PE-A* Algorithm for Ship Route Planning Based on Field Theory

Abstract

Route planning is the key to safe, efficient and intelligent navigation of maritime traffic. Autonomous route planning is a complex optimization problem, which requires both global route planning and local collision avoidance. In this paper, we propose an optimization algorithm which can consider both global route planning and local collision avoidance. Firstly, nonlinear constraint optimization models of obstacle limitation, safe water depth limitation and ship steering limitation are established. Then, the PE-A * algorithm and route planning framework are proposed by using potential energy field to accurately express the environment. Finally, the safety and feasibility of the route planned by PE-A * algorithm are discussed through simulation experiments. Simulation results show that PE-A * algorithm can realize both global route planning and local collision avoidance, and the safety and feasibility of the planned route are greatly improved. From the perspective of potential energy, this work proposes an automatic route planning algorithm and establishes a flexible mathematical model, which can add fuel consumption, time and other related engineering requirements into the model to plan the optimal route meeting the requirements.INDEX TERMS Ship, potential energy, A * algorithm, route planning.

TPS-Genetic Algorithm for Real-Time Sailing Route Planning based on Potential Field Theory

“…Similarly, this theory can accurately express the changes of Marine meteorology in the course of ship navigation and plan the navigation route. Liu et al [26] carried out route planning in the coastal waters of the Yangtze Estuary of China based on potential field theory, which further proved that the theory could be used for ship route planning.…”

Ship Global Traveling Path Optimization via a Novel Non-Dominated Sorting Genetic Algorithm

“…Silveira et al [6] and Wang et al [7] made targeted improvements to the Dijkstra algorithm, although there is still more room for improvement. Liu et al proposed a PE-A* algorithm, which uses the potential energy field to express the environmental field to achieve the effect of global planning and local collision avoidance [8]. Addressing this problem, Shin et al proposed an improved A-star algorithm, which can avoid the limitations of the initial A-star algorithm [9].…”

A Ship Route Planning Method under the Sailing Time Constraint

“…Since the ship's navigational task often has complex influences, planning a ship route is often regarded as a pathfinding problem, which assumes that the ship's speed or main engine power is maintained at a fixed value and only the ship's geographical path is considered as a variable. In this way, route optimization has been researched based on various methods or algorithms, such as the modified isochrones method [7], dynamic programming [8][9][10], Dijkstra's algorithm [11], and the A* algorithm [12], and some evolutionary algorithms such as the genetic algorithm [13,14] and the swarm algorithm [15] have also been used. However, for ocean-going ships, the meteorological and marine environment changes rapidly, and it is not easy to maintain a stable and uniform speed for a long time on the route.…”