Gridding low-altitude three-dimensional traffic light representation and calculation method and device

Abstract

The embodiment of the invention aims to provide a gridding low-altitude three-dimensional traffic light representation and calculation method and device, a computer program product and a computer program storage medium. Wherein the current three-dimensional grid position of at least one unmanned aerial vehicle is tracked in real time; and when detecting that one or more unmanned aerial vehicles trigger a conflict event at the current three-dimensional grid position, instructing the unmanned aerial vehicle triggering the conflict event to hover, and determining a new flight path for the unmanned aerial vehicle. According to the embodiment of the invention, the three-dimensional airspace grid unit configures the state of the airspace, such as a no-fly zone or a green light suitable-to-fly zone. The system tracks the current grid position of the unmanned aerial vehicle, and when the unmanned aerial vehicle triggers a conflict event, the system sends a hovering instruction to the unmanned aerial vehicle and gives a corresponding conflict solution, such as detour or sequential passage.

Description

Technical Field

[0001] The various embodiments of the present disclosure relate to the field of unmanned aerial vehicles, and in particular to a technology for representing and calculating gridded low-altitude three-dimensional traffic lights. Background Art

[0002] Existing technologies mainly focus on static airspace restrictions, such as no-fly zones, and sensor-based collision avoidance, and lack active conflict warning and resolution mechanisms. Especially in conflict resolution between unmanned aerial vehicles, existing systems still rely mainly on operator intervention. Summary of the invention

[0003] The purpose of each embodiment of the present disclosure is to provide a grid-based low-altitude three-dimensional traffic traffic light representation and calculation method, device, computer program product and computer program storage medium.

[0004] According to one aspect of the present disclosure, a grid-based low-altitude three-dimensional traffic light representation and calculation method is provided, wherein the method comprises the following steps:

[0005] The airspace is divided into multiple three-dimensional grid cells, some of which are assigned as unauthorized flight zones and are represented in red, and other three-dimensional grid cells are represented in green;

[0006] The method further comprises the following steps:

[0007] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0008] When it is detected that the current three-dimensional grid position of one or more unmanned aerial vehicles is adjacent to the red airspace, the adjacent unmanned aerial vehicles are instructed to hover and a new flight path is determined for them.

[0009] According to one aspect of the present disclosure, a grid-based low-altitude three-dimensional traffic light representation and calculation method is provided, wherein the method comprises the following steps:

[0010] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0011] When it is detected that one or more of the UAVs trigger a conflict event at their current three-dimensional grid position, the UAVs that trigger the conflict event are instructed to hover and a new flight path is determined for them.

[0012] According to one aspect of the present disclosure, a grid-based low-altitude three-dimensional traffic light representation and calculation device is also provided, wherein the device includes a memory and a processor, the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the device is configured to perform the following operations:

[0013] The airspace is divided into multiple three-dimensional grid cells, some of which are assigned as unauthorized flight zones and are represented in red, and other three-dimensional grid cells are represented in green;

[0014] Among other things, the device is further configured to perform the following operations:

[0015] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0016] When it is detected that the current three-dimensional grid position of one or more unmanned aerial vehicles is adjacent to the red airspace, the adjacent unmanned aerial vehicles are instructed to hover and a new flight path is determined for them.

[0017] According to one aspect of the present disclosure, a grid-based low-altitude three-dimensional traffic light representation and calculation device is also provided, wherein the device includes a memory and a processor, the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the device is configured to perform the following operations:

[0018] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0019] When it is detected that one or more of the UAVs trigger a conflict event at their current three-dimensional grid position, the UAVs that trigger the conflict event are instructed to hover and a new flight path is determined for them.

[0020] According to one aspect of the present disclosure, a computer program product is also provided, including computer program instructions, wherein when the computer program instructions are executed by a computer device, the computer device is configured to execute a grid-based low-altitude three-dimensional traffic light representation and calculation method, wherein the method includes the following steps:

[0021] The airspace is divided into multiple three-dimensional grid cells, some of which are assigned as unauthorized flight zones and are represented in red, and other three-dimensional grid cells are represented in green;

[0022] The method further comprises the following steps:

[0023] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0024] When it is detected that the current three-dimensional grid position of one or more unmanned aerial vehicles is adjacent to the red airspace, the adjacent unmanned aerial vehicles are instructed to hover and a new flight path is determined for them.

[0025] According to one aspect of the present disclosure, a computer program product is also provided, including computer program instructions, wherein when the computer program instructions are executed by a computer device, the computer device is configured to execute a grid-based low-altitude three-dimensional traffic light representation and calculation method, wherein the method includes the following steps:

[0026] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0027] When it is detected that one or more of the UAVs trigger a conflict event at their current three-dimensional grid position, the UAVs that trigger the conflict event are instructed to hover and a new flight path is determined for them.

[0028] According to one aspect of the present disclosure, a computer program storage medium is also provided, in which computer executable instructions are stored. When the computer executable instructions are executed by a computer device, the computer device is configured to execute a grid-based low-altitude three-dimensional traffic light representation and calculation method, wherein the method includes the following steps:

[0029] The airspace is divided into multiple three-dimensional grid cells, some of which are assigned as unauthorized flight zones and are represented in red, and other three-dimensional grid cells are represented in green;

[0030] The method further comprises the following steps:

[0031] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0032] When it is detected that the current three-dimensional grid position of one or more unmanned aerial vehicles is adjacent to the red airspace, the adjacent unmanned aerial vehicles are instructed to hover and a new flight path is determined for them.

[0033] According to one aspect of the present disclosure, a computer program storage medium is also provided, in which computer executable instructions are stored. When the computer executable instructions are executed by a computer device, the computer device is configured to execute a grid-based low-altitude three-dimensional traffic light representation and calculation method, wherein the method includes the following steps:

[0034] tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle;

[0035] When it is detected that one or more of the UAVs trigger a conflict event at their current three-dimensional grid position, the UAVs that trigger the conflict event are instructed to hover and a new flight path is determined for them.

[0036] According to the various embodiments of the present disclosure, the three-dimensional airspace grid unit configures the status of the airspace, such as a no-fly zone or a green-light flying zone. The system tracks the current grid position of the UAV. When the UAV triggers a conflict event, the system sends a hovering command to the UAV and gives corresponding conflict resolution methods, such as detouring or passing in order. When the airspace environment changes in real time, the system can perceive it in real time and actively initiate the detection of conflict events based on the airspace flight status of the updated airspace grid unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Other features, objects and advantages of the present disclosure will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0038] Figure 1 A flowchart of a gridded low-altitude three-dimensional traffic light representation and calculation method according to an embodiment of the present disclosure is shown.

[0039] The same or similar reference numerals in the drawings represent the same or similar components. DETAILED DESCRIPTION

[0040] The specific embodiments of the present disclosure will be further described below in conjunction with the accompanying drawings.

[0041] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments of the present disclosure are described as devices represented by block diagrams and processes or methods represented by flow charts. Although the flow charts describe the operating processes of the various embodiments of the present disclosure as sequential processing, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The processes of the various embodiments of the present disclosure can be terminated when their operations are completed, but can also include additional steps not shown in the flow charts. The processes of the various embodiments of the present disclosure can correspond to methods, functions, procedures, subroutines, subprograms, etc.

[0042] The methods illustrated by the flow charts and the devices illustrated by the block diagrams discussed below may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware, or microcode, program code or code segments that perform the necessary tasks may be stored in a machine or computer readable medium such as a storage medium. (One or more) processors may perform the necessary tasks.

[0043] Similarly, it will also be understood that any flow charts, flow diagrams, state transition diagrams, and the like represent various processes that can be fully described as program code stored in a computer readable medium and thereby executed by a computer device or processor, whether or not such computer device or processor is explicitly shown.

[0044] As used herein, the term "storage medium" may refer to one or more devices for storing data, including read-only memory (ROM), random access memory (RAM), magnetic RAM, kernel memory, magnetic disk storage media, optical storage media, flash memory devices and / or other machine-readable media for storing information. The term "computer-readable medium" may include, but is not limited to, portable or fixed storage devices, optical storage devices, and various other media capable of storing and / or containing instructions and / or data.

[0045] A code segment may represent a procedure, function, subprogram, program, routine, subroutine, module, software package, class, or any combination of instructions, data structures, or program descriptions. A code segment may be coupled to another code segment or hardware circuit by passing and / or receiving information, data, arguments, parameters, or storage contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including storage sharing, information passing, token passing, network transmission, etc.

[0046] The "computer device" referred to in this context refers to an electronic device that can perform predetermined processing procedures such as numerical calculations and / or logical calculations by running predetermined programs or instructions, and may include at least a processor and a memory, wherein the processor executes program instructions pre-stored in the memory to perform the predetermined processing process, or the predetermined processing process is performed by hardware such as ASIC, FPGA, DSP, or a combination of the above two.

[0047] The above-mentioned "computer device" is usually expressed in the form of a general-purpose computer device, and its components may include but are not limited to: one or more processors or processing units, system memory. The system memory may include a computer-readable medium in the form of a volatile memory, such as a random access memory (RAM) and / or a cache memory. The "computer device" may further include other removable / non-removable, volatile / non-volatile computer-readable storage media. The memory may include at least one computer program product having a set (e.g., at least one) of program modules that are configured to perform the functions and / or methods of the various embodiments of the present disclosure. The processor executes various functional applications and data processing by running the program stored in the memory.

[0048] For example, a computer program for executing various functions and processes of multiple embodiments of the present disclosure is stored in the memory, and when the processor executes the corresponding computer program, multiple embodiments of the present disclosure are implemented.

[0049] Typically, the computer device may be, for example, a user device or a network device, or even a combination of the two. The user device includes, but is not limited to, a personal computer (PC), a laptop, a mobile terminal, etc. The mobile terminal includes, but is not limited to, a smart phone, a tablet computer, etc. The network device includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud consisting of a large number of computers or network servers based on cloud computing (Cloud Computing), wherein cloud computing is a type of distributed computing, a super virtual computer consisting of a group of loosely coupled computer sets. The computer device may be operated alone to implement the various embodiments of the present disclosure, or may be connected to a network and implement the various embodiments of the present disclosure through interactive operations with other computer devices in the network. The network in which the computer device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a VPN network, etc.

[0050] It should be noted that the user equipment, network equipment and network are only examples. Other existing or future computing devices or networks that are applicable to the embodiments of the present disclosure should also be included in the scope of protection of the present disclosure and are included here by reference.

[0051] The specific structural and functional details disclosed herein are merely representative and are for the purpose of describing exemplary embodiments of the present disclosure. However, the various embodiments of the present disclosure may be implemented in many alternative forms and should not be interpreted as being limited to only the embodiments set forth herein.

[0052] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0053] The terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments. Unless the context clearly indicates otherwise, the singular forms "one", "one" and "item" used herein are also intended to include plural numbers. It should also be understood that the terms "include" and / or "comprise" used herein specify the existence of stated features, integers, steps, operations, units and / or components, without excluding the existence or addition of one or more other features, integers, steps, operations, units, components and / or combinations thereof.

[0054] It should also be noted that, in some alternative implementations, the functions / actions mentioned may occur in a different order than that indicated in the accompanying drawings. For example, depending on the functions / actions involved, two figures shown in succession may actually be performed substantially simultaneously or may sometimes be performed in the reverse order.

[0055] See also Figure 1 , which shows a process of gridding low-altitude three-dimensional traffic light representation and calculation according to an embodiment of the present disclosure.

[0056] See also Figure 1 In step S100, the computer device tracks the current three-dimensional grid position of at least one unmanned aerial vehicle in real time; in step S200, when it is detected that one or more of the unmanned aerial vehicles trigger a conflict event at their current three-dimensional grid positions, the computer device instructs the unmanned aerial vehicle that triggered the conflict event to hover and determines a new flight path for it.

[0057] Here, "computer equipment" generally refers to various types of computing resource collections, such as cloud computing platforms, server clusters, virtualized environments, etc., which can generally be functionally referred to as "conflict management platforms / systems" and can be used equivalently herein unless otherwise specified. These computer devices can be configured to implement the functions required by the various embodiments of the present disclosure, including but not limited to data storage, processing, analysis, and application deployment. Through flexible configuration and optimization, these computer devices can support high-performance computing, real-time data processing, data security, and system scalability to meet the actual needs of the technical solutions of the present disclosure.

[0058] Specifically, in step S100, the computer device tracks the current three-dimensional grid position of at least one unmanned aerial vehicle in real time.

[0059] In some embodiments, the airspace is divided into a plurality of three-dimensional grid cells, and the three-dimensional grid cells are assigned as no-fly zones or proper-fly zones.

[0060] The low-altitude airspace is divided into multiple three-dimensional grid cells using three-dimensional grid technology. Each three-dimensional grid cell represents an airspace area with a specific range and altitude. This grid division method allows the entire airspace to be subdivided into many small, easy-to-manage areas. Each grid cell is assigned specific attributes, usually based on the usage rules and management requirements of the area.

[0061] The three-dimensional meshing algorithms that can be used include:

[0062] GeoSOT 3D grid division: Based on GeoSOT (Geographic Space Organization Theory) theory, the space is divided into equal intervals and the earth space is divided into multiple levels using binary bits. GeoSOT supports both planar geographic location division and height dimension (Z axis) division, which is suitable for 3D airspace division.

[0063] BeiDou grid location coding: By dividing the earth's surface into multiple three-dimensional grids and assigning a unique code to each grid, it provides accurate three-dimensional geographic location identification. This system uses data from the BeiDou satellite system to support efficient regional division and location management, and is widely used in aviation, drones, and map making.

[0064] Geodesic Gridding: The space is divided by dividing the surface of the sphere into regular geometric shapes (such as hexagons and pentagons). Common gridding methods include projecting the sphere onto a regular dodecahedron or a regular icosahedron to generate polygonal grid units of equal area.

[0065] Multi-dimensional space-time grid division algorithm: Introducing the time dimension, the space is divided into three dimensions (XYZ axis) + time (T axis), allowing the dynamic changes of the airspace at different times to be described in grid form. Space-time grid division is suitable for processing real-time data and dynamic environmental changes.

[0066] The system receives the real-time location information of the UAV through the communication interface. The positioning module equipped with the UAV will continuously provide the three-dimensional coordinate data of its current location. These data include latitude, longitude, altitude and other information.

[0067] The system maps the 3D coordinates of the UAV to the corresponding grid cells to determine the grid cell where the UAV is currently located, that is, the current 3D grid position. The system confirms the grid cell where the UAV is located and its airspace status by comparing the position of the UAV with the spatial coordinates of the grid cell.

[0068] The system updates the current position of the UAV in real time and maps it to the corresponding grid cells. The status information of these grid cells (such as no-fly zones or suitable flying zones) is also updated in real time to facilitate subsequent conflict detection and management operations.

[0069] In some embodiments, the unmanned aerial vehicle is equipped with a Beidou positioning module, which can determine the current spatial position information of the unmanned aerial vehicle through communication with Beidou satellites, and obtain the Beidou grid position code corresponding to the current spatial position information based on the Beidou position coding algorithm. The conflict management system can also use the Beidou grid position code to divide the airspace into multiple three-dimensional grid units. Thus, the conflict management system can directly track the current three-dimensional grid position of the unmanned aerial vehicle based on the positioning report of the unmanned aerial vehicle.

[0070] A 3D grid cell can be marked as a no-fly zone or a flyable zone. This marking is done based on the use of the airspace and the prescribed flight rules. For example, a no-fly zone is an area where unmanned aerial vehicles cannot enter. These grid cells will be clearly marked as no-fly to prevent unmanned aerial vehicles from entering these areas.

[0071] In contrast, a suitable flying zone refers to an area where unmanned aerial vehicles are allowed to fly. These grid cells are marked as suitable for flying, indicating that these areas allow unmanned aerial vehicles to fly and can carry out missions and operations safely.

[0072] This three-dimensional gridding method not only improves the efficiency of airspace management, but also enables the status of airspace to be intuitively reflected on the graphical interface, thereby supporting real-time monitoring and dynamic adjustment. When airspace management requirements change, the system can quickly adjust the status of the grid unit and update it to the relevant unmanned aerial vehicles and control systems in a timely manner to ensure that the flight of the unmanned aerial vehicle complies with the latest airspace management rules.

[0073] Further, in some examples, the three-dimensional grid cells assigned as no-fly zones are set to red, and the three-dimensional grid cells assigned as suitable-fly zones are set to green.

[0074] The grid cells of the no-fly zone are usually marked in red to clearly identify those areas where UAVs are not allowed to enter. In contrast, the grid cells of the flyable zone are marked in green to indicate that UAVs are allowed to fly in these areas.

[0075] In some embodiments, some three-dimensional grid cells that currently belong to the suitable flying zone will be reallocated as the temporary no-fly zone. In some examples, when these three-dimensional grid cells are changed from the suitable flying zone to the temporary no-fly zone, their colors will also change from green to red.

[0076] In actual operation, it may happen that some three-dimensional grid cells in suitable flying areas are reassigned as no-fly zones due to temporary needs. For example, some areas may temporarily need to restrict the flight of unmanned aerial vehicles due to special events, maintenance or other reasons. At this time, these grid cells originally marked as green will be re-marked as red to reflect their new status. This state change can be dynamic, and the computer equipment will update the status of these grid cells in real time and perform conflict detection and resolution based on the updated information.

[0077] In step S200, when it is detected that one or more UAVs trigger a conflict event at their current three-dimensional grid positions, the computer device instructs the UAVs that trigger the conflict event to hover and determines a new flight path for them.

[0078] Monitor the position of the UAV in real time and detect conflict events based on the airspace status corresponding to its current grid position. If the UAV is found to have entered a no-fly zone (red light grid unit) or is not within a safe distance from other aircraft, the system will identify it as a conflict event. Once a conflict event is confirmed, the system will immediately send a hovering command to the UAV that triggered the conflict event. The command requires the UAV to stop flying at its current position and hover in the current airspace to prevent further danger or conflict.

[0079] According to one example, if the UAV approaches or enters a no-fly zone (i.e., a red light grid cell), the system will trigger a conflict event. The system will immediately issue a hover command, requiring the UAV to stop moving forward. In addition, the system will provide the UAV with a new flight path to bypass the no-fly zone and enter a safe suitable flying zone (i.e., a green light grid cell).

[0080] According to one example, if the flight distance between two or more unmanned aerial vehicles is detected to be less than the preset safety distance, the system will issue a collision warning. All related unmanned aerial vehicles will be required to hover and display red flashing lights to indicate danger. The system will adjust the flight path according to the priority and current position of the aircraft to ensure collision avoidance.

[0081] While the drone is hovering, the system will calculate and generate a new flight path based on the current airspace status and conflict conditions. The new flight path will bypass no-fly zones or other dangerous areas to ensure that the drone enters a safe flight zone.

[0082] The system sends new flight path instructions to the conflicting UAVs, instructing them to continue flying along the replanned path. These instructions are optimized based on airspace conditions, aircraft priority, and conflict situations to ensure that the aircraft can safely avoid the conflict area and fly smoothly along the new path.

[0083] While the conflicting UAV is hovering, the system can also instruct the UAV that triggered the conflict event to turn on a flashing red light to indicate that it is currently in a conflict state.

[0084] During the hovering of the conflicting UAV, the system will not only instruct the UAV to stop moving, but also issue an additional command to require the UAV to turn on the flashing red light. The flashing red light function is designed to enhance the visual warning, make the current status of the aircraft more obvious, and remind surrounding aircraft or monitoring personnel that the aircraft is in a conflict state.

[0085] This visual warning helps increase the vigilance of aircraft and other airspace users and reduce potential safety risks. The flashing red light also enables the system to more intuitively identify the occurrence of conflict events on the monitoring platform, further improving the system's real-time tracking capabilities of aircraft status. In addition, by lighting up the red light, the system can effectively notify the aircraft operator or relevant management personnel to take further operational measures to ensure that the unmanned aerial vehicle can be effectively managed and adjusted during the hovering period to avoid the escalation of conflict events.

[0086] In some embodiments, the conflict event includes the UAV approaching an unauthorized area, such as a no-fly zone or a temporary no-fly zone.

[0087] The computer device instructs the unmanned aerial vehicle that triggered the current conflict event to stop moving and calculates a new flight path for the conflicting unmanned aerial vehicle to bypass the unauthorized area.

[0088] When the computer device detects that the UAV approaches these unauthorized areas at its current three-dimensional grid position, a conflict event is triggered. This situation may involve the UAV approaching a no-fly zone marked in red, or a temporary no-fly zone that has just been established. For example, some airspace is set as a temporary no-fly zone due to an emergency. The system detects the surroundings of the temporary no-fly zone based on the real-time airspace status changes. When a UAV is found approaching, it will issue a hovering command to it and determine a new flight path for it.

[0089] In response to the detected conflict event, the computer device will first instruct the unmanned aerial vehicle that triggered the event to stop moving immediately. At this time, the unmanned aerial vehicle will enter a hovering state to avoid further approaching the no-fly zone or temporary no-fly zone to prevent any potential violations or safety risks.

[0090] After the unmanned aerial vehicle enters the hovering state, the computer equipment will begin to calculate a new flight path. This process involves analyzing the existing airspace data and the latest status of the no-fly zone, and using algorithms to generate a new flight route that avoids the no-fly zone or temporary no-fly zone. The system will take into account the current position of the aircraft, the flight target, and the dynamic changes in the airspace to plan a safe and effective alternative path.

[0091] After the computer device generates a new flight path, it transmits this path instruction to the UAV, instructing it to bypass the no-fly zone or temporary no-fly zone. The UAV restarts navigation according to the new flight path to ensure that it can safely continue its flight mission without entering the restricted area. This method helps maintain the safety of the airspace and avoids any potential violations caused by UAVs in airspace management.

[0092] In some embodiments, a conflict event includes a flight distance between two or more unmanned aerial vehicles being less than a predetermined warning distance.

[0093] The computer device instructs all the UAVs that trigger the current conflict event to hover, and determines new flight paths for them respectively. The new flight paths can be instructions for the travel order of these conflicting UAVs, or instructions for whether some or all of these conflicting UAVs should detour, or a combination of the two instructions.

[0094] When the flight distance between two or more unmanned aerial vehicles is less than the preset warning distance, it indicates that there is a risk of collision between these aircraft. In order to prevent potential collisions, the system will trigger a conflict event in time.

[0095] When the computer equipment detects this type of conflict event, a series of measures will be taken to ensure flight safety. First, the system instructs all involved unmanned aerial vehicles to hover immediately. This means that these aircraft will suspend their current flight missions and enter a stable hovering state to prevent further mutual approach or collision.

[0096] While all the relevant UAVs are hovering, the computer equipment will conduct a detailed analysis to determine how to adjust the flight paths of these aircraft. The new flight path may include the following instructions:

[0097] Travel order indication: The system can specify a new travel order for conflicting UAVs. This means that the system will determine the order of priority and secondary aircraft so that the priority aircraft passes first, while other aircraft continue to fly after waiting for it to pass. This can effectively avoid flying in the same area at the same time and reduce the risk of collision.

[0098] Detour instructions: The system can also instruct some or all of the conflicting UAVs to detour. This means that the system will calculate an alternative path for each UAV to bypass the current conflict area. The detour path can be a path that completely avoids the conflict area, or a reasonable adjustment of the distance between the aircraft to ensure that they maintain a safe distance during flight.

[0099] Combined instructions: The system can also combine the travel order and detour instructions to provide a more comprehensive flight path adjustment solution. This method can handle complex flight scenarios more flexibly. For example, when the distance between aircraft is close and the flight paths need to be adjusted at the same time, the system can comprehensively consider the relative positions of the aircraft, optimize their travel order and specify a suitable detour path.

[0100] Through these adjustments, computer equipment can effectively manage and control the flight paths between unmanned aerial vehicles, ensuring that they can avoid collisions and maintain a safe flight distance during flight. This method not only improves the efficiency of airspace use, but also enhances the safety of unmanned aerial vehicles.

[0101] Based on the flight status update of part of the airspace, the system starts the detection of conflict events related to the updated flight status. Here, since the airspace is divided into multiple three-dimensional grid cells, each grid cell can be associated with a flight status in its three-dimensional space, such as whether it is a no-fly zone, weather data, terrain data, etc. Since the flight status may change, for example, part of the airspace suddenly changes from a suitable flying zone to a temporary no-fly zone, part of the airspace suddenly experiences drastic weather changes, and the unmanned aerial vehicle is at risk of collision, such as approaching ground obstacles in the grid cell. When the flight status of the grid cells affected by these flight status changes is updated accordingly, the system starts the detection of conflict events related to the updated flight status.

[0102] For example, the system identifies whether the currently updated flight status involves a potential conflict event. For example, check whether the UAV is approaching a newly added temporary no-fly zone, sudden weather changes (such as strong winds, lightning), or the appearance of ground obstacles that may affect the safety of the UAV's flight path. When the system confirms that a conflict event has been detected based on the current position of the UAV and the latest flight status of the corresponding grid unit, it first issues a hovering command and then takes appropriate measures to avoid collision, such as adjusting the flight path.

[0103] It should be noted that the various embodiments of the present disclosure may be implemented in software and / or a combination of software and hardware, for example, may be implemented using an application specific integrated circuit (ASIC), a general purpose computer, or any other similar hardware device. In one embodiment, the software program of the various embodiments of the present disclosure may be executed by a processor to implement the steps or functions described above. Similarly, the software program of the various embodiments of the present disclosure (including related data structures) may be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive, or a floppy disk and the like. In addition, some steps or functions of the various embodiments of the present disclosure may be implemented using hardware, for example, as a circuit that cooperates with a processor to perform various steps or functions.

[0104] In addition, at least a portion of the embodiments of the present disclosure may be applied as a computer program product, such as a computer program instruction, which, when executed by a computing device, can call or provide the method and / or technical solution according to the embodiments of the present disclosure through the operation of the computing device. The program instruction for calling / providing the method of the embodiments of the present disclosure may be stored in a fixed or removable recording medium, and / or transmitted through a data stream in a broadcast or other signal-bearing medium, and / or stored in a working memory of a computing device that runs according to the program instruction.

[0105] For those skilled in the art, it is obvious that the embodiments of the present disclosure are not limited to the details of the above exemplary embodiments, and the embodiments of the present disclosure can be implemented in other specific forms without departing from the spirit or basic features of the embodiments of the present disclosure. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present disclosure is limited by the attached claims rather than the above description, so it is intended to include all changes within the meaning and scope of the equivalent elements of the claims in the embodiments of the present disclosure. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "including" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claim can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any specific order.

Claims

1. A grid-based low-altitude three-dimensional traffic light representation and calculation method, wherein: The method comprises the following steps: The airspace is divided into multiple three-dimensional grid cells, some of which are assigned as unauthorized flight zones and are represented in red, and other three-dimensional grid cells are represented in green; The method further comprises the following steps: tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle; When it is detected that the current three-dimensional grid position of one or more unmanned aerial vehicles is adjacent to the red airspace, the adjacent unmanned aerial vehicles are instructed to hover and a new flight path is determined for them.

2. The method according to claim 1, wherein: The instruction steps specifically include: The adjacent unmanned aerial vehicle is instructed to stop and a new flight path is calculated for it to bypass the unauthorized flight area.

3. The method according to claim 1, wherein: The instruction step also includes: The adjacent unmanned aerial vehicle is also instructed to turn on a flashing red light to indicate that it is currently in a conflict state.

4. The method according to claim 1, wherein: The method further comprises the following steps: Based on the flight status update of the partial airspace, conflict detection related to the updated flight status is initiated.

5. A grid-based low-altitude three-dimensional traffic light representation and calculation method, wherein: The method comprises the following steps: tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle; When it is detected that one or more of the UAVs trigger a conflict event at their current three-dimensional grid position, the UAVs that trigger the conflict event are instructed to hover and a new flight path is determined for them.

6. The method according to claim 5, wherein: The airspace is divided into a number of three-dimensional grid cells, some of which are assigned as unauthorized flight zones; The conflict event includes an unmanned aerial vehicle approaching the unauthorized flight area.

7. The method according to claim 6, wherein: The unmanned aerial vehicle that triggered the conflict event is instructed to stop moving and a new flight path is calculated for it to bypass the unauthorized flight area.

8. The method according to claim 6, wherein: The three-dimensional grid cells assigned as unauthorized flight zones are set in red, and the other three-dimensional grid cells are set in green.

9. The method according to claim 5, wherein: The conflict event includes the flight distance between two or more unmanned aerial vehicles being less than a predetermined warning distance; The method further comprises the following steps: All UAVs that trigger the conflict event are instructed to hover, and their respective new flight paths are determined, including the order of travel and / or whether to detour.

10. The method according to claim 5, wherein: The unmanned aerial vehicle that triggered the conflict event is also instructed to turn on a flashing red light to indicate that it is currently in a conflict state.

11. The method according to claim 5, wherein: The airspace is divided into a plurality of three-dimensional grid cells, wherein the method further comprises the following steps: Based on the flight status update of the partial airspace, the detection of conflict events related to the updated flight status is initiated.

12. A grid-based low-altitude three-dimensional traffic light representation and calculation device, wherein: The device comprises a memory and a processor, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the device is configured to perform the following operations: The airspace is divided into multiple three-dimensional grid cells, some of which are assigned as unauthorized flight zones and are represented in red, and other three-dimensional grid cells are represented in green; Among other things, the device is further configured to perform the following operations: tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle; When it is detected that the current three-dimensional grid position of one or more unmanned aerial vehicles is adjacent to the red airspace, the adjacent unmanned aerial vehicles are instructed to hover and a new flight path is determined for them.

13. A grid-based low-altitude three-dimensional traffic light representation and calculation device, wherein: The device comprises a memory and a processor, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the device is configured to perform the following operations: tracking in real time a current three-dimensional grid position of at least one unmanned aerial vehicle; When it is detected that one or more of the UAVs trigger a conflict event at their current three-dimensional grid position, the UAVs that trigger the conflict event are instructed to hover and a new flight path is determined for them.

14. A computer program product comprising computer program instructions, wherein: When the computer program instructions are executed by a computer device, the computer device is configured to perform the method according to any one of claims 1 to 4.

15. A computer program storage medium storing computer executable instructions, wherein when the computer executable instructions are executed by a computer device, the computer device is configured to perform the method according to any one of claims 1 to 4.

16. A computer program product comprising computer program instructions, wherein: When the computer program instructions are executed by a computer device, the computer device is configured to perform the method according to any one of claims 5 to 11.

17. A computer program storage medium storing computer executable instructions, wherein when the computer executable instructions are executed by a computer device, the computer device is configured to perform the method according to any one of claims 5 to 11.

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