In 2018, the CCNR adopted an initial international definition of levels of automation in inland navigation (Resolution 2018-II-16). The CCNR has charged its Police Regulations Committee monitoring developments in automated navigation (from navigation assistance to fully automated navigation) and considering the possible need for regulatory measures.
The CCNR Secretariat publishes below a list of the relevant national and international of projects including the assessment of the specific level of automation.
Project stakeholders are invited contact the Secretariat (firstname.lastname@example.org) to modify or add information regarding on-going projects on automation in inland navigation.
|Ref. no. ||Pilot project name ||Project sponsors ||Work duration ||Country ||Degree of |
|Brief description ||Links |
“Guidance and assistance system for increasing the safety of navigation on inland waterways”
|Consortium comprising four public and private organisations: |
- in-innovative navigation GmbH,
- Alberding GmbH
|2015-2018||DE||1||Advanced assistance system with 4 features: |
• The bridge collision warning system provides timely warning to the vessel’s master in the event of a problem when passing beneath a bridge.
• The berthing assistant displays distance measurements and calculations relative to the quayside or other vessels, thereby assisting the boatmaster during a difficult berthing manoeuvre.
• The track control assistant assists the boatmaster by maintaining the vessel on a predetermined track when travelling through a sector.
• The control screen permanently displays all the vessel’s movements, the rudder position and speed of the propeller.
|2||Shipping Technology |
(Shipping factory / Xomnia)
|Shipping Technology |
(Shipping factory / Xomnia)
|2016-…||NL||4||Use of (existing) nautical equipment for collecting on-board data and building a predictive model to enable automated navigation based on artificial intelligence (AI). |
Released base product: Black Box Pro which collects all the data from nautical systems such as radar, pilot, motor management, and GPS, and stores it in the Cloud. + storage of camera images and mariphone.
With all this data, provide insights through a dashboard into the day-to-day business process and the possibility to reproduce what happened at historical events such as collisions, groundings etc. etc.
Future applications (which run on the Black Box Pro): collision detection static, collision detection dynamic, autostowage, semi-autonomous shipping (based on Deep Learning Algorithms).
Live testing predictive models already on existing ship (Shipping Factory) in the Netherlands
|3||Zulu 3, Zulu 4||Zulu Associates||Vessels entering service in 2021/2022||BE||4||Zulu Associates is developing an autonomous barge with low to zero emission propulsion for navigation on European inland waters. The barge is called the X-Barge and is a CEMT class 4 barge. The aim is to prove that this type of vessel can operate on the Rhine in 2023 and to obtain the permit for permanent uncrewed commercial operation.||zulu-associates.com|
|4||NOVIMAR ||The consortium comprises 22 partners, logistics operators, industry, public bodies and research organisations |
Coordinator: Netherlands Maritime Technology (NMT)
|2017-2021||EU||3||Reorganisation of navigation with ship trains (platooning): 1 lead vessel + accompanying vessels (remotely controlled and with a reduced crew). |
Areas of research interest are: business concept of the vessel train, waterborne transport system, composition and design of the vessel train, navigating and manoeuvring the vessel train, human factor, waterway infrastructure and operations, safety, regulations
|5||Seafar||Seafar NV, Port of Antwerp, De Vlaamse waterweg||2018-…||BE||4||Existing vessel equipped with sensors for automated navigation on a predetermined course, taking account of the environment (but with remote control). |
Test on the Albert Canal in December 2018 (vessel Tuimelaar).
Test on Ypres-IJzer Canal and the Plassendale-Nieuwpoort Canal in November 2019 (vessel Watertruck X).
As of April 2020, they have been granted additional authorisation to deploy two more Watertrucks on the same route. The experience with Seafar has been very positive. So far, all the tests have taken place with crew on board, however the vessels are already being controlled from their Shore Control Center in Antwerp. Preparations are currently being made for an unmanned trial in the Westhoek, to be held in the near future. This is being arranged in consultation with DVW. Seafar has also developed safety procedures. These are currently being tested to ensure that, once unmanned sailings start, the vessel will continue to sail safely.
As of April 2020, they also have authorisation to deploy a (different) Watertruck on the Leuven-Dijle Canal (on behalf of Celis). The actual tests will only start in October 2021.
Since September 2020, Seafar has also been testing the vessel Gamma on the Bocholt-Herentals Canal and the Brussels-Scheldt Canal. This ship is manned: the captain is always on board, but the ship is controlled from Seafar's SCC.
Since February 2021 the container ship DESEO has been sailing between Zeebrugge and Antwerp. For this application we provided advice, but the licence itself was granted by the GNA. Currently the vessel is supported from the shore control centre in Antwerp with a full crew on board. The intention is to move on to full control of the SCC and reduced crew on board after this step.
Since March 2021 the barge Tercofin II has been sailing between the Port of Antwerp and Liège via the Albert Canal. There is always a crew on board, but the control lies with SCC.
|6||Autonomous shipping in the “Westhoek”||KU-Leuven (Catholic University of Louvain), De Vlaamse waterweg, POM West-Vlaanderen||2017-2019||BE||4||Unmanned autonomous inland cargo vessel demonstrator. Tests with a scale model (1:8 of CEMT I) on the Yser in November 2018 and September 2019. |
The project has been completed.
|7||Towards Autonomous Inland Shipping||KU Leuven||2017-2021||BE||4||PhD research project focusing on the modelling, identification, and motion control of unmanned inland cargo vessels. This project is now finished.||www.mech.kuleuven.be|
|8||Feasibility study - Autonomes Fahren in der Binnenschifffahrt||North Rhine Westphalia |
Entwicklungszentrum für Schiffstechnik und Transportsysteme (DST)
Westdeutsches Kompetenzzentrum in Sachen Binnenschiff.
|2018||DE||-||With automated and (partially) autonomous navigation in inland navigation, the following opportunities are identified: |
- relieve the nautical personnel in the future and thus alleviate the shortage of skilled personnel
- transport costs would fall, and smaller ships with smaller lot sizes would also be economically viable.
- Accidents caused by human error could be avoided.
- The digitalisation and networking associated with autonated navigation would create the conditions for better linking of modes of transport to intermodal and integrated transport chains and increase the transparency of traffic flows.
According to the study, the Rhine-Ruhr region is ideally suited as a test field for automated navigation, as the waterway and port infrastructure offers different requirements: There are areas with little traffic as well as complex port areas. Ship owners, operators, institutes are also located in the region.
|10||Smart Shipping: Strategic Analyses in the Netherlands for Rijkswaterstaat||Rijkswaterstaat||2018||NL||-||The objective of this research was to give a inside in the potential impact of Smart Shipping on the role and task of Rijkswaterstaat (the Dutch fairway authority). Three stages: |
- perform a scenario study with potential future scenario's for society, based on current existing trends and developments. (timeframe 2030)
- research on the potential impact of these scenarios on the role and task of Rijkswaterstaat. Looking at for example fairway maintenance, traffic management and the possible changes of the (digital) infrastructure.
- identify possible measure or moves that Rijkswaterstaat could make on this moment based on the foreseen futures.
|11||Test and control center for autonomous inland navigation vessels||Development Centre for Ship Technology and Transport Systems (DST) |
University of Duisburg-Essen
RWTH Aachen University
Transport Ministry of North Rhine-Westphalia
|October 2020 (opening planned)||DE||-||The Centre represents the essential research infrastructure for the subsequent research and development activities around autonomous inland shipping. |
The centre encompasses amongst others:
• a modern, freely configurable control stand in a ship-piloting simulator with a 360-degree 3D projection system,
• a control center with three workplaces for the coordination of the mixed traffic with conventional and autonomous inland vessels, and
• four workplaces for research scientists containing the necessary computer equipment for the development of AI-based autonomous control systems.
|12||AutonomSOW||Alberding GmbH |
LUTRA Hafen Königs-Wusterhausen
Bundesverband Öffentlicher Binnenhäfen
|2019-…||DE||-||The project objective is the development of a concept for the establishment of a digital test field for inland navigation for automated and autonomous operation on the Spree-Oder-Waterway (SOW). |
2019 Feasibility study for an automated and autonomous inland navigation trials area on the Spree-Oder waterway.
2019 Setting up of the trials area
202X Operating trials on the Spree-Oder waterway
|13||Autonome Schifffahrt auf der Kieler Förde |
(CAPTin – Clean Autonomous Public Transport)
|Christian-Albrechts-Universität zu Kiel||2018-…||DE||3||Development of an automated boatmaster lock entry and exit assistance system. |
Provision of a shore-based server and of transmission infrastructure for integrating, validating and demonstrating the system
|14||SCIPPPER, “SChleusenassIstenzsystem basierend auf PPP (Precise Point Positioning) und VDES für die BinnenschifffahRt” ||Consortium seven private and public organisations: |
- in-innovative navigation GmbH,
- Alberding GmbH,
- Weatherdock AG,
- Argonics GmbH,
- Bundesanstalt für Wasserbau (BAW)
|2018-2021||DE||3||Development of an automated boatmaster lock entry and exit assistance system. |
Provision of a shore-based server and of transmission infrastructure for integrating, validating and demonstrating the system
|15||Captain AI||Captain AI works together with the Port of Rotterdam, Watertaxi Rotterdam and Kotug ||2018-||NL||4||Captain AI is developing a safe and fully autonomous shipping solution using high-fidelity simulation, cutting-edge sensors and state-of-the-art deep learning techniques. ||www.captainai.com|
|16||AMS Roboats||Massachusetts Institute of Technology (MIT), Delft University of Technology (TU Delft) |
Wageningen University and Research (WUR).
|2016-2020||NL||?||In the third research year activities will focus, among others, on: |
- Upscaling navigation and autonomy to a 1:2 scale Roboat. Due to their size, these vessels have different dynamics and navigation behavior.
- Further developing the latching mechanism for 1:2 scale prototypes to latch individual vessels or dock them to the quays.
- Designing and refining the propulsion technology, the energy system and the electric charging technology for 1:2 scale prototypes.
- Further developing the water sensor technology in collaboration with Waternet.
|17||Remote Control Tug||Kotug, Alphatron, KPN, M2M Blue, Veth||2018||NL||3||Kotug can remotely control the RT Borkum. Studies the possibility of unmanned towing.||www.kotug.com|
|18||Sensing||Marinminds||2018-||NL||4||A broad range of new and existing technologies need to be integrated into one system. Project Sensing focuses on developing a prototype of an on-board sensor- and data acquisition system. With testing automotive grade sensors and object recognition software, gain insight in the required alterations and development of the algorithms for later use in autonomous systems ||www.marinminds.com|
|19||AURIS (AUtonomous Remotely monitored Innovative Ship)||MARIN ||2018-…||NL||4||The objective of this project is to research which sensors and analysis methods are required to achieve optimal situational awareness of the marine environment from a ship, and to interface an (autonomous) vessel with a Shore Control Centre. This will be done by developing and testing a modular intelligent situational awareness module (ISAM) on a 6m rigid-hulled inflatable boat. |
|20||modular Autonomous Underwater Vehicle (mAUV) ||MARIN||2018-||NL||4||The objective of the mAUV v1.0 project is the development of a modular underwater vehicle (mAUV) hardware & software, including all a first approach for 6D control and allocation. It will be used for basin model tests at MARIN in 2019. In the coming years the model will serve as one of MARIN's underwater test platform for AUV research. |
|21||AUTOSHIP||The consortium comprises industrial technology providers, logistics operators, public bodies and research organisations including: KONGSBERG Group, Blue Line Logistics, De Vlaamse waterweg, Bureau Veritas, SINTEF and University of Strathclyde. |
Co-ordinator: Ciatech (PNO Group).
|2019-2022||EU/BE||4||AUTOSHIP is an EU funded (Horizon 2020) project that will build and operate an autonomous barge and its needed shore control and operational infrastructure, reaching and going over TRL7. Testing will take place during a pilot demonstration in inland waterways near Antwerp in Flanders. This demonstration is intended for inland navigation. Another pilot demonstration will take place in Norway: an unmanned vessel will operate along a Short Sea Shipping route where it carries fish feed to the fish farms. |
The project will speed-up development of the Next Generation of Autonomous Ships with the technology package including for example autonomous navigation, situational awareness, remote monitoring, electronic route exchange, as well as communication technology enabling a prominent level of cyber security and integrating the vessel into upgraded e-infrastructure. In parallel, digital tools and methodologies for design, simulation and cost analysis will be developed for the whole community of autonomous ships.
AUTOSHIP will help ship operators/owners to improve the profitability of their investments, to effectively gain competitiveness and renew their fleets, making them more competitive to replace road transport within the EU.
The project was started in 2020. In March 2020 visits to the test area in Flanders are organised as well as several workshops on communication, safety, interaction with infrastructure and other vessels. This information will feed into the further development of software and hardware.
An analysis of the current legislation (international and national legal aspects regarding the areas where the demonstrations will take place) is currently underway and will be completed shortly. Supply Chain Mapping has been elaborated for both vessels.
|22||A-SWARM (Autonome elektrische Schifffahrt auf WAsseRstrassen in Metropolenregionen)||BEHALA (Berliner Hafen- und Lagerhausgesellschaft GmbH) |
SVA (Schiffbau-Versuchsanstalt Potsdam GmbH)
Technische Universität Berlin
|2019-2022||DE||4||The project is intended to contribute to modern city logistics on the basis of autonomous, connectable and electrically operated watercraft. The main focus is on the development and testing of autonomous watercraft, i.e. with the exception of GPS, without any significant land-based support. The feasibility of such a system is to be demonstrated by a demonstrator operation in a real laboratory in the area of Berlin's Westhafen (Spree / Charlottenburger Verbindungskanal / Westhafenkanal/ Berlin Spandauer Schifffahrtskanal)||www.behala.de|
|23||AKOON (Automatisierte und koordinierte Navigation von Binnenfähren)||RWTH Aachen University |
Voith GmbH & Co
Rheinfähre Maul GmbH
in - innovative navigation GmbH
|2019-2022||DE||4||The experimental craft in the AKOON research project is the ferry "Horst" of the company ferry Maul, which operates near Mainz between the towns of Oestrich-Winkel and Ingelheim. |
Due to narrow passages, sandbanks and strong currents, the area of operation is considered particularly challenging, especially at low water levels. Such difficult conditions take the ferry drivers of the Rhine ferry to the limits of their capabilities, which is why the automated operation of inland ferries can relieve the ferry personnel, especially in such exceptional situations.
The research project is intended to lay the foundations for full automation in inland navigation and act as a technology driver. Future developments in the field of ship assistance systems, especially in the area of inland navigation, are to be derived from this project in the future.
|24||Prepare Ships||ANAVS |
|2019-2022||EU||3||Prepare Ships is creating a smart positioning solution by developing and demonstrating a data fusion of different sensor and signal sources to enable a robust navigation application. The idea is that vessels with accurate positioning based on EGNSS, data and machine-learning should be able to predict future positions of nearby vessels. Besides a decreased risk for collisions, this also means additional benefits in the form of a more energy effective manoeuvring of the vessels, something which can also reduce the (negative) environmental impact of navigation.||www.prepare-ships.eu|
|25||Remotely controlled, coordinated driving in inland navigation – FernBin||Consortium |
Entwicklungszentrum für Schiffstechnik und Transportsysteme e.V. (Development centre for ship technology and transport systems) (DST coordinator) Dr.-Ing. Jan Oberhagemann
Bundesanstalt für Wasserbau (BAW) (Federal Waterways Engineering and Research Institute)
Ingenieurbüro Kauppert (consulting engineers)
in - innovative navigation GmbH
Rheinisch-Westfälisch Technische Hochschule Aachen (RWTH Aachen University) Institut für Regelungstechnik (irt) (control systems technology)
University of Duisburg-Essen (UDE)
• Institut für Schiffbau, Meerestechnik und Transportsysteme (ISMT) (Institute of shipbuilding, marine engineering and transport systems)
• Lehrstuhl Steuerung, Regelung und Systemdynamik (SRS) (Faculty of control engineering and system dynamics)
• Lehrstuhl für Mechatronik und Systemdynamik (IMECH) (Faculty of mechatronics and system dynamics)
Associated partners Imperial Shipping Rhenus Partnership
Central Commission for the Navigation of the Rhine (CCNR)
|07/2020 – 12/2023||DE||3||Remotely controlled driving is an intermediate step on the way to automated driving. The FernBin project develops all the necessary components and requirements for a remotely controlled inland navigation vessel to achieve the same transport performance and traffic safety as vessels steered conventionally from aboard. |
This enables two broader objectives to be achieved: the shortage of boatmasters can be mitigated on the one hand by making the boatmaster profession more attractive once again for young people while on the other hand the use of assistance systems to steer craft affords the prospect of fewer boatmasters being required than there are craft. Remote control also enables smaller craft to be operated economically, enabling new logistics concepts to be implemented, thereby enabling freight transport movements to be switched to inland waterway transport.
Various steps are required to deliver this project. In the first instance these include the corresponding technical wherewithal for remotely controlling craft. This encompasses the necessary sensors and actuators together with the associated interfaces, the shore-based remote steering position, the data protocol for ensuring robust and secure data transmission, channel guidance and collision warning assistance systems and a central control centre for monitoring and guidance functions.
Implementing the assistant systems includes forecasting other traffic participants’ boat handling, especially in running water. The central parameters to take into consideration here are first and foremost the vessels’ manoeuvring characteristics and other boatmasters’ behaviour.
The objective is an adaptive navigation system that responds dynamically to the surrounding traffic and processes traffic information in real time. It supports the remotely controlling boatmaster by forecasting and visualising the spatial requirements for encountering other vessels and
displaying the boatmaster’s possible options in a “predictive mode”. It thereby enables him to navigate his own vessel safely and reliably as dictated by other traffic participants’ behaviour.
Smart decision-making support for inland navigation logistics chains based on ETA forecasts
|TU Berlin Logistics Faculty, |
BEHALA Berliner Hafen- und Lagerhausgesellschaft mbH,
Deutsche Binnenreederei AG, Duisburger Hafen AG,
Imperial Shipping Services GmbH, modal 3 Logistik GmbH
Associated partners: Contargo GmbH & Co. KG, HVCC Hamburg Vessel Coordination Center GmbH, Rhenus PartnerShip GmbH & Co. KG
|1.3.2020 – 28.02.2023||DE||-||The project aims to develop an IT system for port operators and shipping companies that automatically and dynamically forecasts inland navigation vessel transport processes and thus their arrival times (ETA) at both inland and seaports and which, based on this, at system level, generates situationally specific recommendations for action for waterborne transport and port transshipments, and enables this information to be exchanged digitally between the players|
Autonomous inland navigation vessel – simulation and demonstration of automated driving in inland navigation
|Entwicklungszentrum für Schiffstechnik und Transportsysteme (DST) (Development centre for ship technology and transport systems), University of Duisburg-Essen ||10/2019 – 09/2022||DE||-||The project will entail equipping an inland navigation vessel with all the necessary sensor and actuator technology. A first stage will see an artificial intelligence-based control system in a simulator developed through machine learning to the point of being able to steer the inland navigation vessel safely from a departure point to a destination having regard to the traffic situation and rules of the road. Learning in the simulator is followed by the testing and demonstration of the control system fitted in the inland navigation vessel on a preselected test stretch|
|28||Marine Litter Hunter||DEME||October 2020 – October 2021||BE||5||Since October 2020, DEME has been testing the autonomous vessel Marine Litter Hunter (MLH) on the Temse-Bornem Scheldt bridges. In a first phase, testing was done with crew and since March 2021 the vessel has switched to unmanned operation. The MLH now sails autonomously and takes certain actions itself in case of problems. In case of unforeseen problems, a supervisor can provide assistance if necessary. |
The set-up consists of a combination of a fixed installation that continuously removes 'passively' floating waste from the water and a mobile system (the MLH) that 'actively' collects larger floating debris, which can be harmful to navigation in the Scheldt. This large floating debris is detected by smart cameras (AI) installed on the old Temse bridge near the navigation channel. The waste collects in the collection pontoon and is regularly transferred into a container by means of a crane equipped with a grabber. The fixed crane is remotely controlled by an operator, using VR-3D-vision technology. When the container is full, the MLH autonomously brings it to the docking station, where the container is unloaded by a transfer crane on the Belgomine quay. The waste is then transferred to a waste container of De Vlaamse Waterweg nv.
|29||ETN-SAS||KU Leuven and others||Novembre 2018 – octobre 2022||BE, UK, FR, NL, DE||/||Autonomous systems offer humankind tremendous opportunities, like freeing us from mundane tasks, carrying out risky procedures and generally giving us more time to enjoy the things we like doing. However, we lack trust in many forms of autonomous systems: partly this is human nature, but primarily because these systems, such as self-driving cars, have not demonstrated their safety credentials. Only by making these systems safer can we expect their widespread acceptance. The Safer Autonomous Systems (SAS) ETN is about getting people to trust these systems by making the systems safer. In order to achieve this objective and to train a group of highly skilled, responsible, future innovators, we will bring together 15 early-stage researchers (ESRs) to investigate new forms of system-safety engineering, dependability engineering, fault-tolerant and failsafe hardware/software design, model-based safety analysis, safety-assurance case development, cyber-security, as well as legal and ethical aspects. SAS will actively research the development of safer autonomous systems at multi-nationals like Bosch, but it also wants to stimulate the development of new safety designs, modelling and assurance techniques by involving the ESRs in SMEs and, potentially, their own start-ups. To help the ESRs put what they have learned during their research and S/T training into practise in their future careers, they will also receive soft-skills training to help them communicate effectively at all levels and become sought-after recruits. SAS is closely aligned with the high-priority areas of the EU, addressing many Horizon 2020 thematics, e.g. Industrial Leadership (Advanced manufacturing and processing), Societal Challenges (Smart, green and integrated transport; Secure, clean and efficient energy) and Excellent Science. But the most important output of SAS will be 15 well qualified people who have been trained to tackle many of the problems now being faced by European industry. |
One of the case studies is about autonomous vessels.
|30||ETN AUTOBARGE||KU Leuven and others||?||BE, NL, NO, SE, DE||/||The European training and research network on Autonomous Barges for Smart Inland Shipping will: |
• Build-up a highly skilled workforce for the autonomous inland waterway transport sector;
• Further develop the essential building blocks of the SUDA-model of an AV (Sense the environment, Understand the environment, Decide about the next action/ maneuver to take, Act according to that decision) that are needed for an autonomous vessel to take over the role of the human captain and crew;
• Address the many other socio-technical, logistic, economic, and regulatory conditions that need to be met for the successful and future-proof implementation of autonomous vessels in the inland-waterway transport sector