Despite the tremendous efforts of maritime organizations to achieve a safe and secure maritime transportation system, the losses through maritime accidents and incidents are still increasing. This paper analyzes the spatial distribution of maritime accidents occurring from January 1, 2002, to December 31, 2011, based on the Marine Casualties and Incidents module of the Global Integrated Shipping Information System. The geographic information system, an effective and efficient tool for spatial analysis with high visualization, is used to carry out the analysis. Hot-spot analysis of maritime accidents identifies the hot spots. Buffer analysis is used to calculate accidents that occurred in coastal areas. Finally, the following two important results are obtained from the analysis. First, the identification of hot spots reveals the area around the United Kingdom as the area with the greatest number of accidents and the coastal areas around East Asian countries (such as China, Japan, and South Korea) and the Mediterranean Sea as the areas with the next highest number of accidents. These results compare well with a previously published paper. Second, maritime accidents may not frequently occur in the open sea; however, accidents frequently happen in coastal areas, with 51.1% of the total accidents happening within 25 mi of the continents and 62.2% within 50 mi.

The maritime system has a high level of uncertainty, which makes it difficult to assess its safety. This paper proposes an improved formal safety assessment (FSA) method based on fuzzy logic and employing if–then rules, which model the qualitative aspects of human knowledge and reasoning processes. A fuzzy expert system is then designed to address FSA's risk assessment step. An investigation is performed to gain expert knowledge, which is essential to building this system. An example that assesses the safety of Chinese maritime passages is used to illustrate the methodology. The method is effective in the solution of problems with high uncertainty. Finally, suggestions are given to enhance the level of safety.

As a scarce strategic resource, crude oil is closely intertwined with national strategies, global policies, international relationships, and national competence. Unbalanced demand and production of crude oil lead to huge amounts of import and export activities. Marine transportation accounts for about 80% of the total oil transport because of the low cost. However, it also incurs an extremely high risk in doing so. Therefore, it is significantly important to assess and control risk effectively in crude oil transportation. In risk assessment, uncertainty evaluation becomes a key variable that cannot be neglected. Previous cases show that fuzzy logic can be applied to manage uncertainty. However, the use of fuzzy logic usually encounters two difficulties: determination of the membership functions and establishment of the reference machine. This paper presents a dynamic fuzzy logic model (DFLM) that can improve the stated problems. The DFLM is developed from fuzzy theory and an incident causation model. The model is examined with a hypothetical case. Preliminary results show that the model reduces the time of risk assessment and increases the reliability of evaluation.

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