A route planning method, device, equipment and storage medium

Abstract

The present invention discloses a route planning method. The method comprises: pre-processing the acquired initial route to obtain a plurality of route edges; obtaining route information and meteorological information, and calculating the edge weight of each route edge according to the route information and meteorological information; calculating the total fuel consumption of flying along the initial route based on the edge weight; taking the minimum total fuel consumption as the optimization target, optimizing the initial route using the RRT* algorithm to obtain the optimal route. The present invention takes into account the influence of aircraft performance and environmental factors on flight fuel consumption, and can obtain the optimal route with lower fuel consumption.

Description

Technical Field

[0001] The present invention relates to the field of aviation technology, and in particular to a route planning method, device, equipment and storage medium. Background Art

[0002] In the concept of free route airspace, fixed air traffic service routes are cancelled in the free route airspace, and airlines can freely plan routes between designated entry and exit points. With the continuous promotion of free route airspace, it is particularly important to explore route planning methods within free routes. This is not only related to the cost reduction and efficiency improvement of airlines, but also an important guarantee for the sustainable development of the natural environment.

[0003] The existing technology of route planning in free airspace only plans the route with the shortest distance as the goal, and does not consider the impact of factors such as aircraft takeoff weight, wind direction, temperature, etc. on flight fuel consumption, resulting in high actual fuel consumption and difficulty in obtaining the optimal route with low fuel consumption. Summary of the invention

[0004] The embodiment of the present invention provides a route planning method, which takes into account the impact of aircraft performance and environmental factors on flight fuel consumption, thereby being able to obtain an optimal route with lower fuel consumption.

[0005] In a first aspect, an embodiment of the present invention provides a route planning method, comprising:

[0006] Preprocess the acquired initial route to obtain multiple route edges;

[0007] Acquire route information and weather information, and calculate the edge weight of each route edge according to the route information and the weather information;

[0008] Calculate the total fuel consumption of flying along the initial route based on the edge weight;

[0009] Taking the minimum total fuel consumption as the optimization goal, the initial route is optimized using the RRT* algorithm to obtain the optimal route.

[0010] Furthermore, the obtained initial route is preprocessed to obtain multiple route edges, including:

[0011] Generate a great circle route between the starting point and the target point, and use the great circle route as the initial route;

[0012] The initial route is divided according to a preset distance to obtain a plurality of waypoints, and the waypoints are sequentially connected to obtain a plurality of route edges.

[0013] Further, the calculating the edge weight of each of the route edges according to the route information and the weather information includes:

[0014] Calculate the fuel flow of the aircraft at each of the waypoints and the flight time at each of the wayside based on the route information and the weather information;

[0015] The edge weight of each of the route edges is calculated according to the flight time and the fuel flow.

[0016] Further, the calculating of the fuel flow of the aircraft at each of the waypoints and the flight time at each of the waysides based on the route information and the weather information includes:

[0017] Based on the route information and weather information, obtaining a heading angle, wind temperature and wind speed;

[0018] Calculating the weight of the aircraft at each of the waypoints according to the distance between the current waypoint and the target point, the average fuel consumption per unit distance and the fuel-free weight of the aircraft;

[0019] Calculating the fuel flow of the aircraft at each of the waypoints according to the weight of the aircraft, the current flight altitude and the wind temperature;

[0020] Based on the fuel flow rate, a corresponding Mach number in an aircraft performance table is obtained, and the true air speed of the aircraft is calculated according to the Mach number and the wind temperature;

[0021] The ground speed is calculated according to the true airspeed of the aircraft, the wind speed, and the heading angle, and the flight time of the aircraft on each of the airways is calculated according to the airway length of each of the airways and the ground speed.

[0022] Furthermore, taking the minimum total fuel consumption as the optimization target, optimizing the initial route using the RRT* algorithm to obtain the optimal route includes the following steps:

[0023] Step 1: construct an RRT* tree, initialize the root node and the maximum number of iterations of the RRT* tree;

[0024] Step 2: randomly sampling to obtain a sampling point, connecting the sampling point with the node closest to the sampling point in the RRT* tree to obtain a connecting line, generating a new node on the connecting line, and obtaining a set of neighboring points of the new node in the RRT* tree;

[0025] Step 3: Calculate the fuel consumption corresponding to the line connecting each neighboring point in the neighboring point set and the new node;

[0026] Step 4: taking the adjacent point corresponding to the line with the minimum fuel consumption and an acute angle with the initial route as the parent node of the new node, adding the new node to the RRT* tree, and calculating the fuel consumption of the first path from the root node to the new node;

[0027] Step 5: traverse all neighboring points in the neighboring point set, and for each neighboring point, modify the parent node of the neighboring point to the new node, and calculate the fuel consumption of the second path from the root node to the neighboring point via the new node. If the fuel consumption of the second path is less than the fuel consumption of the first path and the angle between the line connecting the new node and the neighboring point and the initial route is an acute angle, then retain the modification; if the fuel consumption of the second path is greater than or equal to the fuel consumption of the first path, then cancel the modification;

[0028] Step 6: Determine whether the current number of iterations is less than the maximum number of iterations. If so, continue to execute step 2. If not, end the iteration and obtain the optimal route in the RRT* tree according to the Dijkstra algorithm.

[0029] Furthermore, the sampling points are obtained by the following steps:

[0030] Taking each of the waypoints as the center of the circle, calculating the radius according to a preset length, and establishing a circular sampling range for each of the waypoints;

[0031] The sampling points are obtained by randomly sampling in the circular sampling range of all the waypoints.

[0032] Furthermore, the calculating the total fuel consumption of flying along the initial route based on the edge weights includes:

[0033] The edge weights of all the route edges are added up to obtain the total fuel consumption of flying along the initial route.

[0034] In a second aspect, an embodiment of the present invention provides a route planning device, comprising:

[0035] A preprocessing module is used to preprocess the acquired initial route to obtain multiple route edges;

[0036] An edge weight calculation module, used for obtaining route information and weather information, and calculating the edge weight of each route edge according to the route information and weather information;

[0037] A total fuel consumption calculation module, used for calculating the total fuel consumption of flying along the initial route based on the edge weight;

[0038] The route planning module is used to optimize the initial route by using the RRT* algorithm with the minimum total fuel consumption as the optimization target to obtain the optimal route.

[0039] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0040] Memory for storing computer programs;

[0041] A processor, configured to execute the computer program;

[0042] Wherein, when the processor executes the computer program, it implements the route planning method described in any one of the first aspects above.

[0043] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed, the route planning method described in any one of the first aspects above is implemented.

[0044] Compared with the prior art, the route planning method provided by the embodiment of the present invention has the following beneficial effects: by preprocessing the acquired initial route, a plurality of route edges are obtained; route information and weather information are obtained, and the edge weight of each route edge is calculated according to the route information and weather information; the total fuel consumption of flying along the initial route is calculated based on the edge weight; taking the minimum total fuel consumption as the optimization goal, the improved RRT* algorithm is used to optimize the initial route to obtain the optimal route. The edge weight value can be calculated in real time during the route planning process, and the route planning under the influence of flight performance and environmental factors can be considered, so as to obtain the optimal route with low fuel consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical features of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 It is a flowchart of an embodiment of a route planning method provided by the present invention;

[0047] Figure 2 is a schematic diagram of an embodiment of random sampling in a route planning method provided by the present invention;

[0048] Figure 3 It is a structural schematic diagram of an embodiment of a route planning device provided by the present invention;

[0049] Figure 4 It is a structural schematic diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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.

[0051] In a first aspect, an embodiment of the present invention provides a route planning method, see Figure 1 , which is a flow chart of an embodiment of a route planning method provided by the present invention.

[0052] like Figure 1 As shown, the method comprises the following steps:

[0053] S1: pre-processing the acquired initial route to obtain multiple route edges;

[0054] S2: Obtain route information and weather information, and calculate the edge weight of each route edge according to the route information and weather information;

[0055] S3: Calculating the total fuel consumption of flying along the initial route based on the edge weight;

[0056] S4: Taking the minimum total fuel consumption as the optimization goal, the initial route is optimized using the RRT* algorithm to obtain the optimal route.

[0057] In a specific implementation, an initial route is first obtained based on the starting point and target point of the aircraft's flight, the initial route is preprocessed to obtain multiple route edges, route information and weather information are obtained, and the edge weight of each route edge is calculated based on the route information and weather information. The edge weight represents the fuel consumption of the aircraft on each route edge. The total fuel consumption of flying along the initial route is calculated based on the edge weight. Taking the minimization of the total fuel consumption as the optimization goal, the initial route is optimized using the RRT* algorithm to obtain the optimal route.

[0058] In summary, the present invention obtains multiple route edges by preprocessing the acquired initial route; obtains route information and weather information, and calculates the edge weight of each route edge according to the route information and weather information; calculates the total fuel consumption of flying along the initial route based on the edge weight; takes the minimum total fuel consumption as the optimization goal, and uses the RRT* algorithm to optimize the initial route to obtain the optimal route. The edge weight value can be calculated in real time during the route planning process, and the route planning under the influence of flight performance and environmental factors can be considered, so as to obtain the optimal route with low fuel consumption.

[0059] In an optional implementation, the preprocessing of the acquired initial route to obtain multiple route edges includes:

[0060] Generate a great circle route between the starting point and the target point, and use the great circle route as the initial route;

[0061] The initial route is divided according to a preset distance to obtain a plurality of waypoints, and the waypoints are sequentially connected to obtain a plurality of route edges.

[0062] Specifically, the latitude and longitude values ​​of the starting point and the target point are obtained, and a great circle route from the starting point to the target point is generated. Since the great circle route is the shortest route between two points, it is used as the initial route of the aircraft. Starting from the starting point, multiple waypoints are generated on the initial route in sequence according to a preset distance, and adjacent waypoints are connected in sequence to obtain multiple route edges. For example, the preset distance can be set to 50 nautical miles, which is not specifically limited here.

[0063] In an optional implementation, the calculating the edge weight of each of the route edges according to the route information and the weather information includes:

[0064] Calculate the fuel flow of the aircraft at each of the waypoints and the flight time at each of the wayside based on the route information and weather information;

[0065] The edge weight of each of the route edges is calculated according to the flight time and the fuel flow.

[0066] Specifically, the route information data and weather information data are loaded, and the fuel flow consumed by the aircraft when passing each waypoint and the flight time of the aircraft on the route side corresponding to the waypoint are calculated. Based on the flight time and fuel flow, the fuel consumption of the aircraft on each route side is calculated, and the fuel consumption is used as the edge weight of each route side.

[0067] In an optional implementation, the calculating of the fuel flow of the aircraft at each waypoint and the flight time at each side of the route based on the route information and the weather information includes:

[0068] Based on the route information and weather information, obtaining a heading angle, wind temperature and wind speed;

[0069] Calculating the weight of the aircraft at each of the waypoints according to the distance between the current waypoint and the target point, the average fuel consumption per unit distance and the fuel-free weight of the aircraft;

[0070] Calculating the fuel flow of the aircraft at each of the waypoints according to the weight of the aircraft, the current flight altitude and the wind temperature;

[0071] Based on the fuel flow rate, a corresponding Mach number in an aircraft performance table is obtained, and the true air speed of the aircraft is calculated according to the Mach number and the wind temperature;

[0072] The ground speed is calculated according to the true airspeed of the aircraft, the wind speed, and the heading angle, and the flight time of the aircraft on each of the airways is calculated according to the airway length of each of the airways and the ground speed.

[0073] Specifically, based on the acquired route information and weather information, wind temperature, wind speed and heading angle are obtained. First, the aircraft weight W is estimated when the aircraft is on a certain route. a , the specific formula is as follows:

[0074]

[0075] Among them, f c Indicates the average fuel consumption per unit distance, Indicates the distance between the current waypoint and the target point, W ZFW Indicates the aircraft's fuel-free weight.

[0076] The fuel flow rate FF of the aircraft at each waypoint is calculated based on the current flight altitude, wind temperature and the calculated aircraft weight. e , and obtain the corresponding Mach number MN from the aircraft performance table, and calculate the true airspeed of the aircraft based on the Mach number MN and wind temperature According to the true airspeed of the aircraft And the obtained wind speed and heading angle, calculate the ground speed The specific formula is as follows:

[0077]

[0078] in, Indicates the true airspeed of the aircraft. represents the wind speed, and θ represents the angle between the wind and the route.

[0079] According to the length of the airside and the ground speed, calculate the flight time T of the aircraft on each of the airsides e , the specific formula is as follows:

[0080]

[0081] Among them, L e Indicates the length of the route edge.

[0082] In an optional implementation, taking the minimum total fuel consumption as the optimization target, optimizing the initial route using the RRT* algorithm to obtain the optimal route includes the following steps:

[0083] Step 1: construct an RRT* tree, initialize the root node and the maximum number of iterations of the RRT* tree;

[0084] Specifically, first construct an RRT* tree T containing only the starting point s, initialize the starting point s as the root node, and set the maximum number of iterations.

[0085] Step 2: randomly sampling to obtain a sampling point, connecting the sampling point with the node closest to the sampling point in the RRT* tree to obtain a connecting line, generating a new node on the connecting line, and obtaining a set of neighboring points of the new node in the RRT* tree;

[0086] In this step, sampling points are obtained by performing random sampling in a preset sampling area, and the node closest to the sampling point is found in the RRT* tree, and the node is connected to the sampling point to obtain a connecting line. A new node is generated on the connecting line with a preset step length. For example, the preset step length can be set to 50 nautical miles, and a new node is generated every 50 nautical miles on the connecting line. Finally, a new node is also generated for less than 50 nautical miles. A circular area is constructed with the new node as the center and the preset length as the radius. The nodes on the RRT* tree T in the circular area constitute a set of neighboring points of the new node.

[0087] Step 3: Calculate the fuel consumption corresponding to the line connecting each neighboring point in the neighboring point set and the new node;

[0088] Step 4: taking the adjacent point corresponding to the line with the minimum fuel consumption and an acute angle with the initial route as the parent node of the new node, adding the new node to the RRT* tree, and calculating the fuel consumption of the first path from the root node to the new node;

[0089] Specifically, the fuel consumption corresponding to the line between each node in the neighboring point set and the new node is calculated, and the node corresponding to the line with the smallest fuel consumption and an acute angle with the great circle route from the starting point to the target point is selected, and the node is used as the parent node of the new node. The new node is added to the RRT* tree, and the fuel consumption from the root node to the new node is calculated, which is recorded as the first path fuel consumption.

[0090] Step 5: traverse all neighboring points in the neighboring point set, and for each neighboring point, modify the parent node of the neighboring point to the new node, and calculate the fuel consumption of the second path from the root node to the neighboring point via the new node. If the fuel consumption of the second path is less than the fuel consumption of the first path and the angle between the line connecting the new node and the neighboring point and the initial route is an acute angle, then retain the modification; if the fuel consumption of the second path is greater than or equal to the fuel consumption of the first path, then cancel the modification;

[0091] Specifically, for all neighboring points in the neighboring point set of the new node, try to modify its parent node to the new node, and calculate the fuel consumption from the root node via the new node to the neighboring point, which is recorded as the second path fuel consumption. If the modified second path fuel consumption is less than the first path fuel consumption and the angle between the line connecting the new node and the neighboring point and the initial route is an acute angle, then retain the modification and modify the parent node of the neighboring point to the new node. If the modified second path fuel consumption is greater than or equal to the first path fuel consumption, cancel the modification.

[0092] Step 6: Determine whether the current number of iterations is less than the maximum number of iterations. If so, continue to execute step 2. If not, end the iteration and obtain the optimal route in the RRT* tree according to the Dijkstra algorithm.

[0093] Specifically, this step verifies whether the current number of iterations has reached the maximum number of iterations and checks whether the iteration conditions are met. If the maximum number of iterations has not been reached, the process returns to step 2. If the maximum number of iterations has been reached, the iteration ends and the Dijkstra algorithm is used to obtain a path from the starting point to the target point, i.e., the optimal route.

[0094] In an optional implementation, the sampling points are obtained by the following steps:

[0095] Taking each of the waypoints as the center of the circle, calculating the radius according to a preset length, and establishing a circular sampling range for each of the waypoints;

[0096] The sampling points are obtained by randomly sampling in a circular sampling range set of all the waypoints.

[0097] For example, see Figure 2 , with each waypoint x on the initial route p The radius r is calculated according to the preset length R0, and the circular sampling range of each waypoint is established, where x n is a new node, r can be obtained by the following formula:

[0098]

[0099] Among them, FF e is the fuel flow of the aircraft at each of the waypoints, F e0 is the fuel consumption along the route without considering the wind direction, that is When R0 is a parameter, R0 can be taken as 100 nautical miles. When the ratio is large, it means that the fuel consumption is greatly affected by these wind directions. The side where the fuel consumption is greatly affected by the conditions corresponds to a larger radius, that is, a larger sampling range. The sampling point x is randomly sampled in the circular sampling range of all waypoints. r ,In order to reach the target point quickly, the target point is sampled with a probability of 10% during sampling.

[0100] In an optional implementation, the calculating the total fuel consumption of flying along the initial route based on the edge weights includes:

[0101] The edge weights of all the route edges are added up to obtain the total fuel consumption of flying along the initial route.

[0102] Specifically, the edge weight of each route edge is the fuel consumption of the aircraft on the route edge, and the edge weights of all route edges are added together to obtain the total fuel consumption of flying along the initial route.

[0103] In a second aspect, an embodiment of the present invention provides a route planning device, see Figure 3 , which is a structural schematic diagram of an embodiment of a route planning device provided by the present invention.

[0104] like Figure 3 As shown, the device comprises:

[0105] A preprocessing module 31 is used to preprocess the acquired initial route to obtain multiple route edges;

[0106] An edge weight calculation module 32, used for obtaining route information and weather information, and calculating the edge weight of each route edge according to the route information and weather information;

[0107] A total fuel consumption calculation module 33, used for calculating the total fuel consumption of flying along the initial route based on the edge weight;

[0108] The route planning module 34 is used to optimize the initial route by using the RRT* algorithm with the minimum total fuel consumption as the optimization target to obtain the optimal route.

[0109] In an optional implementation, the preprocessing module 31 is used to:

[0110] Generate a great circle route between the starting point and the target point, and use the great circle route as the initial route;

[0111] The initial route is divided according to a preset distance to obtain a plurality of waypoints, and the waypoints are sequentially connected to obtain a plurality of route edges.

[0112] In an optional implementation, the edge weight calculation module 32 includes:

[0113] A first calculation unit 321, used for calculating the fuel flow and flight time of the aircraft on each of the route sides based on the route information and weather information;

[0114] The second calculation unit 322 is used to calculate the edge weight of each of the route edges according to the flight time and the fuel flow.

[0115] In an optional implementation, the first calculation unit 321 is used to:

[0116] Based on the route information and weather information, obtaining a heading angle, wind temperature and wind speed;

[0117] Calculating the weight of the aircraft on each of the airway edges according to the distance between the current airway edge and the target point, the average fuel consumption per unit distance and the aircraft's fuel-free weight;

[0118] Calculating the fuel flow of the aircraft at each side of the route according to the weight of the aircraft, the current flight altitude and the wind temperature;

[0119] Based on the fuel flow rate, a corresponding Mach number in an aircraft performance table is obtained, and the true air speed of the aircraft is calculated according to the Mach number and the wind temperature;

[0120] The ground speed is calculated according to the true airspeed of the aircraft, the wind speed, and the heading angle, and the flight time of the aircraft on each of the airways is calculated according to the airway length of each of the airways and the ground speed.

[0121] In an optional implementation, the route planning module 34 is used to:

[0122] Step 1: construct an RRT* tree, initialize the root node and the maximum number of iterations of the RRT* tree;

[0123] Step 2: randomly sampling to obtain a sampling point, connecting the sampling point with the node closest to the sampling point in the RRT* tree to obtain a connecting line, generating a new node on the connecting line, and obtaining a set of neighboring points of the new node in the RRT* tree;

[0124] Step 3: Calculate the fuel consumption corresponding to the line connecting each neighboring point in the neighboring point set and the new node;

[0125] Step 4: taking the adjacent point corresponding to the line with the minimum fuel consumption and an acute angle with the initial route as the parent node of the new node, adding the new node to the RRT* tree, and calculating the fuel consumption of the first path from the root node to the new node;

[0126] Step 5: traverse all neighboring points in the neighboring point set, and for each neighboring point, modify the parent node of the neighboring point to the new node, and calculate the fuel consumption of the second path from the root node to the neighboring point via the new node. If the fuel consumption of the second path is less than the fuel consumption of the first path and the angle between the line connecting the new node and the neighboring point and the initial route is an acute angle, then retain the modification; if the fuel consumption of the second path is greater than or equal to the fuel consumption of the first path, then cancel the modification;

[0127] Step 6: Determine whether the current number of iterations is less than the maximum number of iterations. If so, continue to execute step 2. If not, end the iteration and obtain the optimal route in the RRT* tree according to the Dijkstra algorithm.

[0128] In an optional implementation, the route planning module 34 is further used for:

[0129] Taking each of the waypoints as the center of the circle, calculating the radius according to a preset length, and establishing a circular sampling range for each of the waypoints;

[0130] The sampling points are obtained by randomly sampling in the circular sampling range of all the waypoints.

[0131] In an optional implementation, the total fuel consumption calculation module 33 is used to:

[0132] The edge weights of all the route edges are added up to obtain the total fuel consumption of flying along the initial route.

[0133] In a third aspect, an embodiment of the present invention provides an electronic device, see Figure 4 , which is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0134] like Figure 4 As shown, the device includes:

[0135] A memory 41, used for storing computer programs;

[0136] A processor 42, configured to execute the computer program;

[0137] Wherein, when the processor 42 executes the computer program, the route planning method as described in any of the above embodiments is implemented.

[0138] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory 41 and executed by the processor 42 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0139] The processor 42 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0140] The memory 41 can be used to store the computer program and / or module, and the processor 42 realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory 41, and calling the data stored in the memory 41. The memory 41 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory 41 can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0141] It should be noted that the above electronic device includes, but is not limited to, a processor and a memory. Those skilled in the art can understand that Figure 4 The structural diagram is merely an example of the electronic device described above and does not constitute a limitation on the electronic device, and may include more components than shown in the figure, or a combination of certain components, or different components.

[0142] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed, the route planning method described in any of the above embodiments is implemented.

[0143] It should be understood that the present invention implements all or part of the processes in the above-mentioned route planning method, and can also be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned route planning method can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0144] The above description is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto. It should be pointed out that for those skilled in the art, several equivalent obvious variations and / or equivalent substitutions can be made without departing from the technical principles of the present invention. These obvious variations and / or equivalent substitutions should also be regarded as the protection scope of the present invention.

Claims

1. A route planning method, characterized in that: include: Preprocess the acquired initial route to obtain multiple route edges; Acquire route information and weather information, and calculate the edge weight of each route edge according to the route information and the weather information; Calculate the total fuel consumption of flying along the initial route based on the edge weight; Taking the minimum total fuel consumption as the optimization goal, the initial route is optimized by using the RRT* algorithm to obtain the optimal route; The method of optimizing the initial route by taking the minimum total fuel consumption as the optimization target and using the RRT* algorithm to obtain the optimal route includes the following steps: Step 1: construct an RRT* tree, initialize the root node and the maximum number of iterations of the RRT* tree; Step 2: randomly sampling to obtain a sampling point, connecting the sampling point with the node closest to the sampling point in the RRT* tree to obtain a connecting line, generating a new node on the connecting line, and obtaining a set of neighboring points of the new node in the RRT* tree; Step 3: Calculate the fuel consumption corresponding to the line connecting each neighboring point in the neighboring point set and the new node; Step 4: taking the adjacent point corresponding to the line with the minimum fuel consumption and an acute angle with the initial route as the parent node of the new node, adding the new node to the RRT* tree, and calculating the fuel consumption of the first path from the root node to the new node; Step 5: traverse all neighboring points in the neighboring point set, and for each neighboring point, modify the parent node of the neighboring point to the new node, and calculate the fuel consumption of the second path from the root node to the neighboring point via the new node. If the fuel consumption of the second path is less than the fuel consumption of the first path and the angle between the line connecting the new node and the neighboring point and the initial route is an acute angle, then retain the modification; if the fuel consumption of the second path is greater than or equal to the fuel consumption of the first path, then cancel the modification; Step 6: Determine whether the current number of iterations is less than the maximum number of iterations. If so, continue to execute step 2. If not, end the iteration and obtain the optimal route in the RRT* tree according to the Dijkstra algorithm.

2. The route planning method according to claim 1, characterized in that: The obtained initial route is preprocessed to obtain multiple route edges, including: Generate a great circle route between the starting point and the target point, and use the great circle route as the initial route; The initial route is divided according to a preset distance to obtain a plurality of waypoints, and the waypoints are sequentially connected to obtain a plurality of route edges.

3. The route planning method according to claim 1, characterized in that: The calculating the edge weight of each of the route edges according to the route information and the weather information comprises: Calculate the fuel flow of the aircraft at each of the waypoints and the flight time at each of the wayside based on the route information and the weather information; The edge weight of each of the route edges is calculated according to the flight time and the fuel flow.

4. The route planning method according to claim 3, characterized in that: The step of calculating the fuel flow of the aircraft at each of the waypoints and the flight time at each of the waysides based on the route information and the weather information comprises: Based on the route information and the meteorological information, obtaining a heading angle, a wind temperature and a wind speed; Calculating the weight of the aircraft at each of the waypoints according to the distance between the current waypoint and the target point, the average fuel consumption per unit distance and the fuel-free weight of the aircraft; Calculating the fuel flow of the aircraft at each of the waypoints according to the weight of the aircraft, the current flight altitude and the wind temperature; Based on the fuel flow rate, a corresponding Mach number in an aircraft performance table is obtained, and the true air speed of the aircraft is calculated according to the Mach number and the wind temperature; The ground speed is calculated according to the true airspeed of the aircraft, the wind speed, and the heading angle, and the flight time of the aircraft on each of the airways is calculated according to the airway length of each of the airways and the ground speed.

5. The route planning method according to claim 1, characterized in that: The sampling points are obtained by the following steps: Taking each of the waypoints as the center of the circle, calculating the radius according to a preset length, and establishing a circular sampling range for each of the waypoints; The sampling points are obtained by randomly sampling in the circular sampling range of all the waypoints.

6. The route planning method according to claim 1, characterized in that: The calculating the total fuel consumption of flying along the initial route based on the edge weights includes: The edge weights of all the route edges are added up to obtain the total fuel consumption of flying along the initial route.

7. A route planning device, characterized in that: include: A preprocessing module is used to preprocess the acquired initial route to obtain multiple route edges; An edge weight calculation module, used for obtaining route information and weather information, and calculating the edge weight of each route edge according to the route information and weather information; A total fuel consumption calculation module, used for calculating the total fuel consumption of flying along the initial route based on the edge weight; A route planning module is used to optimize the initial route by using the RRT* algorithm with the minimum total fuel consumption as the optimization target to obtain the optimal route; The method of optimizing the initial route by taking the minimum total fuel consumption as the optimization target and using the RRT* algorithm to obtain the optimal route includes the following steps: Step 1: construct an RRT* tree, initialize the root node and the maximum number of iterations of the RRT* tree; Step 2: randomly sampling to obtain a sampling point, connecting the sampling point with the node closest to the sampling point in the RRT* tree to obtain a connecting line, generating a new node on the connecting line, and obtaining a set of neighboring points of the new node in the RRT* tree; Step 3: Calculate the fuel consumption corresponding to the line connecting each neighboring point in the neighboring point set and the new node; Step 4: taking the adjacent point corresponding to the line with the minimum fuel consumption and an acute angle with the initial route as the parent node of the new node, adding the new node to the RRT* tree, and calculating the fuel consumption of the first path from the root node to the new node; Step 5: traverse all neighboring points in the neighboring point set, and for each neighboring point, modify the parent node of the neighboring point to the new node, and calculate the fuel consumption of the second path from the root node to the neighboring point via the new node. If the fuel consumption of the second path is less than the fuel consumption of the first path and the angle between the line connecting the new node and the neighboring point and the initial route is an acute angle, then retain the modification; if the fuel consumption of the second path is greater than or equal to the fuel consumption of the first path, then cancel the modification; Step 6: Determine whether the current number of iterations is less than the maximum number of iterations. If so, continue to execute step 2. If not, end the iteration and obtain the optimal route in the RRT* tree according to the Dijkstra algorithm.

8. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to execute the computer program; Wherein, when the processor executes the computer program, the route planning method as described in any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the route planning method according to any one of claims 1 to 6 is implemented.

Images