A risk quantification route planning method and device based on a sea ice safety potential field

Abstract

The application relates to a risk quantification route planning method and device based on a sea ice safety potential field, which comprises the following steps: acquiring sea ice physical characteristic data of a target navigation area, gridizing the target navigation area to obtain an environment grid map, establishing a safety potential field model for each grid according to the sea ice physical characteristic data to represent the safety potential field strength of the target position relative to the grid, calculating the risk potential energy value of a target ship in each grid according to the sailing data of the target ship and the safety potential field model of each grid to obtain a risk quantification map, and finally planning a route according to the risk quantification map. Compared with the prior art, the application applies the concept of the safety potential field to the ice area, evaluates the safety potential field based on the sea ice physical characteristic data in the target navigation area, quantitatively calculates the risk according to the actual data to obtain a risk quantification map, and then realizes route planning, so that the purpose of objectively and accurately planning a low-risk route is achieved, and the application has a good application prospect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ship route, and in particular to a risk quantification route planning method and device based on sea ice safety potential field. BACKGROUND

[0002] Although the Arctic route was gradually opened in the 19th and 20th centuries, it did not have commercial value for shipping due to the harsh weather environment and ice conditions. In recent years, due to the rapid melting of sea ice, the potential for navigation in the Arctic is increasing. On the one hand, although the global warming trend shows a certain degree of weakening trend, the climate change in the Arctic region is showing a dramatic acceleration trend, known as the "Arctic amplification" phenomenon. On the other hand, with the rapid rise in temperature, the ice cover in the Arctic summer and autumn is gradually decreasing, and the thickness of the sea ice is continuously decreasing. With the continuous change of ice conditions, the Arctic route will become more and more busy in the future and become the main shipping route of world trade.

[0003] Based on the above background, the problem of how to realize safe navigation in the Arctic region arises. This main problem can be divided into two secondary problems, one is the quantitative problem of navigation risk in the Arctic region, and the other is the route planning problem based on the quantitative risk. In the quantitative problem of navigation risk, the commonly used risk quantification methods include fuzzy comprehensive evaluation method, analytic hierarchy process, and grey correlation method. The models and formulas of these methods are clear and easy to understand, and are very convenient to use.

[0004] However, as a newly opened continent, the Arctic has not been subjected to much research, let alone the risk quantification and path planning problem based on the Arctic route. The data supporting the current risk quantification method is usually obtained by expert evaluation method, without being based on actual data, which makes these methods somewhat objective and leads to the planned route still having a high risk. Therefore, people urgently need a method that can quantify the risk by combining the actual data of the Arctic sea ice region, so as to objectively and accurately plan a low-risk route. SUMMARY

[0005] Therefore, it is necessary to provide a risk quantification route planning based on sea ice safety potential field, so as to achieve the purpose of quantifying the risk by combining the actual data of the Arctic sea ice region, and objectively and accurately planning a low-risk route.

[0006] To achieve the above technical purpose, the present application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a risk quantification route planning method based on sea ice safety potential field, comprising:

[0008] acquire sea ice physical characteristic data of a target navigation area, and grid the target navigation area to obtain an environmental grid map;

[0009] establish a safety potential field model for each grid according to the sea ice physical characteristic data in each grid in the environmental grid map, and the safety potential field model is used to represent safety potential field intensity of a target position relative to the grid;

[0010] acquire navigation data of a target ship, and calculate risk potential energy values of the target ship in each grid according to the navigation data and the safety potential field model of each grid to obtain a risk quantification map;

[0011] plan a route according to the risk quantification map to obtain a target navigation route.

[0012] Further, the safety potential field model for each grid is established according to the sea ice physical characteristic data in each grid in the environmental grid map, and the method comprises:

[0013] obtain potential field operation constants of a target source grid according to sea ice physical characteristic data in the target source grid, and the target source grid refers to each grid in the environmental grid map;

[0014] establish a safety potential field model of the target source grid according to the potential field operation constants, take a distance between the target position and the target source grid as an input variable, and take the safety potential field intensity of the target position relative to the target source grid as an output quantity.

[0015] Further, the sea ice physical characteristic data comprises sea ice thickness and sea ice density, and the potential field operation constants of the target source grid are obtained according to the sea ice physical characteristic data in the target source grid, and the method comprises:

[0016] acquire a ship type of the target ship;

[0017] obtain an RV value of the target grid according to the ship type and the sea ice thickness in the target source grid;

[0018] obtain an RIO value of the target source grid according to the RV value and the sea ice density in the target source grid, and the RIO value is the potential field operation constant.

[0019] Further, the navigation data of the target ship is acquired, and the risk potential energy values of the target ship in each grid are calculated according to the navigation data and the safety potential field model of each grid to obtain a risk quantification map, and the method comprises:

[0020] acquire navigation data of the target ship, and the navigation data comprises ship mass and ship speed;

[0021] Based on the navigation data of the target vessel, the equivalent mass of the target vessel is obtained;

[0022] Based on the equivalent mass, and according to the safety potential field model of each grid, the risk potential energy value of the target vessel within the target assessment grid is calculated, wherein the target assessment grid refers to every grid in the environmental grid diagram;

[0023] The risk quantification map is obtained based on the risk potential value of each target evaluation grid.

[0024] Furthermore, the calculation of the risk potential energy value of the target vessel within the target assessment grid based on the equivalent mass and the safety potential field model for each grid includes:

[0025] Obtain the distance between the target evaluation grid and the target source grid;

[0026] Based on the distance between the target evaluation grid and the target source grid, and using the security potential field model, the security potential field strength of the target evaluation grid relative to the target source grid is obtained.

[0027] Based on the safety potential field strength of the target evaluation grid relative to the target source grid and the equivalent mass, the sub-risk potential energy value of the target evaluation grid relative to the target source grid is obtained;

[0028] The risk potential value of the target vessel within the target assessment grid is obtained based on the sub-risk potential value of the target assessment grid relative to each target source grid.

[0029] Furthermore, the step of planning the route based on the risk quantification map to obtain the target navigation route includes:

[0030] Using the grid in the risk quantification diagram as nodes, the risk potential value of the grid as the actual cost, and the distance between two grids as the path length, an improved actual cost function is established based on the sum of the actual cost and the path length.

[0031] Establish dynamic weights, and establish a heuristic cost function based on the dynamic weights. The weights of the dynamic weights change according to the real-time heuristic cost function value and the maximum heuristic cost function value during calculation.

[0032] Based on the improved actual cost function and the improved heuristic cost function, and according to the risk quantification graph, through A The algorithm obtains the planned path;

[0033] The planned path is smoothed using a Bézier curve to obtain the target navigation path.

[0034] Furthermore, the step of acquiring sea ice physical characteristic data of the target navigation area and gridding the target navigation area to obtain an environmental grid map includes:

[0035] The acquisition of sea ice physical characteristic data for the target navigation area;

[0036] Based on the target navigation area, a projection map of the target area is obtained using stereographic projection.

[0037] The target area projection map is gridded, and combined with the sea ice physical characteristic data, to obtain the environmental schematic diagram.

[0038] Secondly, the present invention also provides a risk quantification route planning device based on sea ice safety potential field, comprising:

[0039] The grid map building module is used to acquire sea ice physical characteristic data of the target navigation area and grid the target navigation area to obtain an environmental grid map;

[0040] The safety potential field calculation module is used to establish a safety potential field model for each grid based on the sea ice physical characteristic data in each grid of the environmental grid map. The safety potential field model is used to characterize the safety potential field intensity of the target location relative to the grid.

[0041] The risk quantification module is used to acquire the navigation data of the target vessel, and calculate the risk potential energy value of the target vessel in each grid according to the navigation data and the safety potential field model of each grid, so as to obtain the risk quantification map.

[0042] The route planning module is used to plan routes based on the risk quantification map to obtain the target navigation route.

[0043] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein,

[0044] Memory, used to store programs;

[0045] The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the risk quantification route planning method based on the sea ice safety potential field in any of the above implementations.

[0046] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which, when executed by a processor, can implement the steps in the risk quantification route planning method based on sea ice safety potential field in any of the above implementation methods.

[0047] This invention provides a risk quantification method and apparatus for route planning based on sea ice safety potential field. It acquires sea ice physical characteristic data of the target navigation area, grids the target navigation area to obtain an environmental grid map, and then establishes a safety potential field model for each grid based on the sea ice physical characteristic data within that grid. The safety potential field model characterizes the safety potential field strength of the target position relative to the grid. Next, it acquires the navigation data of the target vessel and calculates the risk potential energy value of the target vessel within each grid based on the navigation data and the safety potential field model of each grid, obtaining a risk quantification map. Finally, it plans the route based on the risk quantification map to obtain the target navigation route. Compared to existing technologies, this invention applies the concept of safety potential field to ice-covered areas, assesses the safety potential field based on sea ice physical characteristic data within the target navigation area, and quantifies the risk based on actual data to obtain a risk quantification map, thereby achieving route planning. This achieves the goal of objectively and accurately planning low-risk routes and has excellent application prospects. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating an embodiment of the risk quantification route planning method based on sea ice safety potential field provided by the present invention.

[0049] Figure 2 A target area projection map in one embodiment of the risk quantification route planning method based on sea ice safety potential field provided by the present invention;

[0050] Figure 3 An RV value lookup table in one embodiment of the risk quantification route planning method based on sea ice safety potential field provided by the present invention;

[0051] Figure 4 for Figure 1 A flowchart of a method according to an embodiment of step S103;

[0052] Figure 5 for Figure 4 A flowchart of a method according to an embodiment of step S403;

[0053] Figure 6 for Figure 1 A flowchart of a method according to an embodiment of step S104;

[0054] Figure 7 A schematic diagram of an embodiment of the risk quantification route planning device based on sea ice safety potential field provided by the present invention;

[0055] Figure 8 A schematic diagram of the structure of an embodiment of the electronic device provided by the present invention. Detailed Implementation

[0056] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0057] In the description of this application, "multiple" means two or more, unless otherwise expressly and specifically defined.

[0058] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0059] The concept of "safety potential field" has been widely used in road transportation, with little application in the field of water transportation. This invention applies the concept of safety potential field to ice-covered areas, drawing analogies to concepts such as field strength and electric potential energy in electric fields. Based on actual sea ice physical characteristics data, it quantifies risks and achieves quantitative calculation of risks in ice-covered areas, which is more intuitive and objective compared to traditional risk analysis theories.

[0060] This invention provides a risk quantification method, apparatus, equipment, and storage medium for route planning based on sea ice safety potential field, which are described below.

[0061] Combination Figure 1 As shown, a specific embodiment of the present invention discloses a risk quantification route planning method based on sea ice safety potential field, comprising:

[0062] S101. Obtain the sea ice physical characteristics data of the target navigation area, and grid the target navigation area to obtain an environmental grid map;

[0063] S102. Based on the sea ice physical characteristic data in each grid of the environmental grid map, establish a safety potential field model for each grid. The safety potential field model is used to characterize the safety potential field strength of the target location relative to the grid.

[0064] S103. Obtain the navigation data of the target vessel, and calculate the risk potential energy value of the target vessel in each grid according to the navigation data and the safety potential field model of each grid, to obtain a risk quantification map;

[0065] S104. Plan the route according to the risk quantification map to obtain the target navigation route.

[0066] This invention provides a risk quantification method and apparatus for route planning based on sea ice safety potential field. It acquires sea ice physical characteristic data of the target navigation area, grids the target navigation area to obtain an environmental grid map, and then establishes a safety potential field model for each grid based on the sea ice physical characteristic data within that grid. The safety potential field model characterizes the safety potential field strength of the target position relative to the grid. Next, it acquires the navigation data of the target vessel and calculates the risk potential energy value of the target vessel within each grid based on the navigation data and the safety potential field model of each grid, obtaining a risk quantification map. Finally, it plans the route based on the risk quantification map to obtain the target navigation route. Compared to existing technologies, this invention applies the concept of safety potential field to ice-covered areas, assesses the safety potential field based on sea ice physical characteristic data within the target navigation area, and quantifies the risk based on actual data to obtain a risk quantification map, thereby achieving route planning. This achieves the goal of objectively and accurately planning low-risk routes and has excellent application prospects.

[0067] In a preferred embodiment, step S101, acquiring sea ice physical characteristic data of the target navigation area and gridding the target navigation area to obtain an environmental grid map, specifically includes:

[0068] The acquisition of sea ice physical characteristic data for the target navigation area;

[0069] Based on the target navigation area, a projection map of the target area is obtained using stereographic projection.

[0070] The target area projection map is gridded, and combined with the sea ice physical characteristic data, to obtain the environmental schematic diagram.

[0071] The present invention also provides a more detailed embodiment to more clearly illustrate the above step S101:

[0072] First, the sea ice thickness and density of the ice zone on that day are determined based on satellite remote sensing data from different hours and daily ice zone data published by natural environment agencies such as NASA (i.e., sea ice physical characteristic data; in practice, other types of data can also be collected as needed).

[0073] Due to the unique geographical location of the Arctic, commonly used projection methods such as the Mercator projection are no longer suitable. For clarity and ease of display, this embodiment projects the target navigation area in the Arctic region onto a hemisphere using the 70°N polar stereographic projection (resulting in a projected map of the target area, as shown in the image). Figure 2 (As shown). Then, the projected map is gridded to form M. A grid map of N is created, and this map is fused with the data collected in step one to determine the sea ice density and thickness within each grid, resulting in a complete schematic diagram of the Arctic navigation environment.

[0074] In a preferred embodiment, step S102, establishing a safety potential field model for each grid based on the sea ice physical characteristic data within each grid of the environmental grid map, specifically includes:

[0075] Based on the sea ice physical characteristic data within the target source grid, the potential field operation constant of the target source grid is obtained, wherein the target source grid refers to every grid in the environmental grid diagram;

[0076] Based on the potential field operation constant, with the distance between the target location and the target source grid as the input variable and the safe potential field strength of the target location relative to the target source grid as the output, a safe potential field model of the target source grid is established.

[0077] Specifically, in a preferred embodiment, the step in the above process, obtaining the potential field operation constant of the target source grid based on the sea ice physical characteristic data within the target source grid, specifically includes:

[0078] Obtain the ship type of the target vessel;

[0079] The RV value of the target grid is obtained based on the ship type and the sea ice thickness within the target source grid;

[0080] The RIO value of the target source grid is obtained based on the RV value and the sea ice density within the target source grid, and the RIO value is the potential field operation constant.

[0081] The present invention also provides a more detailed embodiment to more clearly illustrate step S102 above:

[0082] The concept of "field strength" borrowed from the electric field concept and is a type of artificial potential field. Current research focuses primarily on its application in road traffic. An electric field is a physical field that exists around a charge and transmits the interactions between charges. An electric field always exists around a charge, and it exerts a force on other charges within the field. Furthermore, Coulomb's theorem states that the electric field strength produced by a point charge is directly proportional to the charge it carries and inversely proportional to the square of the distance; the electric field strength decreases with distance from the source charge.

[0083] Of all navigation risks in the Arctic, sea ice is the most threatening. Due to the unique nature of navigation in ice-covered areas, route restrictions are not a concern; therefore, this invention only considers the risks posed by sea ice. Based on the above description, the safety potential field is defined as follows: Assume that a "safety field" exists around the sea ice within each grid cell. The magnitude of this field is directly proportional to the thickness and density of the sea ice within the grid cell and inversely proportional to the distance. The safety field weakens the farther away from the grid cell. The magnitude of this field is used to quantitatively calculate the risk value. If multiple safety fields exist simultaneously in a given grid cell, the maximum value is used to define the size of the safety field for that grid cell.

[0084] The specific formula for the safety potential field model defined in this embodiment is:

[0085]

[0086] in, This represents the strength of the safety potential field at the target location under the influence of the target source grid. The value represents the distance between the ice and the calculation point; in this embodiment, it is the distance between the target location and the target source grid. This is a correction factor. The RIO value is related to sea ice thickness and density and is defined by the Polar Operational Limit Assessment Risk Indexing System (POLARIS). Its calculation formula is as follows:

[0087]

[0088] in, This refers to the density value of type T sea ice in a certain area. This refers to the RV value for a Type V vessel (i.e., the vessel type mentioned above) navigating in a Type T sea ice covered area. RV values ​​can be found in POLARIS files (e.g., ...). Figure 3 The RV value lookup table shown represents the risk level for 11 types of vessels navigating under 12 different ice thicknesses and ice-free conditions, expressed as integers from +3 to -6. Here, "not ice strengthened" is used. Figure 3 The RV value is used for the "No ice" case. Furthermore, since the RV value represents a negative risk, the absolute value of RV is used here to indicate the degree of ice risk. For areas without ice, the value is determined by referring to the RV lookup table. It is understandable that in practice, different parameters can be chosen as potential field operation constants based on other criteria, depending on the specific circumstances.

[0089] Combination Figure 4As shown, in a preferred embodiment, step S103 of the above process—acquiring the navigation data of the target vessel and calculating the risk potential energy value of the target vessel in each grid based on the navigation data and the safety potential field model of each grid to obtain a risk quantification map—specifically includes:

[0090] S401. Obtain the navigation data of the target vessel, the navigation data including the vessel's mass and speed;

[0091] S402. Based on the navigation data of the target vessel, obtain the equivalent mass of the target vessel;

[0092] S403. Based on the equivalent mass, and according to the safety potential field model of each grid, calculate the risk potential energy value of the target vessel within the target assessment grid, wherein the target assessment grid refers to every grid in the environmental grid diagram;

[0093] S404. Based on the risk potential value of each target evaluation grid, obtain the risk quantification map.

[0094] Specifically, in combination Figure 5 As shown, in a preferred embodiment, step S403 of the above process, calculating the risk potential energy value of the target vessel within the target assessment grid based on the equivalent mass and according to the safety potential field model of each grid, includes:

[0095] S501. Obtain the distance between the target evaluation grid and the target source grid;

[0096] S502. Based on the distance between the target evaluation grid and the target source grid, and using the safety potential field model, obtain the safety potential field strength of the target evaluation grid relative to the target source grid;

[0097] S503. Based on the safety potential field strength of the target evaluation grid relative to the target source grid and the equivalent mass, obtain the sub-risk potential energy value of the target evaluation grid relative to the target source grid.

[0098] S504. Based on the sub-risk potential energy value of the target vessel within the target assessment grid relative to each target source grid, obtain the risk potential energy value of the target vessel within the target assessment grid.

[0099] The present invention also provides a more detailed embodiment to more clearly illustrate the above steps S401~S404:

[0100] The threat posed by sea ice varies depending on the size of the vessel. This is achieved using the power of an electric field. The concept views the ship as a "test charge" that generates a safe potential field from sea ice. It assumes that the ship's mass and speed affect the magnitude of the field force exerted on it by the sea ice. Therefore, the ship's equivalent mass... q Defined as:

[0101]

[0102] In the formula, V B This refers to the ship's speed, specifically the planned speed at which the ship will travel within the target navigation area. m B For ship quality.

[0103] Therefore, the field force generated by ice on the ship F for:

[0104]

[0105] Based on the above analysis, the potential energy of the safe potential field... M The formula for calculating (i.e., the sub-risk potential value) is:

[0106]

[0107] The general formula for calculating this formula is:

[0108]

[0109] Substituting the parameters into this formula yields the safety potential energy exerted by sea ice within a grid on a ship within any other grid. This safety potential energy is then used to quantitatively calculate the risk value (affected by the safety potential field of the target source grid) of a ship passing through any grid (i.e., when the ship is located within the target assessment grid). When a target assessment grid is affected by sea ice from multiple target source grids, the value with the highest potential energy (which can be considered the highest risk value) is taken to define its risk, thus obtaining the final risk potential energy value. It is understood that the final risk potential energy value can be directly derived from the above formula, or the result can be further processed to obtain a risk value convenient for practical application, such as normalizing it to a decimal between 0 and 1 or converting it to a metric value in relevant standards, to facilitate subsequent analysis, assessment, and path planning calculations.

[0110] As the formula shows, the greater the ship's speed, the greater the thickness and density of the ice, the higher the calculated potential energy value, and the higher the risk faced by the ship. Conversely, the greater the distance between the ship and the ice, the greater the ship's mass, the lower the calculated potential energy value, and the lower the risk faced by the ship. Based on the above process, and using the previously obtained environmental grid map that includes the ice thickness and density, a risk quantification map can be calculated through the above steps. The values ​​within the grid represent the magnitude of the risk, and land areas are designated as inaccessible areas.

[0111] Furthermore, in combination Figure 6 As shown, in a preferred embodiment, the above process S104, planning the route according to the risk quantification map to obtain the target navigation route, specifically includes:

[0112] S601. Using the grid in the risk quantification diagram as nodes, the risk potential value of the grid as the actual cost, and the distance between two grids as the path length, an improved actual cost function is established based on the sum of the actual cost and the path length.

[0113] S602. Establish dynamic weights, and establish a heuristic cost function based on the dynamic weights. The weights of the dynamic weights change according to the real-time heuristic cost function value and the maximum heuristic cost function value during calculation.

[0114] S603. Based on the improved actual cost function and the improved heuristic cost function, and according to the risk quantification diagram, through A... The algorithm obtains the planned path;

[0115] S604. Smooth the planned path using a Bezier curve to obtain the target navigation path.

[0116] The present invention also provides a more detailed embodiment to more clearly illustrate the above steps S601~S604:

[0117] Classic path planning algorithms include Dijkstra's algorithm and breadth-first search. One suffers from excessively long search time, and the other from the problem of local optima. A... The algorithm combines the advantages of both approaches, comprehensively considering the estimated and actual costs of the starting point, current node, and ending point, to obtain the optimal solution while ensuring search efficiency. Therefore, this embodiment utilizes existing A algorithms... Based on the algorithm, improvements were made and applied to the planning of Arctic shipping routes.

[0118] In this embodiment, A In the algorithm, each grid cell is used as a node for searching. The starting point and destination of the ship are set on the grid. Starting from the starting point, the algorithm continuously searches for surrounding points, using the newly selected point as the starting point again. This process is repeated until the destination is reached, thus obtaining the optimal path. Specifically, during each search, the algorithm expands outward from the current node to the eight surrounding nodes, calculating the actual cost of each of the eight surrounding nodes. (Also known as movement cost, etc.) Heuristic cost (Also known as estimated cost, projected cost, etc.), and then determine the search function for the next node. ,generally:

[0119]

[0120] In the formula n Represents the current node.

[0121] In this invention, A heuristic function of the algorithm and actual cost function Improvements will be made.

[0122] In existing technologies, the actual cost Typically, the cost function is the sum of the actual costs from the starting point to the current node, such as path length and route expenses. However, in this invention, searching only for risk or only for route length is unrealistic. Therefore, the actual cost function is improved to be the risk potential value through the node. Path length between nodes The sum is used to perform a minimum value search. In this embodiment, the improved actual cost function is:

[0123]

[0124] In the formula, It is an artificially set relaxation constant.

[0125] Let be the heuristic function, representing the estimated cost from the current node to the target node. Commonly used heuristic functions include Manhattan distance, Euclidean distance, and Chebyshev distance. In this invention, the Euclidean distance between two nodes is selected as the estimated cost.

[0126] Furthermore, this invention adds a weight to the heuristic function. This causes the heuristic function to become .if This transforms the algorithm into Dijkstra's algorithm, which traverses the entire globe. While this algorithm will always find an optimal path, its computation speed is too slow. When the size becomes large enough, the algorithm becomes a breadth-first search algorithm, that is, when... While increasing the weight of the heuristic function speeds up the search, it doesn't guarantee an optimal path and can lead to local optima. Based on this analysis, this embodiment assigns a dynamic weight to the heuristic function. Initially, this weight is set relatively large, but as the algorithm progresses, it decreases. Let:

[0127]

[0128] In the formula, The heuristic function value of the current node relative to the target point. This is the maximum value that the heuristic function can take; it's easy to see that this value is the Euclidean distance from the starting point to the target point. A after weight improvement... The algorithm can quickly and accurately find a path from the starting point to the destination that minimizes risk. Thus, the improved A... The algorithm formula becomes:

[0129]

[0130] Furthermore, the calculated path may contain excessively large corners. Therefore, to address this issue, this invention optimizes the weights of A... The route planning results are smoothed using Bézier curves to eliminate nodes with excessively large turns that do not conform to actual ship operation. The general formula for a cubic Bézier curve is:

[0131]

[0132] In the formula, t The weight parameters are used to construct the weight polynomial. B(t) The smoothed curve , , , Given four points, if the four points are on a straight line, the optimized result will also be on a straight line. If the four points are not on a straight line, the points are smoothed according to the formula. After the above steps, a smooth path curve with the least risk can be obtained within the target navigation area.

[0133] This embodiment proposes a method that differs from conventional qualitative risk analysis by quantitatively analyzing the navigation risks posed by sea ice based on actual sea ice thickness and density. This method is primarily derived from the artificial safety potential field theory. Based on this theoretical foundation, this invention considers sea ice distribution characteristics, distance, and the ship's own mass and speed to propose a safety potential field theory suitable for quantitative calculation of risks in ice-covered areas. The calculated risk quantification map is then further optimized using A... The algorithm ensures that the planned route is a low-risk and feasible path. For A... The optimization of the algorithm is reflected in increasing the weight of the heuristic function and using Bézier curves to optimize the smoothness of the generation path.

[0134] To better implement the risk quantification route planning method based on sea ice safety potential field in this invention embodiment, based on the risk quantification route planning method based on sea ice safety potential field, please refer to the corresponding documentation. Figure 7 , Figure 7This is a schematic diagram of an embodiment of the risk quantification route planning device based on sea ice safety potential field provided by the present invention. The embodiment of the present invention provides a risk quantification route planning device 700 based on sea ice safety potential field, comprising:

[0135] The grid map building module 710 is used to acquire sea ice physical characteristic data of the target navigation area and grid the target navigation area to obtain an environmental grid map;

[0136] The safety potential field calculation module 720 is used to establish a safety potential field model for each grid based on the sea ice physical characteristic data in each grid of the environmental grid map. The safety potential field model is used to characterize the safety potential field intensity of the target location relative to the grid.

[0137] The risk quantification module 730 is used to acquire the navigation data of the target vessel, and calculate the risk potential energy value of the target vessel in each grid according to the navigation data and the safety potential field model of each grid, so as to obtain the risk quantification map.

[0138] The route planning module 740 is used to plan the route based on the risk quantification map to obtain the target navigation route.

[0139] It should be noted that the corresponding device 700 provided in the above embodiments can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding content in the above method embodiments, and will not be repeated here.

[0140] Please see Figure 8 , Figure 8 This is a schematic diagram of the electronic device provided in an embodiment of the present invention. Based on the above-described risk quantification route planning method based on sea ice safety potential field, the present invention also provides a risk quantification route planning device 800 based on sea ice safety potential field, i.e., the aforementioned electronic device. The risk quantification route planning device 800 based on sea ice safety potential field can be a mobile terminal, desktop computer, laptop, handheld computer, server, or other computing device. The risk quantification route planning device 800 based on sea ice safety potential field includes a processor 810, a memory 820, and a display 830. Figure 8 Only some components of the risk quantification route planning device based on the sea ice safety potential field are shown. However, it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0141] In some embodiments, memory 820 can be an internal storage unit of the risk quantification route planning device 800 based on sea ice safety potential field, such as a hard disk or memory of the risk quantification route planning device 800 based on sea ice safety potential field. In other embodiments, memory 820 can also be an external storage device of the risk quantification route planning device 800 based on sea ice safety potential field, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the risk quantification route planning device 800 based on sea ice safety potential field. Furthermore, memory 820 can also include both internal storage units and external storage devices of the risk quantification route planning device 800 based on sea ice safety potential field. Memory 820 is used to store application software and various types of data installed on the risk quantification route planning device 800 based on sea ice safety potential field, such as program code installed on the risk quantification route planning device 800 based on sea ice safety potential field. Memory 820 can also be used to temporarily store data that has been output or will be output. In one embodiment, the memory 820 stores a risk quantification route planning program 840 based on the sea ice safety potential field. The risk quantification route planning program 840 based on the sea ice safety potential field can be executed by the processor 810 to realize the risk quantification route planning method based on the sea ice safety potential field in the various embodiments of this application.

[0142] In some embodiments, processor 810 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 820 or process data, such as executing a risk quantification route planning method based on sea ice safety potential field.

[0143] In some embodiments, display 830 may be an LED display, a liquid crystal display, a touch-screen liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 830 is used to display information from the sea ice safety potential field-based risk quantification route planning device 800 and to display a visual user interface. Components 810-830 of the sea ice safety potential field-based risk quantification route planning device 800 communicate with each other via a system bus.

[0144] In one embodiment, when the processor 810 executes the risk quantification route planning program 840 based on the sea ice safety potential field in the memory 820, the steps in the risk quantification route planning method based on the sea ice safety potential field as described above are implemented.

[0145] This embodiment also provides a computer-readable storage medium storing a risk quantification route planning program based on a sea ice safety potential field. When executed by a processor, the risk quantification route planning program based on a sea ice safety potential field can implement the steps in the above embodiment.

[0146] This invention provides a risk quantification method and apparatus for route planning based on sea ice safety potential field. It acquires sea ice physical characteristic data of the target navigation area, grids the target navigation area to obtain an environmental grid map, and then establishes a safety potential field model for each grid based on the sea ice physical characteristic data within that grid. The safety potential field model characterizes the safety potential field strength of the target position relative to the grid. Next, it acquires the navigation data of the target vessel and calculates the risk potential energy value of the target vessel within each grid based on the navigation data and the safety potential field model of each grid, obtaining a risk quantification map. Finally, it plans the route based on the risk quantification map to obtain the target navigation route. Compared to existing technologies, this invention applies the concept of safety potential field to ice-covered areas, assesses the safety potential field based on sea ice physical characteristic data within the target navigation area, and quantifies the risk based on actual data to obtain a risk quantification map, thereby achieving route planning. This achieves the goal of objectively and accurately planning low-risk routes and has excellent application prospects.

[0147] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A risk quantification route planning method based on sea ice safety potential field, characterized in that, include: Obtain sea ice physical characteristic data of the target navigation area, and grid the target navigation area to obtain an environmental grid map; Based on the sea ice physical characteristic data within each grid of the environmental grid map, a safety potential field model is established for each grid, including: obtaining the potential field operation constant of the target source grid based on the sea ice physical characteristic data within the target source grid, wherein the target source grid refers to every grid in the environmental grid map; establishing a safety potential field model for the target source grid based on the potential field operation constant, using the distance between the target location and the target source grid as the input variable and the safety potential field strength of the target location relative to the target source grid as the output variable; the safety potential field model is used to characterize the safety potential field strength of the target location relative to the grid. Acquiring navigation data of the target vessel and, based on the navigation data and the safety potential field model of each grid, calculating the risk potential energy value of the target vessel within each grid to obtain a risk quantification map, includes: acquiring navigation data of the target vessel, the navigation data including vessel mass and vessel speed; obtaining the equivalent mass of the target vessel based on the navigation data; calculating the risk potential energy value of the target vessel within a target assessment grid based on the equivalent mass and the safety potential field model of each grid, the target assessment grid referring to each grid in the environmental grid diagram; and obtaining the risk quantification map based on the risk potential energy value of each target assessment grid. The target navigation route is obtained by planning the route based on the risk quantification map.

2. The risk quantification route planning method based on sea ice safety potential field according to claim 1, characterized in that, The sea ice physical characteristics data include sea ice thickness and sea ice density; The step of obtaining the potential field operation constant of the target source grid based on the sea ice physical characteristic data within the target source grid includes: Obtain the ship type of the target vessel; The RV value of the target source grid is obtained based on the ship type and the sea ice thickness within the target source grid. The RIO value of the target source grid is obtained based on the RV value and the sea ice density within the target source grid, and the RIO value is the potential field operation constant.

3. The risk quantification route planning method based on sea ice safety potential field according to claim 1, characterized in that, Based on the equivalent mass, and according to the safety potential field model for each grid, the calculation of the risk potential energy value of the target vessel within the target assessment grid includes: Obtain the distance between the target evaluation grid and the target source grid; Based on the distance between the target evaluation grid and the target source grid, and using the security potential field model, the security potential field strength of the target evaluation grid relative to the target source grid is obtained. Based on the safety potential field strength of the target evaluation grid relative to the target source grid and the equivalent mass, the sub-risk potential energy value of the target evaluation grid relative to the target source grid is obtained; The risk potential value of the target vessel within the target assessment grid is obtained based on the sub-risk potential value of the target assessment grid relative to each target source grid.

4. The risk quantification route planning method based on sea ice safety potential field according to claim 1, characterized in that, The step of planning the route based on the risk quantification map to obtain the target navigation route includes: Using the grid in the risk quantification diagram as nodes, the risk potential value of the grid as the actual cost, and the distance between two grids as the path length, an improved actual cost function is established based on the sum of the actual cost and the path length. Establish dynamic weights, and establish a heuristic cost function based on the dynamic weights. The weights of the dynamic weights change according to the real-time heuristic cost function value and the maximum heuristic cost function value during calculation. Based on the improved actual cost function and the improved heuristic cost function, and according to the risk quantification graph, through A The algorithm obtains the planned path; The planned path is smoothed using a Bezier curve to obtain the target navigation route.

5. The risk quantification route planning method based on sea ice safety potential field according to claim 1, characterized in that, The process of acquiring sea ice physical characteristic data of the target navigation area and gridding the target navigation area to obtain an environmental grid map includes: The acquisition of sea ice physical characteristic data for the target navigation area; Based on the target navigation area, a projection map of the target area is obtained using stereographic projection. The target area projection map is gridded, and combined with the sea ice physical characteristic data, to obtain the environmental schematic diagram.

6. A risk quantification route planning device based on sea ice safety potential field, characterized in that, include: The grid map building module is used to acquire sea ice physical characteristic data of the target navigation area and grid the target navigation area to obtain an environmental grid map; The safety potential field calculation module is used to establish a safety potential field model for each grid based on the sea ice physical characteristic data within each grid of the environmental grid map. This includes: obtaining the potential field operation constant of the target source grid based on the sea ice physical characteristic data within the target source grid, where the target source grid refers to every grid in the environmental grid map; establishing a safety potential field model for the target source grid based on the potential field operation constant, using the distance between the target location and the target source grid as the input variable and the safety potential field strength of the target location relative to the target source grid as the output variable; the safety potential field model is used to characterize the safety potential field strength of the target location relative to the grid. A risk quantification module is used to acquire navigation data of a target vessel and, based on the navigation data and the safety potential field model of each grid, calculate the risk potential energy value of the target vessel within each grid to obtain a risk quantification map. The module includes: acquiring navigation data of the target vessel, including vessel mass and speed; obtaining the equivalent mass of the target vessel based on the navigation data; calculating the risk potential energy value of the target vessel within a target assessment grid based on the equivalent mass and the safety potential field model of each grid, where the target assessment grid pertains to each grid in the environmental grid diagram; and obtaining the risk quantification map based on the risk potential energy value of each target assessment grid. The route planning module is used to plan routes based on the risk quantification map to obtain the target navigation route.

7. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the risk quantification route planning method based on sea ice safety potential field as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, are capable of implementing the steps in the risk quantification route planning method based on sea ice safety potential field as described in any one of claims 1 to 5.

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