Vessels are found frequently operating under the Automatic Identification System (AIS) ‘Not Under Command’ (NUC) option near ports and close to shores in order to report their manoeuvre status to nearby traffic. When asked if they are under any kind of restriction regarding their engines or steering, they often answer that they are just drifting or waiting for the pilot or shipowner's orders. The question that arises is this: “Are these vessels really under an NUC situation or can the AIS Navigational Status menu adapt to the different circumstances of navigation?”.

The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

Managing the transit vessel traffic in the Strait of Istanbul is a highly complex operation since vessels, weather and water conditions, and a set of regulations affect its operation significantly. At the present time, the Vessel Traffic Services (VTS) operators manage the traffic based on some fundamental rules. After discussions with the VTS, in this report, we present a mathematical formulation of the scheduling process currently in place and validate it by comparing its results with scheduling decisions made by the operators in some days of 2005. The results are highly promising. The fundamental philosophy of the algorithm is to schedule the vessels with highest waiting time first while giving priority to large vessels carrying dangerous cargo. Our goal has been to incorporate the algorithm into a simulation model designed to be used for risk analysis purposes. The proposed algorithm can be slightly altered and used for traffic scheduling in other waterways as well.

Currently Vessel Traffic Service (VTS) does not have enough technical capability to monitor a crowded surveillance area to maintain safety. Without an efficient alerting system, many marine accidents have occurred due to operator oversight. In this article, a new fuzzy logic method is proposed to add vessel collision avoidance capability to VTS/AIS systems for all potential collision ships in the surveillance area. Starting from the VTS standpoint and integrating AIS data into the Marine Geographic Information System (MGIS) as a platform, the calculations of ship domain and ship inertial force are utilized to generate models of a guarding ring and danger index. By this means, a precise prediction of collision time and position can be achieved using a marine GIS spatial analyst module. The proposed method is able to enhance the VTS operator's decision-making abilities by providing a collision avoidance alerting system.

A version of this paper was first presented at the European Navigation Conference 2006, held under the auspices of the RIN at Manchester on 8–10 May 2006.

AIS is the most recent example of a major globally-introduced maritime navigation system. During its evolution, introduction and early in-service life, it has aroused a lot of negative comment. The basis for this negativity is examined, particularly in the light of the real experience that is now being gained by users of the system. The evolution of the AIS concept through the relevant international bodies – IMO, ITU, IALA and IEC – is discussed, together with the type of problems encountered during its introduction. Many of the problems would have been ameliorated if there had been better communication to users of the system. It is argued that the complexity of the system really required mandatory training to be undertaken, in parallel with the installation of the new equipment.

The aviation-shipping analogy cannot be used as an argument for a decrease in the need for maritime pilotage. The increasing complexity and upsizing of modern ships, in combination with a vast variety in ship types, economic maximisation, crewing and technical standards, lead to marginal ship operations that require specialist knowledge and skill. On the other hand, modern commercial aircraft have very standardised equipment and operating procedures and they approach and land at airports which also use standard radio-navigation aids and procedures.

This paper outlines the design of a Vessel Traffic Management and Information System (VTMIS) for the Turkish Straits and taking this as an example shows how modelling and simulation may aid safe and efficient navigation of vessels through waterways which are narrow and winding with changing currents and are therefore difficult to navigate and prone to accidents. Ship Handling and Vessel Traffic Flow simulation models and Hyrographic Prediction model are described and the simulation trials conducted under different traffic and environment conditions are discussed to show the role that these prediction and simulation programmes can play in preventing marine casualities in different waterways, which may result in loss of human lifes and property and contamination of the environment.