Ship Autonomy

01openalex2026-09-11Dominik Frey, Ulf Kargén, Dániel VarróDOI ↗

Automated Generation of Functionally Complete Assurance Suites for COLREGS-Compliance of Autonomous Surface Vehicles (opens in a new tab)

This paper presents a model-based method to automatically generate assurance scenarios for verifying COLREGS compliance in autonomous surface vehicles (ASVs). It derives functional equivalence classes for multi-vessel encounters, maps them to logical scenarios with geometric constraints, and produces initial scenes using search-based and rejection sampling algorithms. The approach ensures full coverage of COLREGS-relevant encounters and scales to scenarios involving up to six vessels. Evaluation confirms its effectiveness for ASV assurance in open-sea conditions.

02crossref2026-09-11Xiaojie ZhangDOI ↗

Safety Analysis of Collision Avoidance for Semi-Autonomous Navigation Ship Based on STPA-CREAM (opens in a new tab)

This study analyzes safety risks in semi-autonomous navigation ships using System-Theoretic Process Analysis (STPA) to model interactions in encounter scenarios and identify potential hazards. To strengthen human factors analysis, the Cognitive Reliability and Error Analysis Method (CREAM) is integrated with STPA. The combined STPA-CREAM approach provides targeted recommendations to enhance the safety of semi-autonomous navigation systems. The research focuses on improving navigation efficiency while addressing risks in intelligent ship operations.

03openalex2026-09-08Carter Noh, Kyle L. Crandall, Connor Yates, Corbin WilhelmiDOI ↗

A Distributed Consensus Particle Filter for Target Tracking using Autonomous Surface Vessels (opens in a new tab)

The paper introduces a modified particle filter for maritime target tracking using autonomous surface vessels (USVs) in scenarios with intermittent communication. The method adjusts particle distribution to prevent overconfidence in local estimates when external data is unavailable. Tests with USVs on a lake show the approach maintains performance under normal conditions while improving results in certain edge cases. The work focuses on distributed consensus without centralized coordination.

04crossref2026-09-07Nam H. Tran, Hung Duc Nguyen, Peter King, Minh TranDOI ↗

Deep Reinforcement Learning Control for Path Following and Static Obstacle Avoidance for Autonomous Surface Vessels (opens in a new tab)

This paper introduces a LiDAR-based deep reinforcement learning (DRL) framework for autonomous surface vessels (ASVs) to follow paths and avoid static obstacles in narrow waterways. Using a Soft Actor-Critic (SAC) policy trained in simulation, the system processes LiDAR data and motion states to control rudder and propulsion, achieving a 95% success rate in 500 simulated trials with low collision rates. Field tests with a model-scale vessel demonstrated obstacle avoidance but showed increased path oscillations and cross-track errors compared to simulation. The approach relies on compact LiDAR sector features and continuous control commands for real-time navigation.

05openalex2026-09-13Yuqing Lin, Youngroung KimDOI ↗

Language-Grounded Semantic Target Navigation for Autonomous Surface Vehicles (opens in a new tab)

This study introduces SGNav, a framework enabling Autonomous Surface Vehicles (ASVs) to navigate toward targets described in natural language rather than predefined coordinates. The system combines semantic grounding, harbour-specific filtering, and CLIP-based verification to interpret descriptions, filter distractions, and execute control policies. Experiments in simulated port environments showed success rates of 90–97% across tasks, with high semantic accuracy and low error rates. Ablation studies confirmed the critical role of semantic grounding and filtering for reliable performance.

06openalex2026-09-12Wei‐Chang YehDOI ↗

AεL-A: Current-Aware ε-Lexicographic A for Autonomous Surface Vessels — Reproducibility Package (code, synthetic benchmark, Strait of Gibraltar case, raw results, and figures) (opens in a new tab)

The paper provides a reproducibility package for the CAεL-A* algorithm, a two-stage search method optimizing travel time and maneuvering for autonomous surface vessels. It includes source code, 540 synthetic current fields, Strait of Gibraltar data (from NOAA/NCEP and Natural Earth), and raw results from 11,880+ runs. The package also contains derived tables, figures, and scripts to regenerate analyses without rerunning searches. Two archive versions are offered: a full dataset with checkpoints and a smaller, aggregated version.

07openalex2026-09-11Shuaikun Zhang, Hui Feng, Haixiang Xu, Song Pei +1 moreDOI ↗

QSD-STFormer: Quaternion Ship Domain-guided Spatiotemporal Transformer for ship trajectory prediction (opens in a new tab)

The paper introduces QSD-STFormer, a quaternion ship domain-guided spatiotemporal transformer for ship trajectory prediction in dense maritime environments. It combines a CVAE framework with a QSD-guided Interaction Prior Module to incorporate physical navigation constraints, improving data-driven modeling. A Spatiotemporal Joint Modeling module captures dynamic ship interactions, while a GMM-Latent Representation module enhances prediction diversity. Tests on AIS data from the Port of New York and Wuhan Riverfront show a 15.28% reduction in minADE and 24.15% in minFDE compared to existing methods.

08openalex2026-09-10Doreen Jirak, Armeen Saroukanoff, Dirk van RooyDOI ↗

Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations (opens in a new tab)

A survey of maritime stakeholders assessed attitudes toward AI-supported collision-avoidance systems. Participants showed general openness to maritime technology, with no age-related differences, and stable trust across scenarios, though explanation quality varied. Open responses highlighted appreciation for decision support and situation awareness but raised concerns about AI reliability and over-reliance. The study recommends designing AI systems for calibrated reliance with transparent, expert-informed features.

09crossref2026-09-08Sergey I. Kondratyev, Evgeniy V. Khekert, Nikita V. Martyushev, Boris V. Malozyomov +5 moreDOI ↗

Risk-Aware Fault-Tolerant Multisensor Fusion for Human–Machine Decision Support in Autonomous Navigation and Mooring in Confined Waters (opens in a new tab)

A risk-aware multisensor fusion system was developed for autonomous navigation and mooring in confined waters, integrating data from RTK-GNSS, inertial sensors, radar, LiDAR, cameras, and other sources. The system uses fault detection, sensor-quality assessment, and dynamic authority allocation between automation and operators to maintain reliability. Testing over five days with 40 runs and 480 evaluation epochs showed horizontal-position and heading errors of 0.043 m and 0.176°, respectively, under normal conditions. The system detected all 64 fault events, with 99.3% protection-level coverage for single faults and 100% for combined faults, ensuring safe operation even under degraded sensor conditions.

10crossref2026-09-07Yingying Wang, Fan Zhang, Wenru Zhang, Yihao Liu +2 moreDOI ↗

AIS-Based Forecasting of STEAM-Estimated Ship CO2 Emissions for Sustainable Maritime Transportation Using a Spatio-Temporal Graph Transformer (opens in a new tab)

This study introduces the Carbon-oriented Spatio-Temporal Graph Transformer (C-STGT) to forecast ship CO₂ emissions using AIS data. The model combines temporal learning, vessel-specific attributes, and emission-focused attention to improve accuracy. Tested on five containerships, C-STGT achieved an RMSE of 0.89, MAE of 0.51, WAPE of 3.11%, and R² of 0.96, outperforming ten baseline models. The approach aims to enhance real-time carbon monitoring and support maritime decarbonization efforts.

11openalex2026-09-13Sijin Yu, Yunbo Li, Jiaye GongDOI ↗

A risk-aware multimodal temporal reinforcement learning approach for collision avoidance of unmanned surface vehicles in multi-dynamic-obstacle scenarios (opens in a new tab)

This paper introduces a Risk-Aware Multimodal Temporal Proximal Policy Optimization algorithm for autonomous collision avoidance in unmanned surface vehicles navigating dynamic maritime environments with varying obstacles. The method uses a collision risk index and Transformer-based network to encode risk maps and vehicle states, improving spatiotemporal feature extraction. Training is enhanced with curriculum learning, progressing from simple to complex tasks. Simulations demonstrate improved performance in success rate, safety, and adaptability compared to baseline methods.

12openalex2026-09-12Hamed Majidiyan, Gholam Reza Emad, TR Islam, Mohan AnantharamanDOI ↗

Physics-guided machine-learning surrogate for AIS-based ship fuel-consumption inventory—part a: Framework development and diagnostic evaluation (opens in a new tab)

This study introduces a physics-guided machine-learning model to estimate ship fuel consumption, combining operational, environmental, and hydrodynamic factors. The model, trained on synthetic data from a resistance-to-power chain, outperformed existing methods (STEAM2, IMO, and STEAM) with a −3.22% aggregate error across five voyages of a 197 m bulk carrier. Diagnostic evaluations showed errors were linked to limited directional wave data and underrepresented added-wave resistance. The framework offers a computationally efficient, vessel-specific approach for fuel estimation while highlighting the need for improved physics fidelity.

13crossref2026-09-11Keping Guan, Miao Chen, Yue ZhouDOI ↗

A Maritime Occluded Ship Detection and Tracking Method Based on Improved YOLOv8 Fused with AIS Trajectory (opens in a new tab)

This study presents an improved YOLOv8-based method for detecting and tracking occluded ships in maritime environments. The approach enhances the model with an SEConv structure using Swish activation, integrates a CBAM attention mechanism, and fuses AIS trajectory data to address occlusion and tracking interruptions. Tested on the SeaShips dataset and a custom occlusion dataset, the method achieves stable mAP gains and improves multi-target tracking accuracy (MOTA) and IDF1 by 6.3% and 8.1%, respectively. The system reduces occlusion reconstruction error to under 1.4 seconds, demonstrating improved performance in complex maritime scenarios.

14crossref2026-09-11Marios Xanthidis, Kostas Alexis, Eleni KelasidiDOI ↗

Autonomous navigation and active perception with complex articulated AUVs (opens in a new tab)

This paper introduces a new motion planning framework for complex articulated autonomous underwater vehicles (AUVs) to enable safe navigation and active perception in dynamic, uncertain environments. The method adapts an existing pipeline for holonomic AUVs to handle high-dimensional, articulated systems with unknown dynamics and multiple sensors. Simulations using an underwater snake robot and an underwater vehicle-manipulator system demonstrate real-time, efficient, and safe performance. The study also highlights computational challenges and potential improvements.

15openalex2026-09-08Samira Alkaee Taleghan, Younghyun Koo, Farnoush Banaei‐KashaniDOI ↗

An Autonomous GeoAI Agent for Arctic Eco-Navigation (opens in a new tab)

This paper presents a multi-agent GeoAI system for Arctic eco-navigation that balances vessel safety, efficiency, ecological protection, and community impacts. The system integrates operational, physical, ecological, and social criteria, using specialized agents to process geospatial data, generate multi-objective routes, and provide decision support. It explicitly accounts for sensitive habitats like Essential Fish Habitat and seal critical areas while keeping human oversight for value-based decisions. The framework aims to improve transparency and social responsibility in Arctic maritime routing.

16openalex2026-09-10Luci CareyDOI ↗

Jurisdictional Issues (opens in a new tab)

The paper explores jurisdictional challenges posed by uncrewed surface vessels (USVs) or maritime autonomous surface ships (MASS) controlled via remote-operation centers (ROCs) in commercial maritime activities. It highlights that ROCs are currently used for marine surveys, where crews operate USVs from onshore locations rather than onboard. The focus is on legal and regulatory uncertainties arising from this remote operational model. The analysis centers on how jurisdiction is determined when vessels are controlled from a different location than where they operate.

17crossref2026-09-08Bhupen Pervaiz Bheem, Khatiba Noor, Zeeshan Riaz, Junaid Ahmed Khan +3 moreDOI ↗

Design and Development of an Uncrewed Surface Vessel (USV) for Hydrographic Survey (opens in a new tab)

This paper details the design of an autonomous Uncrewed Surface Vessel (USV) for hydrographic surveys in shallow or hazardous waters. The USV features a catamaran hull, Brushless DC motors, and Lithium Polymer batteries for improved endurance and real-time data transmission. Computational Fluid Dynamics (CFD) simulations using OpenFOAM and static stability analysis with Paramarine software validated its hydrodynamic performance. A prototype was built and tested, confirming its stability, maneuverability, and suitability for marine research and commercial use.

18crossref2026-09-10Manuel Vázquez Neira, Francisco J. Pérez-Castelo, Genaro Cao Feijóo, José A. OrosaDOI ↗

Artificial Intelligence Applications for Human-Factor Risk Reduction in Merchant Ship Operations: Regulatory Challenges and Future Maritime Safety Frameworks (opens in a new tab)

This paper reviews AI applications for reducing human-factor risks in merchant ship operations, analyzing 23 core sources and recent technical evidence. It evaluates AI technologies like computer vision, fatigue analysis, and edge processing, noting high but context-dependent detection performance. A proposed system architecture integrates sensors, edge processing, and fail-safe protocols, while regulatory adaptations for SOLAS, ISM Code, and other frameworks are suggested. The 2026 IMO MASS Code is cited as a precedent for goal-based approval and progressive implementation.

19crossref2026-09-11Jiamian Sun, Weifeng LiDOI ↗

Safety-Aware Path Planning for Unmanned Surface Vehicle: An Adaptive Hybrid Collision Avoidance Operation (opens in a new tab)

This paper introduces an adaptive path planning algorithm for unmanned surface vehicles (USVs) to improve navigation in dynamic maritime settings. The method combines an enhanced ant colony optimization (ACO) algorithm—using a pheromone penalty mechanism and path smoothing—with a modified dynamic window approach (DWA) that optimizes overshoot, selection efficiency, and adaptive weight adjustments. Simulations show the approach reduces travel length and improves collision avoidance compared to existing methods. The result is more reliable navigation in complex marine environments.

20openalex2026-09-09Hang Zou, Jie Qi, Nailong Wu, Yanjie LiDOI ↗

Simulation Result Data for Lyapunov Constrained Soft Actor-Critic based Hierarchical Control for Dynamic Positioning of Unmanned Surface Vessels (opens in a new tab)

This dataset presents simulation results for a Lyapunov-constrained Soft Actor-Critic hierarchical control system applied to unmanned surface vessels. It covers performance under Sea State 3 and 4 conditions, including tracking responses, control inputs, actuator states, and environmental disturbances. The data supports findings in an associated manuscript by Zou, Qi, Wu, and Li. No experimental or real-world validation is included.

21openalex2026-09-11Ocean Networks Canada SocietyDOI ↗

Mantis Navigation System Deployed 2026-07-24 (opens in a new tab)

The Mantis ROV Navigation 01 system was deployed on July 24, 2026, aboard the Mantis ROV operated by CanPac Marine Services Inc. It records positional data such as latitude, longitude, speed, heading, pitch, roll, and depth for ships, buoys, and AUVs. The system was installed on a mobile platform, and its data is stored and accessible via Ocean Networks Canada’s Oceans 3.0 infrastructure. Quality assurance and derived data products follow standard procedures.

22crossref2026-09-09Xinyi Wang, Kun Liu, Shuai ZongDOI ↗

Conditional Kriging prediction of ship–ship hydrodynamic responses during non-parallel berthing (opens in a new tab)

This study examines how berthing angle, water depth, and lateral spacing affect hydrodynamic forces and moments on two ships (KVLCC2 and Aframax) during non-parallel berthing. Eighteen Kriging models were developed and tested across three parameter groups, with performance varying by response type—CaseA showed the highest accuracy (R² ~0.96–1.00), while CaseH and CaseY had mixed results, including some negative R² values. The findings highlight that Kriging model reliability depends on specific conditions and responses, limiting their use to validated scenarios. Water depth effects were analyzed within moderate-to-large depth-to-draft ratios, not shallow-water conditions.

23crossref2026-12-01Achim Schlüter, Maarten BavinckDOI ↗

Ocean privatisation: the ‘processes of property’ occurring in the world’s maritime domains (opens in a new tab)

The paper examines the growing trend of ocean privatisation, where individuals, corporations, states, and organizations claim property rights over maritime domains. It highlights increasing research on related topics like blue-grabbing and tradable quotas, often presenting polarized views—either as solutions or risks. The collection analyzes diverse perspectives using varied theoretical frameworks and global case studies, aided by AI-assisted qualitative tools. Key findings show privatisation as dynamic "processes of property," shaped by bargaining, discourse, and power dynamics, with a focus on distributive consequences.

24crossref2026-09-07Lin Zhou, Zhuo Wang, Zhou Nan, Zhongchao Deng +2 moreDOI ↗

An Information‐Driven Multilevel Path Planning Framework for Unmanned Surface Vehicles in Environmental Monitoring of Uninhabited Islands and Reefs (opens in a new tab)

This paper introduces an information-driven, multilevel path planning framework for unmanned surface vehicles (USVs) to improve environmental monitoring of uninhabited islands and reefs. The framework uses three algorithms: one for broad mapping of irregular areas, another for fine-tuned local mapping adjusted to tidal changes, and a third for energy-efficient ecological sampling despite ocean currents. Tests show the method outperforms existing approaches in path length, coverage accuracy, and energy use. The system enhances observation efficiency and reliability for long-term monitoring tasks.

25openalex2026-09-07Fengchuan Song, Shanliang Yao, Maohan Liang, Young-Rong Kim +1 moreDOI ↗

An uncertainty-aware 4D millimeter wave radar–camera fusion method for robust environmental perception under dynamic maritime conditions (opens in a new tab)

No abstract or body text was available, so this entry is reported from metadata only.

26crossref2026-09-07Xinyu Zhang, Hongxing Zheng, Junjie NiDOI ↗

Integrated Rescheduling Optimization of Vessel Sequencing and Berth Allocation Under Vessel Delay Impacts (opens in a new tab)

This study proposes an integrated rescheduling model for vessel sequencing and berth allocation to address disruptions caused by vessel delays at ports with one-way channels. It introduces a rolling decision-making mechanism and strategies like berth reallocation, Normal Berth Shifting (NBS), Cross-Terminal Berth Shifting (CTBS), and Cargo Discharge-Only (CDO) to minimize rescheduling costs. An integer linear programming model and an adaptive large neighborhood search (ALNS) algorithm optimize vessel sequencing and berth use. Case studies and sensitivity analysis confirm the framework’s effectiveness in reducing delay impacts.

27crossref2026-09-10Rohit Bohara, Omkar Joglekar, Mirko Ross, Rob van KranenburgDOI ↗

Towards Automated Liability Determination for Autonomous Vehicles in Road Accidents (opens in a new tab)

This paper proposes an automated framework for determining liability in accidents involving autonomous vehicles. It uses edge intelligence, machine learning, and graph theory to process real-time sensor data from vehicles, weather, and roadside units. The system constructs event identity graphs to map causal relationships and cross-references them with insurance codes, traffic laws, and ethical policies. The approach aims to improve transparency, fairness, and efficiency in liability assessments compared to traditional manual methods.

28crossref2026-09-10Ovidiu Vermesan, Valerio Frascolla, Patrick Pype, Vahid HashemiDOI ↗

The AI-Defined Vehicle: Navigating the Convergence of AI and Autonomous Systems (opens in a new tab)

The paper examines the shift in the automotive industry toward AI-defined vehicles (AIDVs), driven by AI integration, advanced data processing, and sensor-communication convergence. It explores the progression from connected vehicles to software-defined vehicles (SDVs) and ultimately AIDVs, which use generative AI for scenario synthesis and agentic AI for decision-making. The authors analyze the transition from hardware-centric to AI-centric designs, emphasizing the role of vehicle-to-everything (V2X) communication. The article also discusses future challenges and opportunities in automated intelligent transportation systems (ITSs).

Automated Generation of Functionally Complete Assurance Suites for COLREGS-Compliance of Autonomous Surface VehiclesAutomated Generation of Functionally Complete Assurance Suites for COLREGS-Compliance of Autonomous Surface Vehicles ↗ (opens in a new tab)

Safety Analysis of Collision Avoidance for Semi-Autonomous Navigation Ship Based on STPA-CREAMSafety Analysis of Collision Avoidance for Semi-Autonomous Navigation Ship Based on STPA-CREAM ↗ (opens in a new tab)

A Distributed Consensus Particle Filter for Target Tracking using Autonomous Surface VesselsA Distributed Consensus Particle Filter for Target Tracking using Autonomous Surface Vessels ↗ (opens in a new tab)

Deep Reinforcement Learning Control for Path Following and Static Obstacle Avoidance for Autonomous Surface VesselsDeep Reinforcement Learning Control for Path Following and Static Obstacle Avoidance for Autonomous Surface Vessels ↗ (opens in a new tab)

Language-Grounded Semantic Target Navigation for Autonomous Surface VehiclesLanguage-Grounded Semantic Target Navigation for Autonomous Surface Vehicles ↗ (opens in a new tab)

QSD-STFormer: Quaternion Ship Domain-guided Spatiotemporal Transformer for ship trajectory predictionQSD-STFormer: Quaternion Ship Domain-guided Spatiotemporal Transformer for ship trajectory prediction ↗ (opens in a new tab)

Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime OperationsUnderstanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations ↗ (opens in a new tab)

Risk-Aware Fault-Tolerant Multisensor Fusion for Human–Machine Decision Support in Autonomous Navigation and Mooring in Confined WatersRisk-Aware Fault-Tolerant Multisensor Fusion for Human–Machine Decision Support in Autonomous Navigation and Mooring in Confined Waters ↗ (opens in a new tab)

A Maritime Occluded Ship Detection and Tracking Method Based on Improved YOLOv8 Fused with AIS TrajectoryA Maritime Occluded Ship Detection and Tracking Method Based on Improved YOLOv8 Fused with AIS Trajectory ↗ (opens in a new tab)

Autonomous navigation and active perception with complex articulated AUVsAutonomous navigation and active perception with complex articulated AUVs ↗ (opens in a new tab)

An Autonomous GeoAI Agent for Arctic Eco-NavigationAn Autonomous GeoAI Agent for Arctic Eco-Navigation ↗ (opens in a new tab)

Jurisdictional IssuesJurisdictional Issues ↗ (opens in a new tab)

Design and Development of an Uncrewed Surface Vessel (USV) for Hydrographic SurveyDesign and Development of an Uncrewed Surface Vessel (USV) for Hydrographic Survey ↗ (opens in a new tab)

Safety-Aware Path Planning for Unmanned Surface Vehicle: An Adaptive Hybrid Collision Avoidance OperationSafety-Aware Path Planning for Unmanned Surface Vehicle: An Adaptive Hybrid Collision Avoidance Operation ↗ (opens in a new tab)

Mantis Navigation System Deployed 2026-07-24Mantis Navigation System Deployed 2026-07-24 ↗ (opens in a new tab)

Conditional Kriging prediction of ship–ship hydrodynamic responses during non-parallel berthingConditional Kriging prediction of ship–ship hydrodynamic responses during non-parallel berthing ↗ (opens in a new tab)

Ocean privatisation: the ‘processes of property’ occurring in the world’s maritime domainsOcean privatisation: the ‘processes of property’ occurring in the world’s maritime domains ↗ (opens in a new tab)

Integrated Rescheduling Optimization of Vessel Sequencing and Berth Allocation Under Vessel Delay ImpactsIntegrated Rescheduling Optimization of Vessel Sequencing and Berth Allocation Under Vessel Delay Impacts ↗ (opens in a new tab)

Towards Automated Liability Determination for Autonomous Vehicles in Road AccidentsTowards Automated Liability Determination for Autonomous Vehicles in Road Accidents ↗ (opens in a new tab)

The AI-Defined Vehicle: Navigating the Convergence of AI and Autonomous SystemsThe AI-Defined Vehicle: Navigating the Convergence of AI and Autonomous Systems ↗ (opens in a new tab)