COLREGs Compliant Fuzzy-Based Collision Avoidance System for Multiple Ship Encounters

Assessment of Ship-Overtaking Situation Based on Swarm Intelligence Improved KDE

This paper proposes a data-driven risk assessment model for ship overtaking based on the particle swarm optimization (PSO) improved kernel density estimation (KDE). By minimizing the mean square error between the real probability distribution of the ship overtaking point and the kernel density estimation probability distribution calculated by the current kernel density bandwidth, the longitude and latitude of the ship overtaking point are displayed by the color corresponding to the probability as the cost objective function of the search bandwidth of the algorithm. This can better show the distribution of the overtaking points of channel propagation traffic flow. A probability-based ship-overtaking risk evaluation model is developed through the bandwidth and density analysis optimized by an intelligent algorithm. In order to speed up searching the optimal variable width of the kernel density estimator for ship encountering positions, an improved adaptive variable-width kernel density estimator is proposed. The latter reduces the risk of too smooth probability density estimation phenomenon. Its convergence is proved. Finally, the model can efficiently evaluate the risk status of ship overtaking and provide navigational auxiliary decision support for pilots.

A Quantitative Evaluation Method for Obstacle Avoidance Performance of Unmanned Ship

In response to the urgent need for quantitative evaluation of the obstacle avoidance performance of an unmanned ship, a quantitative evaluation model is established to evaluate quantitatively the obstacle perception performance, static obstacle avoidance performance and dynamic obstacle avoidance performance of an unmanned ship. The base data for calculating are derived from the shore-based database; the evaluation factor layer is evaluated by the cost function method. Based on the established evaluation model, the quantitative evaluation score of the obstacle perception performance of the unmanned ship is obtained by data analysis for the 50 to 100 m buoy and 100 m island obstacle perception test. The quantitative evaluation score of the static obstacle avoidance performance obtained by testing the performance of a single obstacle, continuous obstacle and inflection obstacle is 68.8 points. For buoys as dynamic obstacles, the dynamic obstacle avoidance performance quantitative evaluation score of 64.13 points is obtained by testing the performance of obstacle avoidance in chasing, facing and crossing encounters. The analysis of the test data saved to the database verify the rationality of the quantitative evaluation model, which can provide reference for the quantitative evaluation and improvement of the unmanned ship’s obstacle avoidance performance.