Vessel Path Research Articles

Data-driven construction of maritime traffic networks for AI-based route prediction

Abstract Predicting the routes of maritime traffic can improve economic efficiency, decrease ecological impact, and improve safety at sea. Over scales that are small (few hundred meters) and large (dozens to hundreds of kilometers), vessel trajectories have successfully been predicted by deep learning and (static) network-based approaches, respectively. We present an approach for medium to large scales (few kilometers) where (a) a maritime traffic network is automatically constructed from AIS messages, and (b) vessel trajectories are predicted as most likely paths through the network. Using three regions (Stavanger, Tromsø, and Oslo), we show that the network can capture up to ∼ 90 per cent of all maritime traffic (excluding pleasure craft) with a median absolute error of ∼ 80 meters. Vessel paths are sequences of waypoints and legs (nodes and edges) and are map-matched onto the network from vessel trajectories. Once mapped, we predict future paths for two subproblems – (i) known destination, and (ii) unknown destination. We use four algorithms (Dijkstra, Markov, MOGen, GRETEL). For known destinations, we find that Dijkstra performs best. In Stavanger (Tromsø, Oslo), Dijkstra predicts 64 (42, 68) per cent of path segments correctly and keeps the median path error below 15 (33 and 55) meters. For unknown destinations, performance depends on the forecast horizon (the number of legs k to predict). For k ≤ 5, Markov is best and predicts 62 (48, 72) per cent of legs correctly. For k > 5, GRETEL performs best and predicts 54 (47, 63) per cent of legs correctly. For some types of vessels, models improve by considering vessel type. For passenger vessels, models specific to them predict ∼ 10 per cent better paths with half the distance error. For tankers, paths (and distance errors) are 6 (20) per cent worse. For auxiliary vessels, path quality is unchanged, but distance error improves ∼ 36 per cent.

Exploring Innovative Methods in Maritime Simulation: A Ship Path Planning System Utilizing Virtual Reality and Numerical Simulation

In addressing the high costs, inefficiencies, and limitations of purely digital simulations in maritime trials for unmanned vessel path planning, this paper introduces a ship virtual path planning simulation test system. This system, unbound by temporal and spatial constraints, vividly showcases the navigational performance of vessels. After analyzing the virtual testing requirements for the autonomous navigation performance of unmanned surface vehicles (USVs), we established the overall framework of this system. Data-driven by a numerical simulation platform, the system achieves synchronized operation between physical and virtual platforms and supports interactive path planning simulations between USVs and the virtual testing system. Furthermore, to address the limitations of traditional ship trajectory planning evaluation, this paper develops a global path planning fitness evaluation function that comprehensively considers trajectory safety, navigation distance, and vessel stability, achieving optimal comprehensive routes through the particle swarm optimization algorithm. Test results indicate an average roll reduction of 14.31% in the planned routes, with a slight increase in navigation distance. By integrating two-dimensional curve simulation with three-dimensional visualization, this paper not only overcomes the limitations of purely physical and purely virtual simulations but also enhances the overall credibility and intuitiveness of the simulation. Experimental results validate the system’s effectiveness, providing a novel method for autonomous navigation testing and evaluation of USVs.

Quasi-Infinite Horizon Model Predictive Control with Fixed-Time Disturbance Observer for Underactuated Surface Vessel Path Following

As a flexible, autonomous and intelligent motion platform, underactuated surface vessels (USVs) are expected to be an ideal means of transport in dangerous and complex marine environments. The success and efficiency of maritime missions performed by USVs depend on their ability to accurately follow paths and remain robust against wind and wave disturbances. To this end, this paper focuses on accurate and robust path following control for USVs under wave disturbances. Model predictive control with a quasi-infinite horizon is proposed which converts the objective function from an infinite horizon to an approximate finite horizon, providing the convergence performance in long prediction horizons and reducing the computation load explicitly. To enhance robustness against disturbances, a fixed-time disturbance observer is applied to estimate the time-varying and bounded disturbances. The estimated value is provided to the controller input to form a robust control framework with disturbance feedforward compensation and predictive control feedback correction, which is substantially different from existing works. The convergence and optimality of the proposed algorithm are presented mathematically. Finally, we demonstrate the advantages of the algorithm in both theory and simulation.

Construction of a large-scale maritime element semantic schema based on knowledge graph models for unmanned automated decision-making

In maritime logistics optimization, considerable research efforts are focused on the extraction of deep behavioral characteristics from comprehensive shipping data to discern patterns in maritime vessel behavior. The effective linkage of these characteristics with maritime infrastructure, such as berths, is critical for the enhancement of ship navigation systems. This endeavor is paramount not only as a research focus within maritime information science but also for the progression of intelligent maritime systems. Traditional methodologies have primarily emphasized the analysis of navigational paths of vessels without an extensive consideration of the geographical dynamics between ships and port infrastructure. However, the introduction of knowledge graphs has enabled the integration of disparate data sources, facilitating new insights that propel the development of intelligent maritime systems. This manuscript presents a novel framework using knowledge graph technology for profound analysis of maritime data. Utilizing automatic identification system (AIS) data alongside spatial information from port facilities, the framework forms semantic triplet connections among ships, anchorages, berths, and waterways. This enables the semantic modeling of maritime behaviors, offering precise identification of ships through their diverse semantic information. Moreover, by exploiting the semantic relations between ships and berths, a reverse semantic knowledge graph for berths is constructed, which is specifically tailored to ship type, size, and category. The manuscript critically evaluates a range of graph embedding techniques, dimensionality reduction methods, and classification strategies through experimental frameworks to determine the most efficacious methodologies. The findings reveal that the maritime knowledge graph significantly enhances the semantic understanding of unmanned maritime equipment, thereby improving decision-making capabilities. Additionally, it establishes a semantic foundation for the development of expansive maritime models, illustrating the potential of knowledge graph technology in advancing intelligent maritime systems.

Lymphatic Mapping for LVA with Noncontrast Lymphatic Ultrasound: How We Do It.

Recently, lymphatic ultrasonography has received increasing attention. Although there are several reports on contrast-enhanced lymphatic ultrasound as a preoperative examination for lymphaticovenous anastomosis (LVA), we have been reporting the usefulness of preoperative noncontrast lymphatic ultrasound. In this article, the detailed procedure for conducting lymphatic ultrasound during the preoperative examination of LVA is thoroughly described. The only items required for lymphatic ultrasound are an ultrasound device, an echo jelly, a straw for marking, and a marker. We use an ordinary ultrasound device with an 18-MHz linear probe. We apply the Doppler, Crossing, Uncollapsible, Parallel, and Superficial fascia index to identify the lymphatic vessels. While imagining the course of the lymph vessels, we position the probe perpendicular to the long axis of the lymphatic vessels. When a vessel is found under the superficial fascia, the probe is moved proximally to trace the vessel's path. If the vessel transverses a nearby vein without connecting to it, it is most likely a lymphatic vessel. To confirm, we ensure that the vessel does not exhibit coloration in the Doppler mode. As LVA is most effective when the dilated lymph vessels are anastomosed, we use lymphatic ultrasound to identify the most dilated lymphatic vessels in each lymphosome, and mark incision lines where suitable veins are in close proximity. No contrast agent is required; therefore, medical staff such as nurses and ultrasound technicians can autonomously conduct the test.

Possible vascular complications due to anatomical variations in dental surgical treatments

The facial artery undergoes multiple anatomic variations that condition the territory that vascularizes to the facial level. During the dissection of several pieces, we find a curious anatomic alteration in which the transverse facial artery is the one that replaces the facial artery because it disappears at the level of the submandibular gland. This anatomic variance can help to improve the knowledge of the vascularization of this area and be helpful in the different surgical or aesthetic processes in the facial region, and doing so minimizes the damages that can be caused in the anatomical surfaces treated. This is why in the planning of the treatment it would be always useful to know the path of the main vessels and nerves to avoid their possible injury and, in this case, we recommend the use of means such as ultrasound.

Quantifying the probability of a successful marine bioinvasion due to source-destination risk factors.

The increasing spread of marine non-indigenous species (NIS) due to the growth in global shipping traffic is causing widespread concern for the ecological and economic impacts of marine bioinvasions. Risk management authorities need tools to identify pathways and source regions of priority concern to better target efforts for preventing NIS introduction. The probability of a successful NIS introduction is affected by the likelihood that a marine species entrained in a transport vector will survive the voyage between origin and destination locations and establish an independently reproducing population at the destination. Three important risk factors are voyage duration, range of environmental conditions encountered during transit and environmental similarity between origin and destination. In this study, we aimed for a globally comprehensive approach to assembling quantifications of source-destination risk factors from every potential origin to every potential destination. To derive estimates of voyage-related marine biosecurity risk, we used computer-simulated vessel paths between pairs of ecoprovinces in the Marine Ecoregions Of the World biogeographic classification system. We used the physical length of each path to calculate voyage duration risk and the cross-latitudinal extent of the path to calculate voyage path risk. Environmental similarity risk was based on comparing annual average sea surface temperature and salinity within each ecoprovince to those of other ecoprovinces. We derived three separate sets of risk quantifications, one each for voyage duration, voyage path and environmental similarity. Our quantifications can be applied to studies that require source-destination risk estimates. They can be used separately or combined, depending on the importance of the types of source-destination risks that might be relevant to particular scientific or risk management questions or applications.

The problem of implementing the concept of maximum integration of heterogeneous data in practical navigation

The topic of the work is the research of the problem of the practical realization of opportunistic navigation, which actually consists in the fact that the “signals of opportunity” are not optimized for global navigation according to their original purpose. A hypothesis about the possibility of strategic application of the navigation concept based on the principles of data integration with the objective existence of tactically surmountable difficulties is put forward. In the conditions of vulnerability of the global satellite system, an approach to use an additional source of combined signals in order to continuously ensure accurate geolocation of water transport vehicles is proposed. The comparative assessment confirms the comparability of the positioning error of alternative navigation with the data of classical satellite observations of mobile objects. An assumption about the effectiveness of spline modeling of the cartographic standard of informativeness for the practical organization of the basic principle of opportunistic positioning by analogy with the paradigm of correlation-extreme navigation is made. A computer visualization of a fixed fragment of the ocean gravitational field based on spline approximation is performed in order to optimize the problem of simultaneous localization and three-dimensional representation of the ship movement in a graphical environment unaffiliated with foreign software. A hybrid algorithm for mathematical synthesis of the navigational isosurface has been tested as a harmonized support for the navigation staff to implement the “terrain-referenced procedure” in the landscape coordinate space. The variants of the “ambiguity resolution” problem implementation in the issue of maximum integration of heterogeneous navigation data are considered. The probability of practical use of the opportunistic navigation postulates in marine applications, taking into account the “navigation gap” factor for leveling local satellite incapacity with a real possibility of countering malicious interception of ship control, is estimated. The expediency of using the factor of observational reckoning of the vessel path as an additional condition for navigation safety in the aspect of packet processing of the “signals of opportunity” slot is substantiated.

Anatomical Features of the Ventricular System Relevant to Endoscopic Surgery for Hydrocephalus.

In endoscopic surgery for hydrocephalus and associated intraventricular lesions, a thorough understanding of the required microsurgical anatomy is paramount. Endoscopic procedures in hydrocephalus treatment typically fall into two categories: ventriculocisternostomy and ventriculostomy for obstructive hydrocephalus. In the former, precise knowledge of intraventricular structures, such as the configuration of the ventricles and the path of internal vessels within them, is essential. In the latter, a comprehensive grasp of neural pathways, neural nuclei, and especially venous pathways beneath the ventricular wall is crucial for surgical success. Given that many cases exhibit deviations from normal anatomy, careful examination of preoperative images and a solid understanding of anatomical landmarks during surgery are indispensable. This is particularly critical in endoscopic procedures, which may lack stereoscopic vision, underscoring the importance of acquiring visual cues during the surgical intervention.

Spatial Clustering Approach for Vessel Path Identification

Spatial Clustering Approach for Vessel Path Identification

Poster Session: After up to a year of hyperglycemia Ins2Akita mice show minimal capillary change.

Diabetic retinopathy (DR) is a leading cause of blindness and is detected clinically via retinal vascular changes. Here we measure the impact of hyperglycemia in a mouse model to evaluate changes in retinal capillary density, path length and pericyte coverage. We crossbred mice with fluorescent pericytes (NG2DSRed) with hyperglycemic mice (Ins2Akita) to produce offspring with labeled pericytes and sustained hyperglycemia. Retinas from male mice (7 to 53 weeks) were fixed, flat mounted, then imaged with confocal microscopy (Nikon eclipse Ti2e). Pericytes and vessel path length were manually measured with ImageJ. Custom MATLAB code rendered path length as a function of depth. Two-tailed t-tests were used for statistics. Regardless of hyperglycemic duration, Akita+ mice (n=7) had a pericyte density of 307.03 ± 69.09 cells/mm2 which was less than, but not statistically different from Akita- mice (n=5; 348.51 ± 29.78 cells/mm2; p=0.12). We did not find a difference in total path length in any of the trilaminar layers: superficial (p=0.08), intermediate (p=0.95) or deep (p=0.52). Akita+ mice had increased blood glucose, decreased body weight, and polyuria. Despite a systemic phenotype, we saw no reduction in pericytes or vessel path length, even after ~1 year of hyperglycemic insult. These findings indicate that Ins2Akita vascular changes may be more subtle than previously reported and neural/behavioral deficits may not correlate with microvascular path length or pericyte density.

3D winding path modeling of overwrapped pressure vessels with novel mesh-based directional projection and normal adaptive convex helix algorithms

Filament winding is a technique that precisely places continuous fibers along a preset path on a rotating mandrel. However, traditional 2D winding paths based on the original mandrel surface ignore the effect of thickness stacking on doffing points. To physically simulate the build-up of tows on the mandrel, a novel numerical method, including the mesh-based directional projection (MDP) and normal adaptive convex helix (NACH) algorithms, is proposed. The MDP algorithm is employed to sort out tow overlaps in the thickness direction, and is 200 times more efficient than the existing algorithms, such as the backward search algorithm. Subsequently, the “cliffs” generated in the overlap removal process are smoothed by the NACH algorithm. Furthermore, the advantages of these two algorithms in terms of efficiency, reliability, and universality are discussed in detail. In summary, a method for developing a physical-based 3D path and ever-updating workpiece contour of pressure vessels is proposed, which serves as an essential reference for high-precision winding and workpiece shape optimization.

Operational reliability study of ice loads acting on oil tanker bow

As a result of climate change, the Arctic glaciers start to melt, and the summer season arrives, making it acceptable for trade ships. There is still shattered ice in the saltwater even though the Arctic glaciers melt in the summer. The stochastic ice loading on the ship's hull is a complex ship-ice interaction. In order to properly build a vessel, it is necessary to reliably estimate the consequent high bow stresses using statistical extrapolation techniques. The bivariate reliability approach is used in this study to compute the excessive bow forces that an oil tanker encounters while sailing in the Arctic Ocean. Two stages are taken in the analysis. First, ANSYS/LS-DYNA is used to compute the oil tanker's bow stress distribution. Second, high bow stresses are projected utilizing a unique dependability methodology to evaluate return levels associated with extended return times. This research focuses on bow loads of an oil tanker travelling in the Artic Ocean using the recorded ice thickness distribution. To take advantage of weaker ice, the vessel's itinerary across the Arctic Ocean was windy (not the shortest straight path). This results in the ship route data used being inaccurate concerning the ice thickness statistics for the area yet skewed concerning the ice thickness data that was particular to a vessel's path. Therefore, this work aims to present a quick and precise approach for estimating the high bow stresses experienced by oil tankers along a given path. Most designs incorporate univariate characteristic values, while this study advocates a bivariate reliability approach for a safer and better design.

A mutation operator self-adaptive differential evolution particle swarm optimization algorithm for USV navigation.

To keep the global search capability and robustness for unmanned surface vessel (USV) path planning, an improved differential evolution particle swarm optimization algorithm (DePSO) is proposed in this paper. In the optimization process, approach to optimal value in particle swarm optimization algorithm (PSO) and mutation, hybridization, selection operation in differential evolution algorithm (DE) are combined, and the mutation factor is self-adjusted. First, the particle population is initialized and the optimization objective is determined, the individual and global optimal values are updated. Then differential variation is conducted to produces new variables and cross over with the current individual, the scaling factor is adjusted adaptively with the number of iterations in the mutation process, particle population is updated according to the hybridization results. Finally, the convergence of the algorithm is determined according to the decision standard. Numerical simulation results show that, compared with conventional PSO and DE, the proposed algorithm can effectively reduce the path intersection points, and thus greatly shorten the overall path length.

Imaging the Subsurface Using Acoustic Signals Generated by a Vessel

The acoustic wavefield originating from a vessel has historically not been considered as a source of signal in the imaging of marine seismic data and is therefore treated as a source of noise. In this work, the feasibility of acquiring seismic data without an active source and instead using the acoustic wavefield generated by a vessel for imaging the subsurface has been investigated. There are areas around the world where the use of active marine seismic sources is not permitted throughout the year, or only permitted during short time periods. In such areas, acquiring seismic data using the acoustic signals generated by a vessel as a source may be an alternative. Using a vessel as a seismic source may also offer a low cost and low impact 4D monitoring solution with an opportunity for much more frequent acquisition of time lapse data especially over permanent receiver installations. This work demonstrates that it is possible to obtain very high-resolution seismic images of the shallow subsurface by using acoustic signals generated by a vessel. This outcome is due to the broadband signals that the vessel generates combined with the fact that these signals are generated continuously while the vessel is moving, allowing for extremely dense source-side sampling along the vessel path.

An unsupervised image segmentation algorithm for coronary angiography

Computer visual systems can rapidly obtain a large amount of data and automatically process them with ease. These characteristics constitute advantages for the application of such systems in the automatic analysis of medical images, as well as in processing technology. The precision of image segmentation, which plays a critical role in computer visual systems, directly affects the quality of processing results. Coronary angiographs feature various background colors, complex patterns, and blurry edges. The image areas containing blood vessels cannot be precisely segmented through regular methods. Therefore, this study proposed an unsupervised learning algorithm that uses regional parameter expansion (RPE). This method was derived from the flood fill algorithm, which can effectively segment image areas containing blood vessels despite a complex background or uneven light and shadow. An optimal cover tree (OCT) algorithm was proposed for the establishment of coronary arteries and the estimation of vessel diameter. Through the region growing method, spanning trees were used to record the cover length of adjacent connections, thereby establishing vessel paths, and the length can be used to track changes in vessel diameter.

Soft Actor–Critic based active disturbance rejection path following control for unmanned surface vessel under wind and wave disturbances

The research of unmanned surface vessel (USV) path tracking has always been of great interest in maneuvering control. In the course of navigation, a USV will inevitably be affected by disturbances such as wind and waves, or the USV’s operating conditions will suddenly change. To overcome the impact of these disturbances or uncertainties is of great significance to its safe and efficient navigation. In this paper, the three-degree-of-freedom (DOF) manipulative modeling group (MMG) model is used to express the dynamic characteristics of a USV so that its motion process is closer to its real states. We consider the underactuated control problem of using rudder angles to realize the tracking control of the USV’s position and heading angle. To this end, we propose a guidance law and design a linear active disturbance rejection controller (LADRC), and the stability of the guidance law and controller are analyzed. This paper combines control and decision-making in reinforcement learning and proposes an LADRC control strategy based on soft actor–critic (SAC) algorithm to realize the adaptive control of USV path tracking. The effectiveness of the proposed method is verified by line and circle under wind and wave environments.

Development of Stereo NIR-II Fluorescence Imaging System for 3D Tumor Vasculature in Small Animals.

Near-infrared-II (NIR-II, 1000–1700 nm) fluorescence imaging boasts high spatial resolution and deep tissue penetration due to low light scattering, reduced photon absorption, and low tissue autofluorescence. NIR-II biological imaging is applied mainly in the noninvasive visualization of blood vessels and tumors in deep tissue. In the study, a stereo NIR-II fluorescence imaging system was developed for acquiring three-dimension (3D) images on tumor vasculature in real-time, on top of the development of fluorescent semiconducting polymer dots (IR-TPE Pdots) with ultra-bright NIR-II fluorescence (1000–1400 nm) and high stability to perform long-term fluorescence imaging. The NIR-II imaging system only consists of one InGaAs camera and a moving stage to simulate left-eye view and right-eye view for the construction of 3D in-depth blood vessel images. The system was validated with blood vessel phantom of tumor-bearing mice and was applied successfully in obtaining 3D blood vessel images with 0.6 mm- and 5 mm-depth resolution and 0.15 mm spatial resolution. The NIR-II stereo vision provides precise 3D information on the tumor microenvironment and blood vessel path.

Incidence of Aberrant Right Subclavian Artery in General Population

Objective: The existence of an anomalous right subclavian artery is the most significant aortic arch defect. Dysphagia, wheezing, stridor, and other symptoms may occur if this vessel pressures the neighbouring structures. The goal of this study is to find out how common ARSA is based on CT scans of the thorax and neck (plain and contrast).
 Method: Between January 1st and December 31st, 2020, 1122 patients had CT Thorax/neck scans, and the data were evaluated. The origin of the ARSA, the vessel's path, and the Kommerell diverticulum were all assessed. We looked at the literature to see how important ARSA is in clinical practise.
 Results: ARSA was found in eight of 1122 patients. All of the ARSAs in these eight individuals began at the posterior part of the aortic arch and travelled via the retroesophageal path to the thoracic outlet. All eight ARSA were found in the front part of the thoracic vertebral bodies, from the first to the fourth.
 Conclusion: Other clinical symptoms such as dysphagia, dyspnea, retrosternal discomfort, cough, and weight loss must be differentiated from compression of surrounding tissues by an abnormal right subclavian artery.

Determination of optimal control of a vessel diesel engine during non-stationary traffic regimes

The high pressure fuel system is the fundamental system that forms the indicator of the minimum fuel consumption per unit of the vessel's path. The calculation of the optimal control of the vessel complex with the main diesel engine is performed according to the criterion of the minimum fuel consumption per unit path at a given average velocity of the vessel. The propulsion of a vessel with a main diesel engine is described by equations. The equations contain a significant number of parameters, the reduction of which is performed by introducing dimensionless quantities, followed by bringing the equations into dimensionless forms. This made it possible to present a solution to the optimal control law for the main vessel diesel engine as part of the vessel complex. Optimal control of the vessel complex under stormy navigation conditions has been investigated. The calculations of the control law of the vessel complex, which ensure the movement of the vessel with the maximum average velocity in conditions of stormy navigation, are presented. It is determined that the established law of control of the vessel complex ensures the minimum fuel consumption per mile at a given average velocity of its movement. The influence of a high-pressure fuel system on the optimal control of a vessel diesel engine has been investigated. Thus, the calculated studies indicate that for all values of the parameters of the vessel complex according to the law of control of the fuel system Ф=а+b∙C2(τ), they give fuel savings up to 6% per unit of way in comparison with the law of control of the vessel complex Ф=а+b∙(c1(τ)/c2(τ)). The obtained ratios during modeling and optimal control of the main diesel engine of the vessel complex allow using the dynamic programming method to analyze the fuel consumption per unit path with optimal control compared to the corresponding constant control