# Abnormal Ship Behavior Detection Based on AIS Data
## 1 Introduction  
Maritime transportation is favored and being rapidly developed due to its advantages of large freight volumes, low cost, low energy consumption, and low required investment. With the continuous innovation of shipbuilding technology, there are more than 4 million ships sailing within the coastal waters of China every year [1]. Maritime transport undertakes 90% of the work of world trade and transportation [2]. Therefore, it can be said that the development of seaborne trade is a barometer of the development trend of the global economy [3]. At the same time, China's national policy vigorously supports the development of the maritime transport industry. In 2013, President [PERSON] proposed the cooperation initiatives to build the \"New Silk Road Economic Belt\" and the \"21 st Century Maritime Silk Road\" [4]. In 2016, China also issued the \"Outline of the Development Plan for the Yangtze River Economic Belt\" to promote the orderly and free flow of economic factors and build a new bidirectional corridor based on land and sea with the outside world. Therefore, the supervision of maritime traffic is crucial. However, with the continuous development of the maritime shipping industry and continuous application of the integrated system of various marine services, the number of marine traffic accidents is also increasing. According to the \"Transportation Safety Production Accident Report (2019)\", a total of 197 marine traffic accidents occurred during this period, resulting in the deaths of 115 people and the loss of up to 12 Gt of goods. Marine traffic accidents usually result from abnormal ship-related behaviors. In order to better supervise maritime safety, one needs to detect abnormal ship behaviors. In order to ensure safety in navigation, the AIS base station came into being. International Convention for Safety of Life at Sea (SOLAS) regulation V/19 stipulates that all ships of 300 gross tonnage and above engaged in international voyages, cargo ships of 500 gross tonnage and above not engaged in international voyages, and all passenger ships (regardless of size) should be fitted with automatic identification systems (AISs). The requirement came into effect for all ships on 31 December 2004 [5]. An AIS is a self-reporting information system mainly designed for collision avoidance that uses VHF radio information to track and monitor ship movements by exchanging position, heading, and speed information with other AIS-equipped ships and AIS base stations in the vicinity [6]. There are 27 categories of AIS message types, which can be divided into three types: static information, dynamic information, and voyage-related information [7]. However, this study focuses on the use of the dynamic information and static information of ships to further explore the law of ship behavior. The static attributes include the vessel's IMO number, vessel name, Maritime Mobile Service Identity (MMSI), callsign number, and size and type of the vessel. The dynamic attributes include the ship position, time stamp, speed over ground (SOG), course over ground (COG), and other information [8]. Meanwhile, vessels have different punctuation intervals due to differences in static information, dynamic information, and voyage-related information during the course of their journeys. The AIS system provides data support for the analysis and modeling of maritime traffic and enhances the feasibility of research into abnormal behavior detection for ships. Ship behavior is not the specific behavior of a ship but refers to the mode and law of similar actions of ship groups, which not only depend on human consciousness, thinking, decision making, and manipulation but are also affected by the characteristics of the ship and the surrounding environment [9]. Existing research has not effectively combined the characteristics of ship behavior to discriminate abnormal patterns.