Artificial Intelligence Methods in Safe Ship Control Based on Marine Environment Remote Sensing

Abstract

This article presents a combination of remote sensing, an artificial neural network, and game theory to synthesize a system for safe ship traffic management at sea. Serial data transmission from the ARPA anti-collision radar system are used to enable computer support of the navigator’s maneuvering decisions in situations where a large number of ships must be passed. The following methods were used to determine the safe and optimal trajectory of one’s own ship: static optimization, dynamic programming with neural constraints on the state of the control process in the form of domains of encountered ships generated by a three-layer artificial neural network, and positional and matrix games. Then, computer calculations for the safe trajectory of one’s own ship were carried out using the presented algorithms. The calculations were carried out for an actual navigational situation recorded on a r/v HORYZONT II research/training vessel radar screen under a real navigational situation in the Skagerrak–Kattegat Straits.

Keywords

• environmental remote sensing
• neural network
• game theory
• optimization
• computer simulation