Helicopter maritime search area planning based on a minimum bounding rectangle and K-means clustering

Helicopters are widely used in maritime Search and Rescue(SAR) missions. To ensure the success of SAR missions, search areas need to be carefully planned. With the development of computer technology and weather forecast technology, the survivors’ drift trajectories can be predicted more precisely, which strongly supports the planning of search areas for the rescue helicopter. However, the methods used to determine the search area based on the predicted drift trajectories are mainly derived from the continuous expansion of the area with the highest Probability of Containment(POC), which may lead to local optimal solutions and a decrease in the Probability of Success(POS), especially when there are several subareas with a high POC. To address this problem, this paper proposes a method based on a Minimum Bounding Rectangle and Kmeans clustering(MBRK). A silhouette coefficient is adopted to analyze the distribution of the survivors’ probable locations, which are divided into multiple clusters with K-means clustering. Then,probability maps are generated based on the minimum bounding rectangle of each cluster. By adding or subtracting one row or column of cells or shifting the planned search area, 12 search methods are used to generate the optimal search area starting from the cell with the highest POC in each probability map. Taking a real case as an example, the simulation experiment results show that the POS values obtained by the MBRK method are higher than those obtained by other methods,which proves that the MBRK method can effectively support the planning of search areas and that K-means clustering improves the POS of search plans.

Evaluation method for helicopter maritime search and rescue response plan with uncertainty

Helicopter plays an increasingly significant role in Maritime Search and Rescue(MSAR),and it will perform MSAR mission based on response plans when an accident occurs.Thus the rationality of response plan determines the success of MSAR mission to a large extent.However,with the impact of many uncertainty factors,it is difficult to evaluate response plans comprehensively before performing them.Aiming at these problems,an evaluation framework of helicopter MSAR response plan named UMAD is proposed in this paper,which reveals the influence mechanism of uncertainty factors based on Multi-Agent method and analyzes the mission flow based on Discrete Event System(DEVS)method.Furthermore,the evaluation criterion and indicators of response plan are extracted from the aspects of safety and effectiveness.Meanwhile,the Monte Carlo method is adapted to calculate the probability distribution and robustness of response plan comprehensive result.Finally,in order to illustrate the validity of this method,it is discussed and verified by an application example of evaluating multiple response plans to the same MSAR scenario.The results show that this method can analyze the influence of uncertainty more systematically and optimize response plans more comprehensively.