Ship path planning method based on ship trajectory and ant colony algorithm

Abstract

The invention discloses a ship path planning method based on a ship trajectory and an ant colony algorithm, a clustering object is changed from a point to a track segment, information of the track segment relative to a trajectory point, a ship course, a ship speed and the like is reserved, and a clustering result is more accurate during clustering. In similarity measurement, similarity measurement calculation is carried out by adopting more multi-dimensional angles, and four dimensions of a horizontal distance, a vertical distance, a steering angle and a speed are considered. Thus, the overall clustering result is more accurate. According to the method, an improved DBSCAN algorithm is used, information such as the speed and the direction contained in a ship track is reserved, and meanwhile the clustering speed is increased. According to the improved ant colony algorithm provided by the invention, experiments show that compared with the previous ant colony algorithm, the ant colony algorithm suitable for ship route planning provided by the invention improves the convergence speed when solving the problem of ship route planning.

Description

technical field [0001] The present invention relates to the technical field of path planning, in particular to a multi-stop ship path planning method, in particular to a multi-stop ship path planning method based on ship trajectory data and an ant colony algorithm. Background technique [0002] During the actual voyage of the ship, due to the loading and unloading of personnel or cargo, or because of replenishment and other issues, it is necessary to plan multiple stops in the course. The route planning of the ship with multiple stops is based on known information, planning a route from the starting point to the The route with the optimal comprehensive distance (comprehensive distance in terms of safety, cost and time) of each stop on the way. [0003] With the development of shipping technology, the development of Automatic Identification System (AIS system for short) is becoming more and more mature. Today, the vast majority of ships are equipped with AIS systems. Throug...

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Problems solved by technology

[0007] The timeliness of the planned path is not strong, and there is a possibility of path failure; the traditional DBSCAN clustering is easy to lose the comprehensive information of the ship contained in the trajectory, and the number of clusters is large, and the clustering speed is slow; if the precise algorithm is used, the amount of calculation is too large; ant colony There are problems in the algorithm that it is easy to fall into the local optimal solution and cannot continue, and the convergence speed of the algorithm is slow, which affects the overall efficiency and other problems.

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