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PREParE SHIPS - PREdicted Positioning based on Egnss for SHIPS

Periodic Reporting for period 2 - PREPARE Ships (PREParE SHIPS - PREdicted Positioning based on Egnss for SHIPS)

Reporting period: 2021-06-01 to 2022-05-31

A digital solution to increase safety and energy efficiency within shipping. By developing a smart positioning solution based on machine learning and connected navigation applications, ship collisions are to be prevented and environmental impact set to decrease.
Purpose and goal
One of the most common reasons for ship collisions today is the lack of information about the intentions of other vessels. This especially applies to navigation in restricted areas, such as fairways, port areas and inland water ways. With an increased focus on autonomous vessels in the shipping industry, this problem is expected to become more accute.
The Prepare Ships project aimed to create 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. This made possible through a dynamic exchange of information ship-to-ship and ship-to-land by using VDES to simplify the decision-making and navigation of 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 environmental impact of shipping in line with IMO’s targets.

Challenge
Increasing the energy efficiency and safety for vessels in today’s industry.

Solution
Together with partners RISE set out to present and validate a positioning solution. This was done through development of existing software using Galileo-signals and combining it with nautical information regarding internal and external parameters and sensor technology. The project developed a navigation decision support system for shipping with:

• EGNSS resilience positioning:
The possibility of dynamically predict future positions of other vessels based on the positions reported from the Galileo receiver/transmitter.

• Real-time dynamic predictor:
Use data learning in order to use information of earlier ship behavior to exchange near-future positions with vessels in the vicinity and VTS centers to increase safety and improve decision making.

• Ship2ship / ship2shore interaction:
In order to define the correct requirements for PREParE SHIPS combined positioning solution, a collaborative automated vessel application was defined and developed. The vessel application relies on the high availability positioning solution and use it to couple its various navigational systems with ship2ship/ ship2shore and aggregate information received from other connected vessels by using the next generation AIS - VDES.

Effect
PREParE SHIPS has the potential to increase safety and efficiency significantly and be the base of future autonomous operations and standardisations. Based on the usage of Galileo’s positioning services, PREParE SHIPS is also expected to create value for companies.
SWEPOS (Swedish Network RTK) infrastructure has been extended to include the test area of Prepare-Ships project by establishing three new reference stations. Stations are up and running and are part of the infrastructure which generates the GNSS corrections for the GNSS receiver onboard the ships. It has also been decided to distribute the correction data in broadcast mode (one-way stream) using modern technique (casters), and to implement a new distribution stream via VDES to the ship.
Tests have been performed on the test platforms with PPP and RTK, converging towards the same value, integrity check leads to a common position within some centimeters. Both systems are deemed consistent, but PPP needs more time to align.
Hardware has been developed and “maritimised”, and an integrity service for NRTK (SWEPOS) has been developed and tested.
The team has participated in discussions with RTCM SC 135 related to the integrity standardization.
Result from this project serves as proof of concept of the suggested solution and might serve as basis for future standardization.

The design and development of the Dynamic Realtime Predictor has been finalized, as well the necessary verification and the validation tests. In its last iteration, the predictor is a software module written in C++ with an Application Programming Interface (API) written in C. The C-API enables the integration of the predictor with Electronic Chart and Information System (ECDIS) software.

The architecture for the Predictor software has been set with three modules making up the envisioned functionalities of the predictor system: the dynamic predictor, the machine learning coefficient tuner, and the predictions monitor. Functioning prototypes for the dynamic predictor and the machine learning coefficient tuner were developed and tested. The development of the prediction monitor has continued. The ambition is to open-source the software so that it can be used as a “reference implementation” for developers of maritime decision support systems (such as an ECDIS).

The communication architecture describing the principles for exchange of predictors Ship2Ship over VDES has been developed,and also include broadcast of Network RTK-corrections over VDES. The architecture consists of VDES transponders on participating vessels and a VDES base station for Shore-to-ship communication. Two prototype units have been produced and the required VDES communication protocols have been developed and implemented in the software radio module of the prototypes. Simulators for RTK transmissions and Predictor over VDES are available and tested. Saab is now preparing for full scale production of the shipborne VDES transponder based on the prototypes we used in Prepare Ship project.

The navigation decision support sub-system developed by the team under Telko’s lead serves as a primary interface between results from other work packages) and human operators, being realized as a module in an Electronic Chart Display and Information System (ECDIS). A working engineering prototype of this system has been completed, including interaction with the positioning, predictor and communication sub-systems. The prototype has been successfully tested during the test campaigns.
Work has continued with focus on moving from engineering prototype to production, design of an HMI for navigators, as well as automation and graphical presentation
Results from the test campaigns showed good possibility for greatly improving the safety at sea when navigating in confined waters and in interactions with other vessels.
The project has come along way with preparatory work regarding standardisation for worldwide adaptation of new communication and decision support for increased situational awareness.
In the longer run increased safety at sea translates into fewer accidents, loss of life and pollution.

The Prepare System has the potential of increasing the safety and efficiency of maritime operations by providing highly accurate positioning and predictions of the future movements of the vessel. Furthermore, the technical solutions developed within the project for the Prepare System are also foundational work for the development of Maritime Autonomous Surface Ships (MASS) and connected ships. Highly accurate positioning at sea is a cornerstone technology for the development of MASS, while VDES provides a maritime specific communication link that can be used for ship-to-shore and ship-to-ship communication.
GNSS antennas on Pilot boat
Prepare Ships Pilotboat_Yacht_Stena
Kick-off image
Prepareships loggo
Stena Vinga as a demonstration case
Logo Prepare Ships