CN117928533A - North-pole ship route planning method based on space-based sea ice product - Google Patents
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Abstract
The invention provides a arctic ship route planning method based on a space-based sea ice product, which comprises the following steps: judging whether the traffic is possible or not according to sea/land (or island) distribution and margin limiting factors; calculating the comprehensive navigation risk index of each pixel by using the space-based sea ice density, the sea ice thickness product and the ship type; the pixel with the positive comprehensive navigation risk index is marked as passable, and the rest pixels are not passable; determining the shortest path between a starting point and a destination point based on an A * algorithm according to the trafficability of the pixels; taking the shortest path obtained under the ice condition and the ice breaking capacity of the ship as the optimal route planning of the ship between the starting point and the ending point. The invention can efficiently plan the arctic ship route.
Description
Technical Field
The invention relates to a north pole ship route planning method based on a space-based sea ice product, and belongs to the technical fields of ship route design and space-based remote sensing products.
Background
The rapid planning of the route by utilizing sea ice data obtained by the space-based observation is particularly important for guaranteeing the navigation safety of the ship. The traditional route planning mainly considers the sailing cost without taking the sea ice condition as a limiting factor, and the existing arctic channel trafficability research is limited by the data acquisition capability, and the sea ice condition is analyzed by taking sea ice concentration data as a single parameter; and the Dijkstra shortest path analysis algorithm commonly used in the optimal path planning process has lower operation efficiency. Therefore, the method for efficiently planning the optimal route of the arctic ship based on the real-time sea ice conditions based on various sea ice parameters has important application value.
Disclosure of Invention
The technical solution of the invention is as follows: the arctic ship route planning method based on the space-based sea ice product is provided, and the accuracy and timeliness of arctic ship route planning are improved.
The technical scheme of the invention is as follows:
the invention discloses a arctic ship route planning method based on a space-based sea ice product, which comprises the following steps of:
Generating an image marked by the primary pixels;
according to the space-based sea ice density, the sea ice thickness and the ship ice breaking capacity, calculating the comprehensive navigation risk index of each pixel in the image after the pixel is marked;
determining the trafficability of each pixel according to the comprehensive navigation risk index;
Determining the shortest path between a starting point and an end point according to a cost function based on a heuristic search A * algorithm according to the trafficability of the pixels;
and taking the shortest path as the optimal planning route of the ship between the starting point and the ending point.
Further, in the above planning method, the generating the image after the preliminary pixel mark specifically includes:
Pixels which are attributed to land, islands and cannot pass due to land limitation factors are marked as non-passing based on sea-land distribution data and literature data.
Further, in the above planning method, the calculating the comprehensive navigation risk index of each pixel specifically includes:
RIOV＝CT×RVV,T
wherein RIO V is the comprehensive navigation risk of ship type V in the area represented by the pixel, C T is the sea ice concentration of sea ice type T in the pixel, and RV V,T is the ship navigation risk index corresponding to ship type V and sea ice type T.
Further, in the planning method, the ship type V is classified according to the ship ice breaking capacity, and the sea ice type T is determined by the sea ice thickness according to the correlation between the sea ice development stage and the sea ice thickness; RV V,T ranges from-6 to 3.
Further, in the above planning method, the sea ice density C T and the sea ice thickness data are used as the same phase space-based sea ice product, and the sea ice density C T and the sea ice thickness data need to be resampled to the same spatial resolution for use.
Further, in the above planning method, the determining, based on the heuristic search a * algorithm, a shortest path between a start point and an end point according to a cost function, and determining a shortest path between the start point and the end point specifically includes:
s1, acquiring coordinates of a starting point and a finishing point and coordinates of each passable pixel on a pixel passable image;
S2, setting an Open table and a Closed table, wherein the Open table stores known adjacent pixels which can pass but are not accessed, and the Closed table stores the accessed pixels;
s3, adding the starting point into an Open table;
S4, calculating a cost value G from the starting point to each adjacent passable pixel, and taking the starting point as a father node of each adjacent passable pixel;
s5, adding adjacent passable pixels of the starting point into an Open table, and moving the starting point into a Closed table;
S6, calculating a cost estimated value H from each passable pixel adjacent to the starting point to the end point in the Open table, and combining the cost value G to obtain a comprehensive estimated value F;
s7, searching adjacent passable pixels with the minimum comprehensive estimated value F from the starting point in the Open table as a node n, and moving the adjacent passable pixels from the Open table into a Closed table;
s8, judging all the passable pixels in the adjacent pixels of the node n;
S9, repeating the steps S6-S8, and if the end point is added into the Closed table, the shortest path exists, and ending the algorithm; if the Open table is empty but the endpoint is not added to the Closed table, then there is no shortest path and the algorithm ends.
Further, in the above planning method, the judging process is performed on all passable pixels in the adjacent pixels of the node n, specifically:
s21, judging whether the adjacent passable pixel i of the node n is already in the Closed table, if so, repeating the step S21, and judging the next adjacent passable pixel i+1; if not, go to step S22;
s22, judging whether the adjacent passable pixels i are in an Open table, if not, adding the adjacent passable pixels i into the Open table, and entering a step S23; if yes, go to step S23;
S23, setting a node n as a father node of an adjacent passable pixel i, and calculating a cost value G from a starting point to the adjacent passable pixel i;
S24, judging whether the node n is used as a parent node of the adjacent passable pixel i to enable the cost value G to be smaller, if so, using the node n as the parent node, and recalculating the cost value G.
Further, in the above planning method, the comprehensive estimation value is calculated by the following formula:
F＝G+H
Wherein F is a comprehensive estimated value from the starting point to the end point through a passable pixel; g is a cost value from the origin point to the passable pixel along the determined path; h is a cost estimate from the passable pel to the endpoint.
Further, in the above-mentioned planning method, the measurement units of the cost value G and the cost estimation value H are identical, and manhattan distance or euclidean distance formula is adopted for calculation.
Further, in the planning method, the pixels with the comprehensive navigation risk index greater than 0 are marked as passable, and the rest are not passable.
The beneficial effects of the invention compared with the prior art are as follows:
(1) The invention carries out arctic ship route planning based on the latest polar region operation limiting risk assessment system (POLARIS) on the basis of two parameters reflecting the sea ice conditions of sea ice concentration and sea ice thickness, and can improve the accuracy and timeliness of arctic ship route planning by using a space-based sea ice data product with high space-time resolution.
(2) The invention carries out the determination of the optimal path based on the heuristic search algorithm A * algorithm, integrates the advantages of accuracy and high speed of the conventional algorithm Dijkstra algorithm and the early heuristic algorithm, and can efficiently determine the optimal arctic ship route.
Drawings
FIG. 1 is a schematic illustration of a arctic ship route planning framework provided by an embodiment of the present invention;
FIG. 2 is a flow chart of a arctic ship route planning method based on a space-based sea ice product provided by an embodiment of the invention;
FIG. 3 is a table of the risk assessment RV for each ship type ice area of the POLARIS system to be referred in the embodiment of the present invention;
Fig. 4 is a flowchart of planning an optimal path based on an a * algorithm according to an embodiment of the present invention.
Detailed Description
The present invention is described in further detail below with reference to the drawings and detailed description.
As shown in fig. 1, the invention discloses a arctic ship route planning method based on a space-based sea ice product, which comprises the following steps:
step one, generating an image marked by a primary pixel;
step two, calculating the comprehensive navigation risk index of each pixel in the image after the pixel marking according to the space-based sea ice density, sea ice thickness and ship ice breaking capacity;
step three, determining the trafficability of each pixel according to the comprehensive navigation risk index;
determining the shortest path between the starting point and the end point according to the cost function based on a heuristic search A * algorithm according to the trafficability of the pixels;
and fifthly, taking the shortest path as an optimal planning route of the ship between the starting point and the ending point.
Preferably, in the first step, the generating the image after the preliminary pixel mark specifically includes:
Pixels which are attributed to land, islands and cannot pass due to land limitation factors are marked as non-passing based on sea-land distribution data and literature data.
Preferably, in the second step, the calculating a comprehensive navigation risk index of each pixel specifically includes:
RIOV＝CT×RVV,T
wherein RIO V is the comprehensive navigation risk of ship type V in the area represented by the pixel, C T is the sea ice concentration of sea ice type T in the pixel, and RV V,T is the ship navigation risk index corresponding to ship type V and sea ice type T.
Preferably, the ship type V is classified according to the ship ice breaking capacity, and the sea ice type T is determined by the sea ice thickness according to the correlation between the sea ice development stage and the sea ice thickness; RV V,T ranges from-6 to 3.
Preferably, the sea ice concentration C T and the sea ice thickness data are used as a day-based sea ice product with the same time phase, and the sea ice concentration C T and the sea ice thickness data are required to be resampled to the same spatial resolution for use.
Preferably, in the fourth step, the shortest path between the starting point and the end point is determined according to the heuristic search a * algorithm, and the shortest path between the starting point and the end point is determined specifically:
s1, acquiring coordinates of a starting point and a finishing point and coordinates of each passable pixel on a pixel passable image;
S2, setting an Open table and a Closed table, wherein the Open table stores known adjacent pixels which can pass but are not accessed, and the Closed table stores the accessed pixels;
s3, adding the starting point into an Open table;
S4, calculating a cost value G from the starting point to each adjacent passable pixel, and taking the starting point as a father node of each adjacent passable pixel;
s5, adding adjacent passable pixels of the starting point into an Open table, and moving the starting point into a Closed table;
S6, calculating a cost estimated value H from each passable pixel adjacent to the starting point to the end point in the Open table, and combining the cost value G to obtain a comprehensive estimated value F;
s7, searching adjacent passable pixels with the minimum comprehensive estimated value F from the starting point in the Open table as a node n, and moving the adjacent passable pixels from the Open table into a Closed table;
s8, judging all the passable pixels in the adjacent pixels of the node n; the method comprises the following steps:
S81, judging whether the adjacent passable pixel i of the node n is already in the Closed table, if so, repeating the step S81, and judging the next adjacent passable pixel i+1; if not, go to step S82;
S82, judging whether the adjacent passable pixels i are in an Open table, if not, adding the adjacent passable pixels i into the Open table, and entering step S83; if yes, go to step S83;
S83, setting a node n as a father node of an adjacent passable pixel i, and calculating a cost value G from a starting point to the adjacent passable pixel i;
S84, judging whether the node n is used as a parent node of the adjacent passable pixel i to enable the cost value G to be smaller, if so, using the node n as the parent node, and recalculating the cost value G.
S9, repeating the steps S6-S8, and if the end point is added into the Closed table, the shortest path exists, and ending the algorithm; if the Open table is empty but the endpoint is not added to the Closed table, then there is no shortest path and the algorithm ends.
Preferably, in the second step, the pixels with the integrated navigation risk index greater than 0 are marked as passable, and the rest are not passable.
Preferably, the comprehensive estimation value is calculated by the following formula:
F＝G+H
Wherein F is a comprehensive estimated value from the starting point to the end point through a passable pixel; g is a cost value from the origin point to the passable pixel along the determined path; h is a cost estimate from the passable pel to the endpoint.
Preferably, the cost value G and the cost estimate H are consistent in unit of measure and are calculated using a manhattan distance or euclidean distance formula.
Examples
As shown in fig. 1, firstly, judging whether the traffic is possible or not according to sea/land (or island) distribution and margin limiting factors; calculating the comprehensive navigation risk index of each pixel by using the space-based sea ice density, the sea ice thickness product and the ship type; the pixel with the comprehensive navigation risk index larger than 0 is marked as passable, and the rest is not passable; determining the shortest path between a starting point and a destination point based on an A * algorithm according to the trafficability of the pixels; taking the shortest path obtained under the ice condition and the ice breaking capacity of the ship as the optimal route planning of the ship between the starting point and the ending point.
Referring to a arctic ship route planning method flow chart based on a space-based sea ice product shown in fig. 2, the method comprises the following steps:
Firstly judging whether the sea ice product can pass or not according to sea/land (or island) distribution and land limit factors, selecting sea Liu Yanmo data of the same resolution "landmask _arc_12.5km.hdf" provided by the sea ice product according to the space resolution of 12.5km×12.5km of the sea ice product used in the embodiment, and generating grid data of the same space resolution in GIS software by adopting vector sea land distribution data; in this embodiment, the northeast channel area is considered as the main channel available in the future of our country, so the sea area where the northeast channel is located is referred to as the passable area according to the literature.
The integrated navigation risk index for each pixel was calculated using the space-based sea ice concentration and sea ice thickness product and the ship type, which in this example were respectively using the ASI 5.4 arctic sea ice concentration product of dela Mei Da, germany (based on AMSR-E data, spatial resolution 6.25km x 6.5km in%) and the SMOS Level 1c arctic sea ice thickness product (based on SMOS data, spatial resolution 12.5km x 12.5km in cm), and resampling the former to 12.5km x 12.5km. Determining a ship navigation risk index RV V,T of the area represented by the pixel based on a ship type V and a sea ice type T according to an International Maritime Organization (IMO) polar operation limiting risk assessment system (POLARIS) rule; the ship types are classified in the POLARIS system according to the ship ice breaking capacity, and the sea ice types are determined by the sea ice thickness according to the correlation between the sea ice development stage and the sea ice thickness; RV values range from-6 to 3, as shown in FIG. 3 for a class 1C boat for example:
And calculating the comprehensive navigation risk RIO V,RIOV＝CT×RVV,T,CT of the ship type V in the area represented by the pixel, wherein the comprehensive navigation risk RIO V,RIOV＝CT×RVV,T,CT is the sea ice concentration of the sea ice type T in the pixel, and RV V,T is the ship navigation risk index corresponding to the ship type V and the sea ice type T. And marking pixels with the comprehensive navigation risk index RV V,T larger than 0 as passable, and the rest as not passable.
Based on the trafficability of the pels, the shortest path between the start point and the end point is determined based on the A * algorithm as shown in FIG. 4. Firstly, acquiring coordinates of a starting point and an ending point and a pixel trafficability image based on a space-based sea ice product; setting an Open table and a Closed table to respectively store the pixels which are not accessed and the pixels which are accessed; adding the starting point into an Open table; calculating a cost value G from the starting point to each adjacent passable pixel, and taking the starting point as a father node of the adjacent pixel; adding adjacent passable pixels of the starting point into an Open table, and moving the starting point into a Closed table; calculating a cost estimation value H from each pixel to the end point in the OpenTable, and obtaining a comprehensive estimation value F, wherein F represents the comprehensive estimation value of the cost and the future estimated cost spent by the path from the start point to the end point through the pixel, H is a heuristic function and represents the cost estimation value from the pixel to the end point; searching a pixel with the minimum F value in the Open table as a node n, and moving the pixel from the Open table into the Closed table; judging the passable pixels in the adjacent pixels of the node n: 1) If the adjacent passable pixel is already in the Closed table, skipping the pixel and continuing to judge the next pixel; 2) If the adjacent passable pixel is not in the Open table, adding the adjacent passable pixel into the Open table, setting a node n as a father node of the adjacent passable pixel, and calculating an F value of the adjacent passable pixel; 3) If the adjacent passable pel is already in the Open table, judging whether the G value can be reduced by taking the node n as a father node of the node n; 4) Taking node n as its parent node may make the G value smaller, then taking node n as its parent node and recalculating the G value and F value. Repeating the above two steps until the end point, if the end point has been added to the Closed table, then there is a shortest path; if the endpoint is not added to the Closed table, but the Open table is empty, then there is no shortest path.
Taking the shortest path obtained under consideration of ice conditions and the ice breaking capacity of the ship as the optimal route planning of the ship between the starting point and the ending point; i.e. the resulting path from the end point looking for the parent node of each node up to the start point, in case there is an optimal path.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Of course, it will be appreciated by those skilled in the art that implementing all or part of the above-described methods in the embodiments may be implemented by a computer level to instruct a control device, where the program may be stored in a computer readable storage medium, and the program may include the above-described methods in the embodiments when executed, where the storage medium may be a memory, a magnetic disk, an optical disk, or the like.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
While the present invention has been described in detail through the foregoing description of the preferred embodiment, it should be understood that the foregoing description is not to be considered as limiting the invention. Many modifications and substitutions of the present invention will become apparent to those of ordinary skill in the art upon reading the foregoing. Accordingly, the scope of the invention should be limited only by the attached claims.
What is not described in detail in the present specification belongs to the known technology of those skilled in the art.
Claims (10)
1. The arctic ship route planning method based on the space-based sea ice product is characterized by comprising the following steps of:
Generating an image marked by the primary pixels;
according to the space-based sea ice density, the sea ice thickness and the ship ice breaking capacity, calculating the comprehensive navigation risk index of each pixel in the image after the pixel is marked;
determining the trafficability of each pixel according to the comprehensive navigation risk index;
Determining the shortest path between a starting point and an end point according to a cost function based on a heuristic search A * algorithm according to the trafficability of the pixels;
and taking the shortest path as the optimal planning route of the ship between the starting point and the ending point.
2. A arctic ship route planning method based on a space-based sea ice product according to claim 1, wherein: the image after the primary pixel mark is generated is specifically:
Pixels which are attributed to land, islands and cannot pass due to land limitation factors are marked as non-passing based on sea-land distribution data and literature data.
3. A arctic ship route planning method based on a space-based sea ice product according to claim 1, wherein: the calculating of the comprehensive navigation risk index of each pixel is specifically as follows:
RIOV＝CT×RVV,T
wherein RIO V is the comprehensive navigation risk of ship type V in the area represented by the pixel, C T is the sea ice concentration of sea ice type T in the pixel, and RV V,T is the ship navigation risk index corresponding to ship type V and sea ice type T.
4. A arctic ship route planning method based on a space-based sea ice product according to claim 3, characterized in that: the ship type V is classified according to the ship ice breaking capacity, and the sea ice type T is determined by the sea ice thickness according to the correlation between the sea ice development stage and the sea ice thickness; RV V,T ranges from-6 to 3.
5. A arctic ship route planning method based on a space-based sea ice product according to claim 3, characterized in that: the sea ice density C T and the sea ice thickness data are the same-phase space-based sea ice product, and the sea ice density C T and the sea ice thickness data are required to be resampled to the same spatial resolution for use.
6. A arctic ship route planning method based on a space-based sea ice product according to claim 1, wherein: the heuristic search A * algorithm is based, the shortest path between the starting point and the end point is determined according to the cost function, and the shortest path between the starting point and the end point is determined specifically as follows:
s1, acquiring coordinates of a starting point and a finishing point and coordinates of each passable pixel on a pixel passable image;
S2, setting an Open table and a Closed table, wherein the Open table stores known adjacent pixels which can pass but are not accessed, and the Closed table stores the accessed pixels;
s3, adding the starting point into an Open table;
S4, calculating a cost value G from the starting point to each adjacent passable pixel, and taking the starting point as a father node of each adjacent passable pixel;
s5, adding adjacent passable pixels of the starting point into an Open table, and moving the starting point into a Closed table;
S6, calculating a cost estimated value H from each passable pixel adjacent to the starting point to the end point in the Open table, and combining the cost value G to obtain a comprehensive estimated value F;
s7, searching adjacent passable pixels with the minimum comprehensive estimated value F from the starting point in the Open table as a node n, and moving the adjacent passable pixels from the Open table into a Closed table;
s8, judging all the passable pixels in the adjacent pixels of the node n;
S9, repeating the steps S6-S8, and if the end point is added into the Closed table, the shortest path exists, and ending the algorithm; if the Open table is empty but the endpoint is not added to the Closed table, then there is no shortest path and the algorithm ends.
7. The arctic ship route planning method based on the space-based sea ice product according to claim 6, wherein: the judging process is performed on all the passable pixels in the adjacent pixels of the node n, specifically:
s21, judging whether the adjacent passable pixel i of the node n is already in the Closed table, if so, repeating the step S21, and judging the next adjacent passable pixel i+1; if not, go to step S22;
s22, judging whether the adjacent passable pixels i are in an Open table, if not, adding the adjacent passable pixels i into the Open table, and entering a step S23; if yes, go to step S23;
S23, setting a node n as a father node of an adjacent passable pixel i, and calculating a cost value G from a starting point to the adjacent passable pixel i;
S24, judging whether the node n is used as a parent node of the adjacent passable pixel i to enable the cost value G to be smaller, if so, using the node n as the parent node, and recalculating the cost value G.
8. The arctic ship route planning method based on the space-based sea ice product according to claim 6, wherein: the comprehensive estimation value is calculated according to the following formula:
F＝G+H
Wherein F is a comprehensive estimated value from the starting point to the end point through a passable pixel; g is a cost value from the origin point to the passable pixel along the determined path; h is a cost estimate from the passable pel to the endpoint.
9. A arctic ship route planning method based on a space-based sea ice product according to claim 8, wherein: the cost value G is consistent with the cost estimation H in measurement unit, and is calculated by adopting a Manhattan distance or Euclidean distance formula.
10. A arctic ship route planning method based on a space-based sea ice product according to claim 1, wherein: and marking the pixels with the comprehensive navigation risk index larger than 0 as passable, and the rest pixels are not passable.
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