CN113961018A - Method and device for determining collision risk of unmanned aerial vehicle - Google Patents
Method and device for determining collision risk of unmanned aerial vehicle Download PDFInfo
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Abstract
The application provides a method and a device for determining collision risk of an unmanned aerial vehicle, wherein the method comprises the following steps: acquiring an unmanned aerial vehicle with changed longitude and latitude and/or height information, and determining the unmanned aerial vehicle as a target unmanned aerial vehicle; determining a target geocode corresponding to the longitude and latitude, and determining a height code corresponding to the height information; the target geographic code is used for uniquely identifying the plane area range of the target unmanned aerial vehicle, and the height code is used for uniquely identifying the height range of the target unmanned aerial vehicle; and determining whether the target unmanned aerial vehicle has collision risk or not according to a target stereo code formed by the target geocode and the altitude code and/or the target geocode. This application has solved discernment unmanned aerial vehicle and has had the technical problem that collision risk calculated amount is big and inefficiency through comparing unmanned aerial vehicle's stereo coding or geocoding, reaches the technological effect that improves discernment unmanned aerial vehicle and whether has the efficiency of collision risk.
Description
Technical Field
The application relates to the technical field of computers, in particular to a method and a device for determining collision risk of an unmanned aerial vehicle.
Background
In the prior art, when the early warning of the collision risk of flying the unmanned aerial vehicle is carried out, the distance value between the unmanned aerial vehicles needs to be calculated in real time according to the longitude and latitude and the height information of the unmanned aerial vehicle. Under the more condition of unmanned aerial vehicle, need carry out a large amount of calculations. If under the circumstances of unmanned aerial vehicle's flight volume and density sharply increase, prior art's inefficiency, and the early warning effect is poor, can't effectively ensure unmanned aerial vehicle's flight safety in time.
Disclosure of Invention
In view of this, an object of the present application is to provide at least a method and an apparatus for determining a collision risk of an unmanned aerial vehicle, which solve the technical problems of large calculated amount and low efficiency in identifying whether the unmanned aerial vehicle has a collision risk by comparing stereo codes or geocodes of the unmanned aerial vehicle, and achieve the technical effect of improving the efficiency of identifying whether the unmanned aerial vehicle has a collision risk.
The application mainly comprises the following aspects:
in a first aspect, an embodiment of the present application provides a method for determining a collision risk of an unmanned aerial vehicle, where the method includes: acquiring an unmanned aerial vehicle with changed longitude and latitude and/or height information, and determining the unmanned aerial vehicle as a target unmanned aerial vehicle; determining a target geocode corresponding to the longitude and latitude, and determining a height code corresponding to the height information; the target geographic code is used for uniquely identifying the plane area range of the target unmanned aerial vehicle, and the height code is used for uniquely identifying the height range of the target unmanned aerial vehicle; and determining whether the target unmanned aerial vehicle has collision risk or not according to a target stereo code formed by the target geocode and the altitude code and/or the target geocode.
Optionally, determining the height code corresponding to the height information includes: setting a preset height range and preset dividing precision; the preset height range comprises a preset height minimum value and a preset height maximum value; determining a middle value of a preset height range; judging whether the height information is between the preset height minimum value and the middle value or between the middle value and the preset height maximum value; if the height information is located between the preset height minimum value and the middle value, the division mark of the time is 0, the preset height minimum value and the middle value are used as a new preset height range, and the difference value between the middle value and the preset height minimum value is determined as a height range difference value; if the height information is located between the middle value and the preset height maximum value, the division mark of the time is 1, the middle value and the preset height maximum value are used as a new preset height range, and the difference value between the preset height maximum value and the middle value is determined as a height range difference value; judging whether the height range difference value is equal to the preset dividing precision or not; and if the height range difference value is equal to the preset division precision, combining all the division marks according to the sequence, and determining the combined result as the height code of the target unmanned aerial vehicle.
Optionally, determining whether the target drone has a collision risk according to a target stereo code composed of a target geocode and an altitude code, including: judging whether a target three-dimensional code exists in the three-dimensional code sets of all unmanned aerial vehicles except the target unmanned aerial vehicle; and if the target stereo code exists in the stereo code set, determining the unmanned aerial vehicle corresponding to the target stereo code in the stereo code set, and having a collision risk with the target unmanned aerial vehicle.
Optionally, determining whether the target drone is at risk of collision according to the target geocode includes: acquiring geocodes adjacent to the target geocode; comparing the geocode sets of all unmanned aerial vehicles except the target unmanned aerial vehicle with adjacent geocodes, and determining whether the target unmanned aerial vehicle has collision risks according to comparison results.
Optionally, determining whether the target drone has a collision risk according to the comparison result, including: judging whether geocodes adjacent to the target geocode exist in the geocode set or not; if the geocode adjacent to the target geocode exists in the geocode set, determining the unmanned aerial vehicle corresponding to the adjacent geocode in the geocode set as the unmanned aerial vehicle to be determined; and judging whether the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have collision risks or not according to the longitude and latitude and the height information of the unmanned aerial vehicle to be determined.
Optionally, judging whether the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have a collision risk according to the longitude and latitude and the height information of the unmanned aerial vehicle to be determined includes: acquiring longitude and latitude and height information of an unmanned aerial vehicle to be determined and longitude and latitude and height information of a target unmanned aerial vehicle; calculating a distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle; judging whether the distance value is smaller than a preset safety distance or not; and if the distance value is smaller than the preset safety distance, determining that the unmanned aerial vehicle to be determined has collision risk with the target unmanned aerial vehicle.
Optionally, the method further comprises: obtaining a region corresponding to the target geocode, and trisecting the long side and the wide side corresponding to the region, so that the region is divided into nine subregions with equal size; identifying whether the target unmanned aerial vehicle is located in a central subregion of the subregions or not according to the longitude and latitude of the target unmanned aerial vehicle; calculating the distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle, wherein the distance value comprises the following steps: and if the target unmanned aerial vehicle is not in the central subarea of the subarea, calculating the distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle.
Optionally, calculating a distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and altitude information of the unmanned aerial vehicle to be determined and the longitude and latitude and altitude information of the target unmanned aerial vehicle, including: judging whether the target unmanned aerial vehicle is located in a first sub-area of the area or in a second sub-area of the area; the first sub-area refers to any sub-area positioned at four corners of the area, and the second sub-area refers to any sub-area except the central sub-area and the first sub-area in the area; if the target unmanned aerial vehicle is located in the first sub-region, selecting the unmanned aerial vehicle to be determined corresponding to the three geocodes adjacent to the first sub-region from the unmanned aerial vehicles to be determined, and determining the unmanned aerial vehicle to be determined as the target unmanned aerial vehicle to be determined; if the target unmanned aerial vehicle is located in the second sub-region, selecting the unmanned aerial vehicle to be determined corresponding to one geocode adjacent to the second sub-region from the unmanned aerial vehicles to be determined, and determining the unmanned aerial vehicle to be determined as the target unmanned aerial vehicle to be determined; judging whether the distance value between the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle is smaller than a preset safety distance or not; and if the distance value between the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle is smaller than the preset safety distance, determining that the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have collision risk.
In a second aspect, an embodiment of the present application further provides an apparatus for determining a collision risk of an unmanned aerial vehicle, where the apparatus includes: the first determining module is used for acquiring the unmanned aerial vehicle with changed longitude and latitude and/or height information and determining the unmanned aerial vehicle as a target unmanned aerial vehicle; the second determination module is used for determining the target geocode corresponding to the longitude and latitude and determining the altitude code corresponding to the altitude information; the target geographic code is used for uniquely identifying the plane area range of the target unmanned aerial vehicle, and the height code is used for uniquely identifying the height range of the target unmanned aerial vehicle; and the third determining module is used for determining whether the target unmanned aerial vehicle has collision risk according to a target stereo code formed by the target geocode and the altitude code and/or the target geocode.
In a third aspect, an embodiment of the present application further provides an electronic device, including: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, when the electronic device runs, the processor and the memory communicate with each other through the bus, and when the processor runs, the machine-readable instructions perform the steps of the method for determining collision risk of the unmanned aerial vehicle in the first aspect or any one of the possible implementation manners of the first aspect.
In a fourth aspect, this application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the step of determining the collision risk of the unmanned aerial vehicle in the first aspect or any one of the possible implementation manners of the first aspect.
The embodiment of the application provides a method and a device for determining collision risk of an unmanned aerial vehicle, and the method comprises the following steps: acquiring an unmanned aerial vehicle with changed longitude and latitude and/or height information, and determining the unmanned aerial vehicle as a target unmanned aerial vehicle; determining a target geocode corresponding to the longitude and latitude, and determining a height code corresponding to the height information; the target geographic code is used for uniquely identifying the plane area range of the target unmanned aerial vehicle, and the height code is used for uniquely identifying the height range of the target unmanned aerial vehicle; and determining whether the target unmanned aerial vehicle has collision risk or not according to a target stereo code formed by the target geocode and the altitude code and/or the target geocode. This application has solved discernment unmanned aerial vehicle and has had the technical problem that collision risk calculated amount is big and inefficiency through comparing unmanned aerial vehicle's stereo coding or geocoding, reaches the technological effect that improves discernment unmanned aerial vehicle and whether has the efficiency of collision risk.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 shows a flowchart of a method for determining a collision risk of an unmanned aerial vehicle according to an embodiment of the present application.
Fig. 2 shows a flowchart for determining a height code corresponding to height information according to an embodiment of the present application.
Fig. 3 shows a flowchart for determining whether a target drone is at a collision risk according to a target stereo code composed of a target geocode and a height code, provided by an embodiment of the present application.
Fig. 4 shows a flowchart for determining whether a target drone is at risk of collision according to a target geocode, according to an embodiment of the present application.
Fig. 5 shows a schematic diagram of target stereo encoding provided by an embodiment of the present application.
Fig. 6 shows a schematic diagram of a target geocode and its neighboring geocodes provided by an embodiment of the present application.
Fig. 7 shows a schematic diagram of a sub-region of a target geocode and its neighboring geocodes provided by an embodiment of the present application.
Fig. 8 shows a functional block diagram of an apparatus for determining a collision risk of an unmanned aerial vehicle according to an embodiment of the present application.
Fig. 9 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, 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, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of protection of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and that steps without logical context may be performed in reverse order or concurrently. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.
In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
The mode of determining whether the unmanned aerial vehicle has collision risk in the prior art is to acquire the longitude and latitude and the height of all unmanned aerial vehicles, calculate the distance value between the unmanned aerial vehicles, and when a large number of unmanned aerial vehicles carry out high-altitude operation, the calculated amount of the mode is too large, so that the recognition efficiency and the accuracy are influenced.
Based on this, the embodiment of the application provides a method and a device for determining collision risk of an unmanned aerial vehicle, and the application solves the technical problems of large collision risk calculation amount and low efficiency in identifying whether the unmanned aerial vehicle has collision risk by comparing stereo codes or geocodes of the unmanned aerial vehicle, and achieves the technical effect of improving the efficiency of identifying whether the unmanned aerial vehicle has collision risk, and the method and the device are specifically as follows:
referring to fig. 1, fig. 1 is a flowchart of a method for determining a collision risk of an unmanned aerial vehicle according to an embodiment of the present application. As shown in fig. 1, the method for determining the collision risk of the unmanned aerial vehicle provided by the embodiment of the application includes the following steps:
s101, acquiring the unmanned aerial vehicle with the changed longitude and latitude and/or height information, and determining the unmanned aerial vehicle as a target unmanned aerial vehicle.
Specifically, longitude and latitude and height information of all unmanned aerial vehicles in the flying airspace are monitored in real time, the unmanned aerial vehicles with changed longitude and latitude and/or height information are obtained and determined as target unmanned aerial vehicles, and the number of the target unmanned aerial vehicles is not limited. If the unmanned aerial vehicles in the flying airspace have no changes of longitude and latitude and height information, the unmanned aerial vehicle does not have a target.
S102, determining target geocodes corresponding to the longitude and latitude, and determining altitude codes corresponding to altitude information.
Specifically, a target geocode corresponding to the longitude and latitude of the target unmanned aerial vehicle is determined, and a height code corresponding to the height information of the target unmanned aerial vehicle is determined. The target geocode is used for uniquely identifying the plane area range of the target unmanned aerial vehicle, and the height code is used for uniquely identifying the range of the height of the target unmanned aerial vehicle.
And determining the geocode corresponding to the longitude and latitude of other unmanned aerial vehicles except the target unmanned aerial vehicle. Geocoding is also called geohash, which is a hierarchical data structure whose main idea is to divide the space into meshes, and is commonly used for planar 2D maps.
Referring to fig. 2, fig. 2 is a flowchart for determining a height code corresponding to height information according to an embodiment of the present disclosure. As shown in fig. 2, the height code corresponding to the determined height information provided in the embodiment of the present application includes the following steps:
s10221, setting a preset height range and preset dividing precision; the preset height range comprises a preset height minimum value and a preset height maximum value.
Specifically, the preset division accuracy depends on the result of bisection of the preset height range.
Illustratively, if the height information is 222.4628 meters, setting a preset height range of 0-1000 meters away from the sea level, wherein 0 meter is a preset height minimum value, 1000 meters is a preset height maximum value, and 15.625 meters is set as a preset division precision. That is, 0 to 1000 meters are divided by 15.625 meters as one layer.
S10222, determining a middle value of the preset height range.
Illustratively, the median value of the preset height range is 500 meters.
S10223, judging the height information is located between the preset height minimum value and the middle value, or between the middle value and the preset height maximum value.
Specifically, the height information is compared with the intermediate value, and it is determined that the height information is located between the preset height minimum value and the intermediate value, or between the intermediate value and the preset height maximum value.
That is, it is determined whether the height information is equal to or less than the intermediate value or greater than the intermediate value.
S10224, if the height information is located between the preset height minimum value and the middle value, the division is marked as 0, the preset height minimum value and the middle value are used as a new preset height range, and the difference between the middle value and the preset height minimum value is determined as a height range difference.
That is, if the height information is located between the preset height minimum value and the middle value, that is, if the height information is equal to or less than the middle value, the division of this time is marked as 0, and the preset height minimum value and the middle value are taken as a new preset height range.
If the height information is exactly equal to the median value, the division of this time is marked 0.
Illustratively, the height information is 222.4628 meters, 222.4628 meters is between the preset height minimum and the median, the division of this time is marked as 0, and 0 meters to 500 meters is determined as the new preset height range, 500 meters being the height range difference.
S10225, if the height information is located between the middle value and the preset height maximum value, the division is marked as 1, the middle value and the preset height maximum value are used as a new preset height range, and the difference between the preset height maximum value and the middle value is determined as a height range difference.
That is, if the height information is located between the middle value and the preset height maximum value, that is, if the height information is greater than the middle value, the division of this time is marked as 1, and the middle value and the preset height maximum value are taken as a new preset height range.
S10226, determining whether the height range difference is equal to the preset division precision.
And if the height range difference value is equal to the preset division precision, combining all the division marks according to the sequence, and determining the combined result as the height code of the target unmanned aerial vehicle.
If the height range difference is not equal to the preset dividing precision, the process returns to step S10222 to determine the middle value of the preset height range, and continues dividing.
Illustratively, when the division is performed to a preset height minimum value of 218.75 m, a median value of 234.375 m, and a preset height maximum value of 250 m, where 222.4628 m is between 218.75 m and 234.375 m, the division is marked as 0 this time, and the difference between 218.75 m and 234.375 m is 15.625 m, i.e., the height range difference is 15.625 m, which is equal to the preset division accuracy, the division is stopped.
S10227, all the division marks are combined according to the sequence, and the combined result is determined as the height code of the target unmanned aerial vehicle.
Illustratively, a preset height range is set to be 0-1000 m away from the sea level, wherein 0 m is a preset height minimum value, 1000 m is a preset height maximum value, and 15.625 m is set as a preset division precision. If the height information is 222.4628 m, the process of determining the height code refers to table one:
table one:
| preset height minimum | Median value | Preset maximum height | Height range difference | Division mark |
| 0 | 500 | 1000 | 500 | 0 |
| 0 | 250 | 500 | 250 | 0 |
| 0 | 125 | 250 | 125 | 1 |
| 125 | 187.5 | 250 | 62.5 | 1 |
| 187.5 | 218.75 | 250 | 31.25 | 1 |
| 218.75 | 234.38 | 250 | 15.625 | 0 |
Then, the height information is 222.4628 meters and is encoded as 001110.
S103, determining whether the target unmanned aerial vehicle has collision risk according to a target stereo code formed by the target geocode and the altitude code and/or the target geocode.
The first embodiment is as follows: and determining whether the target unmanned aerial vehicle has collision risk or not according to a target stereo code formed by the target geocode and the altitude code.
Referring to fig. 5, fig. 5 is a schematic diagram of target stereo encoding in the embodiment of the present application. That is, in flight airspace, the target drone is located in the spatial region corresponding to the target stereo code wtmk4rbp001110 shown in fig. 5.
Referring to fig. 3, fig. 3 is a flowchart for determining whether a target drone has a collision risk according to a target stereo code composed of a target geocode and a height code according to an embodiment of the present application. As shown in fig. 3, the determining whether the target drone has a collision risk according to the target stereo code composed of the target geocode and the altitude code provided in the embodiment of the present application includes the following steps:
and S10311, judging whether the target stereo codes exist in the stereo code sets of all the unmanned aerial vehicles except the target unmanned aerial vehicle.
That is, in the stereo code set of all drones except the target drone, it is confirmed whether there is a stereo code identical to the target stereo code.
Illustratively, it is determined whether a stereo encoding wtmk4rbp001110 exists in the stereo encoding set.
And S10312, determining the unmanned aerial vehicle corresponding to the target stereo code in the stereo code set, wherein a collision risk exists between the unmanned aerial vehicle and the target unmanned aerial vehicle.
And if the target stereo code exists in the stereo code set, determining the unmanned aerial vehicle corresponding to the target stereo code in the stereo code set, and having a collision risk with the target unmanned aerial vehicle.
If the target stereo code does not exist in the stereo code set, the target unmanned aerial vehicle does not have collision risk.
Example two: and determining whether the target unmanned aerial vehicle has collision risk or not according to the target geocode.
Referring to fig. 4, fig. 4 is a flowchart for determining whether a target drone is at a collision risk according to a target geocode according to an embodiment of the present application. As shown in fig. 4, the determining whether the target drone is at risk of collision according to the target geocode provided in the embodiment of the present application includes the following steps:
s10321, acquiring geocodes adjacent to the target geocode.
The geocode adjacent to the target geocode refers to the geocode of the grid adjacent to the grid corresponding to the target geocode.
The adjacent geocoding in the embodiment of the application refers to that a nine-square grid is created by taking the target geocode as the center, and the other eight geocodes of the nine-square grid are arranged except the target geocode at the center. Referring to fig. 6, fig. 6 is a schematic diagram of a target geocode and its neighboring geocodes according to an embodiment of the present application. As shown in fig. 6, wtmk4rbp is the target geocode of the target drone, and wtmk4rbr, wtmk4rbn, wtmk4pzy, wtmk6202, wtmk4rbp, wtmk4pzz, wtmk6200, wtmk60pb, and wtmk4rbq are geocodes adjacent to the target geocode.
S10322, comparing the geocode sets of all the drones except the target drone with adjacent geocodes, and determining whether there is a geocode adjacent to the target geocode in the geocode set.
Specifically, the geocode sets of all unmanned aerial vehicles except the target unmanned aerial vehicle are compared with adjacent geocodes, and whether the target unmanned aerial vehicle has collision risks or not is determined according to comparison results.
Illustratively, it is determined whether the following geocodes exist in the geocode set: wtmk4rbr, wtmk4rbn, wtmk4pzy, wtmk6202, wtmk4pzz, wtmk6200, wtmk60pb, and wtmk4 rbq.
S10323, determining the unmanned aerial vehicle corresponding to the adjacent geocode in the geocode set as the unmanned aerial vehicle to be determined.
And if the geocode adjacent to the target geocode does not exist in the geocode set, the target unmanned aerial vehicle has no collision risk.
And if the geocode adjacent to the target geocode exists in the geocode set, determining the unmanned aerial vehicle corresponding to the adjacent geocode in the geocode set as the unmanned aerial vehicle to be determined.
That is, there is at least one geocode in the set of geocodes: and determining the unmanned aerial vehicle corresponding to the geocode as the unmanned aerial vehicle to be determined by wtmk4rbr, wtmk4rbn, wtmk4pzy, wtmk6202, wtmk4pzz, wtmk6200, wtmk60pb and wtmk4 rbq.
Specifically, whether the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have collision risks or not is judged according to longitude and latitude and height information of the unmanned aerial vehicle to be determined.
S10324, acquiring longitude and latitude and height information of the unmanned aerial vehicle to be determined and longitude and latitude and height information of the target unmanned aerial vehicle.
S10325, calculating a distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle.
Specifically, if a plurality of unmanned aerial vehicles to be determined exist, distance values between the plurality of unmanned aerial vehicles to be determined can be calculated, and whether collision risks exist between the plurality of unmanned aerial vehicles to be determined is judged.
And S10326, judging whether the distance value is smaller than a preset safety distance.
Specifically, the preset safe distance is generally set to be 100 meters, and can be adjusted according to actual conditions.
S10327, determining that the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have collision risks.
And if the distance value is smaller than the preset safety distance, determining that the unmanned aerial vehicle to be determined has collision risk with the target unmanned aerial vehicle.
And if the distance value is greater than or equal to the preset safety distance, determining that the unmanned aerial vehicle to be determined does not have collision risk with the target unmanned aerial vehicle.
In an embodiment, the method for judging whether there is a collision risk between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and the altitude information of the unmanned aerial vehicle to be determined further includes:
and obtaining a region corresponding to the target geocode, and trisecting the long side and the wide side corresponding to the region, so that the region is divided into nine sub-regions with equal size.
For example, please refer to fig. 7, fig. 7 is a schematic diagram of a target geocoded sub-region and its adjacent geocodes provided by the embodiment of the present application. As shown in fig. 7, the area corresponding to the target geocode of the target drone is divided equally into sub-areas numbered 1, 2, 3, 4, 5, 6, 7, 8, and 9.
And identifying whether the target unmanned aerial vehicle is located in a central sub-area of the sub-areas or not according to the longitude and latitude of the target unmanned aerial vehicle.
Specifically, whether the target unmanned aerial vehicle is located in the central sub-area is identified according to the longitude and latitude range of the sub-area and the longitude and latitude of the target unmanned aerial vehicle. I.e. whether the target drone is located within the sub-area numbered 5.
And if the target unmanned aerial vehicle is in a central sub-area of the sub-areas, the target unmanned aerial vehicle is considered to have no collision risk. That is, the target drone is located within the sub-area of number 5, then the target drone is considered to be collision-free.
And if the target unmanned aerial vehicle is not in the central subarea of the subarea, calculating the distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle.
Specifically, calculating the distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and the height information of the unmanned aerial vehicle to be determined and the longitude and latitude and the height information of the target unmanned aerial vehicle includes:
judging whether the target unmanned aerial vehicle is located in a first sub-area of the area or in a second sub-area of the area; the first sub-region refers to any sub-region located at four corners of the region, and the second sub-region refers to any sub-region in the region except for the central sub-region and the first sub-region.
If the target unmanned aerial vehicle is located in the first sub-region, selecting the unmanned aerial vehicle to be determined corresponding to the three geocodes adjacent to the first sub-region from the unmanned aerial vehicles to be determined, and determining the unmanned aerial vehicle to be determined as the target unmanned aerial vehicle to be determined.
That is to say, if the target drone is located in the first sub-area numbered 1, or numbered 3, or numbered 7, or numbered 9, it is only necessary to identify the drone to be determined corresponding to the three geocodes adjacent to the number 1, or numbered 3, or numbered 7, or numbered 9, and determine that the drone is the target drone to be determined.
Illustratively, if the target drone is located within the sub-region numbered 1, the drone geocoded as wtmk4rbr, wtmk4rbn, wtmk6202 is the target drone to be determined.
And if the target unmanned aerial vehicle is located in the second sub-area, selecting the unmanned aerial vehicle to be determined corresponding to the geocode adjacent to the second sub-area from the unmanned aerial vehicles to be determined, and determining the unmanned aerial vehicle to be determined as the target unmanned aerial vehicle to be determined.
That is to say, if the target drone is located in the second sub-area numbered 2, or numbered 4, or numbered 6, or numbered 8, it is only necessary to identify the drone to be determined corresponding to the three geocodes adjacent to the number 2, or numbered 4, or numbered 6, or numbered 8, and determine that the drone is the target drone to be determined.
Illustratively, if the target drone is located within the sub-area numbered 2, the drone geocoded as wtmk4rbn is the target drone to be determined.
Judging whether the distance value between the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle is smaller than a preset safety distance or not; if the distance value between the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle is smaller than the preset safety distance, determining that the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have collision risk; and if the distance value between the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle is not less than the preset safety distance, the target unmanned aerial vehicle has no collision risk.
Based on the same application concept, the embodiment of the present application further provides a device for determining a collision risk of an unmanned aerial vehicle corresponding to the method for determining a collision risk of an unmanned aerial vehicle provided by the above embodiment, and as the principle of solving the problem of the device in the embodiment of the present application is similar to the method for determining a collision risk of an unmanned aerial vehicle provided by the above embodiment of the present application, the implementation of the device can refer to the implementation of the method, and repeated parts are not repeated. Referring to fig. 8, fig. 8 is a functional block diagram of the apparatus 10 for determining a collision risk of an unmanned aerial vehicle according to an embodiment of the present application. As shown in fig. 8, the apparatus 10 for determining the risk of collision of an unmanned aerial vehicle includes: a first determination module 101, a second determination module 102 and a third determination module 103; the first determining module 101 is configured to acquire an unmanned aerial vehicle with changed longitude and latitude and/or altitude information, and determine the unmanned aerial vehicle as a target unmanned aerial vehicle; the second determining module 102 is configured to determine a target geocode corresponding to longitude and latitude, and determine an altitude code corresponding to altitude information; the target geographic code is used for uniquely identifying the plane area range of the target unmanned aerial vehicle, and the height code is used for uniquely identifying the height range of the target unmanned aerial vehicle; and the third determining module 103 is configured to determine whether the target unmanned aerial vehicle has a collision risk according to a target stereo code formed by the target geocode and the altitude code, and/or the target geocode.
Based on the same application concept, referring to fig. 9, a schematic structural diagram of an electronic device 20 provided in the embodiment of the present application includes: a processor 201, a memory 202 and a bus 203, wherein the memory 202 stores machine-readable instructions executable by the processor 201, when the electronic device 20 is operated, the processor 201 communicates with the memory 202 through the bus 203, and the machine-readable instructions are executed by the processor 201 to perform the steps of the method for determining the collision risk of the unmanned aerial vehicle according to any one of the above embodiments.
Based on the same application concept, the embodiment of the application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program is executed by a processor to perform the steps of the method for determining the collision risk of the unmanned aerial vehicle provided by the embodiment. Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, and the like, when a computer program on the storage medium is run, the method for determining the collision risk of the unmanned aerial vehicle can be executed, and by comparing the stereo codes or the geocodes of the unmanned aerial vehicle, the technical problems that the calculated amount is large and the efficiency is low when identifying whether the unmanned aerial vehicle has the collision risk are solved, and the technical effect of improving the efficiency of identifying whether the unmanned aerial vehicle has the collision risk is achieved.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit is merely a division of one logic function, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solutions of the present application may be essentially implemented or are part of the technical solutions or parts of the technical solutions contributing to the prior art, and the computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method for determining a collision risk of an unmanned aerial vehicle, the method comprising:
acquiring an unmanned aerial vehicle with changed longitude and latitude and/or height information, and determining the unmanned aerial vehicle as a target unmanned aerial vehicle;
determining a target geocode corresponding to the longitude and latitude, and determining a height code corresponding to the height information; wherein the target geocode is used to uniquely identify a planar area range of the target drone, and the altitude code is used to uniquely identify a range of altitudes of the target drone;
and determining whether the target unmanned aerial vehicle has collision risk according to a target stereo code formed by the target geocode and the altitude code and/or the target geocode.
2. The method of claim 1, wherein the determining the height code corresponding to the height information comprises:
setting a preset height range and preset dividing precision; the preset height range comprises a preset height minimum value and a preset height maximum value;
determining a middle value of the preset height range;
judging that the height information is positioned between the preset height minimum value and the intermediate value or between the intermediate value and the preset height maximum value;
if the height information is located between the preset height minimum value and the middle value, the division mark of the time is 0, the preset height minimum value and the middle value are used as a new preset height range, and the difference value between the middle value and the preset height minimum value is determined as a height range difference value;
if the height information is located between the middle value and the preset height maximum value, the division mark of the time is 1, the middle value and the preset height maximum value are used as a new preset height range, and the difference value between the preset height maximum value and the middle value is determined as a height range difference value;
judging whether the height range difference value is equal to preset dividing precision or not;
and if the height range difference value is equal to the preset division precision, combining all the division marks according to the sequence, and determining a combination result as the height code of the target unmanned aerial vehicle.
3. The method of claim 1 or 2, wherein the determining whether the target drone is at risk of collision according to the target stereo code consisting of the target geocode and the altitude code comprises:
judging whether the target three-dimensional codes exist in three-dimensional code sets of all unmanned aerial vehicles except the target unmanned aerial vehicle;
and if the target stereo code exists in the stereo code set, determining the unmanned aerial vehicle corresponding to the target stereo code in the stereo code set, and having a collision risk with the target unmanned aerial vehicle.
4. The method of claim 1 or 2, wherein said determining whether the target drone is at risk of collision from the target geocode comprises:
acquiring geocodes adjacent to the target geocode;
comparing the geocode sets of all unmanned aerial vehicles except the target unmanned aerial vehicle with adjacent geocodes, and determining whether the target unmanned aerial vehicle has collision risks according to comparison results.
5. The method of claim 4, wherein the determining whether the target drone is at risk of collision according to the comparison result comprises:
judging whether geocodes adjacent to the target geocode exist in the geocode set or not;
if the geocode adjacent to the target geocode exists in the geocode set, determining the unmanned aerial vehicle corresponding to the adjacent geocode in the geocode set as the unmanned aerial vehicle to be determined;
and judging whether the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have collision risks or not according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined.
6. The method of claim 5, wherein the determining whether the unmanned aerial vehicle to be determined has a collision risk with the target unmanned aerial vehicle according to the longitude and latitude and the altitude information of the unmanned aerial vehicle to be determined comprises:
acquiring longitude and latitude and height information of the unmanned aerial vehicle to be determined and longitude and latitude and height information of the target unmanned aerial vehicle;
calculating a distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle;
judging whether the distance value is smaller than a preset safety distance or not;
and if the distance value is smaller than a preset safety distance, determining that the unmanned aerial vehicle to be determined has a collision risk with the target unmanned aerial vehicle.
7. The method of claim 6, further comprising:
obtaining a region corresponding to the target geocode, and trisecting the long side and the wide side corresponding to the region, so that the region is divided into nine sub-regions with equal size;
identifying whether the target unmanned aerial vehicle is located in a central sub-area of the sub-areas or not according to the longitude and latitude of the target unmanned aerial vehicle;
the calculating the distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle comprises the following steps:
and if the target unmanned aerial vehicle is not in the central subregion of the subregion, calculating the distance value between the unmanned aerial vehicle to be determined and the target unmanned aerial vehicle according to the longitude and latitude and height information of the unmanned aerial vehicle to be determined and the longitude and latitude and height information of the target unmanned aerial vehicle.
8. The method of claim 7, wherein calculating the distance value between the drone to be determined and the target drone according to the longitude and latitude and altitude information of the drone to be determined and the longitude and latitude and altitude information of the target drone comprises:
judging whether the target unmanned aerial vehicle is located in a first sub-area of the area or in a second sub-area of the area; the first sub-area refers to any sub-area positioned at four corners of the area, and the second sub-area refers to any sub-area except the central sub-area and the first sub-area in the area;
if the target unmanned aerial vehicle is located in the first sub-area, selecting the unmanned aerial vehicle to be determined corresponding to the three geocodes adjacent to the first sub-area from the unmanned aerial vehicles to be determined, and determining the unmanned aerial vehicle to be determined as the target unmanned aerial vehicle to be determined;
if the target unmanned aerial vehicle is located in the second sub-area, selecting the unmanned aerial vehicle to be determined corresponding to one geocode adjacent to the second sub-area from the unmanned aerial vehicles to be determined, and determining the unmanned aerial vehicle to be determined as the target unmanned aerial vehicle to be determined;
judging whether the distance value between the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle is smaller than a preset safety distance or not;
and if the distance value between the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle is smaller than a preset safety distance, determining that the target unmanned aerial vehicle to be determined and the target unmanned aerial vehicle have a collision risk.
9. An apparatus for determining a risk of collision of a drone, the apparatus comprising:
the first determining module is used for acquiring the unmanned aerial vehicle with changed longitude and latitude and/or height information and determining the unmanned aerial vehicle as a target unmanned aerial vehicle;
the second determination module is used for determining the target geocode corresponding to the longitude and latitude and determining the altitude code corresponding to the altitude information; wherein the target geocode is used to uniquely identify a planar area range of the target drone, and the altitude code is used to uniquely identify a range of altitudes of the target drone;
and the third determining module is used for determining whether the target unmanned aerial vehicle has collision risk according to a target stereo code formed by the target geocode and the altitude code and/or the target geocode.
10. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is run, the machine-readable instructions when executed by the processor performing the steps of the method of determining risk of collision for a drone according to any one of claims 1 to 8.
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