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A modified HEART – 4M method with TOPSIS for analyzing indonesia collision accidents

Bowo L. P., Prilana R. E., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2020

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Vol. 14. no. 3

751--759

EN

Human error is recognized as the most common factor that causes maritime accidents. The human error assessment and reduction technique (HEART) is a human reliability assessment (HRA) that has been widely applied in various industries. Furthermore, the HEART – 4M method has been proposed to assess maritime accidents. The HEART – 4M method can clearly define the relationship between man, machine, media, and management factors and the human error. However, the calculation process to determine the weight of every selected error-producing condition (EPC) suffers from the uncertainty of the assessor's estimation in practical applications, which may affect the objectivity of its result. In this study, a modification of the HEART – 4M method with the technique for order preference by similarity to ideal solution (TOPSIS) is proposed. TOPSIS is a multi-criteria decision making (MCDM) tool. This study aims to develop the HEART – 4M method to make it more comprehensive and objective when assessing maritime accidents. First, the parameter of the generic task is determined as in the conventional HEART method. Second, the causal factors are converted to the suitable EPC – 4M, and there are four classification factors for the 38 standard EPCs, which are divided into man, machine, media, and management factors. Third, the TOPSIS is applied to handle the problems of interdependencies and interaction among EPC – 4M and the uncertainty that exists in the assessor´s judgment. The proportion effect of each EPC – 4M is determined through TOPSIS by considering the correlation among EPC – 4M. Finally, thirteen collision data obtained from the National Transportation and Safety Committee of Indonesia are assessed to apply the proposed method.

2

Developing generative adversarial nets to extend training sets and optimize diiscrete actions

Zhang R. L., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2019

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Vol. 13. no. 4

875--880

EN

This study proposes the use of generative adversarial networks (GANs) to solve two crucial problems in the unmanned ship navigation: insufficient training data for neural networks and convergence of optimal actions under discrete conditions. To achieve smart collision avoidance of unmanned ships in various sea environments, first, this study proposes a collision avoidance decision model based on a deep reinforcement learning method. Then, it utilizes GANs to generate enough realistic image training sets to train the decision model. According to generative network learning, the conditional probability distribution of ship maneuvers is learnt (action units). Subsequently, the decision system can select a reasonable action to avoid the obstacles due to the discrete responses of the generated model to different actions and achieve the effect of intelligent collision avoidance. The experimental results showed that the generated target ship image set can be used as the training set of decision neural networks. Further, a theoretical reference to optimize the optimal convergence of discrete actions is provided.

3

The Development of Marine Accidents Human Reliability Assessment Approach: HEART Methodology and MOP model

Bowo L. P., Mutmainnah W., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2017

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Vol. 11, no. 2

249--254

EN

Humans are one of the important factors in the assessment of accidents, particularly marine accidents. Hence, studies are conducted to assess the contribution of human factors in accidents. There are two generations of Human Reliability Assessment (HRA) that have been developed. Those methodologies are classified by the differences of viewpoints of problem-solving, as the first generation and second generation. The accident analysis can be determined using three techniques of analysis; sequential techniques, epidemiological techniques and systemic techniques, where the marine accidents are included in the epidemiological technique. This study compares the Human Error Assessment and Reduction Technique (HEART) methodology and the 4M Overturned Pyramid (MOP) model, which are applied to assess marine accidents. Furthermore, the MOP model can effectively describe the relationships of other factors which affect the accidents; whereas, the HEART methodology is only focused on human factors.

4

Conversion timing of seafarer’s decision-making for unmanned ship navigation

Zhang R. L., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2017

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Vol. 11, no. 3

463--468

EN

The aim of this study is to construct an unmanned ship swarms monitoring model to improve autonomous decision-making efficiency and safety performance of unmanned ship navigation. A framework is proposed to determine the relationship between on-board decision-making and shore side monitoring, the process of ship data detection, tracking, analysis and loss, and the application of decision-making algorithm, to discuss the different risk responses of specific unmanned ship types under various latent hazard environments, particularly in terms of precise conversion timing in switching over to remote control and full manual monitoring, to ensure safe navigation when the capability of automatic risk response inadequate. This frame-work makes it easier to train data and the adjustment for machine learning based on Bayesian risk prediction. It can be concluded that the automation level can be increased and the workload of shore-based seafarers can be reduced easily.

5

Causative chaindifference for each type of accidents in Japanese Maritime Traffic Systems (MTS)

Mutmainnah W., Bowo L. P., Sulistiyono A. B., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2017

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Vol. 11, no. 3

489--494

EN

Causative chain (CC) is a failure chain that cause accident as an outcome product of the second step of MOP model, namely line relation analysis (LRA). This CC is a connection of several causative factors (CF), an outcome product of first step of MOP model, namely corner analysis (CA). MOP Model is an abbreviation from 4M Overturned Pyramid, created by authors by combining 2 accident analysis models. There are two steps in this model, namely CA and LRA. Utilizing this model can know what is CF that happen dominantly to the accidents and what is a danger CC that characterize accidents in a certain place and certain period. By knowing the characteristics, the preventive action can be decided to decrease the number of accident in the next period. The aim of this paper is providing the development of MOP Model that has been upgraded and understanding the characteristics of each type accident. The data that is analyzed in this paper is Japanese accidents from 2008 until 2013, which is available on Japan Transportation Safety Board (JTSB)’s website. The analysis shows that every type of accidents has a unique characteristic, shown by their CFs and CCs. However, Man Factor is still playing role to the system dominantly.

6

Ship Behavior Analysis for Real Operating of Container Ships Using AIS Data

Gao X., Makino H., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2016

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Vol. 10, no. 2

213--220

EN

The aim of this paper is to understand the real activity and operating situation of container ships in order to improve navigation efficiency. The study focused on the navigation for an entire ship voyage to understand the real activity of container ships using the historical ship navigation based on Automatic Identification System (AIS) data, which is possible so as to unveil the characteristics of real ship activity. The analysis considers ship voyages in the Seto Inland Sea and its oceanic waters, which are the primary traffic routes for container transportation particularly for China, Japan, and South Korea. The results of this study can be used to improve the efficiency of container ships and develop a smoother maritime transportation.

7

A Study of Social Networks for Maritime Education and Training

Takimoto T., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2016

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Vol. 10, no. 3

409--414

EN

This study analyzes the role played by social networks in maritime education and training. The objective of this study is to investigate the shortage of seafarers in maritime global transportation, as mentioned by the BIMCO. The authors divide the processes of maritime education and training into two categories: “Maritime educational institute” and “Maritime Company.” These are not systematically connected but are found in the processes between social networks; it has the social networks to both. Therefore, teaching staff members, in their roles as job advisors in “Maritime educational institutes,” use social networks in conjunction with “Maritime companies.” The teaching staff members communicate with students using these processes. The teaching staffs are the carriers in regard to how these processes are related. This study surveyed aspects of “personality” and “social networks” pertaining to teaching staffs and quantitatively analyzed the processes related to social networks.

8

4M Overturned Pyramid (MOP) Model Utilization: Case Studies on Collision in Indonesian and Japanese Maritime Traffic Systems (MTS)

Mutmainnah W., Furusho M.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2016

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Vol. 10, no. 2

257--264

EN

4M Overturned Pyramid (MOP) model is a new model, proposed by authors, to characterized MTS which is adopting epidemiological model that determines causes of accidents, including not only active failures but also latent failures and barriers. This model is still being developed. One of utilization of MOP model is characterizing accidents in MTS, i.e. collision in Indonesia and Japan that is written in this paper. The aim of this paper is to show the characteristics of ship collision accidents that occur both in Indonesian and Japanese maritime traffic systems. There were 22 collision cases in 2008–2012 (8 cases in Indonesia and 14 cases in Japan). The characteristics presented in this paper show failure events at every stage of the three accident development stages (the beginning of an accident, the accident itself, and the evacuation process).

9

Mental workload of the VTS operators by utilising heart rate

Kum S., Furusho M., Duru O., Satir T.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

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2007

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Vol. 1, no. 2

145--151

EN

This study clarifies the mental workload of VTS Operator; by understanding their characteristics during carrying out their task, with a physiological index. The objective is to determine VTS Operators’ mind stress that might trigger any human error based on their mental workload during their watches. For this purpose, Heart Rate Monitor (HRM) is utilized as physiological index. The VTS Operators fitted the HRM and all of them have experience as a Master Mariner. During the all experiments, their heart rates and behaviours were recorded on the Event Record Form based on the time scale. After getting the heart rate variability, it is matched with the events, and then Operators’ behaviour is understood as the mental workload due to such kinds of events. Furthermore, these workloads include the Operators’ mind stress and their decisions under these circumstances. This study provides the fundamental information for understanding the VTS Operators’ characteristics.