Unmanned aerial vehicle low-altitude airspace traffic decision method, device, system and equipment

Abstract

The application provides a UAV low-altitude airspace traffic decision method, comprising: obtaining flight path planning data and current flight state information of a UAV in a target airspace; the UAV in the target airspace is represented as all UAVs within a preset range centered on a target UAV; determining whether the current flight state information is consistent with the flight path planning data; if yes, marking the UAV in the target airspace as a normal flight UAV, and if no, marking the UAV in the target airspace as an abnormal flight UAV; monitoring positioning points of the UAV in the target airspace and the target UAV in real time; based on the flight path planning data, determining collision risk information and a collision risk UAV; the collision risk information is represented as a collision time and a collision position; based on the positioning points, adjusting path planning data of the collision risk UAV to avoid collision.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of unmanned aerial vehicle management and control, and in particular to an unmanned aerial vehicle low-altitude airspace traffic decision method, device, system and equipment. BACKGROUND

[0002] With the expansion of unmanned aerial vehicle transportation scale, the congestion degree of urban low-altitude airspace traffic will inevitably increase rapidly. How to enable unmanned aerial vehicles to effectively avoid collisions with other nearby unmanned aerial vehicles is a problem to be solved.

[0003] Currently, unmanned aerial vehicle flight mainly relies on pre-declaration and planning of paths, and collision avoidance between unmanned aerial vehicles is mainly achieved by means of path and time conflict-free planning. However, unmanned aerial vehicle flight is different from civil aviation, with great freedom and great randomness of pilots. Therefore, there is a great security risk in collision avoidance by means of "planned flight".

[0004] Meanwhile, the prior art also has a collision avoidance technology using radar on unmanned aerial vehicles. However, there are the following problems: first, the scanning distance of the airborne radar on small unmanned aerial vehicles is very limited, and in the case of high-speed flight, it is often too late to perform collision avoidance operation; second, the airborne radar on small unmanned aerial vehicles has limited recognition capability for low-speed and low-altitude moving unmanned aerial vehicle targets; third, the tracking and scanning capability of the airborne radar on small unmanned aerial vehicles is very limited. SUMMARY

[0005] The present application provides a solution to the problem of great freedom of unmanned aerial vehicle flight and security risk in collision avoidance by means of planning.

[0006] According to a first aspect of the present application, a method for unmanned aerial vehicle low-altitude airspace traffic decision is provided, comprising:

[0007] acquiring flight path planning data and current flight state information of unmanned aerial vehicles in a target airspace; the unmanned aerial vehicles in the target airspace are represented as all unmanned aerial vehicles within a predetermined range centered on a target unmanned aerial vehicle;

[0008] determining whether the current flight state information is consistent with the flight path planning data; if yes, marking the unmanned aerial vehicles in the target airspace as normal flight unmanned aerial vehicles, and if no, marking the unmanned aerial vehicles in the target airspace as abnormal flight unmanned aerial vehicles;

[0009] real-time monitoring of the positioning points of the unmanned aerial vehicles in the target airspace and the target unmanned aerial vehicle;

[0010] determining collision risk information and collision risk unmanned aerial vehicles based on the flight path planning data; the collision risk information is represented as collision time and collision position;

[0011] Adjust the path planning data of the collision risk unmanned aerial vehicle based on the positioning point to avoid collision.

[0012] Optionally, the flight path planning data comprises a planned flight trajectory and a planned flight time of the unmanned aerial vehicle in the target airspace; and the current flight state information comprises a current flight trajectory, a current flight time, a type of the unmanned aerial vehicle, a signal and a flight speed of the unmanned aerial vehicle in the target airspace.

[0013] Optionally, the determining whether the current flight state information is consistent with the flight path planning data comprises:

[0014] determining whether a time deviation between the planned flight time and the current flight time and a position deviation between each trajectory point on the planned flight trajectory and the current flight trajectory are within a first preset time threshold and a first preset distance threshold based on the flight trajectory and the flight time of the unmanned aerial vehicle in the target airspace;

[0015] If yes, the unmanned aerial vehicle in the target airspace is marked as a normal flight unmanned aerial vehicle; and if no, the unmanned aerial vehicle in the target airspace is marked as an abnormal flight unmanned aerial vehicle.

[0016] Optionally, the determining whether the current flight state information is consistent with the flight path planning data further comprises:

[0017] acquiring RID information;

[0018] determining whether the RID information is consistent with the unmanned aerial vehicle in the target airspace based on the RID information;

[0019] If yes, reading an identity code, current position information, speed information, the current flight state information and the flight path planning data of the unmanned aerial vehicle from the RID information;

[0020] If no, continuing to acquire the flight path planning data corresponding to the RID information.

[0021] Optionally, the real-time monitoring of the positioning point of the unmanned aerial vehicle in the target airspace and the target unmanned aerial vehicle comprises:

[0022] positioning the unmanned aerial vehicle in the target airspace and the target unmanned aerial vehicle based on a preset period, and determining a plurality of positioning points;

[0023] determining a real-time flight trajectory based on the plurality of positioning points.

[0024] Optionally, the determining the collision risk information and the collision risk unmanned aerial vehicle based on the flight path planning data comprises:

[0025] determine whether the following conditions are met based on the planned flight trajectory:

[0026] for the normal flight unmanned aerial vehicle, determine whether the target unmanned aerial vehicle exists within a second preset time threshold and a second preset distance threshold of any flight trajectory point on the planned flight trajectory;

[0027] for the abnormal flight unmanned aerial vehicle, determine whether the target unmanned aerial vehicle exists within a second preset time threshold and a third preset distance threshold of any flight trajectory point on the planned flight trajectory;

[0028] if any of the above conditions are met, determine that the target unmanned aerial vehicle is a collision risk unmanned aerial vehicle, and determine that the flight trajectory point is a collision point; the collision risk unmanned aerial vehicle represents an unmanned aerial vehicle that may collide with the normal flight unmanned aerial vehicle and / or the abnormal flight unmanned aerial vehicle.

[0029] Optionally, adjusting the path planning data of the collision risk unmanned aerial vehicle based on the positioning point comprises:

[0030] determining the real-time positioning point of the collision risk unmanned aerial vehicle as a starting point, and the destination position of the collision risk unmanned aerial vehicle as an ending point;

[0031] setting the distance between the path point on the collision risk unmanned aerial vehicle and the collision point to n times the actual distance; wherein n is a positive integer;

[0032] adjusting the range of the path planning data from the entire flight motion to the real-time flight path.

[0033] Optionally, the unmanned aerial vehicle low-altitude traffic decision-making method further comprises:

[0034] scanning the direction of the collision risk unmanned aerial vehicle based on the collision risk information and the time sequence;

[0035] if the collision risk unmanned aerial vehicle is found, obtaining radar position information of the collision risk unmanned aerial vehicle, and determining whether the radar position information is consistent with the positioning point of the collision risk unmanned aerial vehicle and the position information in the RID information of the collision risk unmanned aerial vehicle;

[0036] if yes, adjusting the path planning data of the collision risk unmanned aerial vehicle;

[0037] if no, performing emergency obstacle avoidance based on the radar position information of the collision risk unmanned aerial vehicle;

[0038] replanning the path planning data of the collision risk unmanned aerial vehicle based on the position and speed of the collision risk unmanned aerial vehicle after emergency obstacle avoidance.

[0039] According to a second aspect of the present application, there is provided a UAV low airspace traffic decision device, comprising an acquisition module, a UAV determination module, a monitoring module, a collision determination module and a path adjustment module, wherein:

[0040] The acquisition module is configured to acquire flight path planning data and current flight state information of UAVs in a target airspace; the UAVs in the target airspace are all UAVs within a preset range centered on a target UAV;

[0041] The UAV determination module is configured to determine whether the current flight state information is consistent with the flight path planning data; if yes, the UAVs in the target airspace are marked as normal flight UAVs, and if no, the UAVs in the target airspace are marked as abnormal flight UAVs;

[0042] The monitoring module is configured to monitor positioning points of the UAVs in the target airspace and the target UAV in real time;

[0043] The collision determination module is configured to determine collision risk information and collision risk UAVs based on the flight path planning data; the collision risk information represents a collision time and a collision position;

[0044] The path adjustment module is configured to adjust path planning data of the collision risk UAVs based on the positioning points to avoid collision.

[0045] According to a third aspect of the present application, there is provided a UAV low airspace traffic decision system, comprising a TDOA monitoring station, a UAV RID regulatory system, a UAV flight management system and an airborne radar.

[0046] The UAV flight management system is configured to execute the UAV low airspace traffic decision method of the first aspect and the optional method thereof.

[0047] According to a fourth aspect of the present application, there is provided an electronic device, comprising a processor and a memory, wherein the memory is configured to store a code.

[0048] The processor is configured to execute the code in the memory to implement the method of the first aspect and the optional method thereof.

[0049] According to a fifth aspect of the present application, there is provided a storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the method of the first aspect and the optional method thereof.

[0050] The unmanned aerial vehicle low-altitude airspace traffic decision method provided by the application can divide target unmanned aerial vehicles into normal flight unmanned aerial vehicles and abnormal flight unmanned aerial vehicles by judging whether the current flight state information is consistent with the flight path planning data, further realize the management and control of unmanned aerial vehicles that do not fly according to the plan, and reduce the safety hidden danger of flight. In addition, the application can monitor the positioning point of the target unmanned aerial vehicle in real time, and further determine the relationship between the current position of the target unmanned aerial vehicle and the position of the collision risk unmanned aerial vehicle, so as to realize the accurate adjustment of the path planning data of the collision risk unmanned aerial vehicle to avoid collision, and further improve the flight efficiency of the unmanned aerial vehicle.

[0051] In the preferred embodiment, the application further realizes the confirmation of the collision point by combining the RID information, the airborne radar and the unmanned aerial vehicle positioning information, and further can monitor the flight state of the unmanned aerial vehicle in the target airspace again through the airborne radar after adjusting the path planning data of the collision risk unmanned aerial vehicle, perform emergency avoidance on the collision risk unmanned aerial vehicle that does not fly according to the flight path planning data, and improve the safety of the unmanned aerial vehicle flight. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0053] Figure 1 is a flowchart of the unmanned aerial vehicle low-altitude airspace traffic decision method in an embodiment of the application Figure 1 ;

[0054] Figure 2 is a flowchart of the unmanned aerial vehicle low-altitude airspace traffic decision method in an embodiment of the application Figure 2 ;

[0055] Figure 3 is a flowchart of the unmanned aerial vehicle low-altitude airspace traffic decision method in an embodiment of the application Figure 3 ;

[0056] Figure 4 is a flowchart of the unmanned aerial vehicle low-altitude airspace traffic decision method in an embodiment of the application Figure 4 ;

[0057] Figure 5 is a flowchart of the unmanned aerial vehicle low-altitude airspace traffic decision method in an embodiment of the application Figure 5 ;

[0058] Figure 6is a flowchart of a low-altitude airspace traffic decision method of a UAV in an embodiment of the present application Figure 6 ;

[0059] Figure 7 is a flowchart of a low-altitude airspace traffic decision method of a UAV in an embodiment of the present application Figure 7 ;

[0060] Figure 8 is a structural diagram of a low-altitude airspace traffic decision device of a UAV in an embodiment of the present application

[0061] Figure 9 is a structural diagram of an electronic device in an embodiment of the present application DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0063] The terms "first", "second", "third", "fourth" and the like (if any) in the specification and claims of the present application and the above drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to include only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0064] The technical solutions of the present application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and some embodiments may not be described again for the same or similar concepts or processes.

[0065] Please refer to Figure 1 , the present application provides a low-altitude airspace traffic decision method of a UAV, comprising:

[0066] S1: obtaining flight path planning data and current flight state information of a UAV in a target airspace; the UAV in the target airspace is represented as all UAVs within a preset range centered on a target UAV;

[0067] S2: judging whether the current flight state information is consistent with the flight path planning data; if yes, marking the unmanned aerial vehicle in the target airspace as a normal flight unmanned aerial vehicle, and if not, marking the unmanned aerial vehicle in the target airspace as an abnormal flight unmanned aerial vehicle;

[0068] S3: monitoring the unmanned aerial vehicle in the target airspace and the positioning point of the target unmanned aerial vehicle in real time;

[0069] S4: determining collision risk information and a collision risk unmanned aerial vehicle based on the flight path planning data;

[0070] S5: adjusting the path planning data of the collision risk unmanned aerial vehicle based on the positioning point to avoid collision.

[0071] Wherein, the collision risk information is represented as a collision time and a collision position.

[0072] Wherein, the flight path planning data includes a planned flight trajectory and a planned flight time of the unmanned aerial vehicle in the target airspace; the current flight state information includes a current flight trajectory, a current flight time, a type of unmanned aerial vehicle, a signal and a flight speed of the unmanned aerial vehicle in the target airspace.

[0073] Wherein, the target airspace is represented as an airspace range within 500 meters centered on the target unmanned aerial vehicle, of course, the present application is not limited thereto, and the range of the target airspace can be changed according to user-defined settings.

[0074] Wherein, the unmanned aerial vehicle in the target airspace is represented as an unmanned aerial vehicle having a trajectory point less than 500 meters away from the target unmanned aerial vehicle within three minutes based on the flight path planning data.

[0075] Regarding the classification of the unmanned aerial vehicle in the target airspace, in a preferred embodiment, please refer to Figure 2 and Figure 3 Before judging whether the current flight state information is consistent with the flight path planning data, the method further includes:

[0076] S21: obtaining RID information;

[0077] S22: judging whether the RID information is consistent with the unmanned aerial vehicle in the target airspace based on the RID information;

[0078] S23: if yes, reading the identity code, current position information, speed information, current flight state information and flight path planning data of the unmanned aerial vehicle from the RID information;

[0079] S24: If no, continue to acquire the flight path planning data corresponding to the RID information. The judging whether the current flight state information is consistent with the flight path planning data comprises:

[0080] S231: Based on the flight trajectory and flight time of the unmanned aerial vehicle in the target airspace, judging whether the time deviation between the planned flight time and the current flight time is within a first preset time threshold, and whether the position deviation of each trajectory point on the planned flight trajectory and the current flight trajectory is within a first preset distance threshold;

[0081] S232: If yes, mark the unmanned aerial vehicle in the target airspace as a normal flight unmanned aerial vehicle, and if no, mark the unmanned aerial vehicle in the target airspace as an abnormal flight unmanned aerial vehicle.

[0082] In a specific embodiment, the unmanned aerial vehicle receives the RID information of the unmanned aerial vehicle in the target airspace during flight, and reads the identity code, current position, speed and other information from the RID information; through calculation, if the RID information obtained within 500 meters (i.e. in the target airspace) does not match the unmanned aerial vehicle in the target airspace, the information of the unmanned aerial vehicle is sent to the unmanned aerial vehicle RID supervision system, requesting to keep track of it and informing relevant information (such as flight path planning data), and determining that the unmanned aerial vehicle is an abnormal flight unmanned aerial vehicle.

[0083] In other embodiments, if the time deviation of each trajectory point in the flight path planning data is within 10s, and the position deviation is within 50m, the unmanned aerial vehicle is marked as a normal flight unmanned aerial vehicle, otherwise the unmanned aerial vehicle is marked as an abnormal flight unmanned aerial vehicle.

[0084] In the above scheme, by judging whether the current flight state information is consistent with the flight path planning data, the target unmanned aerial vehicle is divided into a normal flight unmanned aerial vehicle and an abnormal flight unmanned aerial vehicle, further realizing the control of the unmanned aerial vehicle not flying according to the plan, reducing the safety hazard of flight; in addition, the present application can monitor the positioning point of the target unmanned aerial vehicle in real time, and further determine the relationship between the current position of the target unmanned aerial vehicle and the position of the collision risk unmanned aerial vehicle, so as to realize the accurate adjustment of the path planning data of the collision risk unmanned aerial vehicle to avoid collision, thereby improving the flight efficiency of the unmanned aerial vehicle.

[0085] Regarding the positioning of the unmanned aerial vehicle, in a preferred embodiment, please refer to Figure 4 The real-time monitoring of the target airspace unmanned aerial vehicle and the positioning point of the target unmanned aerial vehicle comprises:

[0086] S31: Based on a preset period, positioning the target airspace unmanned aerial vehicle and the target unmanned aerial vehicle, and determining a plurality of positioning points;

[0087] S32: determining a real-time flight trajectory based on the positioning points.

[0088] In specific embodiments, the preset period varies based on the type of the target UAV, for example, positioning once every 0.5 seconds for the abnormal flight UAV and once every second for the normal flight UAV.

[0089] For determination of collision, please refer to Figure 5 , the determination of collision risk information and collision risk UAV based on the flight path planning data includes:

[0090] S41: determining whether the following conditions are met based on the planned flight trajectory:

[0091] For the normal flight UAV, determining that the target UAV exists within a second preset time threshold and a second preset distance threshold of any flight trajectory point on the planned flight trajectory;

[0092] For the abnormal flight UAV, determining that the target UAV exists within a second preset time threshold and a third preset distance threshold of any flight trajectory point on the planned flight trajectory;

[0093] S42: if any of the above conditions is met, determining that the target UAV is a collision risk UAV, and determining that the flight trajectory point is a collision point; the collision risk UAV represents a UAV that may collide with the normal flight UAV and / or the abnormal flight UAV.

[0094] In specific embodiments, for a normal flight UAV, for a predetermined flight trajectory point, if there is a UAV within 5 seconds before and after and within 50 meters of the flight trajectory point, it is determined that there is a collision risk; for an abnormal flight UAV, for a predetermined flight trajectory point, if there is a UAV within 5 seconds before and after and within 100 meters of the flight trajectory point, it is determined that there is a collision risk.

[0095] For adjustment of path planning, please refer to Figure 6 , adjusting the path planning data of the collision risk UAV based on the positioning points includes:

[0096] S51: determining that the real-time positioning point of the collision risk UAV is the starting point, and the destination position of the collision risk UAV is the ending point;

[0097] S52: setting the distance between the path point on the collision risk UAV and the collision point to n times the actual distance; wherein n is a positive integer;

[0098] S53: adjusting the range of the path planning data from the entire flight motion to the real-time flight path.

[0099] In specific embodiments, the path planning is adjusted by the following process:

[0100] (1) The starting point of the path is the current position (i.e. the real-time positioning point), and the end point of the path is the target position of the UAV;

[0101] (2) The distance between the candidate path points with collision risk is set to 5 times the actual distance;

[0102] (3) If there is a UAV within 2 seconds before and after the flight trajectory point of the normal flight UAV and within 30 meters of the flight trajectory point, it is determined that there is a collision risk; if there is a UAV within 5 seconds before and after the flight trajectory point of the abnormal flight UAV and within 50 meters of the flight trajectory point, it is determined that there is a collision risk; and if it is determined that there is a collision risk within the above range, the collision point is determined to be a high-risk collision point, and the actual distance between the high-risk collision point and the real-time positioning point of the target UAV is adjusted to be collision-free;

[0103] (4) The range of dynamic path adjustment is adjusted from the entire motion to 1 minute of flight path.

[0104] For emergency obstacle avoidance, please refer to Figure 7 The UAV low-altitude traffic decision-making method further comprises:

[0105] S61: Based on the collision risk information and the time sequence, the direction of the collision risk UAV is scanned;

[0106] S62: If the collision risk UAV is found, the radar position information of the collision risk UAV is obtained, and it is determined whether the radar position information is consistent with the positioning point of the collision risk UAV and the position information in the RID information of the collision risk UAV;

[0107] S63: If yes, the path planning data of the collision risk UAV is adjusted;

[0108] S64: If no, emergency obstacle avoidance is performed based on the radar position information of the collision risk UAV;

[0109] S65: Based on the position and speed of the collision risk UAV after emergency obstacle avoidance, the path planning data of the collision risk UAV is re-planned.

[0110] In specific embodiments, the UAV on-board radar scans the direction of the risk source UAV in time sequence according to the collision risk, and compares it with the TDOA monitoring station positioning and the received RID information. If they are consistent, the path adjustment avoidance according to S5 is continued; if they are not consistent, the avoidance is performed according to the following process:

[0111] (1) sending the radar scanning positioning determination data to the unmanned aerial vehicle flight management system to perform emergency obstacle avoidance;

[0112] (2) reporting the unmanned aerial vehicle position scanned by the radar to the TDOA monitoring station, applying for monitoring, tracking and information determination on the unmanned aerial vehicle at the position, and sharing data with the unmanned aerial vehicle RID supervision system and the unmanned aerial vehicle flight management system, and then putting the information of the unmanned aerial vehicle into the process management of S1-S4;

[0113] (3) reporting the path of emergency obstacle avoidance to the unmanned aerial vehicle flight management system, and sending the current position and speed of the target unmanned aerial vehicle through the airborne RID module;

[0114] (4) recalculating the path planning according to the position and speed after emergency obstacle avoidance, and reporting to the unmanned aerial vehicle flight management system.

[0115] In addition, after scanning, if the collision risk unmanned aerial vehicle is not found, the scanning time and the radar not scanning the predetermined target (i.e. the collision risk unmanned aerial vehicle) in the scanning airspace range are reported to the system (such as the unmanned aerial vehicle flight management system, the unmanned aerial vehicle RID supervision system, and the TDOA monitoring station) providing the collision risk unmanned aerial vehicle information.

[0116] In the above scheme, the present application further combines the RID information, the airborne radar and the unmanned aerial vehicle positioning information to realize the confirmation of the collision point, and then can monitor the flight state of the unmanned aerial vehicle in the target airspace again through the airborne radar after adjusting the path planning data of the collision risk unmanned aerial vehicle, and perform emergency avoidance on the collision risk unmanned aerial vehicle not flying according to the flight path planning data, thereby improving the safety of unmanned aerial vehicle flight.

[0117] Please refer to Figure 8 The present application further provides a low-altitude airspace traffic decision device 7 of an unmanned aerial vehicle, comprising an acquisition module 71, an unmanned aerial vehicle determination module 72, a monitoring module 73, a collision determination module 74 and a path adjustment module 75, wherein:

[0118] The acquisition module 71 is used for acquiring flight path planning data and current flight state information of an unmanned aerial vehicle in a target airspace; the unmanned aerial vehicle in the target airspace represents all unmanned aerial vehicles in a preset range centered on a target unmanned aerial vehicle.

[0119] The unmanned aerial vehicle determination module 72 is used for judging whether the current flight state information is consistent with the flight path planning data; if yes, the unmanned aerial vehicle in the target airspace is marked as a normal flight unmanned aerial vehicle, and if no, the unmanned aerial vehicle in the target airspace is marked as an abnormal flight unmanned aerial vehicle.

[0120] Optionally, before the judging whether the current flight state information is consistent with the flight path planning data, the method further comprises:

[0121] acquiring RID information;

[0122] judging whether the RID information is consistent with the target airspace unmanned aerial vehicle based on the RID information;

[0123] if yes, reading the identity code, current position information, speed information, the current flight state information and the flight path planning data of the unmanned aerial vehicle from the RID information;

[0124] if no, continuing to acquire the flight path planning data corresponding to the RID information.

[0125] Optionally, the judging whether the current flight state information is consistent with the flight path planning data comprises:

[0126] judging whether the planned flight time and the current flight time are within a first preset time threshold and whether each trajectory point position deviation on the planned flight trajectory and the current flight trajectory is within a first preset distance threshold based on the flight trajectory and the flight time of the target airspace unmanned aerial vehicle;

[0127] if yes, marking the target airspace unmanned aerial vehicle as a normal flight unmanned aerial vehicle, and if no, marking the target airspace unmanned aerial vehicle as an abnormal flight unmanned aerial vehicle.

[0128] The monitoring module 73 is configured to monitor the target airspace unmanned aerial vehicle and the positioning point of the target unmanned aerial vehicle in real time.

[0129] Optionally, the real-time monitoring of the target airspace unmanned aerial vehicle and the positioning point of the target unmanned aerial vehicle comprises:

[0130] positioning the target airspace unmanned aerial vehicle and the target unmanned aerial vehicle based on a preset period, and determining a plurality of positioning points;

[0131] determining a real-time flight trajectory based on the plurality of positioning points.

[0132] The collision determination module 74 is configured to determine collision risk information and a collision risk unmanned aerial vehicle based on the flight path planning data, wherein the collision risk information represents a collision time and a collision position.

[0133] Optionally, the determining collision risk information and a collision risk unmanned aerial vehicle based on the flight path planning data comprises:

[0134] judging whether the following condition is met based on the planned flight trajectory:

[0135] For the normal unmanned aerial vehicle, it is determined that the target unmanned aerial vehicle exists within a second preset time threshold and a second preset distance threshold of a flight trajectory point on any of the planned flight trajectories;

[0136] For the abnormal unmanned aerial vehicle, it is determined that the target unmanned aerial vehicle exists within a second preset time threshold and a third preset distance threshold of a flight trajectory point on any of the planned flight trajectories;

[0137] If any of the above conditions is met, the target unmanned aerial vehicle is determined to be a collision risk unmanned aerial vehicle, and the flight trajectory point is determined to be a collision point; the collision risk unmanned aerial vehicle represents an unmanned aerial vehicle that may collide with the normal unmanned aerial vehicle and / or the abnormal unmanned aerial vehicle.

[0138] The path adjustment module 75 is configured to adjust path planning data of the collision risk unmanned aerial vehicle based on the positioning point to avoid collision.

[0139] Optionally, the adjustment of the path planning data of the collision risk unmanned aerial vehicle based on the positioning point comprises:

[0140] The real-time positioning point of the collision risk unmanned aerial vehicle is determined as a starting point, and the destination position of the collision risk unmanned aerial vehicle is determined as an ending point;

[0141] The distance between the path point on the collision risk unmanned aerial vehicle and the collision point is set to n times of the actual distance; wherein n is a positive integer;

[0142] The range of the path planning data is adjusted from the entire flight motion to the real-time flight path.

[0143] Optionally, the unmanned aerial vehicle low-altitude traffic decision method further comprises:

[0144] Based on the collision risk information and the time sequence, the direction of the collision risk unmanned aerial vehicle is scanned;

[0145] If the collision risk unmanned aerial vehicle is found, radar position information of the collision risk unmanned aerial vehicle is obtained, and it is determined whether the radar position information is consistent with the positioning point of the collision risk unmanned aerial vehicle and the position information in the RID information of the collision risk unmanned aerial vehicle;

[0146] If yes, the path planning data of the collision risk unmanned aerial vehicle is adjusted;

[0147] If no, emergency obstacle avoidance is performed based on the radar position information of the collision risk unmanned aerial vehicle;

[0148] replan path planning data of the collision risk UAV based on the collision risk UAV position and speed after the emergency obstacle avoidance.

[0149] The application further provides a UAV low-altitude airspace traffic decision system, comprising a TDOA monitoring station, a UAV RID supervision system, a UAV flight management system and an airborne radar.

[0150] The UAV flight management system is used in the UAV low-altitude airspace traffic decision method.

[0151] Please refer to Figure 9 , provides an electronic device 8, comprising:

[0152] a processor 81; and,

[0153] a memory 82, configured to store executable instructions of the processor;

[0154] The processor 81 is configured to execute the above-mentioned method by executing the executable instructions.

[0155] The processor 81 can communicate with the memory 82 through the bus 83.

[0156] The application further provides a computer readable storage medium, which stores a computer program, and the program is executed by the processor to realize the above-mentioned method.

[0157] Those skilled in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction related hardware. The foregoing program can be stored in a computer readable storage medium. The program is executed to perform the steps of the above-mentioned method embodiments; and the foregoing storage medium includes ROM, RAM, magnetic disc or optical disc and various storage medium capable of storing program codes.

[0158] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the application, and not to limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the application.

Claims

1. A method for unmanned aerial low airspace traffic decision, characterized in that, The method comprises the following steps: acquiring flight path planning data and current flight state information of a target airspace unmanned aerial vehicle (UAV); the target airspace UAV represents all UAVs within a preset range centered on a target UAV; determining whether the current flight state information is consistent with the flight path planning data; if yes, marking the target airspace UAV as a normal flight UAV; if no, marking the target airspace UAV as an abnormal flight UAV; real-time monitoring of positioning points of the target airspace UAV and the target UAV; based on the flight path planning data, determining collision risk information and a collision risk UAV; the collision risk information represents a collision time and a collision position; based on the positioning points, adjusting path planning data of the collision risk UAV to avoid collision; wherein, the flight path planning data comprises planned flight trajectories of the target airspace UAV; the determination of the collision risk information and the collision risk UAV based on the flight path planning data comprises: based on the planned flight trajectories, determining whether the following conditions are met: for the normal flight UAV, determining whether the target UAV exists within a second preset time threshold and a second preset distance threshold of any flight trajectory point on the planned flight trajectory; for the abnormal flight UAV, determining whether the target UAV exists within a second preset time threshold and a third preset distance threshold of any flight trajectory point on the planned flight trajectory; if any of the above conditions is met, determining that the target UAV is a collision risk UAV, and determining that the flight trajectory point is a collision point; the collision risk UAV represents a UAV that may collide with the normal flight UAV and / or the abnormal flight UAV. 2.The UAV low airspace traffic decision method of claim 1, wherein, The flight path planning data further comprises planned flight time of the target airspace UAV; the current flight state information comprises current flight trajectory, current flight time, UAV type, signal, and flight speed of the target airspace UAV.

3. The UAV low airspace traffic decision method of claim 2, wherein, The determination of whether the current flight state information is consistent with the flight path planning data comprises: based on the flight trajectory and flight time of the target airspace UAV, determining whether a time deviation between the planned flight time and the current flight time is within a first preset time threshold, and whether a position deviation between each trajectory point on the planned flight trajectory and the current flight trajectory is within a first preset distance threshold; if yes, marking the target airspace UAV as a normal flight UAV; if no, marking the target airspace UAV as an abnormal flight UAV.

4. The UAV low airspace traffic decision method of claim 3, wherein, Before the determination of whether the current flight state information is consistent with the flight path planning data, the method further comprises: acquiring RID information; based on the RID information, determining whether the RID information is consistent with the target airspace UAV; if yes, reading an identity code, current position information, speed information, the current flight state information, and the flight path planning data of the UAV from the RID information; If not, continue to acquire the flight path planning data corresponding to the RID information.

5. The UAV low airspace traffic decision method of claim 1, wherein, The real-time monitoring of the positioning points of the unmanned aerial vehicles in the target airspace and the target unmanned aerial vehicle includes: Based on a preset period, the positioning of the unmanned aerial vehicles in the target airspace and the target unmanned aerial vehicle is performed, and a plurality of positioning points are determined; Based on the plurality of positioning points, a real-time flight trajectory is determined.

6. The UAV low airspace traffic decision method of claim 1, wherein, Based on the positioning points, adjusting the path planning data of the collision risk unmanned aerial vehicle includes: Determining the real-time positioning point of the collision risk unmanned aerial vehicle as a starting point, and the destination position of the collision risk unmanned aerial vehicle as an end point; Setting the distance between the path point of the collision risk unmanned aerial vehicle and the collision point to n times of the actual distance; wherein n is a positive integer; Adjusting the range of the path planning data from the whole flight motion to the real-time flight path.

7. The UAV low airspace traffic decision method of claim 6, wherein, Further comprising: Based on the collision risk information and the time sequence, scanning the direction of the collision risk unmanned aerial vehicle; If the collision risk unmanned aerial vehicle is found, acquiring radar position information of the collision risk unmanned aerial vehicle, and determining whether the radar position information is consistent with the real-time positioning point of the collision risk unmanned aerial vehicle and the position information in the RID information of the collision risk unmanned aerial vehicle; If yes, adjusting the path planning data of the collision risk unmanned aerial vehicle; If not, performing emergency obstacle avoidance based on the radar position information of the collision risk unmanned aerial vehicle; Based on the position and speed of the collision risk unmanned aerial vehicle after emergency obstacle avoidance, re-planning the path planning data of the collision risk unmanned aerial vehicle.

8. An unmanned aerial low airspace traffic decision device, comprising: Comprising an acquisition module, an unmanned aerial vehicle determination module, a monitoring module, a collision determination module, and a path adjustment module, wherein: The acquisition module is configured to acquire flight path planning data and current flight state information of unmanned aerial vehicles in a target airspace; the unmanned aerial vehicles in the target airspace represent all unmanned aerial vehicles within a preset range centered on a target unmanned aerial vehicle; The unmanned aerial vehicle determination module is configured to determine whether the current flight state information is consistent with the flight path planning data; if yes, the unmanned aerial vehicles in the target airspace are marked as normal flight unmanned aerial vehicles, and if not, the unmanned aerial vehicles in the target airspace are marked as abnormal flight unmanned aerial vehicles; The monitoring module is configured to monitor the positioning points of the unmanned aerial vehicles in the target airspace and the target unmanned aerial vehicle in real time; The collision determination module is configured to determine collision risk information and collision risk unmanned aerial vehicles based on the flight path planning data; the flight path planning data includes planned flight trajectories of the unmanned aerial vehicles in the target airspace, and the collision risk information represents collision time and collision position; specifically configured to: Based on the planned flight trajectories, determine whether the following conditions are met: For the normal flight unmanned aerial vehicles, determine that the target unmanned aerial vehicle exists within a second preset time threshold and a second preset distance threshold of any flight trajectory point on the planned flight trajectories; For the abnormal flight unmanned aerial vehicles, determine that the target unmanned aerial vehicle exists within a second preset time threshold and a third preset distance threshold of any flight trajectory point on the planned flight trajectories; If any of the above conditions is met, the target UAV is determined as a collision risk UAV, and the flight trajectory point is determined as a collision point; the collision risk UAV represents a UAV that is likely to collide with the normal flight UAV and / or the abnormal flight UAV; The path adjustment module is configured to adjust path planning data of the collision risk UAV based on the positioning point to avoid collision.

9. An unmanned aircraft low airspace traffic decision system, comprising: The method comprises: a TDOA monitoring site, a UAV RID supervision system, a UAV flight management system, and an airborne radar; The UAV flight management system is configured to execute the UAV low-altitude airspace traffic decision method according to any one of claims 1 to 7.

10. An electronic device, comprising: The method comprises a processor and a memory, wherein the memory is configured to store codes; The processor is configured to execute the codes in the memory to implement the method according to any one of claims 1 to 7. 11.A storage medium having a computer program stored thereon, wherein the program is executed by a processor to implement the method according to any one of claims 1 to 7.

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