Pusher tug and barge system (PTBS) can be divided into two parts: an unmanned cargo-stowage part and a manned propelling-power part. While the barge is loading/unloading cargo at a terminal, the pusher tug can uncouple that barge and move to another terminal, and couple another barge to transport the next shipments. This paper examines the possibility of further efficient operation of PTBS for reducing related costs of barge transport in a shuttle service with a relatively short-range distance. We model a pusher tug and barge scheduling problem that can be used to simultaneously determine the optimal operation of pusher tug and barge. Based on numerical experiments, we found that the PTBS reduces the working time of tugs and therefore saves the barge related costs compared to conventional barge system.
In recent years, a car production base globalizes and the transport volume of a finished car is increasing dramatically. There is a vast parking space for storing temporarily export and import and the finished car transshipped in an automobile carrier terminal. In order to realize the loading and unloading in a port smoothly, the operation schedule of a ship and the feature of a terminal layout are grasped. And also this study considers the optimal vehicle arrangement of the finished car, and analyzed the influence on total service time. From the results, it is clear that vehicle arrangement layouts differ in a location region, and it should be considered how to give ship’s berthing location also in the terminal with the small number of berths.
The concept of special circumstances of risk of collision has been frequently used in Japan marine accident inquiry. This is a term used when danger of collision was judged to arise from an innocuous passing due to the action of a ship. No equivalent of this can be found in overseas marine accident inquiry, so it is presumed that the term is a Japanese-specific circumstance in which various sized ships are congested in a narrow sea area. Although this concept has been pointed out and examined before, it is not revealed how it is used.
This paper considers the consistency of judgements of Japan marine accident inquiry and Act on Preventing Collisions at Sea. The investigation of the application of special circumstances of risk of collision in Japan marine accident inquiry was carried out, and the use of this term was examined. The results showed.
In this research, we aim to detect ships sailing around our ship from river navigation images using Faster R-CNN and predict their course. First, we cut out the part of the ship from the learning image and omit the image resizing process of Faster R-CNN. Next, ship detection experiments were carried out from river navigation images by a method for increasing the accuracy of ship detection using time series information. Finally, we reported a method for predicting the path of ships from the position and size of the rectangle containing ships detected after the ship position correction between image frames. The results are summarized as follows:
(1)A data set was created by preprocessing the panoramic images created from river navigation images and the images taken by digital cameras. This dataset makes it possible to omit Faster R-CNN resizing processing and improve processing speed.
(2)The minimum detection rate for ships sailing in rivers was about 40%.
(3)As a result of course prediction, the error angle was 50 ° or less.
Eco-operation with ocean current forecast information leads to energy-saving because it increases the speed over ground and enables less fuel consumption. In 2018, we carried out the Eco-energy project which is subsidy project by Agency for Natural Resources and Energy. In this project, we provided ocean current forecast information to 76 domestic vessels via a tablet, and the captain utilized this information to attempt energy-saving operation. This paper proposes a regression model with statistical test to evaluate the effect of energy-saving operation using ocean current forecast information. As a result, 4 out of 5 ships had an energy-saving operation effect, leading to a fuel efficiency improvement of about 2%.
This study is focused on a maneuverability of a ship driven by POD propulsion systems which is widely used in cruise ships. Although the construction of these ships is not popular in Japan, many ships are coming to Japanese ports, which introduces the necessity to assess the maneuverability and fairway for the safety navigation. However, the maneuverability as well as the reliable prediction method are not sufficient comparing with the conventional propeller-rudder ships. A lot of numerical simulations were provided in the previous researches, however, there was little verification by model tests or full-scale trials.
In this paper, the authors show the results of free-running model tests and investigations of the maneuverability with POD propulsion ships. For the experiments, a compact POD propulsion and steering system has been developed. In the experiments, fin size and shape that is attached on the strut or bottom of POD and the location of propeller were altered. The effects of them on the maneuverability are examined in detail. As the results, it can be confirmed that the course stability and the steering quality are improved by the attachment of the fin. The effects of propeller location are not change in case of the attachment of the fin.
This paper is an examination of the definition of ship in the Maritime Public Law. The systems of the Ship Safety Law will be examined by using coastal non-self-propelled ships excluded from the Ship Law as a matter. The Ship Safety Law allows the ship to enter the coastal state based on the provisions of navigation arear in outside of Japan. Maintaining maritime peace requires demarcating the status of the vessel's maritime law. The argument consideration and examines the current state of domestic and international law, the history of drafting and political background, government documents and prior studies. As a result of verification, there is a discrepancy in the legal system that includes the ship in the framework of the Ship Safety Law. The basis of the system for setting up grounds for establishment of navigation arear in outside of Japan is based on the reciprocity of the “Convention on the International System of Seaports”. Ships that use the system for setting up for the establishment of navigation arear outside of Japan must be legally regulated to exercise the responsibility of the jurisdiction of the Flag State. In summary, we proposed the formulation of a system of jurisdiction that is effective in protecting marine safety and the environment for coastal non-self-propelled ships in Japan.
A survey of newly registered students at KOSEN (National Institute of Technology, NIT) of merchant ships from the academic year 2016 to 2018 was conducted to determine their occupational consciousness. The results showed that 89.4% of the respondents had a job that they were aspiring for their future, with 78.0% aspiring to be seafarers. This is an indication that newly registered students have clear targets before entering the KOSEN (NIT) of merchant ships. The survey respondents with high self-efficacy regarding career decision-making had a clear idea of the occupation they intend making a career out of. The results also showed that the self-efficacy score in relation to career decision-making of the respondents from the KOSEN (NIT) of merchant ships is higher than that of newly registered students of fisheries university and fisheries high schools.
It is necessary to develop a system that reduces the load on the marine traffic control because its work is manual and heavy. In this study, we created a ship behavior prediction model using Recurrent Neural Network (RNN) to explore the possibility of marine traffic control and ship maneuvering support by machine learning. Specifically, we predicted the position and course of a ship that would go through the bend of the Uraga Channel from 5 items (length, width, course, speed and position) and displayed on a map. It shows that the effectiveness of ship behavior prediction by machine learning has been confirmed.
The Sail Training Ship “Kaiwo Maru I” was built in 1930 and retired in 1989. After her retiring, she was moored at Fushiki-Toyama port and permanent preservation of her was decided. Afterward, events such as full-sail exhibition or maritime educational program have been held. And, many ship’s documents, such as Deck log book, Engine log book, Radio log book, some construction documents and so on, have been preserved in the ship. These documents are historical heritage for the field of navigation, shipbuilding, maritime education and so on. So, we tried to create the digital archives of Deck log book. First, we took pictures of the log Book, which had been written at every day for about sixty years and one booklet for one month, by the digital camera. Secondary, we made a list of the booklet of the log Book. Next, we had actual-finding investigation of “Maiden oceangoing voyage to Truck islands”, “Challenging voyage to Bering sea” and “Training voyage at Pacific War”. These investigations find out the possibilities of some maritime education effects.
There are a lot of researches for the prediction of ship movements based on Automatic Identification System (AIS) information for applications such as collision and grounding prevention and sea congestion forecasting. However, most of them are for normal time, and it is also important to detect the sea congestion at the time of disaster in order to support the control of ships to their destinations and to prevent collision. During disaster, it is assumed that ship movements are different from normal. However, there are few available data for the prediction during disaster, which makes it more difficult to improve the accuracy of the prediction. Therefore, we have developed a new model to represent the movement of a ship for the prediction at the time of disaster. In this paper, we evaluate the results of 30 minutes ahead and describe that our model showed more accurate result compared with the rule-based model and machine learning model assumed as the benchmark. In addition, our model reproduced the actual congestion situation in some areas and times by predicting the position of each ship. It is suggested that this model can be applied to the decision-making to solve ship congestion in disaster situations.