Marine emergency rescue route planning method, system and equipment and storable medium

Abstract

The invention discloses a maritime emergency rescue route planning method, system and equipment and a storable medium, which can quickly distinguish passable and impassable areas, optimize the planning process, reduce the resource waste, and utilize the Dikstra algorithm to realize the route planning by dividing the nationwide sea area into basic grids and storing the passage, water depth and passable surface information of the grids. Various factors can be comprehensively considered, an optimal rough path is planned from a starting point to an end point, after a path gap is identified, the algorithm is applied again to analyze an optimal refined path, fill a blank and ensure that rescue workers directly reach a target, meanwhile, path segments intersecting with an impassable surface can be judged and automatically removed, an army is prevented from mistakenly entering a dangerous area, and the rescue efficiency is improved. By identifying the gap and planning the refined path, the continuity and integrity of the rescue path are guaranteed, the rescue failure risk caused by the path problem is reduced, in addition, the accurate planning can also reduce unnecessary detour and stay, and smooth rescue action is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of rescue route planning, and in particular to a method, system, device and storable medium for planning an emergency rescue route at sea. Background Art

[0002] Against the backdrop of growing global marine activities, maritime safety issues have become a growing focus of attention. As an important means of responding to maritime emergencies and protecting the lives and property of personnel, the scientific nature and efficiency of maritime emergency rescue route planning are of vital importance. However, current maritime emergency rescue route planning methods have significant defects: (1) Insufficient planning accuracy: Traditional maritime emergency rescue route planning methods are often based on relatively rough geographic information, such as dividing the entire sea area into larger blocks and planning paths based on these blocks. This method ignores the complex traffic conditions in the sea area (such as water depth changes, seabed topography, etc.), resulting in the planned route being suboptimal or even in some cases inaccurate. (1) Inaccessible; (2) Poor adaptability: Existing planning methods are unable to cope with the dynamically changing marine environment. For example, when new impassable areas (such as military exercise areas, warning areas, etc.) appear in the sea, traditional planning methods are often unable to update the path in time, resulting in obstruction of rescue operations; (3) Algorithm efficiency issues: Traditional path planning algorithms have huge computational complexity when dealing with large-scale sea areas, resulting in excessively long planning time and unable to meet the timeliness requirements of emergency rescue; (4) Lack of intelligence: Existing planning methods mostly rely on manual judgment and decision-making, and lack intelligent auxiliary means, which not only increases the difficulty and complexity of planning, but may also lead to subjectivity and uncertainty in planning results. Summary of the invention

[0003] In view of this, the present invention proposes a method, system, device and storable medium for planning a maritime emergency rescue route, which can improve the scientificity and efficiency of maritime emergency rescue route planning.

[0004] The technical solution of the present invention is achieved in this way:

[0005] A method for planning a maritime emergency rescue route, specifically comprising:

[0006] Divide the national sea area into basic grids, the grid information includes whether it is passable, water depth and passable surface, among which grids that are partially passable and partially impassable are set as suspicious grids;

[0007] Receive the latitude and longitude information of the starting point and the end point transmitted by the rescue personnel;

[0008] According to the latitude and longitude information of the starting point and the end point, the Dijkstra algorithm is used to analyze the optimal rough path from the starting point to the end point;

[0009] Determine whether the optimal rough path intersects with the impassable surface, and if so, obtain a set of path segments that need to be removed;

[0010] Subtract the set of path segments that need to be removed from the optimal rough path set to obtain a set of passable path segments;

[0011] identifying a path gap in the set of navigable path segments;

[0012] Using Dijkstra's algorithm to analyze the optimal refinement path in the path gap;

[0013] If the solution set of the optimal refined path is empty, the optimal rough path is the final rescue path. Otherwise, the optimal refined path is concatenated with the optimal rough path, and the concatenated path is the final rescue path.

[0014] As a further optional solution of the method for planning the route for emergency rescue at sea, the optimal rough path from the starting point to the end point is analyzed using the Dijkstra algorithm according to the latitude and longitude information of the starting point and the end point, which specifically includes:

[0015] According to the latitude and longitude information of the starting point and the end point, a corresponding sub-grid is divided in the basic grid;

[0016] Using Dijkstra's algorithm in the subgrid to analyze the optimal rough path from the starting grid to the end grid;

[0017] If there is no solution for the rough path in the optimal rough path, the Dijkstra algorithm is used again to find the optimal rough path after expanding the grid range.

[0018] As a further optional solution of the marine emergency rescue route planning method, the optimal rough path from the starting grid to the end grid is analyzed using the Dijkstra algorithm in the subgrid, specifically including:

[0019] According to the latitude and longitude of the starting point and the end point input by the front end, the sub-grid area containing the starting point and the end point is divided in the basic grid;

[0020] In the divided sub-grid area, Dijkstra algorithm is applied, taking the starting grid as the source point, to calculate the shortest path length to all other grids;

[0021] From the calculated shortest paths, the path to the end grid is selected as the optimal rough path.

[0022] As a further optional solution of the marine emergency rescue route planning method, the Dijkstra algorithm is applied in the divided sub-grid area, taking the starting grid as the source point, and calculating the shortest path length to all other grids, specifically including:

[0023] Step S11, in the divided sub-grid area, with the starting grid as the source point, initialize a distance array, the distance array records the shortest path length from the source point to all other grids, initially, the distance from the source point to itself is set to 0, and the distance from the source point to other grids is set to infinity;

[0024] Step S12: create an unvisited set, and add all grids except the source point to the set;

[0025] Step S13, selecting the grid closest to the source point from the unvisited set as the current grid, and removing it from the unvisited set;

[0026] Step S14: Update the shortest path length from the adjacent grid of the current grid to the source point. If the path from the current grid to the adjacent grid is shorter than the originally recorded path, update the shortest path length of the adjacent grid and set its parent node as the current grid.

[0027] Repeat steps S13 and S14 until the unvisited set is empty, at which point the distance array records the shortest path length from the source point to all grids.

[0028] As a further optional solution of the method for planning a maritime emergency rescue route, the identifying of path gaps in the set of traversable path segments specifically includes:

[0029] Based on the intersection of the optimal rough path and the impassable surface, the gap location is determined;

[0030] The region containing the path gap is meshed to obtain a path gap mesh unit that is smaller than the sub-grid.

[0031] As a further optional solution of the method for planning the route for emergency rescue at sea, the method of using the Dijkstra algorithm in the path gap to analyze the optimal refined path specifically includes:

[0032] Step S21, initializing the distance values ​​of all path gap grid cells that are smaller than the sub-grid, setting the distance value of the starting grid cell to 0, and setting the distance values ​​of other grid cells to infinity;

[0033] Step S22: establish a priority queue for storing the grid cells to be processed, and add the starting grid cell as the first element to the queue;

[0034] Step S23: Take the grid cell with the smallest distance value from the priority queue as the grid cell currently being processed, and update the distance values ​​of its adjacent grid cells;

[0035] Step S24: If the distance value of the adjacent grid cell is updated to be smaller, add it to the priority queue;

[0036] Repeat step S23 and step S24 until the priority queue is empty or the distance value of the end grid cell is updated to a finite value;

[0037] The optimal refinement path is formed by recording the predecessor grid cell of each grid cell and tracing back from the end grid cell to the starting grid cell.

[0038] As a further optional solution of the method for planning the maritime emergency rescue route, the optimal refined path and the optimal rough path are spliced, and the spliced ​​path is the final rescue path, which specifically includes:

[0039] Specifying the endpoints of each optimal refinement path, wherein the endpoints include a start point and an end point;

[0040] In the optimal coarse path, find the position corresponding to the endpoint of the optimal refined path;

[0041] Compare the relationship between the endpoints of the optimal refined path and the corresponding positions of the optimal rough path, and match the connection points between the optimal refined path and the optimal rough path;

[0042] Based on the matching results, the refined path segments are concatenated with the coarse path segments to form a complete path.

[0043] A marine emergency rescue route planning system, comprising:

[0044] The grid division module is used to divide the national sea area into basic grids and store the traffic status, water depth and passable surface information of each grid. Among them, some grids that contain both passable areas and impassable areas are set as suspicious grids;

[0045] An information receiving module is used to receive the latitude and longitude information of the starting point and the end point transmitted by the rescue personnel;

[0046] The rough path analysis module uses the Dijkstra algorithm to analyze the optimal rough path from the starting point to the end point based on the received latitude and longitude information of the starting point and the end point;

[0047] A path verification module is used to determine whether the optimal rough path intersects with the impassable surface, and if so, determine a set of path segments that need to be removed;

[0048] A passable path screening module, which subtracts the path segment set to be removed from the optimal rough path set to obtain a passable path segment set;

[0049] A gap identification module, identifying a path gap in the set of traversable path segments;

[0050] The refinement path analysis module uses the Dijkstra algorithm to analyze the optimal refinement path in the identified path gaps;

[0051] A path concatenation module, when the solution set of the optimal refined path is not empty, concatenates the optimal refined path with the optimal rough path to obtain a final rescue path; when the solution set of the optimal refined path is empty, determines the optimal rough path as the final rescue path;

[0052] The output module is used to output the final rescue path.

[0053] A computing device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the above-mentioned methods for planning a maritime emergency rescue route when executing the computer program.

[0054] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the above-mentioned methods for planning a maritime emergency rescue route.

[0055] The beneficial effects of the present invention are as follows: by dividing the national sea area into basic grids and storing the traffic status, water depth and passable surface information of the grids, it is possible to quickly identify passable and impassable areas, thereby avoiding wasting time and resources in the planning process, and using the Dijkstra algorithm to analyze the optimal rough path from the starting point to the end point. The algorithm can take into account multiple factors to ensure that the selected path is optimal overall. After identifying the path gaps, the Dijkstra algorithm can be further used to analyze the optimal refined path, thereby filling the blank areas in the path, ensuring that rescue personnel can smoothly reach the target location, and can It can determine whether the optimal rough path intersects with the impassable surface and automatically remove the intersecting path fragments, thereby preventing rescuers from getting lost or encountering danger in impassable areas. By identifying path gaps and planning the optimal refined path, it can ensure the continuity and integrity of the rescue path and reduce the risk of rescue failure due to path interruption or loss. By accurately planning the rescue path, it can reduce unnecessary detours and stops for rescuers during navigation, thereby saving time and fuel costs. At the same time, it can also reasonably allocate rescue resources according to the actual situation of the sea area and rescue needs to ensure the smooth progress of the rescue operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 A schematic diagram of a flow chart of a method for planning a maritime emergency rescue route according to the present invention;

[0058] Figure 2 The present invention is a schematic diagram of the composition of a marine emergency rescue route planning system. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] refer to Figure 1 to Figure 2 , a method for planning a maritime emergency rescue route, specifically comprising:

[0061] Divide the national sea area into basic grids, the grid information includes whether it is passable, water depth and passable surface, among which grids that are partially passable and partially impassable are set as suspicious grids;

[0062] Receive the latitude and longitude information of the starting point and the end point transmitted by the rescue personnel;

[0063] According to the latitude and longitude information of the starting point and the end point, the Dijkstra algorithm is used to analyze the optimal rough path from the starting point to the end point;

[0064] Determine whether the optimal rough path intersects with the impassable surface, and if so, obtain a set of path segments that need to be removed;

[0065] Subtract the set of path segments that need to be removed from the optimal rough path set to obtain a set of passable path segments;

[0066] identifying a path gap in the set of navigable path segments;

[0067] Using Dijkstra's algorithm to analyze the optimal refinement path in the path gap;

[0068] If the solution set of the optimal refined path is empty, the optimal rough path is the final rescue path. Otherwise, the optimal refined path is concatenated with the optimal rough path, and the concatenated path is the final rescue path.

[0069] In this embodiment, by dividing the national sea area into basic grids and storing the traffic status, water depth and passable surface information of the grids, it is possible to quickly identify passable and impassable areas, thereby avoiding wasting time and resources in the planning process. The Dijkstra algorithm is used to analyze the optimal rough path from the starting point to the end point. The algorithm can take into account multiple factors to ensure that the selected path is optimal overall. After identifying the path gaps, the Dijkstra algorithm can be further used to analyze the optimal refined path, thereby filling the blank areas in the path, ensuring that the rescue personnel can successfully reach the target location, and can judge It can determine whether the optimal rough path intersects with the impassable surface and automatically remove the intersecting path fragments, so as to prevent rescuers from getting lost or encountering danger in the impassable area. By identifying the path gaps and planning the optimal refined path, it can ensure the continuity and integrity of the rescue path and reduce the risk of rescue failure caused by path interruption or loss. By accurately planning the rescue path, it can reduce unnecessary detours and stops for rescuers during the navigation process, thereby saving time and fuel costs. At the same time, it can also reasonably allocate rescue resources according to the actual situation of the sea area and rescue needs to ensure the smooth progress of the rescue operation.

[0070] It should be noted that the side length of each basic grid is set to 0.02 degrees. This is to make a fine division of the sea area to facilitate subsequent path planning and analysis.

[0071] Preferably, the method of analyzing the optimal rough path from the starting point to the end point using the Dijkstra algorithm according to the latitude and longitude information of the starting point and the end point specifically includes:

[0072] According to the latitude and longitude information of the starting point and the end point, a corresponding sub-grid is divided in the basic grid;

[0073] Using Dijkstra's algorithm in the subgrid to analyze the optimal rough path from the starting grid to the end grid;

[0074] If there is no solution for the rough path in the optimal rough path, the Dijkstra algorithm is used again to find the optimal rough path after expanding the grid range.

[0075] In this embodiment, by dividing the corresponding sub-grids in the basic grid according to the latitude and longitude information of the starting point and the end point, the path planning can be accurately performed in a smaller spatial range, which increases the accuracy of the path planning and ensures that the planned path can be closer to the actual sea environment and conditions; when the optimal rough path initially planned has no solution, the technical solution can flexibly expand the grid range and re-plan the path. This flexibility ensures that a feasible rescue path can still be found in a complex sea environment; using the Dijkstra algorithm for path planning in the sub-grid can efficiently find the optimal rough path from the starting grid to the end grid. The Dijkstra algorithm is a classic path The path planning algorithm has the characteristics of fast calculation speed and high path quality, and is suitable for time-sensitive scenarios such as maritime emergency rescue. By first planning a rough path and then gradually refining it, the amount of calculation required to directly apply complex algorithms on a global scale is reduced, thereby improving the overall calculation efficiency. This technical solution can handle situations involving suspicious grids (i.e., grids that are partially passable and partially impassable), and by expanding the grid range and replanning the path, it increases the adaptability to complex marine environments. When encountering inaccessible areas (such as land, islands, military exercise areas, warning areas, etc.), it can automatically avoid these areas and replan a feasible rescue path, demonstrating good robustness.

[0076] It should be noted that the side length of each sub-grid is 0.02 degrees.

[0077] Preferably, the step of using the Dijkstra algorithm in the subgrid to analyze the optimal rough path from the starting grid to the ending grid specifically includes:

[0078] According to the latitude and longitude of the starting point and the end point input by the front end, the sub-grid area containing the starting point and the end point is divided in the basic grid;

[0079] In the divided sub-grid area, Dijkstra algorithm is applied, taking the starting grid as the source point, to calculate the shortest path length to all other grids;

[0080] From the calculated shortest paths, the path to the end grid is selected as the optimal rough path.

[0081] In this embodiment, the Dijkstra algorithm is applied in the sub-grid area, and the shortest path from the starting grid to all other grids can be efficiently calculated. Since the sub-grid range is relatively small, the calculation amount and time complexity of the algorithm are reduced, thereby improving the efficiency of path planning; by selecting the shortest path to the end grid as the optimal rough path, the accuracy and optimality of the path are ensured. The Dijkstra algorithm itself can ensure that the shortest path from the source point to all other points is found. Therefore, the algorithm is applied in the sub-grid area, and the optimal path from the starting point to the end point can be accurately found; this technical solution can adapt to different starting points and end points. The changes in the positions of the starting and ending points are due to the division of the sub-grid areas based on the latitude and longitude information of the starting and ending points transmitted by the front end. Therefore, no matter how the positions of the starting and ending points change, the sub-grid areas can be re-divided to adapt to such changes and perform corresponding path planning. This technical solution can be expanded and optimized as needed in the future. For example, more environmental factors (such as wind fields, ocean currents, etc.) can be introduced as constraints for path planning, or the algorithm itself can be optimized to improve computing efficiency and accuracy. These expansions and optimizations can be based on existing technical solutions without major changes to the overall architecture.

[0082] Preferably, the Dijkstra algorithm is applied in the divided sub-grid area, taking the starting grid as the source point, and calculating the shortest path length to all other grids, specifically including:

[0083] Step S11, in the divided sub-grid area, with the starting grid as the source point, initialize a distance array, the distance array records the shortest path length from the source point to all other grids, initially, the distance from the source point to itself is set to 0, and the distance from the source point to other grids is set to infinity;

[0084] Step S12: create an unvisited set, and add all grids except the source point to the set;

[0085] Step S13, selecting the grid closest to the source point from the unvisited set as the current grid, and removing it from the unvisited set;

[0086] Step S14: Update the shortest path length from the adjacent grid of the current grid to the source point. If the path from the current grid to the adjacent grid is shorter than the originally recorded path, update the shortest path length of the adjacent grid and set its parent node as the current grid.

[0087] Repeat steps S13 and S14 until the unvisited set is empty, at which point the distance array records the shortest path length from the source point to all grids.

[0088] In this embodiment, by gradually expanding the shortest path, the Dijkstra algorithm can ensure that the shortest path from the starting grid to all other grids is found, which is crucial in rescue path planning because time is life and the shortest path means a faster rescue response; the algorithm can handle grid areas containing different traffic conditions (such as water depth, land, islands and other impassable areas), and by initializing the distance array and gradually updating the shortest path length, the algorithm can flexibly adapt to complex geographical environments and rescue needs; the algorithm can intelligently identify and remove impassable path segments, thereby avoiding wasting computing resources on invalid paths, which helps to make decisions quickly in emergency situations and improve rescue efficiency; data structures such as unvisited sets and distance arrays in the algorithm, as well as the strategy of gradually updating the shortest path length, enable the algorithm to flexibly adjust when facing impassable factors (such as land, islands, military exercise areas, etc.) and find feasible alternative paths.

[0089] Preferably, the identifying a path gap in the set of passable path segments specifically includes:

[0090] Based on the intersection of the optimal rough path and the impassable surface, the gap location is determined;

[0091] The region containing the path gap is meshed to obtain a path gap mesh unit that is smaller than the sub-grid.

[0092] In this embodiment, by identifying the intersection of the optimal rough path and the impassable surface, the position of the gap in the path can be accurately determined, which is a crucial step in path planning, because the gap may represent an impassable area, or an area that requires a specific strategy (such as a detour) to pass through; more detailed grid segmentation of the area containing the gap can further analyze the traffic conditions inside the gap, which helps to discover small channels or obstacles that may be ignored in the coarse grid, thereby improving the accuracy of path planning; by accurately identifying path gaps and performing targeted grid segmentation, the algorithm can reduce unnecessary calculations, which helps to find the optimal path more quickly with limited computing resources, thereby improving rescue efficiency; accurate path planning and optimization can ensure that the rescue team can quickly reach the target area along the optimal path, thereby improving the success rate of rescue.

[0093] Preferably, the step of using the Dijkstra algorithm to analyze the optimal refinement path in the path gap specifically includes:

[0094] Step S21, initializing the distance values ​​of all path gap grid cells that are smaller than the sub-grid, setting the distance value of the starting grid cell to 0, and setting the distance values ​​of other grid cells to infinity;

[0095] Step S22: establish a priority queue for storing the grid cells to be processed, and add the starting grid cell as the first element to the queue;

[0096] Step S23: Take the grid cell with the smallest distance value from the priority queue as the grid cell currently being processed, and update the distance values ​​of its adjacent grid cells;

[0097] Step S24: If the distance value of the adjacent grid cell is updated to be smaller, add it to the priority queue;

[0098] Repeat step S23 and step S24 until the priority queue is empty or the distance value of the end grid cell is updated to a finite value;

[0099] The optimal refinement path is formed by recording the predecessor grid cell of each grid cell and tracing back from the end grid cell to the starting grid cell.

[0100] In this embodiment, by using the Dijkstra algorithm in the path gap, the optimal refined path from the starting grid cell to the end grid cell (or the nearest point within the reachable range) can be accurately calculated, which ensures the accuracy and reliability of the rescue path in complex environments; path gaps often contain complex terrains and obstacles, such as narrow passages, shoals, reefs, etc. The Dijkstra algorithm can flexibly adapt to these complex terrains and find a feasible optimal path by gradually expanding the shortest path; using a priority queue to store the grid cells to be processed can ensure that the grid cells with the smallest current distance value are processed each time, thereby greatly improving the calculation efficiency of the algorithm, which is helpful in limited calculation. The optimal path can be quickly found under the resources; by recording the predecessor grid unit of each grid unit and forming the optimal refined path in the backtracking process, the repeated calculation of path length and path fragments can be avoided, which further improves the resource utilization efficiency of the algorithm; by recording the predecessor grid unit of each grid unit and forming the optimal refined path in the backtracking process, the path can be presented in a visual way, which helps rescuers to intuitively understand the path situation and make more accurate decisions; the optimal refined path not only provides a clear action guide for rescuers, but also serves as the basis for decision support, for example, selecting the optimal path among multiple rescue paths, evaluating the risks and costs of different paths, etc.

[0101] Preferably, the optimal refined path and the optimal rough path are spliced ​​to obtain a final rescue path, which specifically includes:

[0102] Specifying the endpoints of each optimal refinement path, wherein the endpoints include a start point and an end point;

[0103] In the optimal coarse path, find the position corresponding to the endpoint of the optimal refined path;

[0104] Compare the relationship between the endpoints of the optimal refined path and the corresponding positions of the optimal rough path, and match the connection points between the optimal refined path and the optimal rough path;

[0105] Based on the matching results, the refined path segments are concatenated with the coarse path segments to form a complete path.

[0106] In this embodiment, by clarifying the endpoints (including the starting point and the end point) of each optimal refined path and finding the positions corresponding to these endpoints in the optimal rough path, the accuracy and integrity of the path splicing are ensured. This endpoint matching method avoids the situation that the path is broken or misaligned during the splicing process, thereby ensuring the coherence and feasibility of the rescue path; when comparing the relationship between the optimal refined path endpoint and the corresponding position of the optimal rough path, the path can be further optimized by matching the connection points between the optimal refined path and the optimal rough path. This optimization not only considers the shortest distance of the path, but also considers the smoothness and feasibility of the path. At the same time, since the refined path is the optimal solution obtained by the Dijkstra algorithm in the path gap, the spliced ​​path still maintains a high efficiency as a whole; the technical solution also has certain flexibility and scalability. When encountering a new impassable area or a change in navigation conditions, the rescue path can be replanned by adjusting the division of the basic grid, modifying the parameters of the Dijkstra algorithm, or adding new influencing factors (such as wind fields, ocean currents, etc.). This flexibility enables the technical solution to be applicable to different types of rescue missions and different marine environments.

[0107] A marine emergency rescue route planning system, comprising:

[0108] The grid division module is used to divide the national sea area into basic grids and store the traffic status, water depth and passable surface information of each grid. Among them, some grids that contain both passable areas and impassable areas are set as suspicious grids;

[0109] An information receiving module is used to receive the latitude and longitude information of the starting point and the end point transmitted by the rescue personnel;

[0110] The rough path analysis module uses the Dijkstra algorithm to analyze the optimal rough path from the starting point to the end point based on the received latitude and longitude information of the starting point and the end point;

[0111] A path verification module is used to determine whether the optimal rough path intersects with the impassable surface, and if so, determine a set of path segments that need to be removed;

[0112] A passable path screening module, which subtracts the path segment set to be removed from the optimal rough path set to obtain a passable path segment set;

[0113] A gap identification module, identifying a path gap in the set of traversable path segments;

[0114] The refinement path analysis module uses the Dijkstra algorithm to analyze the optimal refinement path in the identified path gaps;

[0115] A path concatenation module, when the solution set of the optimal refined path is not empty, concatenates the optimal refined path with the optimal rough path to obtain a final rescue path; when the solution set of the optimal refined path is empty, determines the optimal rough path as the final rescue path;

[0116] The output module is used to output the final rescue path.

[0117] A computing device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the above-mentioned methods for planning a maritime emergency rescue route when executing the computer program.

[0118] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the above-mentioned methods for planning a maritime emergency rescue route.

[0119] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for planning a maritime emergency rescue route, characterized in that: Specifically include: Divide the national sea area into basic grids, the grid information includes whether it is passable, water depth and passable surface, among which grids that are partially passable and partially impassable are set as suspicious grids; Receive the latitude and longitude information of the starting point and the end point transmitted by the rescue personnel; According to the latitude and longitude information of the starting point and the end point, the Dijkstra algorithm is used to analyze the optimal rough path from the starting point to the end point; Determine whether the optimal rough path intersects with the impassable surface, and if so, obtain a set of path segments that need to be removed; Subtract the set of path segments that need to be removed from the optimal rough path set to obtain a set of passable path segments; identifying a path gap in the set of navigable path segments; Using Dijkstra's algorithm to analyze the optimal refinement path in the path gap; If the solution set of the optimal refined path is empty, the optimal rough path is the final rescue path. Otherwise, the optimal refined path is concatenated with the optimal rough path, and the concatenated path is the final rescue path.

2. A method for planning a maritime emergency rescue route according to claim 1, characterized in that: The optimal rough path from the starting point to the end point is analyzed using the Dijkstra algorithm according to the latitude and longitude information of the starting point and the end point, specifically including: According to the latitude and longitude information of the starting point and the end point, a corresponding sub-grid is divided in the basic grid; Using Dijkstra's algorithm in the subgrid to analyze the optimal rough path from the starting grid to the end grid; If there is no solution for the rough path in the optimal rough path, the Dijkstra algorithm is used again to find the optimal rough path after expanding the grid range.

3. A method for planning a maritime emergency rescue route according to claim 2, characterized in that: The method of using the Dijkstra algorithm in the subgrid to analyze the optimal rough path from the starting grid to the end grid specifically includes: According to the latitude and longitude of the starting point and the end point input by the front end, the sub-grid area containing the starting point and the end point is divided in the basic grid; In the divided sub-grid area, Dijkstra algorithm is applied, taking the starting grid as the source point, to calculate the shortest path length to all other grids; From the calculated shortest paths, the path to the end grid is selected as the optimal rough path.

4. A method for planning a maritime emergency rescue route according to claim 3, characterized in that: In the divided sub-grid area, the Dijkstra algorithm is applied to calculate the shortest path length to all other grids with the starting grid as the source point, specifically including: Step S11, in the divided sub-grid area, with the starting grid as the source point, initialize a distance array, the distance array records the shortest path length from the source point to all other grids, initially, the distance from the source point to itself is set to 0, and the distance from the source point to other grids is set to infinity; Step S12: create an unvisited set, and add all grids except the source point to the set; Step S13, selecting the grid closest to the source point from the unvisited set as the current grid, and removing it from the unvisited set; Step S14: Update the shortest path length from the adjacent grid of the current grid to the source point. If the path from the current grid to the adjacent grid is shorter than the originally recorded path, update the shortest path length of the adjacent grid and set its parent node as the current grid. Repeat steps S13 and S14 until the unvisited set is empty, at which point the distance array records the shortest path length from the source point to all grids.

5. A method for planning a maritime emergency rescue route according to claim 4, characterized in that: The identifying a path gap in the set of passable path segments specifically includes: Based on the intersection of the optimal rough path and the impassable surface, the gap location is determined; The region containing the path gap is meshed to obtain a path gap mesh unit that is smaller than the sub-grid.

6. A method for planning a maritime emergency rescue route according to claim 5, characterized in that: The using of the Dijkstra algorithm in the path gap to analyze the optimal refinement path specifically includes: Step S21, initializing the distance values ​​of all path gap grid cells that are smaller than the sub-grid, setting the distance value of the starting grid cell to 0, and setting the distance values ​​of other grid cells to infinity; Step S22: establish a priority queue for storing the grid cells to be processed, and add the starting grid cell as the first element to the queue; Step S23: Take the grid cell with the smallest distance value from the priority queue as the grid cell currently being processed, and update the distance values ​​of its adjacent grid cells; Step S24: If the distance value of the adjacent grid cell is updated to be smaller, add it to the priority queue; Repeat step S23 and step S24 until the priority queue is empty or the distance value of the end grid cell is updated to a finite value; The optimal refinement path is formed by recording the predecessor grid cell of each grid cell and tracing back from the end grid cell to the starting grid cell.

7. A method for planning a maritime emergency rescue route according to claim 6, characterized in that: The optimal refined path and the optimal rough path are spliced ​​together to obtain a final rescue path, which specifically includes: Specifying the endpoints of each optimal refinement path, wherein the endpoints include a start point and an end point; In the optimal coarse path, find the position corresponding to the endpoint of the optimal refined path; Compare the relationship between the endpoints of the optimal refined path and the corresponding positions of the optimal rough path, and match the connection points between the optimal refined path and the optimal rough path; Based on the matching results, the refined path segments are concatenated with the coarse path segments to form a complete path.

8. A marine emergency rescue route planning system, characterized in that: include: The grid division module is used to divide the national sea area into basic grids and store the traffic status, water depth and passable surface information of each grid. Among them, some grids that contain both passable areas and impassable areas are set as suspicious grids; An information receiving module is used to receive the latitude and longitude information of the starting point and the end point transmitted by the rescue personnel; The rough path analysis module uses the Dijkstra algorithm to analyze the optimal rough path from the starting point to the end point based on the received latitude and longitude information of the starting point and the end point; A path verification module is used to determine whether the optimal rough path intersects with the impassable surface, and if so, determine a set of path segments that need to be removed; A passable path screening module, which subtracts the path segment set to be removed from the optimal rough path set to obtain a passable path segment set; A gap identification module, identifying a path gap in the set of traversable path segments; The refinement path analysis module uses the Dijkstra algorithm to analyze the optimal refinement path in the identified path gaps; A path concatenation module, when the solution set of the optimal refined path is not empty, concatenates the optimal refined path with the optimal rough path to obtain a final rescue path; when the solution set of the optimal refined path is empty, determines the optimal rough path as the final rescue path; The output module is used to output the final rescue path.

9. A computing device, characterized in that The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for planning a maritime emergency rescue route according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for planning a maritime emergency rescue route according to any one of claims 1 to 7.

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