• Journal of Navigation and Port Research
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• v.31 no.4
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• pp.295-307
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• 2007

The statistics of Korean Maritime Safety Tribunal and Japan Marine Accidents Inquiry Agency shows that the major muses of collision at sea are Improper lookout and Non-compliance with marine traffic rules. Those two muses are occupying more than 70% of collision, and it's clear that those muses are undoubtedly closely related to simple human error. In this paper we tried to find out the root muses of this kind of human error of OOWs(officers on watch) through risk identification method and studied how to tackle them via risk control theory. In conclusion, the measures studied in this paper could be applied to help OOWs avoid their own human error as well as be used in shipping company for their fleets' safety management.

• Journal of the Korean Institute of Navigation
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• v.12 no.1
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• pp.71-84
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• 1988

For traffic proceeding in random directions on a plane surface the frequency of collision, if no avoiding action in taken ,is approximately proportional to the square of the traffic density and directly proportional to the size and speed of the ship, Avoiding is normally taken and the rte of collisions is therefore also governed by additional factors such as the visibility, the effectiveness of the collisionavoidance rules, the competence of personnel or watchkeeping attitude, the maneuverability of the ship and the efficiency of radar and other equipments. From the viewpoint of watchkeeper who is responsible for maneuvering, watchkeeping attitude such as lookout and action to avoid collision is the most controllable factor among those mentioned above. In practice, according to the investigation of the institution of marine courts, about 50% co collisions occurred is caused by disorbedience to steering and sailing rules of international regulations for preventing collision at sea including lookout. So we classify the process of collisions with first sight of another ship , assessment of risk of collisions and action to avoid collisions and make a factural survey about lookout and action to avoid collisions from the point on "time" and " distance", namely relationship among ship's size, speed, first sight time of another ship, action to avoid collisions ,and distance from sight of another ship to collision occurred. According to the results of the actual survey , we come to conclude that most of collisions occurred are due to improper lookout and ineffective action to avoid collision which means time lag from first sight of another ship to time of action taken to avoid collision is relatively long. is relatively long.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.31-39
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• 2000

Cellular Phone use while driving is one of the critical causes of traffic accident by falling the driver into the improper lookout and inattention situations by disturbing the driving behaviors and by increasing the driver's mental workloads. These days, therefore, governments in many countries are trying to Prohibit the cellular Phone use while driving by the law focused on the hand-held type of cellular phone. This Paper investigated the impacts on the hands-free cellular Phone use while driving to the drivers Performance among normal and two different level of secondary task driving conditions in the urban of Japan. As the results, quantitative differences of drivers eye movement, subjective mental workload, steering wheel angle entropy, and cognitive Performance of secondary tasks were compared between straight and curve (right turn) section for each driving condition.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.139-145
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• 2004

It is well known that human errors is involved in most of maritime accidents. For the purpose of reducing the influence of human elements on maritime activities, it is necessary to identify the human unsafe acts in those activities. The commonly used methods in identification of human unsafe acts are maritime accident statistics or case analysis. With the statistics data, people could roughly identify what kinds of unsafe acts or human errors have played active role in the accident, however, they often neglected some active unsafe acts while overestimated some mini-unsafe acts because of the inherent shortcoming of the methods. There should be some more accurate approaches for human error identification in maritime accidents. In this paper, the application of technique called grey relational analysis (GRA) into the identification of human unsafe acts is presented. GRA is used to examine the extent of connections between two digits by applying the, methodology of departing and scattering measurement to actual distance measurement. Based on the statistics data of maritime accidents occurred in Chinese waters in last 10years, the relationship between the happening times of maritime accidents and that of unsafe acts are established with GRA. In accordance with the value of grey relational grade, the identified main human unsafe acts involved in maritime accidents are ranked in following orders: improper lookout, improper use of radar and equivalent equipment, error of judgment, act not in time, improper communication, improper shiphandling, use of unsafe speed, violating the rule and ignorance of good seamanship. The result shows that GRA is an effective and practical technique in improving the accuracy of human unsafe acts identification.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.315-323
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• 1997

Driving is a complex vigilance task that includes improper lookout, excessive speed and inattention. The primary objective of this research is to detect driver drowsiness so that the driver can be alerted to an impending traffic accident in performance. We developed the automatic detection and warning system during drowsy driving. A drowsiness detection system must be able to monitor driver status and detect the detrimental changes of a driver performance. Eyeblink has been found to be a reliable factor of drowsiness detection in earlier studies. As an additional parameter, we also considered the yawning which often occurs in a low vigilance state and predicts the drowsy state. We used a computer vision method to extract the eyeblink and yawning in the face image sequences. When the drowsy state was detected, the driver was refreshed by alarming device and menthol scent generator after deciding the warning level by fuzzy logic. For the evaluation of our system, we measured the physiological parameters such as EOG and EEG. The results indicated that it is possible to detect and alert the driver drowsiness temporarily or continuously by using our system.