Nautical traffic model based on optimal control
With the development of international trade, the usage of vessels for transportation increases all over the world. It is getting more and more important to find the balance between safety and capacity in busy ports and inland waterways: when measures are taken to increase capacity, usually the safety decreases. Based on Automatic Identification System (AIS) data analysis, we have identified the basic sailing and route choice characteristics of bridge teams. We developed a new maritime traffic model to predict vessel behaviour (speed, course and path) and vessel traffic in order to assess designs of ports and waterways as well as the consequences of maritime traffic management. To this end, vessel behaviour is categorized into a tactical level and an operational level. According to this hierarchy, this new maritime traffic model comprises two parts: the Route Choice Model and the Operational Model. In our research, these two models are developed and further calibrated using AIS data.
1. The AIS system was commonly applied in the last decade. Until now, the data can be used for maritime traffic research is limited. In our research we analyse the data with respect to operational ship behavior as well as path choice.
2. Vessel behavior including its speed, course and path is difficult to predict, since a lot of factors influence vessel behavior, such as waterway’s geometry, human factors and external conditions including wind, visibility and current. In this research we try to combine all these factors in one model.
3. Vessel behavior is determined by the human behavior (the bridge team), which is by definition difficult to simulate. By applying specific mathematical techniques, we aim to include the stochastic of human behavior in the model.
In this research, a new maritime traffic model is developed. This model can be used by the Port authority, port designer, Vessel Traffic Services (VTS) center, shipping company to predict the vessel movement and vessel traffic in ports and inland waterways. This way, these stakeholders can anticipate the growth of vessel flows as well as a change in the fleet composition in their ports and waterways. Similarly, they can optimize maritime traffic management measures.
In addition, it is possible to use this model to investigate vessel traffic by other researchers.
|Start/end date: 20-10-2010 to 29-2-2016 |
Daily supervisor: Winnie Daamen
Promotor: Serge Hoogendoorn, Han Ligteringen