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PREParE SHIPS - PREdicted Positioning based on Egnss for SHIPS

Periodic Reporting for period 1 - PREPARE Ships (PREParE SHIPS - PREdicted Positioning based on Egnss for SHIPS)

Reporting period: 2019-12-01 to 2021-05-31

PREParE SHIPS
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 grow.
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. This will be done 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, which is challenging related to e.g. recruiting in the sector.
Solution
Together with partners RISE will present and validate a positioning solution. This will be 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 is expected to develop a navigation decision support system within shipping which will contain the following:
• 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 obtain information of earlier ship behaviour to exchange near-future positions with vessels in the vicinity and VTS centers (Vessel Traffic Services) to increase safety and improve decision making.
Ship-to-ship / ship-to-shore interaction
In order to define the correct requirements for PREParE SHIPS combined positioning solution, a collaborative automated vessel application will be defined and developed. The vessel application will rely 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.
• Geo-fencing:
Implement and demonstrate a fairway geo-fencing with high precision positioning, utilizing various data sources (e.g. wind and current) as well as a traffic monitoring and predicted positions so it can allow for safe decisions based on robust data. This means that ‘PREParE SHIPS’ also will implement perception layer sensor fusion that uses information collected historically in similar conditions based on machine learning-hybrid models.
Effect
PREParE SHIPS is expected to increase safety and efficiency significantly and will 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 (Network RTK in Sweden) 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 work is ongoing to implement a new distribution stream via VDES to the ship.
Tests have been performed on the pilot boat 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.

The design and development of the Dynamic Realtime Predictor has been finalized, as well as most of the necessary verification tests have been carried out and some of the validation ones. 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 are developed and tested. The development of the prediction monitor has been continued.
A dummy version of the predictor system, called FAKEDIS, has been developed as an interface towards ECDIS during the development phase.

The communication architecture describing the principles for exchange of predictors Ship-to-Ship over VDES has been developed, in addition to the planned work the architecture has been extended to 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. A transmission permit has been obtained for the trial period
Simulators for RTK transmissions and Predictor over VDES are available and tested.

The navigation decision support sub-system serves as a primary interface between results from other work packages (WP2-WP4) and human operators, being realized as a module in an Electronic Chart Display and Information System (ECDIS). At the end of this reporting period, a working engineering prototype of this system has been completed, including interaction with the positioning (WP2), predictor (WP3) and communication (WP4) sub-systems. The prototype is ready for integration and technical test to be performed during the WP6 test campaigns.
Work is continuing with focus on moving from engineering prototype to production, design of an HMI for navigators, as well as automation and graphical presentation.
Preliminary test results show good possibility for greatly improving the safety at sea when navigating in confined waters and in interactions with other vessels.
The project as come along way with preparatory work regarding standardisation for world wide adaptation of new communication and decision support for increased situational awareness.
In the longer run increased safety at sea translates in to fewer accidents, loss of life and pollution.
GNSS antennas on Pilot boat
Prepare Ships Pilotboat_Yacht_Stena
Kick-off image
Prepareships loggo
Stena Vinga as a demonstration case
Logo Prepare Ships