A Method for Ship Route Planning Fusing the Ant Colony Algorithm and the A* Search Algorithm

Abstract

Route planning has always been an essential issue in navigation research and an important manifestation of ship intelligence. In order to get the shortest route that meets the actual navigation requirements, this paper proposes a shortest path planning method based on Automatic Identification System (AIS) data, which establishes a high-precision environment model and combines ant colony algorithm (ACA) and <inline-formula> <tex-math notation="LaTeX">$\text{A}^{\ast} $ </tex-math></inline-formula> search algorithm. We extract the key points from the initial route obtained by the <inline-formula> <tex-math notation="LaTeX">$\text{A}^{\ast} $ </tex-math></inline-formula> search algorithm and then introduce the Bézier curve method to smooth the route to obtain the planned route. This strategy assures that the planned route satisfies the global optimal and actual navigation needs. A bulk carrier is selected for experimental validation, and the experimental results verify the effectiveness of the method proposed in this paper. Compared with the other algorithm, the algorithm proposed in this paper can obtain shorter paths faster and more efficiently when performed.