ABSTRACT:

The authors propose algorithm for the automatic collision avoidance system using fuzzy inference in this paper. DCPA (distance of closest point of approach) and TCPA (time to closest point of approach) are used as parameters for evaluating degree of collision risk which is expressed with collision risk coe_cient CR. Numerical simulations assuming several encounter situations of plural ships in collision risk were carried out to confirm validity of the presented automatic collision avoidance system. The simulation results demonstrate that the algorithm works well for the encounter scenarios.

INTRODUCTION

In order to realize the automatic navigation device which does not need human operation, much information concerning not only own ship but other ships surrounding own ship. Recently precision of positioning using GPS becomes considerably better and discussion about mandatory installation of Automatic Identification System (AIS) for ships are in progress on the International Maritime Organization (IMO). Using these devices, each ship will be able to obtain her own position exactly and also easily derive information about other ship's position, heading, speed and so on. The authors propose algorithm for the automatic collision avoidance system using fuzzy inference in this paper. The automatic collision avoidance system is one of important function comprised in the automatic navigation device and there are a lot of studies about the system (Hara and Hammer, 1993; Hasegawa and Fujita, 1993; Kose et al., 1998; Kijima and Furukawa, 2001; Lee and Rhee 2001). DCPA (distance of closest point of approach) and TCPA (time to closest point of approach) are used as parameters for evaluating degree of collision risk which is expressed with collision risk coe_cient CR. If the course is deemed safe, the course line is kept. If the course line is dangerous, the ship's course is altered to prevent collision.

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