Sailing status recognition to enhance safety awareness and path routing for a commuter ferry

Abstract

This paper suggests a framework about how log data are used to develop a classifier to recognise the sailing status of a commuter ferry, which, in turn, serves as a tool of safety awareness. Several sailing scenarios are defined under the expertise’s interpretation based on log data. A classifier is developed by support vector machine algorithm to recognise different scenarios. The classifying precision is getting improved as the database getting larger. Heat maps are drawn statistically to obtain the likelihood site of each sailing status. Contour maps are drawn by interpolation according to heat maps. Based on contour maps, two evaluation items are proposed to reflect the safety level. The safety level term is used for optimising the control. The established classifier has a recognition precision over 96 percent. A path following simulation is executed to verify the effectiveness of the safety level for enhancing sailing safety.