To ensure safe and efficient flight operations, air traffic controllers use flight plans and surveillance systems to track and update flight information for each aircraft, thereby managing overall air traffic. In Japan, by sharing this operational information among relevant stakeholders, we aim to achieve Collaborative Decision Making (CDM) based on System Wide Information Management (SWIM). In particular, during the pre-departure phase, the Calculated Take-Off Time (CTOT) is a key factor for airport time-based management, and sharing this information is essential to realizing SWIM-based Airport CDM (A-CDM). Therefore, it is necessary to clarify how to improve the accuracy of CTOT through real-time information sharing via SWIM. In this paper, we analyze flight operation data at Narita International Airport and identify the factors that affect CTOT accuracy.

In this study, we investigated the potential of high precision GNSS technology to support automatic berthing and pilot-assisted ship control. While some pilots already use commercial ship maneuver visualization software based on RTK-GNSS, the suitability of RTK accuracy for berthing operations remains unclear. To address this, we developed a similar system to measuring maneuver and validated its effectiveness through onboard experiments. The system comprises three RTK-GNSS units with LTE module and a tablet device. The tablet displays real-time distances from the bow, stern, and sides of the ship to the wharf with an accuracy of several centimeters, along with the vessel’s attitude. We present the results of this experiment. Additionally, we propose a method to estimate the position of specific ship-side locations where GNSS antenna installation is problematic. By using two GNSS antennas mounted on the line of bow and stern, combined with IMU-derived attitude data, we estimated the shipside position with a horizontal accuracy under 20 cm during second onboard experiments. The results of this second experiment are also presented in this paper. However, this 20 cm accuracy is based on experimental results from small boat and may differ from the results obtained when the proposed method is implemented on larger vessels.

This study evaluates wind speed and direction biases of the JMA MSM based on shipborne observations at four Japanese coast anchorage areas. Ship-based measurements provide realistic sheltered-sea conditions in sheltered coastal waters and that cannot be captured by land stations. Bias structures were quantitatively decomposed by sea area, wind direction, and wind speed, showing consistent regional patterns closely linked to local geography and wind directional dependence. These results offer fundamental insight for developing region-specific MOS-type statistical correction models that can improve operational wind guidance for safe maritime anchorage.

In maritime traffic volume surveys, ship type identification for large vessels can be conducted regardless of day or night using the Automatic Identification System (AIS), which is mandatory under SOLAS. However, many small vessels operating in coastal waters are not equipped with AIS, making nighttime ship type identification labor-intensive and highly dependent on the subjective judgment of observers.

This study investigates the feasibility of ship type identification from nighttime ship images using artificial intelligence (AI) to improve the efficiency and reliability of coastal traffic surveys. Nighttime ship images were acquired using a highly sensitive camera, and suitable exposure conditions were examined to enable extraction of ship outlines under low-visibility environments. A YOLOX-based object detection model was then trained to classify ship types. Experimental results indicate that ship type identification can be achieved with an average precision exceeding 90% for most ship categories, even when using original dark nighttime images without image enhancement, demonstrating the practicality of AI-based nighttime image analysis for automated ship type identification.

This study proposes a method to estimate vessel positions in a harbor by relating real-world coordinates obtained from RTK-GNSS to image coordinates extracted from video footage through a projective transformation (homography). Unlike conventional approaches that rely on fixed landmarks, the proposed method utilizes the vessel's own trajectory to establish calibration correspondences based on time-synchronized RTK-GNSS measurements and image-based vessel tracking. To ensure robustness against measurement noise, the Random Sample Consensus (RANSAC) algorithm is applied to remove outliers prior to estimating the transformation matrix. Field experiments were conducted by filming vessels navigating within a harbor, and the estimated coordinates were compared with ground truth data from RTK-GNSS. The results demonstrated that the proposed method achieved a practically acceptable level of accuracy for trajectory analysis, with average positional errors ranging from several meters to approximately 20 meters. These findings indicate that the proposed method is effectively applicable to harbor monitoring and maritime traffic surveys without the need for ground control points. Future work will focus on improving robustness under varying environmental conditions and developing real-time processing capabilities.

Proper lookout and collision avoidance decision-making are essential for safe maritime navigation, including remote ship operation. Remote operators must accurately perceive surrounding situations and make appropriate collision avoidance decisions. Previous studies have shown that initial judgments influence subsequent decision-making; however, decision-making characteristics under multiple-vessel monitoring conditions in remote navigation environments have not been sufficiently clarified. This study conducted ship handling simulator experiments assuming remote ship operation and analyzed navigational decision-making under single- and multiple-vessel monitoring conditions. The judgment processes and behavioral choices of participants were examined. The results indicate that the safety of collision avoidance actions depends not only on initial decisions but also on the reassessment of judgments in response to subsequent changes in navigational situations.

These findings provide fundamental insights for the development of training methods for remote operators.

In the Kurushima Kaikyo Traffic Route, a tidal-dependent navigation system is applied, and vessel courses may cross near the entrance during southward tidal flow. In response to collision accidents that occurred in this area, new safety measures, including route designation and removal of a light buoy, were implemented by the Japan Coast Guard on July 1, 2024. This study focuses on the area where these safety measures were implemented and examines their effects on maritime traffic flow by comparing vessel navigation before and after their introduction. AIS data were used to analyze vessel traffic characteristics and track distributions. While no significant changes were observed in the basic traffic characteristics of passing vessels, changes in vessel tracks and course-changing behavior were identified. These results indicate that the new safety measures have influenced vessel navigation patterns in the area.

This study aimed to clarify the decision-making dilemmas faced by crew members of different ranks when ships anchored in port are confronted with an approaching tsunami. Semi-structured interviews were conducted with 30 seafarers including captains, navigational officers, and deck crew, and analyzed using a Grounded Theory Approach, yielding 18 categories. Correspondence analysis was applied to visualize relationships between these categories, crew rank, and vessel characteristics, particularly the requirement for departure assistance.

The results showed that captains were primarily constrained by physical and institutional factors such as the feasibility of unberthing and the availability of support resources, whereas navigational officers and deck crew mainly experienced psychological constraints, including ambiguity in command structures and anxiety under extreme conditions. In addition, uncertainty regarding external support increased decision-making complexity on vessels requiring departure assistance, while the availability of onboard operational personnel played a key role for vessels capable of self-departure.

An ocean going vessel has the Internet commutation apparatus that is also used by costal one when she is ordinary daily working. The configuration of the Internet communication and its apparatus are not provided by IMO and other agency. Those standards were written this data communication might be use on other situation without the Internet. This paper describes latest the International standards and certificates of the internet communication and the radio commutation onboard. The authors confirmed that those international, laws and IMO training model courses do not include any skill and knowledge of Internet and connection. However, latest recommendation should recommend to cyber security to ship management. The authors proposed that create another certificate onboard with Internet connection to daily computing work and onboard device and apparatus shall not IoT but also consist of ordinary electric wiring system without Internet protocol such as current loop, RS485 and differential amplifier.

This study designed a self-directed learning material for special education on fall arrest systems in practical training for seafarers, based on the ARCS motivation model. The reliability and validity of the material were evaluated using the Instructional Materials Motivation Survey (IMMS). The results indicated that the proposed material is potentially effective for self-directed learning among experienced seafarers. However, for application to novice seafarers, it was found necessary to provide alternatives for enhancing "Satisfaction," such as the introduction of digital badges to recognize achievement. Furthermore, the verification of learning outcomes revealed a statistically significant positive correlation between the IMMS motivation scores and rubric-based evaluations. Therefore, it is concluded that the approach to enhancing learner motivation in this material is effective for achieving the final learning objectives as measured by rubric evaluations.

This study investigates the hydrodynamic forces and motion characteristics of a pilot boat operating in close proximity to a large vessel during pilot transfer operations. Despite the high risk of accidents during boarding and disembarking, the complex interaction between two ships in difference length overall under forward speed and contact conditions remains insufficiently understood. In this study, first, full-scale measurements were conducted using five different target vessels to identify motion patterns such as motion, alongside position and angle. Second, captive model tests were performed to quantify the steady hydrodynamic forces acting on the pilot boat. The analysis demonstrated that the yaw moment increases when the pilot boat is positioned at the aft section of the ship’s hull (approximately 1/6 L abaft midship). This phenomenon, driven by the fluctuation of pressure distribution near the stern, explains the operational difficulty. These findings provide data for improving pilotage safety and developing operational guidelines for maneuvering in confined hydrodynamic fields.

Regarding the maneuverability of ships in the IMO, some of the information provided to ship operators is the turning circle at maximum rudder angle, and it is thought that it is difficult to use it as a reference for changing course during normal navigation. Therefore, in this paper, we verified an estimating method for the turning characteristics under normal rudder angles (15° or less) during normal navigation, based on the TK model.

The objective of this study is to conduct a preliminary development of a ship-handling simulator that simulates a Remote Operation Center (ROC), with a view toward future education and training for remote vessel operation. In recent years, research and development on Maritime Autonomous Surface Ships (MASS) has progressed, and operational concepts based on remote monitoring and control are expected to be introduced. However, educational and training environments that inadequately consider the cognitive characteristics for remote operators remain insufficient. This study develops a ROC simulator incorporating a status monitoring function that provides visual and auditory intervention alerts from an Autonomous Navigation System (ANS). The configuration and design concept of the simulator are presented as a foundational step toward future remote operation education and training.