Periodic Reporting for period 2 - SafeNav (Safe Navigation)
Berichtszeitraum: 2024-03-01 bis 2025-08-31
SafeNav's project emerges against the backdrop of a critical and growing concern within the maritime industry: the alarming rate of navigational accidents, including collisions, groundings, and the subsequent environmental and economic impacts. This initiative is motivated by the urgent need to enhance maritime safety, not only to protect lives but also to safeguard marine ecosystems and the substantial investments tied to maritime commerce. The strategic imperative for SafeNav is to leverage technological innovation to significantly lower the risks associated with marine navigation.
The overarching goal of SafeNav is to pioneer a cutting-edge digital solution for collision prevention. This ambition is manifested in two primary objectives: firstly, the deployment of advanced sensor technology and data analytics to achieve rapid and real-time situational awareness regarding various marine obstacles, ranging from other vessels and fixed installations to submerged objects and marine life. Secondly, SafeNav aims to provide navigators with an effective visual representation of this compiled multi-source data, enabling swift and informed decision-making in accordance with Collision Regulations (COLREGs).
To realize these objectives, SafeNav has assembled a consortium of ten key partners, encompassing a diverse array of stakeholders from across the maritime industry and academia. This collaboration includes renowned Small and Medium-sized Enterprises (SMEs), research and development (R&D) institutes, and universities, all united by the common goal of addressing the persistent issue of navigational accidents.
The project pathway envisages the development of sophisticated collision avoidance algorithms that integrate multi-sensor data inputs. These inputs will include proprietary sensors and off-the-shelf sensors already present on vessels, enriched by comprehensive accident statistics and additional data sources such as Automatic Identification Systems (AIS) and route exchange services. The culmination of these efforts will be a holistic Decision Support System (DSS) that not only aids in collision avoidance but also enhances container tracking and recovery, while simultaneously protecting marine wildlife through innovative deterrent measures.
The expected impact of SafeNav is substantial, offering a multifaceted solution to a complex set of problems. By reducing the incidence of navigational accidents, SafeNav will not only contribute to the safety and efficiency of maritime operations but also mitigate environmental damage and economic losses. Furthermore, the project's innovative approach to wildlife protection aligns with broader environmental conservation goals, emphasizing SafeNav's potential to deliver significant benefits at both the industry and ecosystem levels. Through its objectives and comprehensive project pathway, SafeNav sets the stage for a safer, more sustainable future in maritime navigation.
The overarching goal of SafeNav is to pioneer a cutting-edge digital solution for collision prevention. This ambition is manifested in two primary objectives: firstly, the deployment of advanced sensor technology and data analytics to achieve rapid and real-time situational awareness regarding various marine obstacles, ranging from other vessels and fixed installations to submerged objects and marine life. Secondly, SafeNav aims to provide navigators with an effective visual representation of this compiled multi-source data, enabling swift and informed decision-making in accordance with Collision Regulations (COLREGs).
To realize these objectives, SafeNav has assembled a consortium of ten key partners, encompassing a diverse array of stakeholders from across the maritime industry and academia. This collaboration includes renowned Small and Medium-sized Enterprises (SMEs), research and development (R&D) institutes, and universities, all united by the common goal of addressing the persistent issue of navigational accidents.
The project pathway envisages the development of sophisticated collision avoidance algorithms that integrate multi-sensor data inputs. These inputs will include proprietary sensors and off-the-shelf sensors already present on vessels, enriched by comprehensive accident statistics and additional data sources such as Automatic Identification Systems (AIS) and route exchange services. The culmination of these efforts will be a holistic Decision Support System (DSS) that not only aids in collision avoidance but also enhances container tracking and recovery, while simultaneously protecting marine wildlife through innovative deterrent measures.
The expected impact of SafeNav is substantial, offering a multifaceted solution to a complex set of problems. By reducing the incidence of navigational accidents, SafeNav will not only contribute to the safety and efficiency of maritime operations but also mitigate environmental damage and economic losses. Furthermore, the project's innovative approach to wildlife protection aligns with broader environmental conservation goals, emphasizing SafeNav's potential to deliver significant benefits at both the industry and ecosystem levels. Through its objectives and comprehensive project pathway, SafeNav sets the stage for a safer, more sustainable future in maritime navigation.
The SafeNav project successfully completed the development, integration, and demonstration of adigital collision-avoidance and decision-support system designed to enhance maritime safety.
1. Data Fusion and Decision Support System:
Algorithms for multi-sensor data fusion were developed, combining RGB and infrared cameras, radar, lidar, AIS, and GNSS inputs. A novel probabilistic interpretation layer was implemented to dynamically adjust detection confidence based on AI outputs and prevailing sea conditions, improving reliability and reducing false detections.
2. Graphical User Interface (GUI):
A fully functional, user-tested interface was created, providing real-time situational awareness and augmented-reality visualization on the bridge.
3. Automated Anti-Collision System:
SafeNav developed and validated a COLREGs-compliant path-planning module and classification algorithms that autonomously suggest optimal collision-avoidance manoeuvres. Simulator testing confirmed accurate rule interpretation across multiple traffic scenarios.
4. LADAR™ Sensor Enhancements increased object-detection range and sensitivity for above-water targets.
5. Marine Mammal Collision Avoidance Studies carried out adding to the poll of research in the field.
6. Navigational Hazard Awareness Platform:
A web-based application and Ocean Observations Database were deployed, enabling real-time sharing of hazard data and marine-mammal sightings via AIS connectivity.
7. Container Loss Mitigation:
Predictive models for container drift trajectories were designed
8. Testing and Validation:
All modules were tested through full-mission bridge simulator campaigns and vessel trials.
1. Data Fusion and Decision Support System:
Algorithms for multi-sensor data fusion were developed, combining RGB and infrared cameras, radar, lidar, AIS, and GNSS inputs. A novel probabilistic interpretation layer was implemented to dynamically adjust detection confidence based on AI outputs and prevailing sea conditions, improving reliability and reducing false detections.
2. Graphical User Interface (GUI):
A fully functional, user-tested interface was created, providing real-time situational awareness and augmented-reality visualization on the bridge.
3. Automated Anti-Collision System:
SafeNav developed and validated a COLREGs-compliant path-planning module and classification algorithms that autonomously suggest optimal collision-avoidance manoeuvres. Simulator testing confirmed accurate rule interpretation across multiple traffic scenarios.
4. LADAR™ Sensor Enhancements increased object-detection range and sensitivity for above-water targets.
5. Marine Mammal Collision Avoidance Studies carried out adding to the poll of research in the field.
6. Navigational Hazard Awareness Platform:
A web-based application and Ocean Observations Database were deployed, enabling real-time sharing of hazard data and marine-mammal sightings via AIS connectivity.
7. Container Loss Mitigation:
Predictive models for container drift trajectories were designed
8. Testing and Validation:
All modules were tested through full-mission bridge simulator campaigns and vessel trials.
The SafeNav project has developed and demonstrated an integrated digital collision-avoidance and decision-support solution for safer navigation at sea. The system fuses data from multiple sensors into a single situational-awareness and decision-support interface that assists the Officer on Watch with COLREG-compliant manoeuvring advice. The results include algorithms for sensor fusion and path planning, a GUI or bridge integration, upgraded LADAR™ hardware for floating objects detection, a risk-based decision model addressing human factors, a web-based Ocean Observation Database, and methods for container drift prediction and marine-mammal collision avoidance.
SafeNav achieved TRL7 through simulator and vessel tests, confirming its potential to reduce collision and grounding risks.
To ensure further uptake, key next steps identified include large-scale demonstrations with classification-society Approval-in-Principle, and targeted business actions defined in the Business Innovation Pla covering market entry via SafeNav Ltd and partner companies. Commercialisation and IPR protection are supported by a robust patent portfolio. Continued R&D will focus on integration with bridge systems and MASS control frameworks, access to finance for demonstration and certification, and partnerships for global market introduction.
SafeNav achieved TRL7 through simulator and vessel tests, confirming its potential to reduce collision and grounding risks.
To ensure further uptake, key next steps identified include large-scale demonstrations with classification-society Approval-in-Principle, and targeted business actions defined in the Business Innovation Pla covering market entry via SafeNav Ltd and partner companies. Commercialisation and IPR protection are supported by a robust patent portfolio. Continued R&D will focus on integration with bridge systems and MASS control frameworks, access to finance for demonstration and certification, and partnerships for global market introduction.