Periodic Reporting for period 1 - AUTOFLEX (AUTOnomous small and FLEXible vessels)
Período documentado: 2024-01-01 hasta 2025-06-30
WP2: Supply and Demand Analysis
Geographical and nautical data were collected, including mapping waterways and infrastructure in the Netherlands and Flanders, focusing on Randstad and Ghent. Transport demand was analyzed using 2022 data from Eurostat and national statistics offices. The study identified potential for modal shift, especially for containerized cargo, and emphasized the need for flexible, frequent services using smaller vessels.
WP3: Infrastructure and System Components
Stow&Charge Concept: A green terminal blueprint was developed for DFDS Ghent, integrating ZES battery systems, solar canopies, and windmills. The concept aligns with ongoing DFDS developments and aims to support electrified logistics.
Temporary Port Terminals - TPT: TPTs are designed to enable transhipment in areas lacking container terminals. Field visits in Duisburg, Copenhagen, and Seville helped identify essential terminal functions: cargo handling, storage, and access control. Conceptual variants were developed.
Mobile Distribution Centers - MDC: Concepts were developed through workshops and expert consultations. Requirements were defined for cargo types, packing methods, and handling mechanisms. Conceptual designs are being evaluated through surveys.
Transport System Architecture: Scenarios were defined to identify high-traffic corridors and underutilized waterways were mapped, and potential customer locations were identified. Barriers to small waterway transport were studied.
WP4: Vessel Design and Technology
Design Impact Analysis: Key changes for reference designs for CEMT I–IV vessels included converting bulk carriers to containerships, replacing diesel engines with electric propulsion, and implementing remote control. CEMT II vessels were found to require the least modification.
Concept Design: Designs were developed ensuring compliance with regulations and operational constraints. Key features include: Electric propulsion with ZESpacks, Autonomous navigation (CCNR Level 3), Compatibility with ISO and pallet-wide containers, Operation in Zone 2 waterways.
CFD simulations validated vessel resistance and maneuverability in various water conditions. Simulations covered deep and shallow water scenarios.
Sensors including SeaSight cameras and LiDAR were installed on the “Sorrento” barge.
Mission Planning: A digital mission planning framework was developed and demonstrated successfully using the Otter X USV in Trondheim. Integration with EuRIS route data is underway.
SeaGuard tool under development, to detect and prioritize anomalies in vessel behavior, whether due to faults or cyberattacks.
WP5: Business Models and Ecosystem
Business Models: A literature review identified the “business ecosystem” framework as key to aligning stakeholders. Coordination among ship owners, operators, tech providers, ports, and regulators is essential to avoid commercial bottlenecks.
Technical Standards: Initial scoping identified the need to define interfaces between remote operations centers and autonomous systems. Participation in ISO SC25 Smart Shipping committee.
WP6: Demonstration and Permits
Permits and Approvals: WP6 was initiated in M18. A draft Concept of Operations (CONOPS) was created, and initial contact with Flemish Waterways and Dutch authorities was established to support full-scale demonstrations.
Based on the work with deliverables D2.1 and D2.2 a methodology has been established for considering road traffic intensity to find highly congested roads and which have waterways in the proximity. This is a data-driven methodology, going through a lot of data such as traffic, waterways, infrastructure (quays and terminals), company databases to reveal if there are clusters of companies in areas along the waterways for potential goods flows. These flows can be moved from road to waterways. QGIS for visualisation. Goods flows data has also been used. Road traffic data distuinguishes between cargo (trucks and vans) and passenger (cars) transport. The challenge lies in the NUTS data, which only operates with larger regions, so it is hard to find the flows between smaller areas in the AUTOFLEX use case.