(03)

Science

↓ (W44 ‘26 · Oct 26–Nov 1)
01openalex2026-10-28Sergey Victorovich Smolentsev, А. А. Мироненко, A.E. FilyakovDOI ↗ (opens in a new tab)

A comprehensive model for assessing the risk of close approach between maritime autonomous surface ships and objects (opens in a new tab)

This study enhances the ship domain model using an N-focal ellipse to improve risk assessment for maritime autonomous surface ships (MASS). It distinguishes between collision-avoidance tasks involving moving objects under COLREGs and other navigational hazards by categorizing foci into vessel dimensions, kinematic parameters, and maneuvering characteristics. The model introduces multipliers to adjust domain boundaries based on navigation conditions and defines a minimum navigational safety margin. Simulations support the findings, suggesting the model could advance MASS navigational safety when integrated into control systems.

02openalex2026-10-28Ольховик Евгений Олегович, Artem Aleksandrovich Butsanets, D. V. IsakovDOI ↗ (opens in a new tab)

Digital route of a maritime autonomous surface ship: from waypoints to a dynamically feasible trajectory (opens in a new tab)

This study redefines the "route" concept for Maritime Autonomous Surface Ships (MASS) by expanding the IEC 61174 RTZ format to include turn arcs, corridors, speed profiles, and time stamps for dynamic feasibility. Using the MMG maneuvering and Nomoto models, the proposed digital route improved trajectory accuracy, reducing maximum deviation from 35.3 m to 11.3 m and rudder angles from 25.1° to 17.6° in tests with a 100 m vessel. The authors introduce an "acceptable solution" hypothesis for tactical replanning and a four-level planning architecture. Future work may explore advanced simulations, deceleration modes, and cooperative planning for multiple MASS.

03openalex2026-10-28Victor Vladimirovich Deryabin, Сазонов Анатолий ЕфимовичDOI ↗ (opens in a new tab)

A neural network-based approach to collision avoidance for maritime autonomous surface ships (opens in a new tab)

This paper proposes a neural network-based method for cooperative collision avoidance in Maritime Autonomous Surface Ships (MASS). The system uses vessel coordinates and velocity components as inputs and outputs course adjustments to maintain a safe distance. The neural network has eight hidden layers with 1,000 neurons each and was trained on one million samples using a two-iteration gradient optimization process. After training, the model achieved a mean prediction error of about 2°, though maximum errors remained high at several tens of degrees.

04openalex2026-10-26Yourak Jang, Yongung YuDOI ↗ (opens in a new tab)

Innocent passage and marine environmental protection of remotely operated MASS: functional equivalence and coastal state jurisdiction (opens in a new tab)

This paper analyzes how remotely operated Maritime Autonomous Surface Ships (MASS) without crew redistribute environmental protection duties among ship systems, Remote Operations Centres (ROCs), and external support. It assesses whether existing pollution prevention, reporting, and emergency response functions can be maintained at equivalent levels under UNCLOS and IMO frameworks. The authors argue that coastal states’ jurisdiction should not expand beyond current limits, with pre-incident regulations and post-incident enforcement requiring clear legal boundaries. The study emphasizes clarifying how existing environmental protections apply to MASS rather than creating new regulatory powers.

05openalex2026-10-27Steven Mallam, Kjetil Nordby, Etienne Gernez, Engy Awad +4 moreDOI ↗ (opens in a new tab)

Developing a Remote Operations Center for Uncrewed and Autonomously-Capable Maritime Surface Ships (opens in a new tab)

This paper presents a design case study for a Remote Operations Center (ROC) supporting an 8-meter uncrewed autonomous test ship in North Atlantic Canadian waters. Researchers conducted user-centered workshops and design iterations to refine the ROC’s physical workspace and human-machine interfaces for shoreside operators. The study offers methodological and design insights for MASS ROC development. It also establishes a framework for future human-performance testing involving ROC operators and autonomous ships.

06openalex2026-10-30Elia Trevisan, Alejandro González-García, Jan Swevers, Javier Alonso–MoraDOI ↗ (opens in a new tab)

Interaction-Aware Sampling-Based Motion Planning for Autonomous Surface Vessels in Urban Waterways (opens in a new tab)

This paper introduces a decentralized motion planner for autonomous surface vessels in urban waterways, using a sampling-based model predictive control method. The planner simultaneously calculates the vessel's trajectory and predicts interactions with other vessels while adhering to traffic rules through discontinuous cost functions. Tested in real Amsterdam canal maps and outdoor experiments with scaled prototypes, the method achieved collision-free and deadlock-free navigation in 780 randomized trials, outperforming optimization-based and non-interaction-aware planners. Onboard execution ran at 10 Hz, successfully handling head-on and crossing scenarios.

07openalex2026-11-01Wentao Lv, Peng Wu, Wenwen Liu, Jianxiong Hu +4 moreDOI ↗ (opens in a new tab)

Ship-shore energy systems for maritime electrification: Voyage-energy provision, configurations and resilience (opens in a new tab)

This paper reviews research (2000–2026) on maritime electrification, focusing on how energy is supplied and replenished for electrified vessels. It identifies two main pathways—shore-electric operation (external power supply) and fuel-carried electric operation (onboard fuel storage)—and four vessel configurations, from battery-dominant to fuel-dominant systems. Case studies show how replenishment access and onboard capabilities influence operational feasibility. The study highlights shifting constraints between port infrastructure and vessel autonomy, affecting resilience to disruptions.

08openalex2026-10-27Danielle Luciana Aurora Soares do Amaral, João Gabriel R. N. Ferreira, Rosa M. B. Cavalcanti, Marcelo Merten Cruz +10 moreDOI ↗ (opens in a new tab)

Autonomous sampling and eDNA metabarcoding for offshore biodiversity monitoring: a pilot study around an FPSO in the Southwestern Atlantic (opens in a new tab)

This pilot study tested autonomous water sampling combined with eDNA metabarcoding to monitor biodiversity near an offshore FPSO in Brazil’s Santos Basin. Using an uncrewed vessel, researchers collected 64 samples, detecting 34 species with 12S and 28 with 16S markers, covering 65–74% of estimated species richness. Weak spatial differences were found around the FPSO, while short-term temporal variation was high, with taxon turnover driving most dissimilarity. The approach proved feasible for offshore monitoring, recommending repeated sampling to identify persistent ecological changes.

09openalex2026-10-26Reyes Poo Argüelles, Jesús A. García MazaDOI ↗ (opens in a new tab)

Algorithms for determining deadlines and COLREG-compliant manoeuvres for safe navigation in multi-ship scenarios using velocity areas (opens in a new tab)

This paper introduces algorithms for automatic collision avoidance in multi-ship scenarios by identifying risk-free navigation areas and compliant maneuvers. Using AIS data, safety parameters, and COLREG rules, the algorithms replicate human decision-making processes of navigational officers. Polar graphs and weighted velocity areas help determine optimal maneuvers while adhering to maritime regulations. The output is designed for integration into autonomous navigation systems.

10openalex2026-10-29Qinghua Zhu, Shenping Hu, JiaXin Du, Jing Xin Xu +1 moreDOI ↗ (opens in a new tab)

Intelligent anti-collision in multi-vessel scenarios: a spatial DPAD decision-making model via accident data-driven (opens in a new tab)

This paper introduces a **Domain Predicted Area of Danger (DPAD)** model for intelligent anti-collision decision-making in multi-vessel scenarios. The model constructs a **Predicted Collision Risk Area (PCRA)** based on COLREGs guidelines and uses **Potential Collision Risk (PCR)** thresholds to evaluate safe navigation resumption. **Grey Wolf Optimization (GWO)** and **Bézier curves** optimize post-collision recovery paths. Validated with real collision cases, the model demonstrates reliable adaptive control for vessel avoidance in complex waters.

12openalex2026-10-31Hong Thao Nguyen, Nguyễn Hoàng ViệtDOI ↗ (opens in a new tab)

Autonomous Maritime Vehicles in Law Enforcement Contexts in the South China Sea (opens in a new tab)

The paper explores the impact of Autonomous Maritime Vehicles in Law Enforcement (AMVLEs) on maritime security and legal frameworks in the South China Sea. It argues that while AMVLEs do not create new tensions, they may worsen existing ones by complicating identification, navigational rights, and lawful responses during encounters. The authors conclude that adapting existing UNCLOS rules—through consistent application, clear state responsibility, and regional cooperation—can address these challenges without requiring a new legal regime. Operational restraint and confidence-building measures are recommended to reduce risks and maintain UNCLOS as the regional legal foundation.

15openalex2026-10-28Zhichao Zhang, Yizhi Zhang, Dewang Zhang, Zhenqiang WuDOI ↗ (opens in a new tab)

PAC-Net: physics-consistent and color-aware maritime image dehazing via adaptive haze modeling and progressive learning (opens in a new tab)

PAC-Net is a new framework for maritime image dehazing, addressing challenges like uneven haze distribution, blue-green color casts, and cross-domain variability in marine environments. It introduces an Adaptive HazeData (AHD) generation method for realistic haze synthesis, a Color-Aware Channel Attention (CCA) module to correct color imbalances, and a progressive learning strategy to handle diverse scenarios. Tested on the Adaptive Maritime Haze Dataset (AMHD) and RESIDE benchmark, PAC-Net outperforms existing methods in structural and color restoration. The approach demonstrates strong cross-domain generalization.

18openalex2026-10-29Shaffiyah Cantika Kamia, Suharyono Soemarwoto Hadiningrat, Jones Zenas Rante, Rudianto Rudianto +1 moreDOI ↗ (opens in a new tab)

The Implementation of Unmanned Lighthouse Systems in Indonesia: Opportunities, Challenges, and Lessons from the Class II Type A Navigation District of Banjarmasin (opens in a new tab)

This study explores the adoption of Unmanned Lighthouse Systems in Banjarmasin, Indonesia, highlighting benefits like a projected 40% cost reduction, improved safety, and compliance with IMO and IALA standards. Challenges include environmental constraints, regulatory gaps, digital skill shortages, unreliable power and telecoms, and cybersecurity risks. Researchers used interviews, observations, and document analysis to develop a three-phase implementation roadmap. The findings offer a socio-technical framework for modernizing maritime navigation in developing nations.

22openalex2026-10-28Vishnudatta Thota, Tyler M. Paine, Anastasia BizyaevaDOI ↗ (opens in a new tab)

Tunable Spatial Task Allocation with Application to Maritime Swarms (opens in a new tab)

This paper presents a task allocation strategy for autonomous agent teams, using a generalized Nonlinear Opinion Dynamics model adapted for spatial movement. The approach allows agents to dynamically redistribute across tasks, producing allocation patterns from fully dispersed to cohesive groups based on environmental and social interaction parameters. Simulations demonstrate real-time reconfiguration under changing demands, with performance near the Hungarian optimum for distance-based preferences. The method is validated in a MOOS-IvP-Multi environment using simulated autonomous underwater vehicles (AUVs).

23openalex2026-11-01Chris CarpenterDOI ↗ (opens in a new tab)

Chemical Treatment Using Completion Rig Achieves Gains Without Service Vessel (opens in a new tab)

The paper discusses an autonomous chemical treatment method for scale management in Brazil’s Buzios Field, eliminating the need for a well-service stimulation vessel by using rig-based infrastructure. This approach reduces logistical complexity and costs while improving operational efficiency and well productivity. The Buzios Field, an ultradeepwater reservoir with depths up to 6,000 meters, relies on intelligent well completions to manage its complex carbonate formations. The proposed strategy focuses on removing and inhibiting inorganic scale through chemical treatments and operational protocols.

30openalex2026-10-28Yutong Guo, Yangjun Wang, Ren ZhangDOI ↗ (opens in a new tab)

Pathway to low-carbon arctic shipping: carbon tax thresholds and market equilibrium under climate change (opens in a new tab)

This study examines how Arctic sea ice melt and carbon pricing policies affect competition between the Northeast Passage and Suez Canal Route for China–Europe shipping. Using a Stackelberg game model, it analyzes the interplay between carbon taxes, voyage speed, costs, route shares, and emissions, revealing non-linear effects on emissions reduction. Findings show that under severe warming, the Arctic route could capture 22% of freight traffic, with emissions surpassing 630,000 metric tonnes. The research highlights how climate change lowers the threshold for effective carbon tax regulation while supporting long-term low-carbon shipping strategies.

31crossref2026-10-28Yuanhao Chen, Tiancan Mei, Bowen YangDOI ↗ (opens in a new tab)

SURT-DETR: Sea–Sky Line Context-aware and Uncertainty-Guided Small Object Detection for Unmanned Surface Vehicles (opens in a new tab)

The paper introduces SURT-DETR, a Transformer-based framework designed to improve small object detection for unmanned surface vehicles (USVs) in maritime environments. It addresses challenges like scale variations and background interference using three innovations: a sea–sky line context-aware module (SLCAM), an uncertainty-guided small object decoder (UGSD), and an uncertainty-regularized NWD loss. Tested on the Pohang Canal dataset, SURT-DETR achieved a 79.5% mAP and 69.2% small-object AP, outperforming the RT-DETR baseline with minimal added parameters. Ablation studies confirmed the effectiveness of its components for practical USV perception.

32openalex2026-10-31Nguyễn Thị Thanh Bình, Nguyễn Anh Cường, Đậu Tuấn NamDOI ↗ (opens in a new tab)

Capability-backed strategic autonomy and Vietnam’s hedging amid U.S.-China rivalry (opens in a new tab)

Vietnam’s strategic autonomy amid U.S.-China rivalry relies on reducing vulnerability through domestic capabilities rather than just diplomatic maneuvering. The country faces asymmetric dependence: the U.S. dominates export demand and advanced technology, while China controls production inputs, logistics, and maritime stability. Hedging remains viable but requires stronger domestic firms, technological absorption, energy resilience, and maritime capacity. Strategic autonomy is framed as maintaining policy options rather than formal alignment.

33openalex2026-10-29Yan Zhou, Jiepeng Huang, Chunmei Xie, Yunxing ZhangDOI ↗ (opens in a new tab)

A fast evaluation framework for the hydrodynamic performance of deformed marine structures using artificial intelligence-based three-dimensional reconstruction (opens in a new tab)

This paper presents an AI-based framework for quickly evaluating the hydrodynamic performance of deformed marine structures like ships and offshore platforms. The method uses multi-view images to reconstruct a 3D model via the HunYuan3D model, followed by numerical simulations to assess stability and motion responses. Validation on a deformed ship showed geometric parameter errors under 3% and results consistent with known damage effects. The approach offers a low-cost, efficient, and reliable tool for emergency decision-making in maintenance and safety planning.

36openalex2026-10-28Taizhi LvDOI ↗ (opens in a new tab)

Research on Intelligent Agent Technology Empowering ICT Skilled Talent Cultivation for Smart Shipping (opens in a new tab)

This paper examines how AI agent technology can address the shortage of skilled ICT talent in smart shipping by improving vocational education. It identifies challenges in key teaching areas like curricula, faculty, and practical training, proposing a "Student–Teacher–Agent" model based on Human-Machine Distributed Cognition theory. The study suggests restructuring curricula around smart shipping’s technical chain and validates skill transfer using data mining and social network analysis. Findings show that AI-driven agent systems can better align education with industry needs, supporting talent development for digital-smart shipping.

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