Discussion

Rule of Law

Counsel for Ever Smart (the at-fault vessel) argued on appeal that “there was no rule of law” as to the priority of the narrow channel rule (Rule 9) in a crossing vessel situation (Rule 15). When interpreting the interaction of Rule 15 and Rule 9, the first instance judge relied (with some emphasis) on statements of principle from two non-binding cases with a similar (although not identical) fact pattern, The Canberra Star [1962] and Kulemesin v HKSAR [2013]; the former a first instance decision and the latter a decision of a foreign court in criminal proceedings. While persuasive, neither case proffered definitive ratio (a finding that sets a legal precedent); the first instance judge chose to apply the statements of principle – both because of the “experience and knowledge” of the respective trial judges and also because he agreed with them – he was not, however, strictly bound to do so.

In determining whether the crossing rule applied, the first instance judge had considered whether Alexandra I was on a “sufficiently defined course.” There is no strict requirement under Rule 15 of the COLREGs that a vessel must be on a sufficiently defined course (or indeed any course) in order to be subject to the rule. The principle was established by Lord Wright in The Alcoa Rambler [1949]. Alexandra I’s course made good varied between 081 and 127 degrees at about 1-2 knots over the ground. She had traveled less than a mile in approximately 20 minutes. The court was satisfied that this was not ‘sufficiently defined’ to be considered a course, notwithstanding the constant south-easterly heading, and instead described Alexandra I as “waiting for the pilot vessel to arrive.” Consequently she was not bound by Rule 15 as she was not on a course that was crossing with that of the Ever Smart.

Neither the court of first instance nor the Court of Appeal provided additional clarification as to when a vessel (either by speed or by line or heading) will be deemed to be on a sufficiently constant course. Rather, the test appears to require an observer (who has spent “sufficient time” observing the vessel) to ascertain if the vessel is not on a defined course (i.e. constantly changing her heading). In the context of automation, this raises an obvious concern. For example, had Alexandra I been travelling at three knots, would that have made a material difference? Equally, had her course made good varied by a lesser degree (say between 90 and 110 degrees), would the system have drawn a different conclusion? What degree of variation would an AI system require to deem another vessel to be on a constant course?

If this situation was not apparent to two experienced masters, and at Court required an application of case law to determine the obligations of the two vessels, then is it likely that two autonomous vessels would have definitively been able to identify their respective obligations under the COLREGs? The very fact that permission to appeal was granted with respect to the issue of priority demonstrates that there was uncertainty as to the application of the narrow channel rule, and indeed this uncertainty would have arguably been amplified had the approach of Alexandra I been from the East (i.e. the hypothetical East to West scenario that the Elder Brethren were asked to comment on by the Court of Appeal judges) and not from the West. Further, absent clear guidance on when a vessel will be considered to be on a “sufficiently defined course,” it remains unclear as to whether a crossing situation could arise in the same or similar factual circumstance if the speed or bearing of Alexandra I had been more established. Even with the use of advanced algorithms, this may be a difficult puzzle for an autonomous system to solve.

Notwithstanding this conclusion, it is possible that autonomous vessels may have been able to avoid a collision, or at least may have acted so as to reduce the damage sustained from the collision, by correcting the “human errors” that were identified as increasing the causative potency of the respective masters’ actions.

As a general comment, many maritime casualties are not caused by one catastrophic mistake or failure; rather they are caused by a series of isolated minor decisions or circumstances which, in combination, result in the incident. To use a modern analogy, the holes in the Swiss cheese line up. These errors include the officer on watch (OOW) not following the correct procedure or missing some warning sign whether it be from the echo sounder, Electronic Chart Display and Information System (ECDIS), automatic radar plotting aid (ARPA) or visually. The OOW is often distracted and can be mentally overloaded by the pressure of the environment and the flood of information, particularly in congested waters. AI would presumably not be distracted in this way and would not miss a warning sign.

Contributing human errors

The location of Alexandra I

There is reason to question why Alexandra I was present at the approach to the narrow channel in the first instance; both as a result of her early arrival to the approach channel (by 25 minutes or so) and the port Vessel Traffic Service (VTS) Officer’s approval for Alexandra 1 to proceed to the channel entrance buoys when Ever Smart was travelling outbound from Jebel Ali. In addition to her proximity to the end of the channel, Alexandra I’s AIS was not operating at the time of the incident, making her less visible to local traffic, and she was criticized for maintaining a poor aural lookout – mistaking a VHF conversation between Port Control and a local tug boat.

While these contributing errors do little to exonerate the actions of Ever Smart from a liability perspective, it is anticipated that autonomous vessels will (by necessity) operate using enhanced AIS, GPS and radar, in addition to a full suite of sensors and cameras (including thermal and infrared), and will adopt predictive control algorithms to track and anticipate future vessel movements and respond accordingly.

Within congested or restricted shipping areas, automated VTS (or eNAV) will likely be implemented to ensure that vessels manoeuvring within a restricted area are informed of potential collision risks in real time – indeed, the Maritime and Port Authority of Singapore has already trialled Artificial Intelligence (AI) to analyze marine traffic risks in the Singapore Strait. The provisional results demonstrate that the technology has the ability to “quantify risk in more detail and more quickly than it could be detected by human operators.”

Standardized messaging formats, including the use of hybrid messaging services such as a VHF Data Exchange Systems (VDES), supported by satellite as opposed to (or in addition to) radio frequencies, also have the potential to reduce miscommunication and increase the speed at which collision threats are communicated – absent the risk of misunderstanding (not identifying the relevant vessel) or miscomprehension (not understanding the VHF message due to linguistic or technological restrictions).

While these technologies are still being trialed, their potential to identify and report a collision risk, when applied to the factual scenario in Evergreen, may very well have highlighted the potential for collision between Alexandra I and Ever Smart substantially sooner than the “three seconds” in which the master of Ever Smart came to realise that a collision was inevitable.

The faults of Ever Smart

The first instance judge concluded that the actions of Ever Smart in proceeding along the port side of the narrow channel, in addition to her excessive speed at 11.8 knots and failure to keep a good visual lookout, had the greatest ‘causative potency’ in causing the damage that resulted from the collision.

Notwithstanding the arguments of the master of Ever Smart as to why he chose not to proceed to the starboard side (namely that he was not required to under the crossing rules), developments in the software designed to assist with unmanned or autonomous navigation could readily ensure that, within a narrow channel, both inbound and outbound vessel proceed on the starboard side (insofar as is practicable for it to do so) at pre-set maximum (safe) speeds.

Modern manned vessels are already equipped with Electronic Nautical Chart Systems (ECDIS), which are in turn linked to speed and depth sensors, as well as GPS and AIS. Implementing these systems to operate autonomously would allow Port Control (with the assistance of relevant hydrographic offices in creating/amending the charts) to better control speed limits, both during ordinary navigation but also when vessels are navigating within pre-specified distances of each other, to ensure that ‘safe speed’ is observed. While these restrictions do not, in themselves, eradicate the risk of collision, they do reduce the scope of likely damage arising from collisions.

With respect to Ever Smart’s failure to keep a good visual lookout, thermal and infrared high resolution cameras have the ability to identify objects when the human eye cannot. While the master of Ever Smart was only able to make out Alexandra I when she turned her deck lights on (three seconds before the collision) – modern cameras may have picked up Alexandra I ‘s heat signature, if not her outline using infrared, significantly earlier than the master.

Potential Issues

While technological advancements undoubtedly demonstrate the potential that autonomous vessels have in reducing collision risk, developers are faced with a number of problems that cannot be readily surmounted.

Unlike our past experience of large-scale adoption of autonomously-controlled machines, there will necessarily be a period in which autonomous, unmanned and manned vessels will navigate in the same waterways. Until there is clear guidance to the contrary, the expectation will be that the human standard will apply. It is relevant to note in this regard that case law has established that overreliance on technology will not satisfy the principles of good seamanship and, in any case, there is currently no case law considering a collision between a manned and unmanned or autonomous Vessel.

The duties under COLREGs differ whether Section II or Section III applies. Section II – Conduct of vessels in sight of one another (Rules 11-18) and Section III – Conduct of vessels in restricted visibility (Rule 19) of Part B – Steering and sailing rules, separately apply to a developing close quarters situation depending on the visibility. As part of applying the COLREGs to manned and unmanned ships, the AI systems will have to be able to understand the limitations of human eyesight to determine whether a manned ship is “not in sight” and then to follow Rule 19, instead of following Rules 11-18.

The fact that the AI system might have infra-red or night vision and therefore is able to “see” the other vessel would not be permitted to change the position, in fog for example, that the vessels are not “in sight” of one another. Alternatively should the regulators remove Rule 19 from the COLREGs altogether as a result of advances in technology on all ships (better radars, ARPA, AIS, better navigation systems, infra-red cameras etc) and rely only on Rule 6 (Safe Speed) and Section II? Rule 19 has been confusing generations of seafarers since 1977 so their deletion may not be mourned. But either way, it is hard to see how regulators can allow autonomous ships to sail the oceans while the COLREGs contain two sets of steering and sailing rules.

There will be a risk to software developers and Owners of autonomous vessels alike. Developers of marine Al systems are not only required to codify compliance with the seamanship standard currently in use, but are also required to produce algorithms that allow autonomous vessels to interact with manned vessels, unmanned (remote controlled) vessels and truly autonomous vessels in a way that is predictable to each of them; irrespective of the differing states of technology on-board (for example, autonomous vessels may be required to interpret standard frequency VHF messages even when equipped with a VDES system).

But even if the COLREGs were unambiguous, comprehensive and consistent (which they are not), then we still would not normally programm systems to have no discretion at all. This is because situations always exist where the best course of action is to ignore or break the rules and designers of systems cannot identify all these exceptional situations in advance. Therefore machine learning will be required which must learn the necessary navigational behaviors to avoid or mitigate collisions, even given (indeed, especially given) ambiguous and conflicting regulations, just as human navigators do. But, of course, effective machine learning is only possible with sufficient data, and particularly data arising from collisions or near misses (what CS people call “edge cases”).

Liability

Despite all of that, accidents may still occur. Given that there is no case law on the matter, third party liability in the event of a collision involving an autonomous vessel is not yet clear. It is possible that developers may be liable for collision damage if it can be proven that a fault in programming onboard systems or in the way the machine learning has developed caused (or contributed to) a collision. Would such fault be akin to unseaworthiness? Would the software writers need to be covered by collision insurance?

In addition, there are also ethical considerations as to how an autonomous vessel should be programmed in scenarios in which AI is required to choose between loss or damage to its own vessel or cargo, and loss of human life or serious pollution (and the inevitable concerns that this may have from a liability perspective to developers, owners and insurers alike).

Consideration must also be given to future scenarios in which an autonomous vessel suffers a catastrophic failure – the worst case scenario being a complete electrical breakdown (for example, as a result of generator failure, cyber-attack, or electro-magnetic disruption). The vessel may no longer be a vessel “under command” for the purposes of the COLREGs, however it may also be restricted in its ability to communicate this to nearby vessels or to shore based control centres in the absence of a ‘non-digital’ Master – who may still have the benefit of a satellite phone or, in the traditional way, hoist two black balls to the top of the mast.

Conclusion

Evergreen demonstrates that autonomous vessels may have struggled in those circumstances to definitively identify their respective obligations under the COLREGs due to the inherent ambiguity in priority. It remains unclear as to whether other factual scenarios can demonstrate similar ambiguities in priority between various rules of the COLREGs and it may be found necessary to review the COLREGs to remove as much uncertainty as possible. That said, no amount of redrafting will be able to give conclusive meaning to phrases such as “which may be required by the ordinary practice of seamen, or by the special circumstances of the case” – Rule 2 – Responsibility.

Evergreen does, however, demonstrate that two autonomous vessels may have been able to identify the collision risk earlier than the Masters of Ever Smart and Alexandra I were able to, principally as a result of enhanced communications, audio-visual and locational technology. Programming of systems should prevent excessive speeds in narrow channels and prevent vessels loitering in hazardous positions. An earlier identification of the potential collision risk could have reduced, or altogether removed, the risk of collision and consequent damage sustained by Alexandra I making the question of a “sufficiently defined course” completely redundant.

Source: nortonrosefulbright


Greece will reopen cruise travel as of August 1, Tourism Minister Haris Theocharis has confirmed.

He said cruise ships will be allowed to berth for homeporting operations at the ports of Piraeus, Rhodes, Heraklion, Volos, Corfu and Katakolon, and that subsequently ships will be able to make transit calls at other Greek ports on their itinerary.

However, Theocharis said the situation and the regulations could be reviewed depending on current epidemiological data. He said cruise travel will abide with all the health and safety protocols set by the European Union due to coronavirus.

EU guidance

The EU guidance for restarting cruise ship operations recommends for cruise ships to carry 60% of the maximum passenger capacity and to conduct mandatory checks on passengers and crew before boarding, which would include thermal screening and the submission of a special health declaration.

The guidance says that ships should make ‘isolation cabins’ available for quarantine purposes should a coronavirus case occur. Also, before starting journeys, cruise companies should make arrangements with local port authorities of the home port for possible isolation procedures. The facilities like hospitals and hotels should also be pre-specified.

Moreover, the guidance says all persons working on board ship, whether officers or crew, who interact with passengers or crew on board or ashore should have training about dealing with COVID-19 cases.

Source: seatrade-cruise


Jul 21, 2020 (AmericaNewsHour) — Kenneth Research has published a detailed report on Autonomous Ships Market which has been categorized by market size, growth indicators and encompasses detailed market analysis on macro trends and region-wise growth in North America, Latin America, Europe, Asia-Pacific and Middle East & Africa region. The report also includes the challenges that are affecting the growth of the industry and offers strategic evaluation that is required to boost the growth of the market over the period of 2020-2025.

Industry Insights

The report covers the forecast and analysis of the Autonomous Ships Market on a global and regional level. The study provides historical data from 2015 to 2019 along with a forecast from 2020 to 2025 based on revenue (USD Billion). The study includes drivers and restraints of the Autonomous Ships Market along with the impact they have on the demand over the forecast period. Additionally, the report includes the study of opportunities available in the Autonomous Ships Market on a global level.

we have included a competitive landscape and an analysis of Porter’s Five Forces model for the market. The study encompasses a market attractiveness analysis, wherein all the segments are benchmarked based on their market size, growth rate, and general attractiveness.

Click Here to Download Sample Report >>  https://www.kennethresearch.com/sample-request-10305395

Summary
Next generation modular control systems and communications technology will enable wireless monitoring and control functions both on and off board. These will include advanced decision support systems to provide a capability to operate ships remotely under semi or fully autonomous control.

The report forecast global Autonomous Ships market to grow to reach xxx Million USD in 2020 with a CAGR of xx% during the period 2020-2025.

The report offers detailed coverage of Autonomous Ships industry and main market trends. The market research includes historical and forecast market data, demand, application details, price trends, and company shares of the leading Autonomous Ships  by geography. The report splits the market size, by volume and value, on the basis of application type and geography.

First, this report covers the present status and the future prospects of the global Autonomous Ships  market for 2015-2025.

And in this report, we analyze global market from 5 geographies: Asia-Pacific[China, Southeast Asia, India, Japan, Korea, Western Asia], Europe[Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland], North America[United States, Canada, Mexico], Middle East & Africa[GCC, North Africa, South Africa], South America[Brazil, Argentina, Columbia, Chile, Peru].

At the same time, we classify Autonomous Ships according to the type, application by geography. More importantly, the report includes major countries market based on the type and application.

Finally, the report provides detailed profile and data information analysis of leading Autonomous Ships company.

By Region
**Asia-Pacific[China, Southeast Asia, India, Japan, Korea, Western Asia]
**Europe[Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland]
**North America[United States, Canada, Mexico]
**Middle East & Africa[GCC, North Africa, South Africa]
**South America[Brazil, Argentina, Columbia, Chile, Peru]

Key Companies
*Kongsberg
*Rolls-Royce
*ASV
*DARPA
*NYK Line
*Mitsui O.S.K. Lines
*HNA Group

Market by Type
*Maritime Autonomous Ships
*Small Autonomous Ships

Market by Application
*Commercial & Scientific
*Military & Security

The report covers the forecast and analysis of the Autonomous Ships Market on a global and regional level. The study provides historical data from 2015 to 2019 along with a forecast from 2020-2025 based on revenue (USD Million). In 2018, the worldwide GDP stood at USD 84,740.3 Billion as compared to the GDP of USD 80,144.5 Billion in 2017, marked a growth of 5.73% in 2018 over previous year according to the data quoted by International Monetary Fund. This is likely to impel the growth of Autonomous Ships Market over the period 2020-2025.

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Competitive Analysis:
The Autonomous Ships Market report examines competitive scenario by analyzing key players in the market. The company profiling of leading market players is included in this report with Porter’s five forces analysis and Value Chain analysis. Further, the strategies exercised by the companies for expansion of business through mergers, acquisitions, and other business development measures are discussed in the report. The financial parameters which are assessed include the sales, profits and the overall revenue generated by the key players of Market.

Key points covered in this report:
*The historical and current data is provided in the report based on which the future projections are made and the industry analysis is performed.
*The import and export details along with consumption value and production capability of every region is mentioned in the report.
*Porter’s five forces analysis, value chain analysis, SWOT analysis are some additional important parameters used for the analysis of market growth.
*The report provides the clients with the facts and figures about the market on the basis of evaluation of the industry through primary and secondary research methodologies.

ANSWERED TO THE FREQUENTLY ASKED QUESTIONS :

WHAT IS THE SCOPE OF THE REPORT?
This market study covers the global and regional market with an in-depth analysis of the overall growth prospects in the market. Furthermore, it sheds light on the comprehensive competitive landscape of the global market. The report further offers a dashboard overview of leading companies encompassing their successful marketing strategies, market contribution, recent developments in both historic and present contexts.

WHAT ARE THE KEY SEGMENTS IN THE MARKET?
*By product type
*By End User/Applications
*By Technology
*By Region

WHICH MARKET DYNAMICS AFFECTS THE BUSINESS?
The report provides a detailed evaluation of the market by highlighting information on different aspects which include drivers, restraints, opportunities, and threats. This information can help stakeholders to make appropriate decisions before investing.

Key Topic Covered in this Report
*Market Growth Opportunities
*Leading Market Players
*Market Size and Growth Rate
*Market Growth Drivers
*Company Market Share
*Market Trends and Technological

The Autonomous Ships Market report highlight the economy, past and emerging trend of industry, and availability of basic resources. Furthermore, the market report explains development trend, analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out. In the end, the report makes some important proposals for a new project of Autonomous Ships Market before evaluating its possibility.

Table of Contents
Part 1 Market Overview
1.1 Market Definition
1.2 Market Development
1.3 By Type
Table Type of Autonomous Ships
Figure Global Autonomous Ships Market Share by Type in 2020
1.4 By Application
Table Application of Autonomous Ships
Figure Global Autonomous Ships Market Share by Application in 2020
1.5 Region Overview
Table Region of Autonomous Ships
Figure Global Autonomous Ships Market Share by Region in 2020
Part 2 Global Market Status and Future Forecast
2.1 Global Market by Region
Table Global Autonomous Ships Market by Region, 2015-2019 (Million USD)
Figure Global Autonomous Ships Market Share by Region in 2020 (Million USD)
Table Price List by Region, 2015-2019
2.2 Global Market by Company
Table Global Autonomous Ships Market by Company, 2015-2019 (Million USD)
Figure Global Autonomous Ships Market Share by Company in 2020 (Million USD)
Table Price List by Company, 2015-2019
2.3 Global Market by Type
Table Global Autonomous Ships Market by Type, 2015-2019 (Million USD)
Figure Global Autonomous Ships Market Share by Type in 2020 (Million USD)
Table Price List by Type, 2015-2019
2.4 Global Market by Application
Table Global Autonomous Ships Market by Application, 2015-2019 (Million USD)
Figure Global Autonomous Ships Market Share by Application in 2020 (Million USD)
Table Price List by Application, 2015-2019
2.5 Global Market by Forecast
Figure Global Autonomous Ships Market Forecast, 2020-2024 (Million USD)
Part 3 Asia-Pacific Market Status and Future Forecast
3.1 Asia-Pacific Market by Company
Table Asia-Pacific Autonomous Ships Market by Company, 2015-2019 (Million USD)
Figure Asia-Pacific Autonomous Ships Market Share by Company in 2020 (Million USD)
Table Price List by Company, 2015-2019
3.2 Asia-Pacific Market by Type
Table Asia-Pacific Autonomous Ships Market by Type, 2015-2019 (Million USD)
Figure Asia-Pacific Autonomous Ships Market Share by Type in 2020 (Million USD)
Table Price List by Type, 2015-2019

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Source: marketwatch


The maritime space is now ready for disruption. A hundred years ago, a single ship was manned by 100 crew. Now, that’s just down to 15 or 30 at most. The trend continues as technology slowly replaces the jobs of seafarers.

Companies from startups to big businesses are developing autonomous ships that would run without a single crew on board. With today’s technology, these “crewless” vessel may soon roam the seven seas delivering cargoes to every port it calls to.

With the rise of artificial intelligence, augmented reality, virtual reality, smart data, 5G and the internet of things (IOT), these developments will serve as the building blocks for unmanned ships.

Human Error

Shipping accidents have plagued the oceans for many decades. Its not only costly but the effects like an oil spill lingers for decades. Human error is mostly at fault for they account 75% to 96% of marine accidents. Grounding, collision, fire, capsizing- you name them. Human element is involved.

Whenever a maritime incident occurs, the world turns its attention to shipping. This is because the magnitude is on a large scale and not only the environment is affected but human lives as well.

To minimize the human interface in a vessel, companies are racing to build autonomous ships. The “Captain” will be located somewhere on shore monitoring the vessel as it navigates. The ship itself will be packed with sensors aside from building it to be robust- able to withstand the toughest weather.

There are still debate as to the cost efficiency of unmanned ships since these will be very expensive to build including the technology required to run them. But since the human factor is taken out, crew expenses will also be removed. This includes seamen’s salary, their provision, insurance, living spaces, crew changes and many others. As the technology matures, autonomous tech may cost less as more robust and cheaper ones will be made available .

Automation

I asked my crew mates about unmanned vessels and they still believe that this will be possible after a hundred years. However, taking a second look about the equipment we have on board points to automation.

The Global Maritime Distress and Safety System (GMDSS) replaced the Radio Officer who was considered vital on board. He was very important that the ship is not allowed to sail without him. Then came the Electronic Chart Display and Information Systems (ECDIS) which replaced the paper charts. Many years ago, engineers would be on watch 24/7 inside the Engine Room. Now, we have Unmanned Machinery (UMS) Space where they can sleep all night in their cabins leaving the engine room without any person.

These developments- small as they may be, follows a trend of race to zero: reducing the number of people on board until only the machines are needed to keep them running. This may look like a long shot but with today’s technology, the future will be promising to those who are prepared.

What do you think of unmanned vessels?

Monitoring and running vessels will soon be made available using laptop or any mobile devices as the industry shifts to autonomous shipping.

Source: marinestartups


New York, July 22, 2020 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Emerging Technology Opportunities for Maritime Autonomous Ships” – https://www.reportlinker.com/p05934512/?utm_source=GNW
Sensors are expected to be pivotal in development of connected and autonomous ships.

Apart from devices communicating with each other, future autonomous ships will interact with the environment around, thereby leading to various forms of business opportunities with the collected data. The scope of this research service is limited to technologies enabling autonomous ships only to sensors and electronics market.

This research service focuses on capturing emerging technologies enabling autonomous ships, industries best practices and use cases. Growth opportunity assessment was done to assess the pathway of sensor technology development, which will lead to making autonomous ships a reality. Key questions addressed in the research service:What are the various types of sensor technologies enabling autonomous ships?What are the benefits and applications of the technology?What are the key innovations and who are the innovators impacting autonomous ship development?What are the use case scenarios in the autonomous shipping arena? What is the impact of COVID-19 on autonomous ships?What are future growth opportunities?
Read the full report: https://www.reportlinker.com/p05934512/?utm_source=GNW


Machine learning (ML) is a process by which large caches of data are analyzed in order to find connections between different elements that human analysts would be unlikely to discover. In the future, all shipping companies will have access to machine learning tools to enhance their productivity. Seamlessly integrating these operations will not happen quickly. But developments in the technology and its adaptability quotient would trigger the adoption of ML in a larger scale in maritime soon.

With machine learning the seamen can detect and diagnose engine faults sooner. This in turn optimises the voyage. Early detection of malfunction prevents further damage and increases the life of a marine engine. By preventing further damage of an engine, the fuel consumption is also optimised which in turn reduces pollution. This is a chain of advantages which can be achieved by implementing machine learning technology in shipping.

Machine learning has made its own niche in maritime and supply chain management. Through it, the sectors are looking to improve their operational efficiencies and at the same time, reduce risks. While in shipping it is being used for network planning, container demand forecasting and the un-/pairing of container flows, the logistics and supply chain management are utilizing it to draw patterns and insights that are proving crucial for the evolution of these sectors.

Machine Learning and Maritime

PSA Marine, a Singapore based marine service provider partnered with Ernst and Young Solutions and began the development of a technology based on machine learning and AI – ‘Blue 5.0.’. Through it, the company plans to predict pilotage transit durations along with planning and allocating terminal resources more efficiently. With technologies like ‘Blue5.0.’ being developed, the maritime sector is also investing in some quality research work to develop machine learning models that could heavily revolutionize the sector.

A new approach incorporating the use of machine learning algorithms in developing a shipping emission inventory model has been suggested in a research paper titled ‘An application of machine learning to Shipping Emission Inventory’. The paper written by Vikram Garaniya (University of Tasmania), Rouzbeh Abbassi (Macquarie University) and Shuhong Chai (Australian Maritime College), published in the December 2018 edition of  The International Journal of Maritime Engineering, extensively discussed and identified 5 machine learning models that can be utilized to predict shipping emissions based on engine parameters like engine load information.

It also suggested that a vast scope of further research and development lies ahead where better pollutant monitoring can be achieved through machine learning algorithms, hence increasing the relevance of estimated emissions.

In addition to the shipping emission inventory, machine learning is also finding its place for maritime surveillance using ASI data streams. Development of a multi-task deep learning architecture model has been proposed for trajectory reconstruction, anomaly detection, and vessel type identification. Although the research is still underway, according to some reports, the on-going work in the field of introducing deep-learning, a sub-field of machine learning, to the maritime sector can revolutionize the maritime surveillance to a great extent.

Apart from the above-mentioned domains, the shipping sector is looking to improve on the following fronts by using machine learning algorithms along with sister technologies like IoT and Artificial Intelligence.

Maintenance: By deploying machine learning algorithms, a better schedule for maintenance work can be developed and thereby improving the liner services in the long term, especially during the times when a ship may need to be out of operations temporarily for maintenance work.

Freight Rates: Machine learning can help in handling the deficits and offer more reliable container capacity utilization; hence more consistent freight rates would prevail.

Sailing schedules: By using machine learning, better and reliable sailing schedules can be achieved as more accurate calculations would be there to predict the delays or estimate the time of arrival of the cargo.

Logistics: Machine learning will have potential impact on the global logistics chain. Machine learning can predict accurately on arrival of container shipments. Using information from a variety of sources across the supply chain—including live demand and pricing data. A more accurate demand forecast can also help to scale up capacity of the existing fleet.

Supply Chain Management

The supply chain management is utilizing machine learning algorithms to locate new patterns in supply chain data almost on a daily basis and use those patterns to improve the supply networks’ success. Improved demand forecasting and production planning, better supplier delivery performance, minimized supplier risk, improved supplier chain and transportation management, physical inspection and maintenance tasks, lower inventory and operation costs, quicker response time, extended life of supply chain assets are the key evolutions happened within supply chain management by the introduction of machine learning algorithms.

Platforms like Nautilus Labs, We4Sea and ClearMetals are working in the direction where ML driven data science is being used to provide effective solutions for voyage optimization, supply chain visibility, and sustainability.

The Way Forward

Although at present, the full potential of machine learning is still to be realized and implemented, machine learning algorithms are capable of churning through different data points and derive key relationships between variables that can assist in improving operations and networking of sectors like shipping, logistics, supply chain management, thereby making it a technology to watch out in the future.

The key to Machine Learning lies around the integration, implementation, and manipulation of data infrastructures as well as machine learning approaches designed for chemical and materials datasets. Machine learning approaches and capability has already revolutionized world’s major industries and shipping industry is next in the queue to take a giant leap towards digitalization and accelerate its working to a great extent.

Machine Learning is an interesting technology that has multiple applications in the maritime sector. The need of the hour is to carry out additional researches to uncover its full potential and harness its benefits to optimize efficiency, safety, productivity and skills of seafarers across the globe.

(References: www.blog.flexis.com; www.researchgate.net; www.forbes.com; www.porttechnology.org; IDTechEx; www.arxiv.org; www.bigdata-madesimple.com)


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