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Verification of ship's trajectory planning algorithms using real navigational data

Lazarowska A.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2019

Vol. 13, no. 3

559--564

The paper presents results of ship's safe trajectory planning algorithms verification. Real navigational data registered from a radar with an Automatic Radar Plotting Aid on board the research and training ship Horyzont II were used as input data to the algorithms. The algorithms verified in the presented research include the Ant Colony Optimization algorithm (ACO), the Trajectory Base Algorithm (TBA), the Visibility Graph-search Algorithm (VGA) ant the Discrete Artificial Potential Field algorithm (DAPF). Details concerning data registration and exemplary results obtained with the use or real navigational data are introduced and summarized in the paper. Presented results prove the applicability of proposed algorithms for solving the ship's safe trajectory planning problem.

A competitive multipopulation evolutionary algorithm for ship trajectory planning

Dziedzicki K., Łebkowski A., Śmierzchalski R.

Prace Naukowe Politechniki Warszawskiej. Elektronika

2008

z. 165

67-76

Determining the optimum trajectory for a ship between its current position and the assumed target point, done taking into account navigational situations which the ship is to face when covering this trajectory, was the subject of numerous publications but has not been finally solved yet. The authors propose to determine the optimum and safe ship trajectory using a competitive multipopulation evolutionary algorithm. The proposed algorithm will also allow the trajectory to be corrected depending on a current navigational situation, for instance the appearance of collision threat. Practical application of the algorithm would considerably relieve navigator's work, and contribute to the increase of safety at sea and reduction of ship operation costs.