Abstract
In the process of ship collision avoidance decision making, steering collision avoidance is the most frequently adopted collision avoidance method. In order to obtain an effective and reasonable steering angle, this paper proposes a decision-making method for ship collision avoidance based on improved cultural particle swarm. Firstly, the ship steering angle direction is to be determined. In this stage, the Kalman filter is used to predict the ship’s trajectory. According to the prediction parameters, the collision risk index of the ship is calculated and the situation with the most dangerous ship is judged. Then, the steering angle direction of the ship is determined by considering the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). Secondly, the ship steering angle is to be calculated. In this stage, the cultural particle swarm optimization algorithm is improved by introducing the index of population premature convergence degree to adaptively adjust the inertia weight of the cultural particle swarm so as to avoid the algorithm falling into premature convergence state. The improved cultural particle swarm optimization algorithm is used to find the optimal steering angle within the range of the steering angle direction. Compared with other evolutionary algorithms, the improved cultural particle swarm optimization algorithm has better global convergence. The convergence speed and stability are also significantly improved. Thirdly, the ship steering angle direction decision method in the first stage and the ship steering angle decision method in the second stage are integrated into the electronic chart platform to verify the effectiveness of the decision-making method of ship collision avoidance presented in this paper. Results show that the proposed approach can automatically realize collision avoidance from all other ships and it has an important practical application value.
Highlights
In the process of ship collision avoidance decision making, steering collision avoidance is the most frequently adopted collision avoidance method
In order to obtain an effective and reasonable steering angle, this paper proposes a decision-making method for ship collision avoidance based on improved cultural particle swarm
Compared with other evolutionary algorithms, the improved cultural particle swarm optimization algorithm has better global convergence. e convergence speed and stability are significantly improved. irdly, the ship steering angle direction decision method in the first stage and the ship steering angle decision method in the second stage are integrated into the electronic chart platform to verify the effectiveness of the decision-making method of ship collision avoidance presented in this paper
Summary
In the practice of ship collision avoidance, it is still inseparable from the subjective decision of the driver, that is, to manually complete the collision avoidance task based on experience. By changing the offset to the autopilot’s heading angle, a limited set of alternative control behaviors can be obtained, and whether these alternative control behaviors meet the COLREGs or not is determined and the relevant collision risk is evaluated to find the best control behavior This method mainly considers the situation of one-to-one ships and does not include the treatment of priority avoidance of the most dangerous target ship in case of multiple target ships (two or more). Aiming at the above problems, this paper proposes a collision avoidance decision method based on improved cultural particle swarm optimization, which combines Kalman filtering algorithm, fuzzy distribution algorithm, CPSO algorithm, and COLREGs. e main contributions of the method in this paper are as follows:. Electronic Chart Platform Integration and Display. is paper uses electronic charts as a display and verification platform and integrates the steering angle decision method based on ship collision risk and the optimal steering angle decision method based on improved cultural particle swarm algorithm into the electronic chart platform. e platform can dynamically display the status and trajectory of all ships in real time, which can show the experimental results of collision avoidance between own ship and target ship and verify the feasibility of the method
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