COLREGs-Compliant Unmanned Surface Vehicles Collision Avoidance Based on Multi-Objective Genetic Algorithm

Abstract

Autonomous ships or Unmanned Surface Vehicles (USV) collision avoidance and path planning problems among multi-vessels are investigated in this paper. Firstly, a modified fuzzy dynamic risk of collision model based on time and space collision risk index is proposed, which is much closer to real ship applications. Then, the fitness functions based on the risk of collision, navigational economy, International Regulations for Preventing Collisions at Sea 1972 (COLREGs) and collision avoidance timing are established respectively to ensure the rationality of ship collision avoidance decisions. Moreover, path planning with global search capability is realized by the multi-objective decision theory combined with a genetic algorithm. The practicability and rationality of the recommended trajectory are guaranteed. Meanwhile, the problem of the non-inferior solution can be addressed by adapting the weight method and the constraint method and the optimized solution of the decision-making system can be achieved finally. Simulation results are further presented to validate the effectiveness of the proposed path planning and collision avoidance methods.

Keywords

• Genetic algorithms
• automatic collision avoidance
• risk of collision
• multi-objective decision making