Flight plan conflict detection method based on three-dimensional subdivision grid and related device thereof

Abstract

The invention relates to the technical field of airspace flight plan management, and provides a flight plan conflict detection method based on a three-dimensional subdivision grid and a related device thereof. The method comprises the following steps: discretizing flight plan track data and limited flight area data to obtain three-dimensional subdivision grid data of the flight plan track data and the limited flight area data; a grid buffer area algorithm and the distance of the grid buffer area are used for generating a flight plan track and a grid buffer area for limiting the three-dimensional subdivision grid data of the flight area; dividing the three-dimensional subdivision grid data and the gridding buffer area of the flight plan track and the three-dimensional subdivision grid data and the gridding buffer area of the limited flight area into a plurality of detection blocks based on the three-dimensional subdivision grid hierarchy; and for each detection block, traversing the three-dimensional subdivision grids of the flight plan track data at each moment to obtain conflict detection results in the detection blocks, and outputting attribute information of the three-dimensional subdivision grids with conflicts. The problems that space-time relation calculation is dense, invalid redundant calculation is more, and the parallel optimization effect is poor can be solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of airspace flight plan management, and in particular relates to a flight plan conflict detection method based on a three-dimensional grid and a related device thereof. Background Art

[0002] Before an aircraft takes off, each aircraft user needs to report the flight plan to the air traffic control department in advance. The air traffic control department calculates the flight trajectory of the aircraft based on the flight plan and conducts flight plan conflict detection: first, detects potential conflicts between the flight plan path and restricted flight airspace, and second, detects potential conflicts between two flight plans. Flight plan conflict detection is an important means of identifying unsafe and non-compliant flight factors in advance, and is a prerequisite for subsequent conflict mediation.

[0003] At present, flight plan conflict detection mainly uses vector calculation methods, which have the following problems: intensive spatiotemporal relationship calculations, many invalid redundant calculations, and poor parallel optimization effects.

[0004] (1) The space-time relationship is computationally intensive. The vector calculation method involves a large number of spherical distance and angle relationship calculations, which are complex steps and repeatedly calculate the space-time relationship between two targets at all times. After programming, it takes up a lot of processing performance and memory space, and the speed is slow.

[0005] (2) There are many invalid redundant calculations. The vector calculation method has a weak perception of the relative positions between aircrafts. It is almost necessary to calculate all possible time-space relationship pairs in a traversal form. The lack of pruning algorithm leads to many redundant judgments that are far from meeting the interval requirements but are still laborious to calculate.

[0006] (3) The parallel optimization effect is poor. The vector calculation method adopts the management concept of flight plan objects and mainly uses linear sequential calculation. It is difficult to interoperate with the gridded airspace management system and lacks attempts to carry out divide-and-conquer parallel optimization in the form of grid data. Summary of the invention

[0007] The present invention overcomes one of the deficiencies of the prior art and provides a flight plan conflict detection method based on a three-dimensional grid and a related device thereof, which can solve the current problems of intensive spatiotemporal relationship calculations, a large number of invalid redundant calculations, and poor parallel optimization effects.

[0008] According to one aspect of the present disclosure, a flight plan conflict detection method based on a three-dimensional grid is proposed, the method comprising: Discretize the flight plan track data and the restricted flight area data to obtain three-dimensional grid data of the flight plan track data and the restricted flight area data respectively; Determine the distance of the grid buffer based on the flight plan interval requirement, and generate the grid buffer of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data by using the grid buffer algorithm and the distance of the grid buffer; Based on the stereoscopic grid level, the flight plan track stereoscopic grid data and the gridded buffer, and the restricted flight area stereoscopic grid data and the gridded buffer, are divided into a plurality of detection blocks respectively; For each detection block, traverse the three-dimensional grid of each flight plan track data at each time to obtain the conflict detection result in each detection block; Based on the conflict detection result in each detection block, the attribute information of the conflicting stereo mesh in the detection block is output.

[0009] In a possible implementation, after generating the gridding buffer of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data, the method further includes: Based on grid set operations, the intersection set between the three-dimensional subdivision grid of the flight plan track and the gridded buffers of other three-dimensional subdivision grids of the flight plan track is solved to obtain a first grid intersection; the intersection set between the three-dimensional subdivision grid of the flight plan track and the gridded buffers of the three-dimensional subdivision grids of each restricted flight area is solved to obtain a second grid intersection.

[0010] In a possible implementation, determining the distance of the gridded buffer zone based on the flight plan interval requirement includes: The distance of the gridded buffer zone is determined based on the flight plan spacing requirement and the flight plan type / restricted flight area type.

[0011] In a possible implementation, traversing the three-dimensional grid of each flight plan track data at each time to obtain the conflict detection result in each detection block includes: For each three-dimensional grid of flight plan track data in the second grid intersection, if the current moment of the three-dimensional grid of the flight plan track data is within the time period of the restricted flight area, there is a conflict in the detection block; For each three-dimensional decomposition grid of the flight plan track data in the first grid intersection, the spatial-temporal relationship between the three-dimensional decomposition grids of different flight plan track grids is calculated using three-dimensional decomposition grid coding algebra, and the conflict result within the detection block is determined by comparing with the flight interval rule.

[0012] In a possible implementation, the space-time relationship includes a relative position relationship, a heading angle relationship, a speed relationship, and a time interval relationship.

[0013] In a possible implementation, after calculating the spatiotemporal relationship between the three-dimensional subdivision grids of different flight plan track grids, determining the heading relationship between the two flight plan tracks, and calculating the time interval relationship and the distance interval relationship between the two flight plan tracks; According to the time interval relationship and distance interval relationship between the two flight plan tracks, the flight interval rule is compared to determine whether the two flight plan tracks in the detection block violate the flight interval rule. If the flight interval rule is violated, there is a conflict in the detection block, and the violation item and the specific violation reason are recorded.

[0014] In a possible implementation, the attribute information of the three-dimensional grid includes grid code, conflict time, flight plan ID, restricted flight area ID, violated flight interval rules, specific violation reasons and violation items.

[0015] According to another aspect of the present disclosure, a flight plan conflict detection device based on a three-dimensional grid is proposed, the device comprising: A discretization module is used to discretize the flight plan track data and the restricted flight area data to obtain three-dimensional grid data of the flight plan track data and the restricted flight area data respectively; A grid buffer generation module, used to determine the distance of the grid buffer based on the flight plan interval requirement, and to generate a grid buffer of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data by using a grid buffer algorithm and the distance of the grid buffer; A division module, for dividing the flight plan track stereoscopic division grid data and the gridded buffer, and the restricted flight area stereoscopic division grid data and the gridded buffer into a plurality of detection blocks based on the stereoscopic division grid level; A traversal module is used to traverse the three-dimensional grid of each flight plan track data at each moment for each detection block to obtain the conflict detection result in each detection block; The output module is used to output the attribute information of the conflicting stereo mesh in each detection block based on the conflict detection result in the detection block.

[0016] According to another aspect of the present disclosure, an electronic device is provided, the device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described above when executing the program.

[0017] According to another aspect of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0018] The flight plan conflict detection method based on stereoscopic grid division disclosed in the present invention discretizes the flight plan track data and the restricted flight area data to obtain the stereoscopic grid data of the flight plan track data and the restricted flight area data respectively; determines the distance of the grid buffer based on the flight plan interval requirement, and generates the grid buffer of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data by using the grid buffer algorithm and the distance of the grid buffer; divides the flight plan track stereoscopic grid data and the grid buffer, as well as the restricted flight area stereoscopic grid data and the grid buffer into a plurality of detection blocks based on the stereoscopic grid division level; for each detection block, traverses the stereoscopic grid of each flight plan track data at each time to obtain the conflict detection result in each detection block; based on the conflict detection result in each detection block, outputs the attribute information of the conflicting stereoscopic grid in the detection block. It can solve the current problems of intensive calculation of spatiotemporal relationship, more invalid redundant calculation, and poor parallel optimization effect.

[0019] Other optional features and technical effects of the embodiments of the present invention are partially described below, and partially can be understood by reading this document. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 A flow chart of a flight plan conflict detection method based on a three-dimensional grid according to an embodiment of the present disclosure is shown; Figure 2 A schematic diagram showing the relationship between the gridding buffers of the three-dimensional grid of the flight plan track according to an embodiment of the present disclosure is shown; Figure 3 A schematic diagram showing the relationship between the three-dimensional grid of the flight plan track and the gridding buffer of the three-dimensional grid data of the flight area according to an embodiment of the present disclosure; Figure 4 A schematic diagram of block detection areas of a three-dimensional grid of a flight plan track according to an embodiment of the present disclosure is shown; Figure 5 A schematic diagram of flight interval rules of a three-dimensional grid of a flight plan track according to an embodiment of the present disclosure is shown; Figure 6A structural diagram of a flight plan conflict detection device based on a three-dimensional grid according to an embodiment of the present disclosure is shown; Figure 7 A schematic diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific implementation methods and drawings. Here, the exemplary implementation methods of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0023] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0024] In addition, the steps shown in the flowchart of the accompanying drawings can be executed in a computer such as a set of computer executable instructions. Also, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described can be performed in a sequence different from that here.

[0025] Figure 1 FIG. 1 shows a flow chart of a flight plan conflict detection method based on a three-dimensional grid according to an embodiment of the present disclosure. Figure 1 As shown, the method may include: Step S1: discretizing the flight plan track data and the restricted flight area data to obtain three-dimensional grid data of the flight plan track data and the restricted flight area data respectively.

[0026] Figure 2 A schematic diagram showing the relationship between the gridding buffers of the three-dimensional grid of the flight plan track according to an embodiment of the present disclosure is shown; Figure 3 A schematic diagram showing the relationship between a three-dimensional mesh of a flight plan track and a gridded buffer of three-dimensional mesh data of a flight area according to an embodiment of the present disclosure is shown.

[0027] The flight plan track is calculated based on the information recorded in the flight plan, and then the flight plan track data and the restricted flight area data are discretized to obtain the three-dimensional grid data of the flight plan track data and the three-dimensional grid data of the restricted flight area data. Among them, the gridding operation can refer to the method of constructing gridded flight plan data based on three-dimensional gridding proposed by Peking University in CN118246640B, which will not be repeated here. For example, Table 1 gives the grid data of flight plan IDs A and D, Figure 2 Table 2 shows the grid data of the three-dimensional subdivision of the track data of the flight plan IDs A and D; Table 2 gives the airspace grid information data of the restricted flight area ID B, Figure 3 The three-dimensional mesh data of the restricted flight area ID B is shown.

[0028] Table 1 Grid data for flight plan IDs A and D

[0029] Table 2 Airspace grid information data for restricted flight area ID B

[0030] In one example, the stereo grid data of the flight plan track data and the restricted flight area data can use the 15-level 1-point GeoSOT grid, with a grid size of about 1.5 km. The level and size of the stereo grid can be selected from the corresponding grid level of other global discrete grid systems as needed, and no limitation is made here.

[0031] By discretizing the flight plan trajectory data and restricted flight area data, the three-dimensional grid data of the flight plan trajectory data and restricted flight area data are obtained, which can be well connected to the airspace grid management system to enhance the grid management capability and grid computing of the flight plan.

[0032] Step S2: Determine the distance of the grid buffer based on the flight plan interval requirement, and generate a grid buffer of the flight plan track stereo grid data and the restricted flight area stereo grid data using the grid buffer algorithm and the distance of the grid buffer.

[0033] Among them, the distance of the grid buffer is determined based on the flight plan interval requirements, including: determining the distance of the grid buffer based on the flight plan interval requirements and the flight plan type / restricted flight area type. For example, the buffer distance of the flight plan needs to be selected according to the interval requirements and the flight plan type. If there are no special requirements, a buffer distance of 40km can be selected as a fallback buffer distance; the buffer distance of the restricted flight area also needs to be selected according to the interval requirements and the area type. If there are no special requirements, a buffer distance of 40km can be selected as a fallback buffer distance.

[0034] Based on the existing grid buffer generation algorithm, according to the maximum interval requirements in the flight interval regulations and the specific project requirements of flight plan conflict detection, the appropriate buffer width is selected to construct the grid buffer of each grid set. Figure 2 As shown, the gridded buffer is generated for the track data with flight plan IDs A and D based on the existing grid buffer generation algorithm, wherein the dark gray grid is the gridded buffer set E of the grid set D of the track with flight plan ID D. Figure 3 As shown, a gridded buffer zone is generated based on the existing grid-based buffer zone generation algorithm for the three-dimensional mesh data with the restricted flight area B, wherein the dark grey grid is the gridded buffer zone set C with the restricted flight area B.

[0035] In one example, after generating the gridding buffer of the flight plan track stereo grid data and the restricted flight area stereo grid data, the method further includes: Based on grid set operations, the intersection set between the three-dimensional decomposition grid of the flight plan track and the gridded buffers of other three-dimensional decomposition grids of the flight plan track is solved to obtain a first grid intersection; the intersection set between the three-dimensional decomposition grid of the flight plan track and the gridded buffers of the three-dimensional decomposition grids of each restricted flight area is solved to obtain a second grid intersection.

[0036] For example, based on the set operation between grid sets, the stereoscopic grid sets of each flight plan trajectory data and the grid buffer sets of the stereoscopic grid sets of other flight plan trajectory data are intersected pairwise to obtain a first grid intersection. The stereoscopic grid sets of each flight plan trajectory data and the grid buffer sets of the stereoscopic grid sets of the restricted flight area are intersected pairwise to obtain a second grid intersection. The situations in which the stereoscopic grid of each flight plan trajectory data is intersected and hit by the grid buffers of the stereoscopic grid sets of other flight plan trajectory data (including other flight plan grids or the restricted flight area grids themselves) are recorded, and the intersection grids are recorded at the same time. These intersection grids (the first grid intersection and the second grid intersection) are the grids with potential conflicts that are the focus of subsequent conflict detection. Figure 2 As shown in FIG. 1 , a schematic diagram of the intersection between the track grid with flight plan ID A and the gridded buffer zone E of the track grid with flight plan ID D is indicated by letters AD. Figure 3 As shown in FIG. 1 , a schematic diagram of the intersection between the track grid with flight plan ID A and the gridded buffer zone C of the airspace grid with restricted flight area ID B is indicated by letters AB. Table 3 gives an example of a potential conflict grid data table.

[0037] Table 3 Example of potential conflict grid data table

[0038] Step S3: Based on the stereoscopic grid level, the flight plan track stereoscopic grid data and gridded buffer, and the restricted flight area stereoscopic grid data and gridded buffer are divided into a plurality of detection blocks respectively.

[0039] This method is similar to the sliding detection window method in the field of digital image processing. It uses the multi-level characteristics of the stereo grid coding to delineate the block detection area (detection block). There is a certain overlap between the detection blocks, and the size can be set to the maximum flight interval distance as needed, and then the gridded flight plan data in each detection block is reorganized.

[0040] Figure 4 A schematic diagram of block detection areas of a three-dimensional grid of a flight plan track according to an embodiment of the present disclosure is shown.

[0041] like Figure 4 As shown, each dotted box is an example of a detection block, with a size of 5×5 and an interval span of 3. There are a total of 66 block detection areas (detection blocks) in 6 rows×11 columns, of which 18 block detection areas (semi-transparent gray) have potential conflict grids (light black with Latin letter marks) inside. The gray fill marks are detection blocks with potential conflict grids inside after the track data / restricted flight area data is gridded in step S2. There are a total of 18 detection blocks, covering 23 potential conflict grids. Among all potential conflict grids, AD is marked as Figure 2 The intersection grid of the buffer set of the flight plan track grid set A and the flight plan track grid set D is marked as AB. Figure 3 DA is the intersection grid of the flight plan track grid set A and the buffer set of the restricted flight area grid B, DA is the intersection grid of the flight plan track grid set D and the buffer set of the flight plan track grid set A, and DB is the intersection grid of the flight plan track grid set D and the buffer set of the restricted flight area grid B.

[0042] Table 4 gives an example of the detection block data organization. The detection area of ​​the detection block ID G10031 is Figure 4 The detection area with potential conflicting meshes in the first detection area of ​​the sixth row has two potential conflicting meshes marked as AB. The detection area with detection block ID G00233 is Figure 4 The detection area with potential conflicting mesh inside the third one in the fourth row has 7 potential conflicting meshes marked as AB, AD, DA, and DB.

[0043] Table 4 Detection block data organization data table

[0044] Subsequently, each detection block is used as a detection unit to detect the specific spatiotemporal relationship between each flight plan object and its potential conflicting object at each moment in each detection block. No detection calculation across detection blocks is performed to avoid redundant and invalid calculations.

[0045] For example, in the processing of civil aviation flight plan conflict detection requirements, different block detection area (detection block) sizes and intervals are selected according to the actual detection speed requirements. The larger the block detection area (detection block) and the smaller the interval, the slower the detection and the less likely it is to miss a detection. The following are three possible block detection area (detection block) division methods: (1) 3 degrees east-west × 2 degrees north-south, 3×2 GeoSOT 9-level 1-degree grids, which are approximately 220 km squares in mid-latitudes, with detection area spacing of 1 degree east-west and 1 degree north-south, and an overlap of approximately 100 km. (2) 1 degree 32 minutes east-west × 1 degree north-south, 3×2 GeoSOT 10-level 32-minute grids, which are approximately 110 km squares in mid-latitudes, with detection area spacing of 32 minutes east-west and 32 minutes north-south, and an overlap of approximately 50 km. (3) 48 minutes east-west × 32 minutes north-south, 3×2 GeoSOT 11-level 16-minute grids, which are approximately 55 km squares in mid-latitudes. The distance between detection areas is 16 minutes east-west and 16 minutes north-south, with an overlap of about 25 km.

[0046] Step S4: For each detection block, traverse the three-dimensional grid of each flight plan track data at each time to obtain the conflict detection result in each detection block.

[0047] Traverse each block detection area (detection block) in parallel. If the grid buffer data preprocessing in step S2 is skipped, process all block detection areas (detection blocks). If the current block detection area (detection block) does not contain data hit by the intersection operation in step S2 (i.e., there is no result when searching the block detection area (detection block) data organization data table in Table 4 with the detection block ID), it means that there is no potential conflict grid in the (detection block) and no detection is required, so the detection area can be skipped. If there is only potential conflict between flight plans in the current block detection area (detection block) and there is no overlap between the time periods of the flight plans, it means that the flight interval controlled by the buffer distance has been satisfied between all flight plans in the block detection area (detection block) at each moment, so the block detection area (detection block) can be skipped.

[0048] Specifically, traversing the three-dimensional grid of each flight plan track data at each time, and obtaining the conflict detection result in each detection block, may include: For each three-dimensional grid of flight plan track data in the second grid intersection, if the current moment of the three-dimensional grid of flight plan track data is within the time period of the restricted flight area, a conflict exists in the detection block; For each three-dimensional grid of flight plan track data in the first grid intersection, the spatial-temporal relationship between the three-dimensional grids of different flight plan track grids is calculated using the three-dimensional grid coding algebra, and the conflict result within the detection block is determined by comparing the flight interval rule. The spatial-temporal relationship may include relative position relationship, heading angle relationship, speed relationship and time interval relationship.

[0049] For example, first, the interval judgment between the three-dimensional grid of the flight plan track data and the gridded buffer of the three-dimensional grid of the restricted flight area is processed. Since the set intersection preprocessing between the buffers has been completed in step S2, for the potential conflict object is the potential conflict grid of the restricted flight area, it is only necessary to judge whether the three-dimensional grid of the flight plan track data is in the restricted time period of the restricted flight area at the current moment. If the current moment is in the restricted time period, it means that at this moment, the flight plan has a conflict between this grid position and the restricted flight area, and the conflict is recorded. Table 5 shows the detection block conflict detection result data, where the first two rows in Table 5 give two judgment result examples, the first row corresponds to the first row in Table 4, and the second row corresponds to the seventh row in Table 4.

[0050] Table 5 Conflict detection result data table

[0051] Secondly, grid coded algebraic calculation is used to obtain the relative position relationship, heading angle relationship, speed relationship, and time interval relationship between a pair of potential conflicting track grids, that is, between the two flight plans at this moment.

[0052] Coding algebraic operation is a method of directly using grid coding for calculation, which can directly obtain the positional relationship value between two grids. Different global discrete grid systems have different coding algebraic operators. After obtaining the spatiotemporal relationship between the two three-dimensional grids, it is necessary to determine in turn whether the two flight plan tracks are the same track, track intersection, or reverse flight.

[0053] After calculating the spatiotemporal relationship between the three-dimensional decomposed grids of different flight plan track grids, it is necessary to determine the heading relationship between the two flight plan tracks, and calculate the time interval relationship and distance interval relationship between the two flight plan tracks; based on the time interval relationship and distance interval relationship between the two flight plan tracks, compare the flight interval rules to determine whether the two flight plan tracks in the detection block violate the flight interval rules; if the flight interval rules are violated, there is a conflict in the detection block, and the violation items and specific reasons for the violation are recorded.

[0054] Figure 5 A schematic diagram of flight interval rules for a three-dimensional mesh of a flight plan trajectory according to an embodiment of the present disclosure is shown.

[0055] like Figure 5 The decision tree for judging some of the separation regulations shown is customized according to the actual use needs and business scenarios. For example, the violation details of two conflicting flight plan track stereoscopic grid data, the G0013132123202 track grid with flight plan ID fp03 and the G0013132132110 track grid with flight plan ID fp12 have a conflict in violation of Article 35 of the separation regulations. The conflict time is 2023-08-31T08:57:40. The reason for the conflict is that two aircraft with the same altitude track crossing should have a longitudinal interval of 10 minutes when crossing the center line of each other's route, but the current plan arrangement is only 2.48 minutes, which does not meet the requirements of the separation regulations.

[0056] Step S5: Based on the conflict detection result in each detection block, output the attribute information of the conflicting stereo mesh in the detection block.

[0057] The attribute information includes grid code, conflict time, flight plan ID, restricted flight area ID, violated flight interval rules, specific violation reasons and violation items.

[0058] Summarize all conflicting grid pairs in step S4, and output their conflict time, grid code, flight plan ID or restricted flight area ID, violated spacing rules, specific violation reasons, violation items and details, to facilitate subsequent other air traffic control operations. Since each conflicting pair has a grid code, it is very convenient to visualize the conflict location and relationship on the map.

[0059] The flight plan conflict detection method based on stereoscopic grid division disclosed in the present invention discretizes the flight plan track data and the restricted flight area data to obtain the stereoscopic grid data of the flight plan track data and the restricted flight area data respectively; determines the distance of the gridding buffer zone based on the flight plan interval requirement, and generates the gridding buffer zone of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data using the gridding buffer zone algorithm and the distance of the gridding buffer zone; divides the flight plan track stereoscopic grid data and the gridding buffer zone, as well as the restricted flight area stereoscopic grid data and the gridding buffer zone into a plurality of detection blocks based on the stereoscopic grid division level; for each detection block, traverses the stereoscopic grid division of each flight plan track data at each moment to obtain the conflict detection result in each detection block; based on the conflict detection result in each detection block, outputs the attribute information of the conflicting stereoscopic grid in the detection block. It can solve the current problems of intensive calculation of spatiotemporal relationship, more invalid redundant calculation, and poor parallel optimization effect.

[0060] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

[0061] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0062] Figure 6 FIG. 4 shows a structural diagram of a flight plan conflict detection device based on a three-dimensional grid according to an embodiment of the present disclosure; Figure 6 As shown, the healing device may include: The discretization module 701 is used to discretize the flight plan track data and the restricted flight area data to obtain three-dimensional grid data of the flight plan track data and the restricted flight area data respectively; A grid buffer generation module 702 is used to determine the distance of the grid buffer based on the flight plan interval requirement, and generate a grid buffer of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data using a grid buffer algorithm and the distance of the grid buffer; A division module 703 is used to divide the flight plan track stereoscopic division grid data and gridded buffer, and the restricted flight area stereoscopic division grid data and gridded buffer into a plurality of detection blocks based on the stereoscopic division grid level; A traversal module 704 is used to traverse the three-dimensional grid of each flight plan track data at each time for each detection block to obtain the conflict detection result in each detection block; The output module 705 is used to output the attribute information of the conflicting stereo mesh in each detection block based on the conflict detection result in each detection block.

[0063] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0064] Figure 7 Schematic diagram of the structure of the electronic device 3 provided in the embodiment of the present application. Figure 7 As shown, the electronic device 3 of this embodiment includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program 303, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 301 executes the computer program 303, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0065] Exemplarily, the computer program 303 may be divided into one or more modules / units, which are stored in the memory 302 and executed by the processor 301 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 303 in the electronic device 3.

[0066] The electronic device 3 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that Figure 7 It is only an example of the electronic device 3 and does not constitute a limitation of the electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0067] The processor 301 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 the processor may be any conventional processor, etc.

[0068] The memory 302 may be an internal storage unit of the electronic device 3, for example, a hard disk or memory of the electronic device 3. The memory 302 may also be an external storage device of the electronic device 3, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 3. Further, the memory 302 may also include both an internal storage unit and an external storage device of the electronic device 3. The memory 302 is used to store computer programs and other programs and data required by the electronic device. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0069] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0070] The exemplary systems and methods of the present invention have been specifically shown and described with reference to the above embodiments, which are merely examples of the best modes for implementing the present systems and methods. It will be appreciated by those skilled in the art that various changes may be made to the embodiments of the systems and methods described herein when implementing the present systems and / or methods without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A flight plan conflict detection method based on three-dimensional grid subdivision, characterized in that: The method comprises: Discretize the flight plan track data and the restricted flight area data to obtain three-dimensional grid data of the flight plan track data and the restricted flight area data respectively; Determine the distance of the grid buffer based on the flight plan interval requirement, and generate the grid buffer of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data by using the grid buffer algorithm and the distance of the grid buffer; Based on the stereoscopic grid level, the flight plan track stereoscopic grid data and the gridded buffer, and the restricted flight area stereoscopic grid data and the gridded buffer, are divided into a plurality of detection blocks respectively; For each detection block, traverse the three-dimensional grid of each flight plan track data at each time to obtain the conflict detection result in each detection block; Based on the conflict detection result in each detection block, the attribute information of the conflicting stereo mesh in the detection block is output.

2. The flight plan conflict detection method according to claim 1, characterized in that: After generating the gridding buffer of the flight plan track 3D grid data and the restricted flight area 3D grid data, it also includes: Based on grid set operations, the intersection set between the three-dimensional subdivision grid of the flight plan track and the gridded buffers of other three-dimensional subdivision grids of the flight plan track is solved to obtain a first grid intersection; the intersection set between the three-dimensional subdivision grid of the flight plan track and the gridded buffers of the three-dimensional subdivision grids of each restricted flight area is solved to obtain a second grid intersection.

3. The flight plan conflict detection method according to claim 1, characterized in that: Determining the distance of the gridded buffer zone based on the flight plan interval requirement includes: The distance of the gridded buffer zone is determined based on the flight plan spacing requirement and the flight plan type / restricted flight area type.

4. The flight plan conflict detection method according to claim 2, characterized in that: The traversal of the three-dimensional grid of each flight plan track data at each time to obtain the conflict detection result in each detection block includes: For each three-dimensional grid of flight plan track data in the second grid intersection, if the current moment of the three-dimensional grid of the flight plan track data is within the time period of the restricted flight area, there is a conflict in the detection block; For each three-dimensional decomposition grid of the flight plan track data in the first grid intersection, the spatial-temporal relationship between the three-dimensional decomposition grids of different flight plan track grids is calculated using three-dimensional decomposition grid coding algebra, and the conflict result within the detection block is determined by comparing with the flight interval rule.

5. The flight plan conflict detection method according to claim 4, characterized in that: The time-space relationship includes a relative position relationship, a heading angle relationship, a speed relationship and a time interval relationship.

6. The flight plan conflict detection method according to claim 4, characterized in that: After calculating the spatiotemporal relationship between the volumetric meshes of different flight plan track grids, including: Determine the heading relationship between two flight plan tracks, and calculate the time interval relationship and distance interval relationship between the two flight plan tracks; According to the time interval relationship and distance interval relationship between the two flight plan tracks, the flight interval rule is compared to determine whether the two flight plan tracks in the detection block violate the flight interval rule. If the flight interval rule is violated, there is a conflict in the detection block, and the violation item and the specific violation reason are recorded.

7. The flight plan conflict detection method according to claim 6, characterized in that: The attribute information of the three-dimensional subdivision grid includes grid code, conflict time, flight plan ID, restricted flight area ID, violated flight interval rules, specific violation reasons and violation items.

8. A flight plan conflict detection device based on three-dimensional grid division, characterized in that: The device comprises: A discretization module is used to discretize the flight plan track data and the restricted flight area data to obtain three-dimensional grid data of the flight plan track data and the restricted flight area data respectively; A grid buffer generation module, used to determine the distance of the grid buffer based on the flight plan interval requirement, and to generate a grid buffer of the flight plan track stereoscopic grid data and the restricted flight area stereoscopic grid data by using a grid buffer algorithm and the distance of the grid buffer; A division module, for dividing the flight plan track stereoscopic division grid data and the gridded buffer, and the restricted flight area stereoscopic division grid data and the gridded buffer into a plurality of detection blocks based on the stereoscopic division grid level; A traversal module is used to traverse the three-dimensional grid of each flight plan track data at each moment for each detection block to obtain the conflict detection result in each detection block; The output module is used to output the attribute information of the conflicting stereo mesh in each detection block based on the conflict detection result in the detection block.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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