Abstract:With the development of the maritime economy, sea traffic is becoming more and more crowded, and sea accidents are also increasing. Research on maritime search and rescue decision-making technology cannot be delayed. This paper studies the maritime search and rescue decision algorithm, based on the optimal search theory. It also analyzes three important concepts: Probability of containment (POC), probability of detection (POD), and probability of success (POS) involved in the maritime search and rescue decisio… Show more
“…The samples detected in the simulation are marked in blue, and the POS was calculated using the ratio of the number of detected samples to the total number of samples. For comparison, search areas were also determined by the PSO [20], [21] and MBR [18] [19] methods, which are the most commonly used planning methods. The simulation results are shown in Fig.…”
Section: ) Simulation Results and Discussionmentioning
confidence: 99%
“…Content may change prior to final publication. while the POS of the search areas planned by the TIP, MBR [18] [19], and PSO [20], [21] methods were compared.…”
Section: Simulation Experiments and Analysismentioning
confidence: 99%
“…Agbissoh et al proposed the calculation algorithm of POC and POD and generated the minimum bounding rectangle (MBR) based on survivors' probable locations. Using the cell iterative search method, they determined the optimal search area [18]. In a further study of Agbissoh's work, Bo Ai et al defined the probability of successful search and rescue (POSSAR) and proposed a SAR resource scheduling model based on the genetic simulated annealing algorithm with the goal of maximizing the POSSAR [19].…”
Helicopters are widely used in maritime search and rescue (SAR) missions. To improve the probability of success (POS) of SAR missions, search areas should be carefully planned. However, the search area is usually determined based on the survivors' probable locations at a given moment by existing planning methods, while the effects of the relative motion between the helicopter and the search objects are ignored, possibly leading to a significant decrease in the POS. To minimize the impact of search object motion, a time domain-based iterative planning (TIP) method is proposed in this paper to obtain the optimal search areas. The survivors' probable locations and mean drift direction are updated iteratively, while the probability map is developed by taking survivors' mean drift direction as a reference. Then, the optimal search area is determined by an iterative search method starting from the cell with the highest probability of containment. To evaluate the effectiveness of a search plan, an agent-based simulation environment of a maritime search mission is constructed based on the AnyLogic simulation platform. Taking a capsizing case as an example, the simulation results show that the novel TIP method minimizes the impact of search object motion on the search effectiveness and obtains higher POS values than those obtained by other methods.
“…The samples detected in the simulation are marked in blue, and the POS was calculated using the ratio of the number of detected samples to the total number of samples. For comparison, search areas were also determined by the PSO [20], [21] and MBR [18] [19] methods, which are the most commonly used planning methods. The simulation results are shown in Fig.…”
Section: ) Simulation Results and Discussionmentioning
confidence: 99%
“…Content may change prior to final publication. while the POS of the search areas planned by the TIP, MBR [18] [19], and PSO [20], [21] methods were compared.…”
Section: Simulation Experiments and Analysismentioning
confidence: 99%
“…Agbissoh et al proposed the calculation algorithm of POC and POD and generated the minimum bounding rectangle (MBR) based on survivors' probable locations. Using the cell iterative search method, they determined the optimal search area [18]. In a further study of Agbissoh's work, Bo Ai et al defined the probability of successful search and rescue (POSSAR) and proposed a SAR resource scheduling model based on the genetic simulated annealing algorithm with the goal of maximizing the POSSAR [19].…”
Helicopters are widely used in maritime search and rescue (SAR) missions. To improve the probability of success (POS) of SAR missions, search areas should be carefully planned. However, the search area is usually determined based on the survivors' probable locations at a given moment by existing planning methods, while the effects of the relative motion between the helicopter and the search objects are ignored, possibly leading to a significant decrease in the POS. To minimize the impact of search object motion, a time domain-based iterative planning (TIP) method is proposed in this paper to obtain the optimal search areas. The survivors' probable locations and mean drift direction are updated iteratively, while the probability map is developed by taking survivors' mean drift direction as a reference. Then, the optimal search area is determined by an iterative search method starting from the cell with the highest probability of containment. To evaluate the effectiveness of a search plan, an agent-based simulation environment of a maritime search mission is constructed based on the AnyLogic simulation platform. Taking a capsizing case as an example, the simulation results show that the novel TIP method minimizes the impact of search object motion on the search effectiveness and obtains higher POS values than those obtained by other methods.
“…By investigating the frequent occurrence of accidents on the Bohai Sea, Agbissoh OTOTE et al optimized the decision-making algorithm for maritime search and rescue schemes, improved calculation methods for probability of containment (POC), probability of detection (POD), and probability of success (POS) models, and increased the search and rescue success rate to a certain extent [17]. After extracting and visualizing the environmental data from the European Meteorological Center, they used the Net Common Data Form (NetCDF) data model to integrate and manage marine dynamic parameter data, while improving the multi-dimensional expression and analysis capabilities of marine dynamic parameters.…”
Section: Overview Of the Articles In The Special Issuementioning
In this paper, we introduce how to identify, rank, evaluate, and respond to risks based on intelligent information processing, providing new ideas and research directions for sustainable emergency management. First, we discuss the contributions and deficiencies of the existing research that have informed the development and launch of this Special Issue and, second, we provide an overview of the three articles included. In addition, this article introduces this particular Special Issue, not only to complement the somewhat lacking body of related literature, but also to help contemporary companies deal with issues related to sustainable emergency management based on intelligent information processing.
“…The completion degree of the SAR area is then used to evaluate the overall progress of the SAR mission. The different search modes used in SAR are shown in Figure 4 and include the extended square, sector, parallel line, and creeping sweep search patterns (Agbissoh Otote et al, 2019). Figure 4.Search modes used in maritime search and rescue (SAR).…”
In maritime search and rescue (SAR), commanders need to understand the task execution efficiency of each SAR unit in real time to improve the overall efficiency of SAR efforts. This study proposes a method to evaluate the progress of maritime SAR missions using automatic identification system (AIS) data. First, the positioning accuracy of the AIS data was improved according to the relationship between position, speed, and course. Second, the historical track of the SAR ship was used to generate the SAR completion area based on a line buffer algorithm. The SAR completion area and SAR mission area were then superimposed to determine the overall progress of the SAR mission. The proposed method has been deployed within the SAR software on-board Haixun01 (China's largest and most advanced large-scale cruise rescue ship) since 2017 and has played an important role in devising SAR strategies and tracking mission progress, during several SAR actions.
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