Search Results (36)

Ship berthing operations are inherently challenging for maritime vessels, particularly within restricted port areas and under unfavorable weather conditions. Contrary to autonomous open-sea navigation, autonomous ship berthing remains a significant technological challenge for the maritime industry. Lidar and optical camera systems have been deployed as auxiliary tools to support informed berthing decisions; however, these sensing modalities are severely affected by weather and light conditions, respectively, while cameras in particular are inherently incapable of providing direct range measurements. In this paper, we introduce a comprehensive, Radar-Based Berthing-Aid Dataset (R-BAD), aimed to cultivate the development of safe berthing systems onboard ships. The proposed R-BAD dataset includes a large collection of Frequency-Modulated Continuous Wave (FMCW) radar data in point cloud format alongside timestamped and synced video footage. There are more than 69 h of recorded ship operations, and the dataset is freely accessible to the interested reader(s). We also propose an onboard support system for radar-aided vessel docking, which enables obstacle detection, clustering, tracking and classification during ferry berthing maneuvers. The proposed dataset covers all docking/undocking scenarios (arrivals, departures, port idle, and cruising operations) and was used to train various machine/deep learning models of substantial performance, showcasing its validity for further autonomous navigation systems development. The berthing-aid system is tested in real-world conditions onboard an operational Ro-Ro/Passenger Ship and demonstrated superior, weather-resilient, repeatable and robust performance in detection, tracking and classification tasks, demonstrating its technology readiness for integration into future autonomous berthing-aid systems. Full article

The growing popularity of Personal Light Electric Vehicles (PLEVs), such as e-scooters, has revolutionized urban mobility by offering compact, cost-effective, and environmentally friendly transportation solutions. However, safety concerns, including inadequate infrastructure, poor protective measures, and high accident rates, remain critical challenges. This paper presents the design and development of an innovative self-balancing microvehicle under the H2020 LEONARDO project, which aims to address these challenges through advanced engineering and user-centric design. The vehicle combines features of monowheels and e-scooters, integrating cutting-edge technologies to enhance safety, stability, and usability. The design adheres to European regulations, including Germany’s eKFV standards, and incorporates user preferences identified through representative online surveys of 1500 PLEV users. These preferences include improved handling on uneven surfaces, enhanced signaling capabilities, and reduced instability during maneuvers. The prototype features a lightweight composite structure reinforced with carbon fibers, a high-torque motorized front wheel, and multiple speed modes tailored to different conditions, such as travel in pedestrian areas, use by novice riders, and advanced users. Braking tests demonstrate deceleration values of up to 3.5 m/s², comparable to PLEV market standards and exceeding regulatory minimums, while smooth acceleration ramps ensure rider stability and safety. Additional features, such as identification plates and weight-dependent motor control, enhance compliance with local traffic rules and prevent misuse. The vehicle’s design also addresses common safety concerns, such as curb navigation and signaling, by incorporating large-diameter wheels, increased ground clearance, and electrically operated direction indicators. Future upgrades include the addition of a second rear wheel for enhanced stability, skateboard-like rear axle modifications for improved maneuverability, and hybrid supercapacitors to minimize fire risks and extend battery life. With its focus on safety, regulatory compliance, and rider-friendly innovations, this microvehicle represents a significant advancement in promoting safe and sustainable urban mobility. Full article

Navigation in offshore wind farm (OWF) areas is essential for construction, maintenance, safety, and traditional activities like fishing. However, the presence of OWFs extends to sea routes, negatively impacting maritime transport economics. This paper examines navigational risk indicators in the vertical and horizontal planes of the ship domain for three representative vessels navigating under different hydrometeorological conditions within the location of a proposed offshore wind farm in the Polish sector of the Baltic Sea. The study compares three types of domain parameters defined by the PIANC guidelines, Coldwell’s two-dimensional model, and Rutkowski’s three-dimensional model. The analysis includes navigational hazards located ahead of the ship’s bow and astern from the aft, as well as keeping under-keel and over-head clearance. Besides the main numerical indicators of navigational risk estimated for obstacles on the port and starboard sides, the study emphasizes the importance of such additional factors. The primary objective of this paper is to identify the ship types that can navigate and fish safely in proximity to and within the OWF area. The analysis employs hydrometeorological data, mathematical models, and operational data derived from maritime navigation and maneuvering simulators. This comprehensive approach aims to enhance maritime safety in OWF areas. Full article

In dynamic environments with continuous variability, such as those affected by typhoons, ship path planning must account for both navigational safety and the maneuvering characteristics of the vessel. However, current methods often struggle to accurately capture the continuous evolution of dynamic obstacles and generally lack adaptive exploration mechanisms. Consequently, the planned routes tend to be suboptimal or incompatible with the ship’s maneuvering constraints. To address this challenge, this study proposes a Space–Time Integrated Q-Learning (STIQ-Learning) algorithm for dynamic path planning under typhoon conditions. The algorithm is built upon the following key innovations: (1) Spatio-Temporal Environment Modeling: The hazardous area affected by the typhoon is decomposed into temporally and spatially dynamic obstacles. A grid-based spatio-temporal environment model is constructed by integrating forecast data on typhoon wind radii and wave heights. This enables a precise representation of the typhoon’s dynamic evolution process and the surrounding maritime risk environment. (2) Optimization of State Space and Reward Mechanism: A time dimension is incorporated to expand the state space, while a composite reward function is designed by combining three sub-reward terms: target proximity, trajectory smoothness, and heading correction. These components jointly guide the learning agent to generate navigation paths that are both safe and consistent with the maneuverability characteristics of the vessel. (3) Priority-Based Adaptive Exploration Strategy: A prioritized action selection mechanism is introduced based on collision feedback, and the exploration factor $ϵ$ is dynamically adjusted throughout the learning process. This strategy enhances the efficiency of early exploration and effectively balances the trade-off between exploration and exploitation. Simulation experiments were conducted using real-world scenarios derived from Typhoons Pulasan and Gamei in 2024. The results demonstrate that in open-sea environments, the proposed STIQ-Learning algorithm achieves reductions in path length of 14.4% and 22.3% compared to the D* and Rapidly exploring Random Trees (RRT) algorithms, respectively. In more complex maritime environments featuring geographic constraints such as islands, STIQ-Learning reductions of 2.1%, 20.7%, and 10.6% relative to the DFQL, D*, and RRT algorithms, respectively. Furthermore, the proposed method consistently avoids the hazardous wind zones associated with typhoons throughout the entire planning process, while maintaining wave heights along the generated routes within the vessel’s safety limits. Full article

Independent living is a central goal for people with disabilities, and the accessibility of the home environment plays a key role in achieving it. In particular, circulation areas within the household are essential to ensure autonomous and safe mobility. Although regulations guide the design of accessible housing, they do not always account for the specific needs of users. This study proposes a method for evaluating the design of universally accessible housing (UAH) through virtual reality simulations, with an emphasis on circulation areas. The Design Science Research Methodology (DSRM) was used to structure the study, guiding the development of an immersive virtual environment that integrates a housing model designed according to physical accessibility standards established by Chilean regulations. The simulation recreated everyday situations related to independent living, assessing indicators such as collisions with environmental elements, the time required to perform specific tasks, and the difficulty of maneuvering a wheelchair. The results show that the use of virtual reality enables the early identification of accessibility barriers from the end-user perspective, allowing design adjustments before construction and contributing to more inclusive and user-centered planning. Full article

Novel and practical methods are always sought across all disciplines; within bioaerosol research, portable, lightweight, and low-cost sampling pumps are few and far between. Fungal spores, key components of bioaerosols, have attracted attention due to their negative effects on human populations, agricultural systems, and ubiquitous nature. In terms of spatial scales, fungal spores across vertical gradients are frequently overlooked and in cases where atmospheric samples are collected, they are often a large distance away from the ground, occurring hundreds or thousands of meters into the atmosphere, which also requires substantial expenses for specialist apparatus. Here, we have utilized a drone and low-cost equipment to produce a new sampling method that can efficiently collect fungal spores and bridge the gap between ground sampling and atmospheric sampling, and sample in areas such as forest canopies or at building rooftop heights, in which planes, helicopters, or other UAVs may not be able to safely or practically maneuver. Additionally, we have created a novel approach to utilizing a drone for bioaerosol sampling during rain events, which, to our knowledge, is the first of its kind, opening up the possibilities for much needed comparisons of fungal spores in varying weather conditions. Full article

The autonomous operation of a device or a system is one of the many vital tasks that need to be achieved in many areas of industry. This is also true for maritime transport. This paper introduces an approach developed in order to achieve the autonomous operation of a ship in a port. A safe trajectory was calculated with the use of the Ant Colony Optimization (ACO) algorithm. The ship motion control was based on two controllers: the master overriding trajectory controller (OTC) and the slave low speed controller based on the Linear Matrix Inequalities (LMI) method. The control object was the model of a Very Large Crude Carrier Blue Lady. The results of our simulation tests, which show the safe trajectories calculated by the ACO algorithm and executed by the ship using the designed controllers (OTC and LMI), are presented in this paper. The results present maneuvers executed by the Blue Lady ship when at port. The area where the tests were conducted is located in the Ship Handling, Research and Training Center of the Foundation for Shipping Safety and Environmental Protection on the Lake Silm in Kamionka, Poland. Full article

Lane graphs are very important for describing road semantics and enabling safe autonomous maneuvers using the localization and path-planning modules. These graphs are considered long-life details because of the rare changes occurring in road structures. On the other hand, the global position of the corresponding topological maps might be changed due to the necessity of updating or extending the maps using different positioning systems such as GNSS/INS-RTK (GIR), Dead-Reckoning (DR), or SLAM technologies. Therefore, the lane graphs should be transferred between maps accurately to describe the same semantics of lanes and landmarks. This paper proposes a unique transfer framework in the image domain based on the LiDAR intensity road surfaces, considering the challenging requirements of its implementation in critical road structures. The road surfaces in a target map are decomposed into directional sub-images with X, Y, and Yaw IDs in the global coordinate system. The XY IDs are used to detect the common areas with a reference map, whereas the Yaw IDs are utilized to reconstruct the vehicle trajectory in the reference map and determine the associated lane graphs. The directional sub-images are then matched to the reference sub-images, and the graphs are safely transferred accordingly. The experimental results have verified the robustness and reliability of the proposed framework to transfer lane graphs safely and accurately between maps, regardless of the complexity of road structures, driving scenarios, map generation methods, and map global accuracies. Full article

Ovarian cancer (OC), the most lethal gynecological malignancy, usually presents in advanced stages. Characterized by peritoneal and lymphatic dissemination, OC necessitates a complex surgical approach usually involving the upper abdomen with the aim of achieving optimal cytoreduction without visible macroscopic disease (R0). Failures in optimal cytoreduction, essential for prognosis, often stem from overlooking anatomical neglected sites that harbor residual tumor. Concealed OC metastases may be found in anatomical locations such as the omental bursa; Morison’s pouch; the base of the round ligament and hepatic bridge; the splenic hilum; and suprarenal, retrocrural, cardiophrenic and inguinal lymph nodes. Hence, mastery of anatomy is crucial, given the necessity for maneuvers like liver mobilization, diaphragmatic peritonectomy and splenectomy, as well as dissection of suprarenal, celiac, and cardiophrenic lymph nodes in most cases. This article provides a meticulous anatomical description of neglected anatomical areas during OC surgery and describes surgical steps essential for the dissection of these “neglected” areas. This knowledge should equip clinicians with the tools needed for safe and complete cytoreduction in OC patients. Full article

Overtaking on a dual-lane road with the presence of oncoming vehicles poses a considerable challenge in the field of autonomous driving. With the assistance of high-definition maps, autonomous vehicles can plan a relatively safe trajectory for executing overtaking maneuvers. However, the creation of high-definition maps requires extensive preparation, and in rural areas where dual two-lane roads are common, there is little pre-mapping to provide high-definition maps. This paper proposes an end-to-end model called OG-Net (Overtaking Guide Net), which accomplishes overtaking tasks without map generation or communication with other vehicles. OG-Net initially evaluates the likelihood of a successful overtaking maneuver before executing the necessary actions. It incorporates the derived probability value with a set of simple parameters and utilizes a Gaussian differential controller to determine the subsequent vehicle movements. The Gaussian differential controller effectively adapts a fixed geometric curve to various driving scenarios. Unlike conventional autonomous driving models, this approach employs uncomplicated parameters rather than RNN-series networks to integrate contextual information for overtaking guidance. Furthermore, this research curated a new end-to-end overtaking dataset, CarlaLanePass, comprising first-view image sequences, overtaking success rates, and real-time vehicle status during the overtaking process. Extensive experiments conducted on diverse road scenes using the Carla platform support the validity of our model in achieving successful overtaking maneuvers. Full article

Factors such as persistent demand growth, expansion project delays, and the rising adoption of renewable energy sources highlight the importance of operating power systems within safe operational margins. The optimal reactive power dispatch (ORPD) seeks to find operating points that allow greater flexibility in reactive power reserves, thus ensuring the safe operation of power systems. The main contribution of this paper is a multi-area and multi-period ORPD (MA-MP-ORPD) model, which seeks the minimization of the voltage deviation in pilot nodes, the reactive power deviation of shunt elements, and the total reactive power generated, all taking into account the operational constraints for each area. The MA-MP-ORPD was implemented in the Python programming language using the Pyomo library; furthermore, the BONMIN solver was employed to solve this mixed-integer nonlinear programming problem. The problem was formulated from the standpoint of the system operator; therefore, it minimizes the variations of critical variables from the desired operative values; furthermore, the number of maneuvers of the reactive compensation elements was also minimized to preserve their lifetimes. The results obtained on IEEE test systems of 39 and 57 buses validated its applicability and effectiveness. The proposed approach allowed obtaining increases in the reactive power reserves of up to 59% and 62% for the 39- and 57-bus test systems, respectively, while ensuring acceptable operation values of the critical variables. Full article

The timely detection and recognizing of distress on an airport pavement is crucial for safe air traffic. For this purpose, a physical inspection of the airport maneuvering areas is regularly carried out, which might be time-consuming due to its size. One of the modern approaches to speeding up this process is unmanned aerial vehicle imagery followed by an automatic evaluation. This study explores the automatic detection of the transverse crack, its dimension measurement, and position determination within the slab on the concrete runway. The aerial image data were obtained from flights at the given altitude above the runway and processed using commercial multi-view reconstruction software to create a dataset for the training, verification, and testing of a YOLOv2 object detector. Once the crack was detected, the main features were obtained by image segmentation and morphological operations. The YOLOv2 detector was tuned with 3279 images until the detection metrics (average precision AP = 0.89) reached sufficient value for real deployment. The detected cracks were further processed to determine their position within the concrete slab, and their dimensions, i.e., length and width, were measured. The automated crack detection and evaluation system developed in this study was successfully verified on the experimental section of the runway as an example of practical application. It was proven that unmanned aerial vehicle imagery is efficient over broad areas and produces impressive results with the combination of artificial intelligence. Full article

One of the components necessary to determine the width of a safe maneuvering area on two-way fairways is a safe passing distance. Existing methods do not consider modern model studies of interactions between passing vessels, additionally, they ignore the influence of the vessel’s position accuracy and navigators’ qualifications. This paper presents a method to determine the passing distance, which is free of the drawbacks of the methods used so far. The proposed method is based on simulation research carried out using an FMBS-type (Full Mission Bridge) simulator. The tests were carried out for three loaded vessels (bulk carrier, tanker, and sea ferry), on four sections of the fairway with different parameters and aids-to-navigation available. The results obtained allowed the modification of the authors’ previous, but still widely used, deterministic–probabilistic MTE (Marine Traffic Engineering) method for determining the width of a safe maneuvering area. Full article

The safe integration of Automated Driving Systems (ADS) into the nation’s on-road transportation system, particularly in rural areas, could vastly improve overall quality of life for a rapidly growing segment of the US population. This paper describes findings from the first half (i.e., three of six phases) of a demonstration project called “ADS for Rural America”. The goal of this project is to conduct a series of demonstrations that utilizes an autonomous shuttle to show how older adults (≥65 years old) could be transported from their rural homes to other locations in rural areas, as well as an urban center. This paper examines older adults’ perceptions of automation before and after riding in an autonomous shuttle and their ratings of anxiety throughout the ride as they experience particular road types and maneuvers. After riding in the shuttle, older adults expressed decreased suspicion, increased trust, and increased reliability of ADS compared to baseline. Older adults reported low levels of anxiety during the 90 min ride in the shuttle. To promote the adoption and acceptance of ADS, older adults should be exposed to this technology. Full article

Navigational channels and approaches to ports may have bends that constitute the specific sailing conditions for ships. A vessel’s entrance into a bend and its safe passing depends on the ship’s position accuracy, turn angle, and internal and external forces influencing the ships, as well as the captain’s or pilot’s experience. In order to assure a ship’s safe navigation under specific conditions, the possibility to measure individual ship movement parameters with the use of special sensors is needed to accurately calculate the ship’s trajectory considering the specific dimensions of ships. Moreover, hydro-meteorological and hydrological limitations for ships with different parameters and maneuverability should be evaluated in advance. The article aims to develop the methodology for calculating ships’ route trajectory in channel bends and approaches to ports under special navigational conditions. The mathematical model that may be used to calculate wind velocity limitations and distance crossed by a ship during maneuvers, depending on the ship’s maneuverability, hydro-metrological, and hydrological conditions, was elaborated. The methodology was verified by the example of a few ships entering specific channel bends. Wind velocity limitations depending on wind direction for the SUEZMAX tanker and other selected types of ships during crossing navigational channel bend near Klaipeda port were calculated. The presented theoretical basis may be used by ships’ captains and pilots who plan and perform operations of vessels’ crossing the approaches to ports and navigational channel bends, as well as by navigational channels designers who plan the channel’s parameters in difficult geographical and navigational conditions. Its application may influence the safety increase of maritime transport in limited or specific areas. Full article