S13: Ship Performance and Design

- A novel method for evaluating ship concept performance in transport systems
H. Nordahl, SINTEF Ocean

- Future Ship Design - From Technology and Sustainability Point of Views
Ching Eng TAN, TCOMS

- Zero emission trough autonomy and modular design
Ann-Sofie Pauwelyn, ZULU

- Can autonomous waterborne transport be an alternative or supplement to traditional ferry operation
Tom Eystø, Massterly

S14: Maritime Safety

- Designing an emergency towing system for vessels without an IMO ETS requirement
Ørjan Selvik, SINTEF Ocean

- Drifting vessel statistics and emergency towing cases
Tor Einar Berg, SINTEF Ocean

- Consideration on safety requirements for Autonomous Navigation System (ANS)
Tomoaki Yamada, ClassNK

- Track pilots in inland shipping: Steering clear of too much trust
Patrick Potgraven, Nederland Ministerie van Infrastructuur en Waterstaat

S15: Maritime Operation

- Pioneering the Future with Reach Remote - Norway’s first 24m unmanned ROV vessels
Bjørg Mathisen Døving, Reach Subsea

- Transparency and supervisory control in autonomous shipping
Koen van de Merwe, DNV

- 1 MASS = 1 master?
Eva Ricarda Lange, University of Bremen

- Use of unmanned autonomous surface vessel for remotely recording scientific measurements
Antonio Vasilijević, NTNU

S16: Inland Waterways

- Understanding Operation of Automated Inland Vessels using Process Diagrams
Thomas Kerkmann, DST

- Impact of automation and zero-emission propulsion on design of small inland cargo vessels
Igor Bačkalov, Development Centre for Ship Technology and Transport Systems

- Ensuring the Resilience and Sustainability of Inland Waterway Transport System in Face of Climate Change
Ramdane Tami, irt-systemx

- The economic and environmental viability of green and autonomous ships in inland shipping ecosystems
Kristoffer Kloch, Aalborg University

S17: Ports

- A Conceptual Model for Automation of Small Ports
Marianne Hagaseth, SINTEF Ocean

- The art of orchestrating nautical services in a port call: A literature classification
João Braga, Tuhh

- A Four-Dimensional Perspective on Building Multi-Tier Digital Twins of Mega Container Terminals
Chu Xin, National University of Singapore

- PortalLite Towns - Logistics Distribution Systems with Unmanned Ports and Vessels in Archipelago and Nearshore Zones
Haobin Li, National University of Singapore

S18: Autonomous Operations

- GreenHopper: The Danish Spearhead Towards Autonomous Waterborne Mobility
Mogens Blanke, DTU

- Touchpoints and Systems for Fully Unmanned Autonomous Urban Ferry Operations
Felix-Marcel Petermann and Ole Andreas Alsos, NTNU

- Boredom, vigilance, and repetition during remote control room work for autonomous ships
Erik Veitch, NTNU

- Enhancing autonomy levels based on technical, operational, and human considerations
Rolph Hijdra, Marin

S19: Maritime Digitisation

- Digital twins for resource optimization in multi-organizational settings – providing enhanced decision-basis in multi-purpose ports
Mathias Karlsson, Umea universitet Institutionen for Informatik

- Coordinate Transformation Techniques for Improved Co-Simulation in the Maritime Industry
Severin Sadjina, SINTEF

- Enabling enhanced data quality for disruption management and emission reduction by the Virtual Watch Tower (VWT) initiative
Mikael Lind, RISE

- A FAIR Framework for Management of Maritime Datasets to Assist in the Development of Common Maritime Dataset
Ping Chong Chua, A-star

S20: Situational Awareness

- A Probabilistic Approach to Correct for Oblique Biases in Sea Ice Parametrization from Shipborne Cameras
Oskar Gjesdal Veggeland, NTNU

- BEYOND – Building an Experience to Yield Optimal Nautical Displays – Measuring Nautical Situation Awareness
Sharmistha Bhattacharya, Fraunhofer Insititute

- Introduction of AI/robotics-based situational awareness technology for MASS and smart ports
Hankeun Kim, Seadronix

- Bridge Detection in Autonomous Shipping: A YOLOv8 Approach with Autodistill and GroundedSAM
Horst Hellbrück, CoSA Center of Excellence, Technical University of Applied Sciences Lübeck

S21: Collision Avoidance

- Software Architecture Design of ASV Rybitwa: Development of an Autonomous Surface Vehicle for Dynamic Navigation and Task Execution
Igor Rusiecki, GUT

- Deep Reinforcement Learning for Multi-Ship Collision Avoidance in Heavy Traffic Regions
#Haobin Li, National University of Singapore

- Decision Support for Collision Avoidance in Maritime Multi-Vessel Encounter
Luka Grgičević, NTNU

- Sequential multi-ship encounter scenarios for testing automatic collision avoidance system
Liangbin Zhao, A-star

S22: MASS testing and approval

- Digital Testing System for Maritime Autonomous Surface Ships
Hongwei Wang, Government of Singapore

- Integrated Testing for Autonomous Surface Vessels using End-to-End Simulation
Øyvind Smogeli, Zeabuz

- Harmonizing Maritime Innovations: Enhancing International and National Standardization in Intelligent Ship Transport Systems
Kwi Yeon Koo, University of South-Eastern Norway

- Insights from a Simulated Study Assessing the Relationship Between Situation Awareness and Experience, Teamwork, and Multi-Sensory Indicators
Ole Andreas Alsos, NTNU

S23: Navigating the Future: Innovations and Advancements in Smart, Autonomous Inland and Short-Sea Shipping

The session will delve into sustainable solutions for autonomous shipping and navigation, focusing on the intersection of green shipping, smart technologies, and maritime safety. It will address logistics and the current availability of technology, particularly in relation to autonomous operations across inland waterways and shortsea shipping.

With specific insights drawn from the AUTOFLEX, FOREMAST, SEAMLESS, and ReNEW projects: These projects will present their approaches to developing solutions that advance automation, improve operational efficiency, and promote sustainability in maritime logistics.

On stage: Ann-Sofie Pauwelyn (Zulu Associates), Kristoffer Kloch (DFDS), Øyvind Pedersen (Maritime Robotics), Matko Barisic (ABB), Kongsberg Maritime, Tomas Ambra (INLECOM), Odd Erik Mørkrid (SINTEF Ocean)

S24: Port and technology

- Enhancing Vessel Estimated Time of Arrival Prediction through Vessel Event Detection and Data Augmentation
Ping Chong Chua, A-star

- Using Hybrid Modeling Formalism to Enhance Artificial Intelligence Capabilities for Maritime Systems
Xiongfei Lai, National University of Singapore

- Port Resilience Assessment Utilising AI-Enhanced Risk Classification, Port Stay Evaluation and Prediction
Zhao Liangbin, A-star

- Ship model-based route optimisation for decision support in deep sea shipping
Agathe Rialland, SINTEF Ocean