Particle swarm optimization-based collision avoidance

Inan T., BABA A. F.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, vol.27, no.3, pp.2137-2155, 2019 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 3
  • Publication Date: 2019
  • Doi Number: 10.3906/elk-1808-63
  • Journal Name: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.2137-2155
  • Keywords: Particle swarm optimization, collision avoidance, collision risk assessment, neural network, fuzzy, NAVIGATION
  • Marmara University Affiliated: Yes

Abstract

Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy logic system to obtain the risk of collision, and a particle swarm optimization algorithm to find the safe and shortest path for collision avoidance.