SafeNav’s ambition is to develop and test a highly innovative digital collision prevention solution that will significantly reduce the probability of collisions, impact damage, grounding, and contribute to safer navigation by a) faster reliable real-time detection of a variety of obstacles (other vessels, fixed installations, submerged/semi-submerged objects, and marine mammals) in the marine environment, using data from state-of-the-art sensors and other relevant sources, and b) effective visual representation of the multi-source data to the navigators for quick COLREG-based decision-making support.
To this end, SafeNav unites 10 key partners from the maritime industry and academia, including renowned SMEs, R&D institutes and universities to address the ‘Navigational Accidents’ aspect of the work programme.

SafeNavwill design collision avoidance algorithms built on multi-sensory data input from propriety (LADARTM sensor suite) and off-the-shelf sensors already installed on vessels, extensive statistics of navigational accidents, and other sources (AIS and route exchange services) to create a holistic decision support system (DSS). Processed information from the automatic DSS will feed into SafeNav collision-avoidance algorithms and generate real-time COLREGs-compliant suggestions for the navigator when an obstacle is detected. This reduces pressure on navigators onboard, providing them with efficient decision-making aid and access to visual navigation data on a single graphical user-interface. Sensors will also be used for container tracking, and mathematical models will predict container drift trajectory, transmitting collected data to a SafeNav Navigational Hazard Database available to nearby vessels/stakeholders, facilitating the recovery of lost containers. Moreover, we propose to prevent vessel collisions with cetaceans with optimal-tuned pingers to alert them of an approaching vessels.