Chihiro Nishizaki

Questionnaire Survey for Adapting Common Performance Conditions to Marine Accidents

An officer of the watch (OOW) is a qualified person with the knowledge and capabilities required to safely navigate a ship. However, many collisions occur that are caused by human errors in navigation. Eighty-four percent of collision accidents are caused by inadequate lookout. It is estimated that such accidents can be prevented if the OOW performs fully to his or her knowledge and capabilities. Many factors can reduce the OOWs reliability, so it can be difficult to specify the cause of an accident. If the cause of an accident can be specified, efficient measures can be taken. This study utilizes a human reliability analysis method to analyze marine accidents. The cognitive reliability and error analysis method (CREAM) divides background factors into nine common performance conditions (CPCs). However, the manner in which CREAM is used in the nuclear industry is not applicable to the maritime domain since the working conditions are very different. To facilitate using CREAM to analyze marine accidents, we sought advice from specialists about redefining the CPCs and their descriptions. We then adapted the dependencies between the CPCs to marine accidents based on a questionnaire survey administered to OOWs. This paper reports the results of the questionnaire survey. In addition, we discuss the dependencies between the CPCs adapted for marine accident analysis. These results confirm the essence and character of the maritime industry.

A Method for Quantifying the Risks of Human Error from Experiments with the Ship Bridge Simulator

Why do vessels collide with each other even though the Navigation Officer on Watch (OOW) keeps a lookout? This study aims to discover what causes human error of the OOW. For this purpose we conducted a series of experiments and surveys. This paper reports on results of two experiments and the present state of marine accidents in Japan. The first experiment objective is to find out the correlation between the angle of an approaching target, and error in overlook (cognitive error), and to put forward a method for estimation of Human Error Probability (HEP) from experiments using a ship bridge simulator. The next experiment objective is to find out the correlation between behavior and error in judgment (decision error). The author found that the OOW tends to overlook a target that is approaching from the port side. The other result shows that the notice time is negatively correlated with the amount of time using binoculars. This study concludes that a method for quantifying the risks of human error from experiments is necessary for implementing highly reliable Human Reliability Analysis.

Development of a method for marine accident analysis with bridge simulator

The ship operation is system of systems consisted of various systems such as ship management, navigational support, cargo handling and port facility. The marine accidents cause considerable damage to logistics and environment. So, it is effective to ensure the safety of the ship operation. The purpose of this paper is to propose an analytical method for marine accident analysis with the bridge simulator and to confirm the effectiveness of the method. By this analytical method, it has shown to find out the most important factor in navigational watch to avoid marine accident.

A Characteristic of a Navigator's Situation Awareness for Crossing Ships

Many ship collisions have been caused by a navigator’s error in the situation awareness (SA) of the navigator. In congested sea areas, navigators classify ships on the basis of different priority levels. For safety measures against ship collision, it is imperative for navigators to recognize the ships with high priority levels. In previous study, navigators’ SA was measured in a ship maneuvering simulator using the Situation Awareness Global Assessment Technique (SAGAT). From the results of the previous study, we proposed a new risk category, named as “attention area,” that covers ships with high priority level in the SA of navigators. However, the extent of data for navigators’ SA was limited. Therefore, the purpose of this study is to confirm the validity of the category using additional data of navigators SA. In this study, the validity of the proposed category was confirmed, and a limit line surrounding ships with high priority levels was identified. In addition, it was evident that the category was able to detect ships with high priority level around the time when the collision avoidance was performed. http://www.transnav.eu the International Journal on Marine Navigation and Safety of Sea Transportation Volume 11

Situation awareness and mental workload of navigator in ship maneuvering simulator

Evading navigation in heavy marine traffic area required high navigation skill for navigator. Ship maneuvering simulator training was effective to improve their navigation skill. For the effective training, it was important that subject appropriately recognized ships that had collision risk. In order to measure navigators situation awareness in simulator training, situation awareness global assessment technique was useful. However, in the case of ship maneuvering simulator training, accuracy of the measured data was insufficient. In order to clarify the reason for insufficient accuracy, this study measured navigators situation awareness and mental workload in ship maneuvering simulator. As a result, this paper indicated that subjects who got appropriate tension during the simulation run had appropriate situation awareness.

A study on application to marine accident of human reliability analysis method

The purpose of this study was to perform quantitative evaluation of human error in marine accidents by post-hoc analysis using the human reliability analysis (HRA) method. Since most marine accidents are caused by human error, it is important to identify which human errors are most important in marine accidents. In the quantitative evaluation of human error, we used the Technique for Human Error Rate Prediction (THERP) as one of the HRA methods. Based on the results of the event tree analysis of a marine accident, THERP was performed. In conclusion, it was found that it is possible to apply THERP to the analysis of human error in marine accidents.

Error Detection in the Navigational Watch Based on the Behavior Analysis of Navigators

Poor lookouts, i.e. one of errors in situation awareness, are pointed out as the major cause of collisions of ships, through investigations of collision accidents. In order to evaluate safety measures for preventing collisions caused by poor lookouts, it is necessary to understand background factors, so called “contexts”, of errors in situation awareness regardless of occurrence of collisions. The purpose of this study is to point out the possible significant contexts, using a navigator’s situation awareness model. As a result, the authors point out that one of the possible significant contexts is a problem on judgment of priority levels of other ships with regard to attention.

A method for feature extraction and classification of marine radar images

There are ship images (target) and non-ship images (noise) on radar images. In order to obtain other ship information from radar images, it is necessary to select and acquire ship images on radar images. Ship images are selected and acquired by navigation officers based on their observation skill and experience. The future purpose of this study is to automatically detect ship images on the radar. Therefore, in this paper, we propose the method for dividing ship images from non-ship images by the image processing and the cluster analysis using radar raster images. Many image feature points were extracted by the image processing using radar raster images. As a result of the cluster analysis using these image feature points, it is possible to detect about 99.8% ship images from radar raster images. However, there were many cases that non-ship images were classed as ship images. Therefore, the accuracy rate of cluster analysis results in this study was about 83%. In other words, it was possible to fairly determine about 83% images in this study.

Development of a method for marine accident analysis with concepts of PRA.

There are a lot of marine accidents caused by human factors. The experiment using bridge simulator is effective for analysis of the human factor. However, the analytical approach for the navigational behavior by the experiment with bridge simulator has not been established yet. The purpose of this paper is to propose an analytical approach by introducing concepts of Probabilistic Risk Assessment (PRA) and the experiment using bridge simulator that can find out the important factor to avoid marine accidents. As a result of experiments and the analysis, it is clearly important that the officers judged the necessary of the constant lookout for dangerous targets. Finding the important factor of avoiding marine accident, this analytical approach is effective.