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

Abstract

The application relates to the technical field of airspace flight plan management, and provides a flight plan conflict detection method based on a three-dimensional dissected grid and a related device thereof. Flight plan track data and restricted flight area data are discretized to obtain three-dimensional dissected grid data of the flight plan track data and the restricted flight area data; a grid buffer algorithm and a grid buffer distance are used to generate a grid buffer of the three-dimensional dissected grid data of the flight plan track and the restricted flight area; based on a three-dimensional dissected grid level, the three-dimensional dissected grid data of the flight plan track and the grid buffer and the three-dimensional dissected grid data of the restricted flight area and the grid buffer are divided into a plurality of detection blocks; for each detection block, the three-dimensional dissected grid of the flight plan track data at each time is traversed to obtain a conflict detection result in the detection block, and attribute information of the three-dimensional dissected grid with the conflict is output. The problems of time-space relationship calculation intensity, more invalid and redundant calculation, and poor parallel optimization effect can be solved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of airspace flight plan management, and particularly relates to a flight plan conflict detection method based on a three-dimensional dissected grid and a related device thereof. BACKGROUND

[0002] Before takeoff, each aircraft using unit needs to report a flight plan to an air traffic control department in advance, and the air traffic control department calculates the flight trajectory of the aircraft according to the flight plan to carry out flight plan conflict detection: one is to detect the potential conflict between the flight plan path and the restricted flight airspace, and the other is to detect the potential conflict between two flight plans. Flight plan conflict detection is an important means to identify unsafe and non-compliant flight factors in advance and is a prerequisite for subsequent conflict mediation.

[0003] Currently, flight plan conflict detection mainly uses a vector calculation method, which has the following problems: time-space relationship calculation is intensive, there is a lot of invalid redundant calculation, and parallel optimization effect is poor.

[0004] (1) Time-space relationship calculation is intensive. The vector calculation method process involves a large number of spherical distance and angle relationship calculations, the steps are complex, and the time-space relationship of all pairs of targets at all times is repeatedly calculated, which requires a large processing performance and memory space after programming implementation, and the speed is slow.

[0005] (2) There is a lot of invalid redundant calculation. The relative position perception between aircrafts is weak when the vector calculation method is calculated, and almost all possible time-space relationship pairs need to be calculated in a traversal form, and there is a lack of pruning algorithm, resulting in a lot of redundant judgments that have already far met the interval requirements but still need to be calculated.

[0006] (3) Parallel optimization effect is poor. The vector calculation method adopts a management idea for flight plan objects, mainly uses a linear sequential calculation method, is difficult to interoperate with a grid-based airspace management system, and lacks attempts to carry out divide-and-conquer parallel optimization in the form of grid data. SUMMARY

[0007] The present application overcomes one of the deficiencies of the prior art and provides a flight plan conflict detection method based on a three-dimensional dissected grid and a related device thereof, which can solve the problems of current time-space relationship calculation intensity, a lot of invalid redundant calculation, and poor parallel optimization effect.

[0008] According to an aspect of the present disclosure, a flight plan conflict detection method based on a three-dimensional dissected grid is provided, and the method comprises:

[0009] Discretizing flight plan track data and restricted flight area data to obtain three-dimensional dissected grid data of the flight plan track data and the restricted flight area data, respectively;

[0010] determine a distance of a grid buffer zone based on flight plan interval requirements, generate a flight plan track solid subdivision grid data and a restricted flight area solid subdivision grid data using a grid buffer zone algorithm and the distance of the grid buffer zone;

[0011] based on a solid subdivision grid level, divide the flight plan track solid subdivision grid data and the grid buffer zone, and the restricted flight area solid subdivision grid data and the grid buffer zone, into a plurality of detection blocks, respectively;

[0012] for each detection block, traverse each flight plan track data solid subdivision grid at each time to obtain a conflict detection result in each detection block;

[0013] based on the conflict detection result in each detection block, output attribute information of a solid subdivision grid with a conflict in the detection block.

[0014] In a possible implementation, after the grid buffer zone of the flight plan track solid subdivision grid data and the restricted flight area solid subdivision grid data is generated, the method further includes:

[0015] based on a grid set operation, solve an intersection set between the grid buffer zone of the flight plan track solid subdivision grid and the grid buffer zone of other flight plan track solid subdivision grids to obtain a first grid intersection, and solve an intersection set between the grid buffer zone of the flight plan track solid subdivision grid and the grid buffer zone of each restricted flight area solid subdivision grid to obtain a second grid intersection.

[0016] In a possible implementation, the determining the distance of the grid buffer zone based on the flight plan interval requirements includes:

[0017] based on the flight plan interval requirements and a flight plan type / restricted flight area type, determine the distance of the grid buffer zone.

[0018] In a possible implementation, the traversing each flight plan track data solid subdivision grid at each time to obtain a conflict detection result in each detection block includes:

[0019] for each flight plan track data solid subdivision grid in the second grid intersection, if a current time of the flight plan track data solid subdivision grid is within a time period of the restricted flight area, there is a conflict in the detection block;

[0020] for each flight plan track data solid subdivision grid in the first grid intersection, use a solid subdivision grid encoding algebra to calculate a space-time relationship between solid subdivision grids of different flight plan track grids, and judge a conflict result in the detection block by comparing with a flight interval rule.

[0021] In a possible implementation, the spatio-temporal relationship includes a relative position relationship, a heading angle relationship, a speed relationship, and a time interval relationship.

[0022] In a possible implementation, after the spatio-temporal relationship between the stereoscopic subdivision grids of different flight plan tracks is calculated, the heading relationship of two flight plan tracks is determined, and the time interval relationship and the distance interval relationship of the two flight plan tracks are calculated.

[0023] According to the time interval relationship and the distance interval relationship of the two flight plan tracks, it is determined whether the two flight plan tracks in the detection block violate the flight interval rule by referring to the flight interval rule, and if the flight interval rule is violated, there is a conflict in the detection block, and a violation entry and a specific violation reason are recorded.

[0024] In a possible implementation, the attribute information of the stereoscopic subdivision grid includes a grid code, a conflict time, a flight plan ID, a restricted flight area ID, a violated flight interval rule, a specific violation reason, and a violation entry.

[0025] According to another aspect of the present disclosure, a flight plan conflict detection device based on stereoscopic subdivision grids is provided, and the device includes:

[0026] A discretization module is configured to discretize flight plan track data and restricted flight area data to obtain stereoscopic subdivision grid data of the flight plan track data and the restricted flight area data, respectively.

[0027] A grid buffer generation module is configured to determine a distance of a grid buffer based on flight plan interval requirements, and generate a grid buffer of flight plan track stereoscopic subdivision grid data and restricted flight area stereoscopic subdivision grid data by using a grid buffer algorithm and the distance of the grid buffer.

[0028] A division module is configured to divide the flight plan track stereoscopic subdivision grid data and the grid buffer, and the restricted flight area stereoscopic subdivision grid data and the grid buffer, into a plurality of detection blocks, respectively, based on a stereoscopic subdivision grid level.

[0029] A traversal module is configured to traverse, for each detection block, a stereoscopic subdivision grid of each flight plan track data at each time to obtain a conflict detection result in each detection block.

[0030] An output module is configured to output attribute information of a stereoscopic subdivision grid with a conflict in each detection block based on a conflict detection result in the detection block.

[0031] 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 on the memory and executable on the processor, the processor implementing the method as described above when executing the program.

[0032] According to another aspect of the present disclosure, a computer readable storage medium is provided, the computer readable storage medium storing a computer program, the computer program implementing the method as described above when executed by a processor.

[0033] The flight plan conflict detection method based on stereoscopic subdivision grid of the present disclosure, by discretizing flight plan track data and restricted flight area data, respectively obtains stereoscopic subdivision grid data of flight plan track data and restricted flight area data; based on flight plan interval requirements, determines the distance of grid buffer zone, generates grid buffer zone of flight plan track stereoscopic subdivision grid data and restricted flight area stereoscopic subdivision grid data by using grid buffer zone algorithm and the distance of grid buffer zone; based on stereoscopic subdivision grid level, divides flight plan track stereoscopic subdivision grid data and grid buffer zone, and restricted flight area stereoscopic subdivision grid data and grid buffer zone into multiple detection blocks respectively; for each detection block, traverses each flight plan track data stereoscopic subdivision grid at each time to obtain conflict detection results in each detection block; based on the conflict detection results in each detection block, outputs attribute information of stereoscopic subdivision grid with conflict in the detection block. It can solve the problems of current time-space relationship calculation intensive, more invalid and redundant calculation, and poor parallel optimization effect.

[0034] Other optional features and technical effects of the embodiments of the present application are described below, and some can be understood by reading this document. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0036] Figure 1 A flow chart of the flight plan conflict detection method based on stereoscopic subdivision grid according to an embodiment of the present disclosure is shown;

[0037] Figure 2 A relationship diagram of the grid buffer zone of the stereoscopic subdivision grid of the flight plan track according to an embodiment of the present disclosure is shown;

[0038] Figure 3A schematic diagram of a relationship between a stereoscopic subdivision grid of a flight plan track and a grid-based buffer of flight region stereoscopic subdivision grid data is shown according to an embodiment of the present disclosure.

[0039] Figure 4 A schematic diagram of a partition detection region of a stereoscopic subdivision grid of a flight plan track is shown according to an embodiment of the present disclosure.

[0040] Figure 5 A schematic diagram of a flight interval rule of a stereoscopic subdivision grid of a flight plan track is shown according to an embodiment of the present disclosure.

[0041] Figure 6 A structural diagram of a flight plan conflict detection device based on a stereoscopic subdivision grid is shown according to an embodiment of the present disclosure.

[0042] Figure 7 A schematic diagram of an electronic device is shown according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions and advantages of the present application clearer, further detailed description will be given to the present application in combination with specific embodiments and drawings. Herein, the schematic embodiments of the present application and the description thereof are used to explain the present application, but not as a limitation to the present application.

[0044] The term "comprising" and variations thereof as used herein are intended to cover a non-exclusive inclusion, i.e., "including, but not limited to". Unless specifically stated, the term "or" means "and / or". The term "based on" means "based, at least in part, on". The terms "one 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. can refer to different or same objects. Other explicit and implicit definitions can also be included below.

[0045] In addition, the steps shown in the flowchart of the drawings can be executed in a computer such as a set of computer-executable instructions. Also, although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from here.

[0046] Figure 1 A flowchart of a flight plan conflict detection method based on a stereoscopic subdivision grid is shown according to an embodiment of the present disclosure. As shown in the figure, Figure 1 the method can include:

[0047] Step S1: Discretization processing is performed on flight plan track data and restricted flight region data, respectively obtaining stereoscopic subdivision grid data of the flight plan track data and the restricted flight region data.

[0048] Figure 2 Fig. 6 shows a schematic diagram of a relationship of a meshed buffer zone of a stereoscopic dissected grid of a flight plan track according to an embodiment of the present disclosure; Figure 3 Fig. 7 shows a schematic diagram of a relationship of a meshed buffer zone of a stereoscopic dissected grid of a flight plan track and a stereoscopic dissected grid data of a flight restricted area according to an embodiment of the present disclosure.

[0049] The flight plan track is calculated according to the information recorded in the flight plan, and then the flight plan track data and the flight restricted area data are discretized to obtain stereoscopic dissected grid data of the flight plan track data and stereoscopic dissected grid data of the flight restricted area data. The meshing operation can refer to a method of constructing meshed flight plan data based on a stereoscopic dissected grid proposed by Peking University in CN118246640B, which will not be repeated here. For example, Table 1 shows the grid data of flight plan IDs A and D, Figure 2 Fig. 4 shows stereoscopic dissected grid data of track data of flight plan IDs A and D; Table 2 shows airspace grid information data of a flight restricted area ID B, Figure 3 Fig. 5 shows stereoscopic dissected grid data of a flight restricted area ID B.

[0050] Table 1 Grid data of flight plan IDs A and D

[0051]

[0052] Table 2 Airspace grid information data of a flight restricted area ID B

[0053]

[0054] In an example, the stereoscopic dissected grid data of the flight plan track data and the flight restricted area data can use a GeoSOT grid of 15 levels and 1 division, and the grid size is about 1.5 km. The level and size of the stereoscopic dissected grid can be selected according to the needs of other global discrete grid systems, which will not be limited here.

[0055] By discretizing the flight plan track data and the flight restricted area data, the stereoscopic dissected grid data of the flight plan track data and the flight restricted area data can be well connected to the airspace grid management system, and the grid management capability and grid computing of the flight plan can be enhanced.

[0056] Step S2: determining the distance of the meshed buffer zone based on the flight plan interval requirement, and generating the meshed buffer zone of the stereoscopic dissected grid data of the flight plan track and the stereoscopic dissected grid data of the flight restricted area by using the grid buffer zone algorithm and the distance of the meshed buffer zone.

[0057] In the method, the distance of the grid buffer zone is determined based on the flight plan interval requirement, including: determining the distance of the grid buffer zone based on the flight plan interval requirement and the flight plan type / limited flight area type. For example, the buffer distance of the flight plan needs to be selected according to the interval requirement and the flight plan type, such as a bottom buffer distance of 40 km if there is no special requirement; the buffer distance of the limited flight area also needs to be selected according to the interval requirement and the area type, such as a bottom buffer distance of 40 km if there is no special requirement.

[0058] Based on the existing grid buffer generation algorithm, the maximum interval requirement in the flight interval regulation and the specific project requirements of the flight plan conflict detection are selected to select the appropriate buffer width to construct the grid buffer of each grid set. For example, Figure 2 As shown in the grid buffer generated by the existing grid buffer generation algorithm for the flight path data of the flight plan ID A and D, the dark gray grid is the grid buffer set E of the grid set D of the flight path of the flight plan ID D. As shown in Figure 3 As shown in the grid buffer generated by the existing grid buffer generation algorithm for the stereoscopic subdivision grid data of the limited flight area B, the dark gray grid is the grid buffer set C of the limited flight area B.

[0059] In an example, after generating the grid buffer of the flight plan path stereoscopic subdivision grid data and the limited flight area stereoscopic subdivision grid data, it further includes:

[0060] Based on the grid set operation, the intersection set between the grid buffer of the flight plan path stereoscopic subdivision grid and the grid buffer of other flight plan path stereoscopic subdivision grid is solved to obtain the first grid intersection; the intersection set between the grid buffer of the flight plan path stereoscopic subdivision grid and the grid buffer of each limited flight area stereoscopic subdivision grid is solved to obtain the second grid intersection.

[0061] For example, based on the set operation between the grid sets, the grid buffer sets of the stereoscopic subdivision grid sets of each flight plan path data and the stereoscopic subdivision grid sets of other flight plan path data are pairwise intersected to obtain the first grid intersection. The stereoscopic subdivision grid sets of each flight plan path data and the grid buffer sets of the limited flight area stereoscopic subdivision grid are pairwise intersected to obtain the second grid intersection. The situation that the stereoscopic subdivision grid of each flight plan path data is intersected by the grid buffer of the stereoscopic subdivision grid set of other flight plan path data (including other flight plan grid or limited flight area grid itself) is recorded, and the intersection grid is recorded. These intersection grids (the first grid intersection and the second grid intersection) are the grids with potential conflicts which are the focus of subsequent conflict detection. For example, Figure 2As shown, the intersection between the flight plan ID A track grid and the grid buffer E of flight plan ID D track grid is schematically shown, labeled with the letter AD. As Figure 3 As shown, the intersection between the flight plan ID A track grid and the grid buffer C of restricted airspace ID B is schematically shown, labeled with the letter AB. Table 3 gives an example of the potential conflict grid data table.

[0062] Table 3 Potential conflict grid data representation example

[0063]

[0064] Step S3: Based on the stereoscopic subdivision grid hierarchy, the flight plan track stereoscopic subdivision grid data and the grid buffer, and the restricted airspace stereoscopic subdivision grid data and the grid buffer, are respectively divided into a plurality of detection blocks.

[0065] This method is analogous to the sliding detection window method in the field of digital image processing, and utilizes the multi-level characteristics of stereoscopic subdivision grid coding to set the detection block. Among them, each detection block has a certain overlap, and the size can be set to the maximum flight interval distance as needed, and then the grid flight plan data in each detection block is reorganized.

[0066] Figure 4 A schematic diagram of the block detection area of the stereoscopic subdivision grid of the flight plan track according to an embodiment of the present disclosure is shown.

[0067] As shown in Figure 4 As shown, each dashed box is an example of a detection block, with a size of 5x5 and an interval span of 3, for a total of 6 rows x 11 columns, i.e. 66 block detection areas (detection blocks), of which 18 block detection areas (semi-transparent gray) have potential conflict grids (light black, with Latin letter labels) inside. The gray fill marks the detection blocks that have potential conflict grids inside after the grid flight track data / restricted airspace data of step S2, for a total of 18, covering 23 potential conflict grids. Among all the potential conflict grids, AD is identified as Figure 2 The intersection grid of the buffer set of flight plan track grid set A and flight plan track grid set D, AB is identified as Figure 3 The intersection grid of the buffer set of flight plan track grid set A and restricted airspace grid B, DA is identified as the intersection grid of the buffer set of flight plan track grid set D and flight plan track grid set A, and DB is identified as the intersection grid of the buffer set of flight plan track grid set D and restricted airspace grid B.

[0068] Table 4 gives an example of the detection block data organization. The detection area of detection block ID G10031 isFigure 4 The detection block with potential conflict grids in the first internal of the sixth row in the middle has two potential conflict grids marked as AB, and the detection block with detection block ID G00233 is Figure 4 The detection block with potential conflict grids in the third internal of the fourth row in the middle has seven potential conflict grids marked as AB, AD, DA, and DB.

[0069] Table 4 Detection block data organization data table

[0070]

[0071] Subsequently, each detection block is taken as a detection unit, and the specific space-time relationship between each flight plan object and its potential conflict object at each time point is detected in each detection block. No detection calculation across detection blocks is performed to avoid redundant and invalid calculations.

[0072] For example, in the civil aviation flight plan conflict detection demand processing, different sizes and intervals of the block detection area (detection block) are selected according to the actual detection speed requirement. The larger the block detection area (detection block) and the smaller the interval, the slower the detection, and the smaller the possibility of missing detection. Three possible block detection area (detection block) division methods are given below: (1) 3 degrees east-west x 2 degrees north-south, 9-level 1-degree grid of 3x2 GeoSOT, about 220km square in the middle latitude area, detection area interval 1 degree east-west, 1 degree north-south, overlap degree about 100km. (2) 1 degree 32 minutes east-west x 1 degree north, 10-level 32-minute grid of 3x2 GeoSOT, about 110km square in the middle latitude area, detection area interval 32 minutes east-west, 32 minutes north-south, overlap degree about 50km. (3) 48 minutes east-west x 32 minutes north, 11-level 16-minute grid of 3x2 GeoSOT, about 55km square in the middle latitude area, detection area interval 16 minutes east-west, 16 minutes north-south, overlap degree about 25km.

[0073] Step S4: For each detection block, traverse each flight plan track data solid subdivision grid at each time point to obtain the conflict detection result in each detection block.

[0074] Parallelly traverse each sub-block detection area (detection block), if step S2 grid buffer data preprocessing is skipped, process all sub-block detection areas (detection blocks). If the current sub-block detection area (detection block) does not contain data hit by the intersection operation in step S2 (i.e. no result is searched in the sub-block detection area (detection block) data organization data table of table 4 with detection block ID), it is indicated that there is no potential conflict grid in the (detection block), and there is no need to detect, so the detection area can be skipped. If there is only a potential conflict between flight plans in the current sub-block detection area (detection block) and there is no overlap between the time periods of the flight plans, it is indicated that all flight plans in the sub-block detection area (detection block) at each time have met the flight interval controlled by the buffer distance, so the sub-block detection area (detection block) can be skipped.

[0075] Specifically, traversing each flight plan track data stereoscopic subdivision grid at each time, the conflict detection result in each detection block can include:

[0076] For each flight plan track data stereoscopic subdivision grid in the second grid intersection, if the current time of the flight plan track data stereoscopic subdivision grid is in the time period of the restricted flight area, there is a conflict in the detection block;

[0077] For each flight plan track data stereoscopic subdivision grid in the first grid intersection, the spatiotemporal relationship between the stereoscopic subdivision grids of different flight plan track grids is calculated using stereoscopic subdivision grid encoding algebra, and the conflict result in the detection block is judged by comparing the flight interval rules. Wherein, the spatiotemporal relationship can include relative position relationship, heading angle relationship, speed relationship and time interval relationship.

[0078] For example, first, the interval judgment between the stereoscopic subdivision grid of flight plan track data and the grid buffer of the restricted flight area stereoscopic subdivision grid is processed. Since the intersection preprocessing of the buffer set in step S2 has been completed, for the potential conflict grid whose potential conflict object is the restricted flight area, it is only necessary to judge whether the current time of the flight plan track data stereoscopic subdivision grid is in the restricted time period of the restricted flight area. If the current time is in the restricted time period, it is indicated that there is a conflict between the flight plan at this time and the restricted flight area at this grid position, and the conflict is recorded. Table 5 shows the detection block conflict detection result data, wherein the first two rows of table 5 give two judgment result examples, the first row corresponds to the first row of table 4, and the second row corresponds to the seventh row of table 4.

[0079] Table 5 conflict detection result data table

[0080]

[0081] Secondly, the relative position relationship, heading angle relationship, speed relationship and time interval relationship between the two flight plans at this moment are obtained by using grid encoding algebraic calculation.

[0082] The encoding algebraic operation is a method of directly calculating using grid encoding, which can directly obtain the position relationship value between two grids. Different global discrete grid systems have different encoding algebraic operators. After obtaining the space-time relationship between two solid subdivision grids, it is necessary to determine which one of the three, i.e., the same flight path, flight path intersection, and reverse flight, the two flight plans are.

[0083] After calculating the space-time relationship between the solid subdivision grids of the flight plan track grids, it is necessary to determine the heading relationship of the two flight plans, calculate the time interval relationship and distance interval relationship of the two flight plans, and determine whether the two flight plans in the detection block violate the flight interval rules according to the time interval relationship and distance interval relationship of the two flight plans, and if the flight interval rules are violated, there is a conflict in the detection block, and the violation entry and specific violation reason are recorded.

[0084] Figure 5 A flight interval rule diagram of the solid subdivision grid of the flight plan track is shown according to an embodiment of the present disclosure.

[0085] As Figure 5 shown in the partial interval provision judgment decision tree, the judgment decision tree can be customized according to the business scenario according to the actual use needs. For example, the violation content details of the two flight plan track solid subdivision grid data with conflicts, the G0013132123202 track grid of flight plan ID fp03 and the G0013132132110 track grid of flight plan ID fp12 exist conflict of the thirty-fifth interval provision, the conflict time is 2023-08-31T08:57:40, and the conflict reason is that the two same height track crossing aircrafts should have a longitudinal interval of 10 minutes when crossing the other route center line, but under the current plan arrangement, only 2.48 minutes, which does not meet the interval provision requirements.

[0086] Step S5: Based on the conflict detection results in each detection block, the attribute information of the solid subdivision grid with conflict in the detection block is output.

[0087] Among them, the attribute information includes grid encoding, conflict time, flight plan ID, restricted flight area ID, violated flight interval rule, specific violation reason and violation entry.

[0088] All the conflict grid pairs in step S4 are summarized, and the conflict time, grid code, flight plan ID or restricted flight area ID, violated separation rule, specific violation reason, violation item and details are output, facilitating subsequent other air traffic control operation processing. Since each conflict pair has a grid code, the conflict position and relationship can be visualized on a map very conveniently.

[0089] The flight plan conflict detection method based on stereoscopic subdivision grid of the present disclosure, by discretizing the flight plan track data and the restricted flight area data, respectively obtains the stereoscopic subdivision grid data of the flight plan track data and the restricted flight area data; based on the flight plan separation requirement, determines the distance of the grid buffer zone, and generates the grid buffer zone of the flight plan track stereoscopic subdivision grid data and the restricted flight area stereoscopic subdivision grid data by using the grid buffer zone algorithm and the distance of the grid buffer zone; based on the stereoscopic subdivision grid level, divides the flight plan track stereoscopic subdivision grid data and the grid buffer zone, and the restricted flight area stereoscopic subdivision grid data and the grid buffer zone, respectively into a plurality of detection blocks; for each detection block, traverses each flight plan track data stereoscopic subdivision grid 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 stereoscopic subdivision grid with conflict in the detection block. It can solve the problems of current time-space relationship calculation intensive, more invalid and redundant calculation, and poor parallel optimization effect.

[0090] All the above optional technical solutions can be combined to form optional embodiments of the present application, which will not be repeated here.

[0091] The following is an apparatus embodiment of the present application, which can be used to execute the method embodiments of the present application. For details not disclosed in the apparatus embodiments of the present application, please refer to the method embodiments of the present application.

[0092] Figure 6 A structure diagram of a flight plan conflict detection device based on stereoscopic subdivision grid according to an embodiment of the present disclosure is shown. As shown in Figure 6 The healing device can include:

[0093] The discretization module 701 is configured to discretize the flight plan track data and the restricted flight area data, and respectively obtain the stereoscopic subdivision grid data of the flight plan track data and the restricted flight area data.

[0094] The grid buffer zone generation module 702 is configured to determine the distance of the grid buffer zone based on the flight plan separation requirement, and generate the grid buffer zone of the flight plan track stereoscopic subdivision grid data and the restricted flight area stereoscopic subdivision grid data by using the grid buffer zone algorithm and the distance of the grid buffer zone.

[0095] The dividing module 703 is configured to divide the flight plan track stereoscopic subdivision grid data and the grid buffer, and the restricted flight area stereoscopic subdivision grid data and the grid buffer, into a plurality of detection blocks based on a stereoscopic subdivision grid level.

[0096] The traversing module 704 is configured to traverse the stereoscopic subdivision grid of each flight plan track data at each time for each detection block to obtain a conflict detection result in each detection block.

[0097] The output module 705 is configured to output attribute information of the stereoscopic subdivision grid with a conflict in each detection block based on the conflict detection result in each detection block.

[0098] It should be understood that the size of the serial number of each step in the above embodiments does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0099] Figure 7 FIG. 3 is a structural schematic diagram of an electronic device 3 provided by the embodiments of the present application. As shown in the figure, the electronic device 3 of the embodiments includes a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. The processor 301 implements the steps in the above various method embodiments when executing the computer program 303. Alternatively, the processor 301 implements the functions of each module / unit in the above various device embodiments when executing the computer program 303. Figure 7

[0100] By way of example, the computer program 303 can 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 can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program 303 in the electronic device 3.

[0101] The electronic device 3 can be a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The electronic device 3 can include but is not limited to the processor 301 and the memory 302. Those skilled in the art can understand that the electronic device 3 is only an example of the electronic device 3 and does not constitute a limitation on the electronic device 3, and can include more or fewer components than those shown, or combine certain components, or different components, for example, the electronic device can also include an input / output device, a network access device, a bus, and the like. Figure 7 The electronic device 3 is only an example of the electronic device 3 and does not constitute a limitation on the electronic device 3, and can include more or fewer components than those shown, or combine certain components, or different components, for example, the electronic device can also include an input / output device, a network access device, a bus, and the like.

[0102] ​The processor 301 can be a central processing unit (CPU), or other general purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like. The general purpose processor can be a microprocessor, or the processor can be any conventional processor.

[0103] The memory 302 can be an internal storage unit of the electronic device 3, for example, a hard disk or a memory of the electronic device 3. The memory 302 can 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, or the like equipped on the electronic device 3. Further, the memory 302 can include both the internal storage unit and the 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 can also be used to temporarily store data that has been output or will be output.

[0104] It can be clearly understood by those skilled in the art that, for the convenience and brevity of description, only the division of the above functional units and modules is taken as an example for illustration, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can exist physically independently, or two or more units can be integrated in one unit, and the integrated unit can be realized in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction, and are not used to limit the protection scope of the present application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0105] Exemplary systems and methods of the present application have been specifically shown and described herein in accordance with the exemplary embodiments, but it will be understood that various changes in the system and / or methods described herein can be made without departing from the spirit and scope of the application, which is 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: 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; Determining a distance of a gridded buffer zone based on a flight plan spacing requirement, and generating a gridded buffer zone for flight plan track stereoscopic subdivision grid data and restricted flight area stereoscopic subdivision grid data using a grid buffer algorithm and the distance of the gridded buffer zone; wherein determining the distance of the gridded buffer zone based on the flight plan spacing requirement includes: determining the distance of the gridded buffer zone based on the flight plan spacing requirement, the flight plan type, and the restricted flight area type; Based on the stereo grid level, the flight plan track stereo grid data and gridded buffer, as well as the restricted flight area stereo grid data and gridded buffer, are divided into a plurality of detection blocks; the detection blocks are divided using the global unified geospatial grid system GeoSOT; For each detection block, traverse the three-dimensional grid of each flight plan trajectory data at each moment to obtain the conflict detection results within each detection block; Based on the conflict detection result in each detection block, 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 flight plan track 3D subdivision grid and the gridded buffer zones of other flight plan track 3D subdivision grids is solved to obtain a first grid intersection set; the intersection set between the flight plan track 3D subdivision grid and the gridded buffer zones of each restricted flight area 3D subdivision grid is solved to obtain a second grid intersection set.

3. The flight plan conflict detection method according to claim 2, characterized in that: The traversing of the three-dimensional grid of each flight plan track data at each moment 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, a conflict exists in the detection block; For each three-dimensional subdivision grid of the flight plan track data in the first grid intersection, the spatial and temporal relationship between the three-dimensional subdivision grids of different flight plan track grids is calculated using three-dimensional subdivision grid coding algebra, and the conflict result within the detection block is determined by comparing with the flight interval rule.

4. The flight plan conflict detection method according to claim 3, characterized in that: The time-space relationship includes a relative position relationship, a heading angle relationship, a speed relationship and a time interval relationship.

5. The flight plan conflict detection method according to claim 3, characterized in that: After calculating the spatiotemporal relationship between the volumetric meshes of different flight plan track grids, including: Determining a heading relationship between two flight plan tracks, and calculating a time interval relationship and a 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, 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, a conflict exists in the detection block, and the violation item and the specific violation reason are recorded.

6. The flight plan conflict detection method according to claim 5, characterized in that: The attribute information of the three-dimensional mesh includes mesh code, conflict time, flight plan ID, restricted flight area ID, violated flight separation rule, specific violation reason and violation item.

7. A flight plan conflict detection device based on three-dimensional grid division, characterized in that: The device comprises: a discretization module, configured 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 gridded buffer generation module, configured to determine a distance of a gridded buffer based on a flight plan spacing requirement, and generate a gridded buffer for flight plan track stereoscopic subdivision grid data and restricted flight area stereoscopic subdivision grid data using a gridded buffer algorithm and the distance of the gridded buffer; wherein determining the distance of the gridded buffer based on the flight plan spacing requirement includes determining the distance of the gridded buffer based on the flight plan spacing requirement and the flight plan type / restricted flight area type; a partitioning module for partitioning the flight plan track 3D grid data and gridded buffer, and the restricted flight area 3D grid data and gridded buffer, into a plurality of detection blocks based on a 3D gridding level; the detection blocks are partitioned using GeoSOT, a globally unified geographic spatial gridding system; A traversal module is used to traverse the three-dimensional grid of each flight plan trajectory data at each moment for each detection block to obtain the conflict detection results within each detection block; The output module is used to output attribute information of the conflicting three-dimensional mesh in each detection block based on the conflict detection result in the detection block.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. 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 6 are implemented.

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