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http://dx.doi.org/10.7840/KICS.2011.36B.3.248

Bayesian Collision Risk Estimation Algorithm for Efficient Collision Avoidance against Multiple Traffic Vessels  

Song, Byoung-Ho (조선대학교 컴퓨터통계학과)
Lee, Keong-Hyo (목포대학교 정보산업연구소)
Jeong, Min-A (목포대학교 컴퓨터공학과)
Lee, Sung-Ro (목포대학교 정보전자공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.36, no.3B, 2011 , pp. 248-253 More about this Journal
Abstract
Collision avoidance algorithm of vessels have been studied to avoid collision and grounding of a vessel due to human error. In this paper, We propose a collision avoidance algorithm using bayesian estimation theory for safety sailing and reduced risk of collision accident. We calculate collision risk for efficient collision avoidance using bayesian algorithm and determined the safest and most effective collision risk is predicted by using re-planned with re-evaluated collision risk in the future(t=t'). Others ship position is assumed to be informed from AIS. Experimental results show that we estimate the safest and most effective collision risk.
Keywords
Collision avoidance; Bayesian; Collision Risk; DCPA; TCPA;
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