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.
Vessel traffic flow is a key parameter for channel-through capacity and is of great significance to vessel traffic management, channel and port design and navigational risk evaluation. Based on the study of parameters of characteristics of vessel traffic flow related to channel-through capacity, this paper puts forward a brand-new mathematical model for one-way channel-through capacity in which parameters of channel length, vessel arrival rate and velocity difference in different vessels are involved and a theoretical calculating mechanism for the channel-through capacity is provided. In order to verify availability and reliability of the model, extensive simulation studies have been carried out and based on the historical AIS data, an analytical case study on the Xiazhimen Channel validating the proposed model is presented. Both simulation studies and the case study show that the proposed model is valid and all relative parameters can be readjusted and optimized to further improve the channel-through capacity. Thus, all studies demonstrate that the model is valuable for channel design and vessel management.
The e-navigation strategy of the International Maritime Organization (IMO) aims to improve the safety of maritime traffic by increasing cooperation between several maritime stakeholders. The COSINUS (Bolles et al., 2014) project contributes to such a strategy by enabling an automated data exchange (observations, routes and maneuver plans) between ship-side and shore-side navigational systems, developing useful sensor fusion applications upon the new information available from data exchange and introducing new Human Machine Interfaces (HMIs) to support the users of navigation systems. The project shows potential for improvement in maritime traffic safety by ensuring continuous awareness to all participants involved through sensor fusion applications, i.e. by providing all participants (mobile and stationary navigation systems) with a complete view at all times. These applications include detection of critical situations like radar shadowing areas, early and accurate prediction of potential collisions or closest point of approach (CPA) based on the exchanged routes, and improving the accuracy of radars by ensuring high quality data for obstructed or far away routes. The new HMI concepts introduced within the COSINUS project aim at highlighting critical maritime traffic situations. Thus, the users of such navigation systems supported with COSINUS facilities can easily detect such critical situations and react efficiently to avoid collisions, possible crowded areas and inefficient routes.
Ship collision is a hazardous event within the chain of maritime transport. Collisions may result in human losses, adverse economic consequences, and environmental damages causing significant impact to local societies and related activities. A major factor in any risk analysis concerning ship collisions is the probability of these collisions occurring. The purpose of this study is to assess the probability of ship-to-ship collision in the Aegean Sea. The basic concept of the developed model is to (statistically) simulate traffic flow in the area of interest and determine the collision candidates; this will be implemented in a pilot study in a segment of the Aegean Sea. The input of this effort is based on values that are extracted from statistical analysis of the international fleet in combination with the study of maps depicting traffic flow in the studied area. Hence, it does not employ detailed AIS data. The obtained results are presented and their agreement with actual incidents is discussed in depth. The paper concludes with interesting insights of the aforementioned tasks.
In the maritime domain, the risk is evaluated within the framework of Formal Safety Assessment (FSA), introduced by International Maritime Organization in 2002. Although the FSA has become internationally recognized and recommended method, the definition, which is adopted there, to describe the risk, seems to be too narrow to reflect properly the actual content of the FSA. Therefore this article discusses methodological requirements for the risk perspective, which is appropriate for risk management in the maritime domain with the special attention to maritime transportation systems (MTS). This perspective considers risk as a set encompassing the following: the set of plausible scenarios leading to an accident, the likelihoods of the unwanted events within the scenarios and the consequences of the events. These elements are conditional upon the available knowledge about the analyzed system, and understanding of the system behaviour, therefore these two are inherent parts of risk analysis, and need to be included in the risk description.
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