CN121277203A - Methods and systems for safe separation control of low-altitude integrated flight of UAVs and manned aircraft - Google Patents

Abstract

This invention discloses a method and system for controlling safe flight separation between unmanned aerial vehicles (UAVs) and manned aircraft at low altitudes, primarily relating to the field of flight safety technology. The method includes: determining the safety level of an equivalent target; obtaining real-time flight data of the UAV and the manned aircraft; evaluating the real-time flight data of the UAV and the manned aircraft using an integrated manned-UAV collision risk assessment model to determine the maximum collision probability; triggering a low-altitude fusion flight conflict command when the maximum collision probability exceeds the safety level of the equivalent target; and determining the flight safety separation based on the low-altitude fusion flight conflict command and the pilot's delay time. The beneficial effects of this invention are: it solves the technical problem in the prior art of lacking dynamic collision risk analysis between UAVs and manned aircraft, leading to low accuracy in safety separation control, and achieves the technical effect of improving the reliability of safety separation control.

Description

Unmanned aerial vehicle and unmanned aerial vehicle low-altitude fusion flight safety interval control method and system

Technical Field

The invention relates to the technical field of flight safety, in particular to a method and a system for controlling a low-altitude fusion flight safety interval of an unmanned aerial vehicle and an organic machine.

Background

With the gradual opening of the urban low-altitude airspace, the low-altitude unmanned aerial vehicle logistics distribution system is rapidly deployed, and particularly in the urban terminal area, the flight environment is complex, and airspace resources are tense. At the same time, there are aviation flight activities (e.g., helicopter training) in some areas, where these pilots use visual flight, lack standard communication, increasing the risk of potential collision of the pilots with the drones in low-altitude areas. Therefore, the problem of fusion operation safety management of the unmanned aerial vehicle and the unmanned aerial vehicle in the low-altitude airspace becomes an important topic to be solved urgently.

Disclosure of Invention

The application provides a method and a system for controlling a low-altitude fusion flight safety interval of an unmanned aerial vehicle and an organic machine, which are used for solving the technical problem of low safety interval control accuracy caused by lack of dynamic collision risk analysis between the unmanned aerial vehicle and the organic machine in the prior art.

In view of the problems, the application provides a method and a system for controlling a low-altitude fusion flight safety interval of an unmanned aerial vehicle and an organic vehicle.

In a first aspect of the application, a method for controlling a low-altitude fusion flight safety interval of a unmanned aerial vehicle and an organic machine is provided, and the method comprises the following steps:

acquiring a preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters for analysis and evaluation, and determining an equivalent target safety level;

acquiring real-time flight data of an unmanned aerial vehicle and an unmanned aerial vehicle, and acquiring the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the unmanned aerial vehicle;

Constructing an unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model, and assessing the unmanned aerial vehicle real-time flight data and the unmanned aerial vehicle real-time flight data by using the unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model to determine the maximum collision probability;

when the maximum collision probability is higher than the equivalent target safety level, triggering a low-altitude fusion flight conflict instruction;

and determining a flight safety interval by combining the flight hand delay time based on the low-altitude fusion flight conflict instruction.

In one possible implementation manner, the method for obtaining the preset flight target safety level, the unmanned aerial vehicle parameter and the man-machine parameter for analysis and evaluation and determining the equivalent target safety level comprises the steps of obtaining an analysis and evaluation function, wherein the analysis and evaluation function is as follows: wherein, the method comprises the steps of, For an equivalent target safety level,Is the collision kinetic energy of the man-machine and has the ratio of collision kinetic energy of the unmanned aerial vehicle,In order to be the ratio of the collision social influence of the man-machine and the unmanned plane,For a preset safety level of the target of flight,,Mass ofSpeed ofNumber of passengersMass ofSpeed ofPassenger carryingAnd evaluating the preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters by using the analysis evaluation function, and determining the equivalent target safety level.

In one possible implementation manner, constructing an unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model, and assessing the unmanned aerial vehicle real-time flight data and the unmanned aerial vehicle real-time flight data by using the unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model to determine the maximum collision probability, wherein the maximum collision probability calculation formula in the unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model is obtained, and the maximum collision probability calculation formula is as follows: wherein, the method comprises the steps of, ,Is the included angle between the relative position vector and the relative speed vector of the unmanned aerial vehicle and the organic vehicle,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,Is the relative velocity vector of the unmanned aerial vehicle and the organic aerial vehicle,For the maximum probability of collision to be the highest,,And evaluating the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the man-machine by using the maximum collision probability calculation formula to determine the maximum collision probability.

In one possible implementation, the flight safety interval is determined based on the low-altitude fusion flight conflict instruction and combined with a flight hand delay time, and the method comprises the steps of obtaining a preset safety interval calculation function, determining an initial safety interval by combining the unmanned plane parameter and the man-machine parameter, obtaining the flight hand delay time, correcting the initial safety interval by combining the flight hand delay time, and determining the flight safety interval.

In one possible implementation, the preset safety interval calculation function is: wherein, the method comprises the steps of, For the initial safety interval of time,Is the safe collision avoidance distance between the unmanned aerial vehicle and the organic vehicle,Is the approach rate of the unmanned aerial vehicle and the organic machine,In order to be able to detect the time required for a collision,Time required for communication.

In a possible implementation manner, the method comprises the steps of mining historical flight time delay time based on unmanned aerial vehicle parameters, determining a historical flight time delay time set, calculating the average value of the historical flight time delay time set to obtain a historical flight time average value, and searching in the historical flight time delay time set by taking the historical flight time average value as a searching starting point to determine flight time.

In a possible implementation manner, the historical flywheel delay time average value is taken as a searching starting point, searching is carried out in the historical flywheel delay time set, and the flywheel delay time is determined, wherein the method comprises the steps of carrying out iteration on the historical flywheel delay time average value based on a kernel density estimation method and a preset iteration bandwidth in combination with an iteration function to obtain an iteration historical flywheel delay time, judging whether a difference value between the historical flywheel delay time average value and the iteration historical flywheel delay time meets a preset time difference value or not, and if yes, taking the iteration historical flywheel delay time as the flywheel delay time.

In a second aspect of the present application, there is provided a low-altitude fusion flight safety interval control system for a drone and an organic vehicle, the system comprising:

The equivalent target safety level determining module is used for acquiring a preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters for analysis and evaluation to determine an equivalent target safety level;

The real-time flight data acquisition module is used for acquiring real-time flight data of the unmanned aerial vehicle and the man-machine and acquiring real-time flight data of the unmanned aerial vehicle and real-time flight data of the man-machine;

the maximum collision probability determining module is used for constructing a man-unmanned aerial vehicle integrated collision risk assessment model, and utilizing the man-unmanned aerial vehicle integrated collision risk assessment model to assess the unmanned aerial vehicle real-time flight data and the man-unmanned aerial vehicle real-time flight data so as to determine the maximum collision probability;

The flight conflict instruction triggering module is used for triggering a low-altitude fusion flight conflict instruction when the maximum collision probability is higher than the equivalent target safety level;

And the flight safety interval determining module is used for determining the flight safety interval by combining the flight hand delay time based on the low-altitude fusion flight conflict instruction.

One or more technical schemes provided by the application have at least the following technical effects or advantages:

the method comprises the steps of obtaining a preset flight target safety level, analyzing and evaluating unmanned aerial vehicle parameters and organic machine parameters to determine an equivalent target safety level, collecting real-time flight data of an unmanned aerial vehicle and an organic machine to obtain the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the organic machine, constructing an organic-unmanned aerial vehicle integrated collision risk assessment model, assessing the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the organic machine by using the organic-unmanned aerial vehicle integrated collision risk assessment model to determine the maximum collision probability, triggering a low-altitude fusion flight conflict instruction when the maximum collision probability is higher than the equivalent target safety level, and determining a flight safety interval based on the low-altitude fusion flight conflict instruction and the flight delay time. The technical effect of improving the control reliability of the low-altitude fusion flight safety interval is achieved.

Drawings

Fig. 1 is a schematic flow chart of a method for controlling a low-altitude fusion flight safety interval of a unmanned aerial vehicle and an organic vehicle according to an embodiment of the present invention.

Fig. 2 is a schematic structural diagram of a low-altitude integrated flight safety interval control system of a unmanned aerial vehicle and an organic vehicle according to an embodiment of the present invention.

The reference numbers shown in the drawings:

the system comprises an equivalent target safety level determining module 11, a real-time flight data obtaining module 12, a maximum collision probability determining module 13, a flight collision instruction triggering module 14 and a flight safety interval determining module 15.

Detailed Description

The application will be further illustrated with reference to specific examples. It is to be understood that these examples are illustrative of the present application and are not intended to limit the scope of the present application. Furthermore, it should be understood that various changes and modifications can be made by one skilled in the art after reading the teachings of the present application, and such equivalents are intended to fall within the scope of the application as defined in the appended claims. It should be noted that the terms "comprises" and "comprising" are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.

In a first embodiment, as shown in fig. 1, the present application provides a method for controlling a low-altitude fusion flight safety interval of an unmanned aerial vehicle and an organic vehicle, where the method includes:

Step 100, acquiring a preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters for analysis and evaluation, and determining an equivalent target safety level;

Further, the step S100 of the embodiment of the present application further includes the steps of obtaining a preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters for analysis and evaluation, and determining an equivalent target safety level:

Obtaining an analysis evaluation function, wherein the analysis evaluation function is:

;

Wherein, the For an equivalent target safety level,Is the collision kinetic energy of the man-machine and has the ratio of collision kinetic energy of the unmanned aerial vehicle,In order to be the ratio of the collision social influence of the man-machine and the unmanned plane,For a preset safety level of the target of flight,,Quality of man-machineSpeed of man-machineMan-machine passenger quantityUnmanned aerial vehicle qualityUnmanned aerial vehicle speedUnmanned aerial vehicle carries passenger;

And evaluating the preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters by using the analysis evaluation function, and determining the equivalent target safety level.

In one possible embodiment, the preset flying target safety level is an important indicator preset by those skilled in the art to measure whether the system is acceptable to society. The unmanned aerial vehicle parameters are used for evaluating flight characteristics, safety performance and collision risk of the unmanned aerial vehicle in the low-altitude fusion operation process, and specifically comprise, but are not limited to, quality, and are used for influencing collision kinetic energy and flight control response. The flying speed refers to the stable cruising speed of the unmanned aerial vehicle or the unmanned aerial vehicle in the course of the operation of the route, and the unit is meters per second (m/s), so that the approaching rate and the avoidance time window are affected. The maximum passenger carrying capacity is the personnel or goods carrying capacity of the unmanned aerial vehicle or the unmanned aerial vehicle. Position maintenance capability refers to the spatial accuracy of a drone or an organic vehicle in maintaining a predetermined flight path in an autonomous flight state, typically expressed in terms of standard deviation sigma of position deviation, including three directions, lateral, longitudinal, and vertical. Wherein, the mass and the speed jointly determine the collision kinetic energy ratio, and the passenger carrying capacity influences the social influence ratio.

Step 200, acquiring real-time flight data of an unmanned aerial vehicle and an organic machine, and acquiring the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the organic machine;

in one possible embodiment, real-time flight data of the aircraft are acquired from the unmanned aerial vehicle system platform and the organic machine monitoring system respectively, wherein the flight data at least comprise three-dimensional coordinate positions of the current aircraft, including longitude, latitude and altitude, and course speed vectors of the aircraft, including horizontal speed, vertical speed and total speed, and course angle/attitude information, are used for assisting in judging flight path trend and turning action, and time stamping, wherein time consistency and synchronism of acquired data are ensured, and the flight path trend and turning action are used for track alignment.

Preferably, the flight state data can be uploaded in real time at a frequency of 1 Hz-10 Hz through a link or a wireless communication mode. For example, for a certain type of logistic unmanned plane FP400, its flight control system reports three-dimensional coordinates, speed and attitude information to the dispatch center once per second, ensuring that the position error is within ±1 meter.

By accurately acquiring and updating the flight state data streams of the unmanned aerial vehicle and the man-machine at any time, the technical effect of providing real-time input conditions for subsequent collision probability calculation and safety interval control is achieved.

Step 300, constructing an unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model, and assessing unmanned aerial vehicle real-time flight data and unmanned aerial vehicle real-time flight data by using the unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model to determine the maximum collision probability;

Step 400, triggering a low-altitude fusion flight conflict instruction when the maximum collision probability is higher than the equivalent target safety level;

further, a man-unmanned aerial vehicle integrated collision risk assessment model is constructed, the man-unmanned aerial vehicle integrated collision risk assessment model is utilized to evaluate the unmanned aerial vehicle real-time flight data and the man-unmanned aerial vehicle real-time flight data, and the maximum collision probability is determined, and step S300 of the embodiment of the application further comprises:

Obtaining a maximum collision probability calculation formula in a man-unmanned aerial vehicle integrated collision risk assessment model, wherein the maximum collision probability calculation formula is as follows:

;

Wherein, the ,Is the included angle between the relative position vector and the relative speed vector of the unmanned aerial vehicle and the organic vehicle,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,Is the relative velocity vector of the unmanned aerial vehicle and the organic aerial vehicle,For the maximum probability of collision to be the highest,,Time to closest point of approach;

and evaluating the unmanned aerial vehicle real-time flight data and the unmanned aerial vehicle real-time flight data by using the maximum collision probability calculation formula, and determining the maximum collision probability.

In one possible embodiment, by calculating the relative position distribution of the unmanned aerial vehicle and the unmanned aerial vehicle at a certain moment and combining the relative speed and the approach angle of the two unmanned aerial vehicles, the overlapping probability when the closest point of approach CPA is further determined, and finally the maximum collision probability is obtained.

Because the relative motion states of the unmanned aerial vehicle and the unmanned aerial vehicle are different, the maximum collision probability in the whole meeting process is also different, so that the nearest approaching points of the two unmanned aerial vehicles and the unmanned aerial vehicle in the whole meeting process are calculated based on a geometric method, namely:

Wherein the method comprises the steps of Is the included angle between the relative position vector and the relative speed vector of the unmanned aerial vehicle and the unmanned aerial vehicle,To at the same timeAt the moment there is a relative position vector of the unmanned aerial vehicle and the unmanned aerial vehicle,Is the relative speed vector of the unmanned aerial vehicle and the unmanned aerial vehicle. Therefore, the relation of the relative positions of the unmanned aerial vehicle and the unmanned aerial vehicle at each moment along with the time t is that。

Finding extremum of relative position by deriving time t, i.e.。

The time to reach the nearest point of approach is. Substituting the determined time reaching the nearest point into a maximum collision probability calculation formula, and carrying out subsequent calculation.

For example, taking a helicopter of a military use of a speed of-8K and an unmanned plane of a flow of an FP400 as an example, the flying speed is 61.7 m/s and 10 m/s respectively, the standard deviation of the position maintaining capacity is that the helicopter is (5, 2) meters, the unmanned plane is (0.76, 0.82, 0.11) meters, the initial relative position of the helicopter and the unmanned plane is 400m, the included angle is 45 degrees, and the relative speed is 51.7 m/s. Through CPA analysis and probability integration, the system calculates that the maximum collision probability in the current intersection process is 2.1 multiplied by 10 ⁻⁴, which is higher than the safety level of the equivalent target, and at the moment, a low-altitude fusion flight conflict instruction is triggered.

Preferably, the low-altitude fusion flight conflict instruction is used for notifying a relevant flight control system or a ground control terminal to take response measures. Optionally, a flight status notification may be included, such as reporting a high risk reminder to a flight attendant console or unmanned aerial vehicle task scheduling system;

and S500, determining a flight safety interval by combining the flight hand delay time based on the low-altitude fusion flight conflict instruction.

Further, based on the low-altitude fusion flight conflict instruction, the flight safety interval is determined in combination with the flight hand delay time, and step S500 of the embodiment of the present application further includes:

acquiring a preset safety interval calculation function, and determining an initial safety interval by combining the unmanned aerial vehicle parameters and the man-machine parameters;

and acquiring the flight hand delay time, correcting the initial safety interval by combining the flight hand delay time, and determining the flight safety interval.

Further, the preset safety interval calculating function is as follows:

;

Wherein, the For the initial safety interval of time,Is the safe collision avoidance distance between the unmanned aerial vehicle and the organic vehicle,Is the approach rate of the unmanned aerial vehicle and the organic machine,In order to be able to detect the time required for a collision,Time required for communication.

Further, the step S500 of the embodiment of the present application further includes:

Historical flying hand delay time mining is carried out based on the unmanned aerial vehicle parameters, and a historical flying hand delay time set is determined;

calculating the average value of the historical flywheel delay time set to obtain the average value of the historical flywheel delay time;

and searching in the historical flywheel delay time set by taking the historical flywheel delay time average value as a searching starting point to determine the flywheel delay time.

Further, taking the average value of the historical flywheel delay time as a searching starting point, searching in the historical flywheel delay time set, and determining the flywheel delay time, wherein the step S500 of the embodiment of the application further comprises:

Based on a kernel density estimation method and a preset iteration bandwidth, iterating the historical flywheel delay time mean value by combining an iteration function to obtain an iteration historical flywheel delay time;

Judging whether the difference value between the historical flywheel delay time average value and the iteration historical flywheel delay time meets a preset time difference value, and if so, taking the iteration historical flywheel delay time as the flywheel delay time.

In one possible embodiment, a basic initial safety interval is determined based on the flight characteristics (e.g., speed, accuracy of operation, etc.) of the drone and the drone, and the current collision recognition time. The initial interval value may be understood as the minimum distance that needs to be maintained between two machines under ideal conditions without considering the delay of the fly-hand operation, to ensure that there is enough time and space to perform the avoidance operation. Further, the fly-hand delay time is obtained. The time delay of the fly hand refers to the time elapsed between the receipt of collision early warning information and the actual avoidance operation of the fly hand. This time has a certain volatility due to the experience, attentiveness status and environmental complexity of different flies. To reflect the actual operating situation, the time required for the fly to perform the avoidance operation in a similar task is typically counted and analyzed based on data in the historical flight records, resulting in a representative delay time. For example, an average of historical pilot delay times may be used as a reference value, and a more accurate representative delay may be determined based on density estimation.

After the flight delay time is obtained, the flight delay time is combined with factors such as the approaching speed between the aircrafts, and the previous initial safety interval is corrected. If the craft takes a longer time to react, the two craft may have come into close proximity before the craft reacts, thus requiring a larger separation, otherwise, a suitable reduction may be made.

The dynamic flight safety interval under the current environment is calculated by comprehensively considering factors such as the aircraft maneuverability, the time required for detection and communication, the flight response time of the flight hands and the like, and the flight instructions or behavior planning of the unmanned aerial vehicle are updated according to the dynamic flight safety interval, so that the sufficient response time and the safety distance are ensured in the actual operation, and the occurrence of air collision is avoided.

In one embodiment, according to the type, flight mode and control mode of the unmanned aerial vehicle currently executing the task, the flight operation records with similar flight task characteristics are extracted from the historical operation database, and a data set containing a plurality of flight response times, namely a historical flight delay time set, is constructed. Further, the set is statistically analyzed, and a mean value of the historical fly-hand delay time is calculated. This average can reflect the approximate time frame that the fly-away responds to upon receipt of the avoidance command under typical operating conditions.

Then, the average value is taken as a searching starting point, and the average value is further searched in the historical fly-hand delay time set, so as to find a representative delay time value which is closer to an actual control scene. Preferably, a kernel density estimation method is introduced, non-parameter distribution modeling is carried out on the set, and the iteration bandwidth and the iteration function are preset by a person skilled in the art, so that the value of the fly-hand delay time is gradually corrected. During each iteration, the difference between the current estimate and the initial mean is recalculated. If the difference is within the preset time difference preset by the person skilled in the art, the current estimated value is sufficiently accurate, and the current estimated value is used as the fly hand delay time adopted in the present flight task. If the accuracy requirement is not met, iteration is continued until a preset condition is met.

By acquiring the flight delay time, the error expansion caused by the abnormal value can be effectively avoided, the method can adapt to actual response differences of different flights and different flight tasks, and the accuracy and the practicability of flight interval assessment are improved.

In summary, the embodiment of the application has at least the following technical effects:

the method comprises the steps of obtaining a preset flight target safety level, analyzing and evaluating unmanned aerial vehicle parameters and organic machine parameters to determine an equivalent target safety level, collecting real-time flight data of an unmanned aerial vehicle and an organic machine to obtain the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the organic machine, constructing an organic-unmanned aerial vehicle integrated collision risk assessment model, assessing the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the organic machine by using the organic-unmanned aerial vehicle integrated collision risk assessment model to determine the maximum collision probability, triggering a low-altitude fusion flight conflict instruction when the maximum collision probability is higher than the equivalent target safety level, and determining a flight safety interval based on the low-altitude fusion flight conflict instruction and the flight delay time. The technical effect of improving the control reliability of the low-altitude fusion flight safety interval is achieved.

In the second embodiment, based on the same inventive concept as the method for controlling the low-altitude fusion flight safety interval of the unmanned aerial vehicle and the unmanned aerial vehicle in the previous embodiment, as shown in fig. 2, the application provides a system for controlling the low-altitude fusion flight safety interval of the unmanned aerial vehicle and the unmanned aerial vehicle. Wherein the system comprises:

the equivalent target safety level determining module 11 is used for acquiring a preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters for analysis and evaluation to determine an equivalent target safety level;

A real-time flight data obtaining module 12, configured to collect real-time flight data of the unmanned aerial vehicle and the unmanned aerial vehicle, and obtain real-time flight data of the unmanned aerial vehicle and real-time flight data of the unmanned aerial vehicle;

The maximum collision probability determining module 13 is configured to construct a man-unmanned aerial vehicle integrated collision risk assessment model, and utilize the man-unmanned aerial vehicle integrated collision risk assessment model to evaluate the unmanned aerial vehicle real-time flight data and the man-unmanned aerial vehicle real-time flight data to determine a maximum collision probability;

A flight conflict instruction triggering module 14, configured to trigger a low-altitude fusion flight conflict instruction when the maximum collision probability is higher than the equivalent target safety level;

The flight safety interval determining module 15 is configured to determine a flight safety interval in combination with a flight hand delay time based on the low-altitude fusion flight conflict instruction.

Further, the system includes:

Obtaining an analysis evaluation function, wherein the analysis evaluation function is:

;

Wherein, the For an equivalent target safety level,Is the collision kinetic energy of the man-machine and has the ratio of collision kinetic energy of the unmanned aerial vehicle,In order to be the ratio of the collision social influence of the man-machine and the unmanned plane,For a preset safety level of the target of flight,,Mass ofSpeed ofNumber of passengersMass ofSpeed ofPassenger carrying;

And evaluating the preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters by using the analysis evaluation function, and determining the equivalent target safety level.

Further, the system includes:

Obtaining a maximum collision probability calculation formula in a man-unmanned aerial vehicle integrated collision risk assessment model, wherein the maximum collision probability calculation formula is as follows:

;

Wherein, the ,Is the included angle between the relative position vector and the relative speed vector of the unmanned aerial vehicle and the organic vehicle,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,Is the relative velocity vector of the unmanned aerial vehicle and the organic aerial vehicle,For the maximum probability of collision to be the highest,,Time to closest point of approach;

and evaluating the unmanned aerial vehicle real-time flight data and the unmanned aerial vehicle real-time flight data by using the maximum collision probability calculation formula, and determining the maximum collision probability.

Further, the system includes:

acquiring a preset safety interval calculation function, and determining an initial safety interval by combining the unmanned aerial vehicle parameters and the man-machine parameters;

and acquiring the flight hand delay time, correcting the initial safety interval by combining the flight hand delay time, and determining the flight safety interval.

Further, the system includes:

;

Wherein, the For the initial safety interval of time,Is the safe collision avoidance distance between the unmanned aerial vehicle and the organic vehicle,Is the approach rate of the unmanned aerial vehicle and the organic machine,In order to be able to detect the time required for a collision,Time required for communication.

Further, the system includes:

Historical flying hand delay time mining is carried out based on the unmanned aerial vehicle parameters, and a historical flying hand delay time set is determined;

calculating the average value of the historical flywheel delay time set to obtain the average value of the historical flywheel delay time;

and searching in the historical flywheel delay time set by taking the historical flywheel delay time average value as a searching starting point to determine the flywheel delay time.

Further, the system includes:

Based on a kernel density estimation method and a preset iteration bandwidth, iterating the historical flywheel delay time mean value by combining an iteration function to obtain an iteration historical flywheel delay time;

Judging whether the difference value between the historical flywheel delay time average value and the iteration historical flywheel delay time meets a preset time difference value, and if so, taking the iteration historical flywheel delay time as the flywheel delay time.

It should be noted that the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the application are intended to be included within the scope of the application.

The specification and figures are merely exemplary illustrations of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.

Claims (8)

1. The unmanned aerial vehicle and the unmanned aerial vehicle low-altitude fusion flight safety interval control method is characterized by comprising the following steps of:

acquiring a preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters for analysis and evaluation, and determining an equivalent target safety level;

acquiring real-time flight data of an unmanned aerial vehicle and an unmanned aerial vehicle, and acquiring the real-time flight data of the unmanned aerial vehicle and the real-time flight data of the unmanned aerial vehicle;

Constructing an unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model, and assessing the unmanned aerial vehicle real-time flight data and the unmanned aerial vehicle real-time flight data by using the unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model to determine the maximum collision probability;

when the maximum collision probability is higher than the equivalent target safety level, triggering a low-altitude fusion flight conflict instruction;

and determining a flight safety interval by combining the flight hand delay time based on the low-altitude fusion flight conflict instruction.

2. The unmanned aerial vehicle and unmanned aerial vehicle low-altitude fusion flight safety interval control method according to claim 1, wherein obtaining a preset flight target safety level, unmanned aerial vehicle parameters and unmanned aerial vehicle parameters for analysis and evaluation, determining an equivalent target safety level comprises:

Obtaining an analysis evaluation function, wherein the analysis evaluation function is:

;

Wherein, the For an equivalent target safety level,Is the collision kinetic energy of the man-machine and has the ratio of collision kinetic energy of the unmanned aerial vehicle,In order to be the ratio of the collision social influence of the man-machine and the unmanned plane,For a preset safety level of the target of flight,,Mass ofSpeed ofNumber of passengersMass ofSpeed ofPassenger carrying;

And evaluating the preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters by using the analysis evaluation function, and determining the equivalent target safety level.

3. The unmanned aerial vehicle-unmanned aerial vehicle low-altitude fusion flight safety interval control method according to claim 1, wherein constructing an unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model, and using the unmanned aerial vehicle-unmanned aerial vehicle integrated collision risk assessment model to assess the unmanned aerial vehicle real-time flight data and the unmanned aerial vehicle real-time flight data, determining the maximum collision probability comprises:

Obtaining a maximum collision probability calculation formula in a man-unmanned aerial vehicle integrated collision risk assessment model, wherein the maximum collision probability calculation formula is as follows:

;

Wherein, the ,Is the included angle between the relative position vector and the relative speed vector of the unmanned aerial vehicle and the organic vehicle,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,To at the same timeThe relative position vectors of the unmanned aerial vehicle and the organic machine at the moment,Is the relative velocity vector of the unmanned aerial vehicle and the organic aerial vehicle,For the maximum probability of collision to be the highest,,Time to closest point of approach;

and evaluating the unmanned aerial vehicle real-time flight data and the unmanned aerial vehicle real-time flight data by using the maximum collision probability calculation formula, and determining the maximum collision probability.

4. The unmanned aerial vehicle and man-machine low-altitude fusion flight safety interval control method of claim 1, wherein determining the flight safety interval in combination with the flight hand delay time based on the low-altitude fusion flight conflict instruction comprises:

acquiring a preset safety interval calculation function, and determining an initial safety interval by combining the unmanned aerial vehicle parameters and the man-machine parameters;

and acquiring the flight hand delay time, correcting the initial safety interval by combining the flight hand delay time, and determining the flight safety interval.

5. The method for controlling a low-altitude fusion flight safety interval of a unmanned aerial vehicle and an organic vehicle according to claim 4, wherein the preset safety interval calculation function is as follows:

;

Wherein, the For the initial safety interval of time,Is the safe collision avoidance distance between the unmanned aerial vehicle and the organic vehicle,Is the approach rate of the unmanned aerial vehicle and the organic machine,In order to be able to detect the time required for a collision,Time required for communication.

6. The method for controlling a low-altitude fusion flight safety interval of a unmanned aerial vehicle and an organic vehicle according to claim 4, wherein obtaining the flight delay time comprises:

Historical flying hand delay time mining is carried out based on the unmanned aerial vehicle parameters, and a historical flying hand delay time set is determined;

calculating the average value of the historical flywheel delay time set to obtain the average value of the historical flywheel delay time;

and searching in the historical flywheel delay time set by taking the historical flywheel delay time average value as a searching starting point to determine the flywheel delay time.

7. The method for controlling a low-altitude fusion flight safety interval of a unmanned aerial vehicle and an organic vehicle according to claim 6, wherein searching in the historical flight delay time set by taking the historical flight delay time average as a searching starting point, and determining the flight delay time comprises:

Based on a kernel density estimation method and a preset iteration bandwidth, iterating the historical flywheel delay time mean value by combining an iteration function to obtain an iteration historical flywheel delay time;

Judging whether the difference value between the historical flywheel delay time average value and the iteration historical flywheel delay time meets a preset time difference value, and if so, taking the iteration historical flywheel delay time as the flywheel delay time.

8. The unmanned aerial vehicle and unmanned aerial vehicle low-altitude fusion flight safety interval control system is characterized in that the system is used for implementing the unmanned aerial vehicle and unmanned aerial vehicle low-altitude fusion flight safety interval control method according to any one of claims 1 to 7, and the system comprises:

The equivalent target safety level determining module is used for acquiring a preset flight target safety level, unmanned aerial vehicle parameters and man-machine parameters for analysis and evaluation to determine an equivalent target safety level;

The real-time flight data acquisition module is used for acquiring real-time flight data of the unmanned aerial vehicle and the man-machine and acquiring real-time flight data of the unmanned aerial vehicle and real-time flight data of the man-machine;

the maximum collision probability determining module is used for constructing a man-unmanned aerial vehicle integrated collision risk assessment model, and utilizing the man-unmanned aerial vehicle integrated collision risk assessment model to assess the unmanned aerial vehicle real-time flight data and the man-unmanned aerial vehicle real-time flight data so as to determine the maximum collision probability;

The flight conflict instruction triggering module is used for triggering a low-altitude fusion flight conflict instruction when the maximum collision probability is higher than the equivalent target safety level;

And the flight safety interval determining module is used for determining the flight safety interval by combining the flight hand delay time based on the low-altitude fusion flight conflict instruction.