Ship route planning in the pirate area via hybrid probabilistic roadmap algorithm within the context of the Maritime Silk Road

Abstract

The frequent occurrence of pirate accidents along the Maritime Silk Road has seriously affected the safety of ships. To guarantee navigation safety in pirate activity area, we present a hybrid probabilistic roadmap (HPRM) algorithm for ship route planning. Our HPRM algorithm consists of the improved learning phase and the enhanced exploration phase. Firstly, to improve the utilization of sampling points, the sampling point reset (SPR) function is introduced to generate new sampling points to replace the sampling points in the dangerous area. Secondly, to reduce the number of ship turns, the Douglas–Peucker (D–P) algorithm is utilized to extract the key waypoints (KWP) for generating the optimized route. Finally, the Euler spiral fitting is applied to smooth the route. Numerical cases verified that the ship route planned via the HPRM algorithm is shorter and smoother. This study is conducive to guarantee the safety of ship navigation in the pirate area and enhance ship navigation efficiency, which is of great practical significance for the advancement of the Maritime Silk Road Initiative.