Low-altitude airspace saturation evaluation method and system

Abstract

The invention relates to a low-altitude airspace saturation evaluation method and system. The low-altitude airspace saturation evaluation method comprises the following steps: dividing a low-altitude airspace into a plurality of three-dimensional grid units; based on the static attribute parameters of the aircrafts in the three-dimensional grid units, the static weighted number of the three-dimensional grid units is obtained; based on the dynamic correlation parameters between the aircrafts in each three-dimensional grid unit, the situation complexity of each three-dimensional grid unit is obtained; based on the capacity attribute parameter of each three-dimensional grid unit, obtaining an airspace use load of each three-dimensional grid unit; and obtaining the low-altitude airspace saturation based on the static weighted number, the situation complexity and the airspace use load of each three-dimensional grid unit. According to the method, the real risk and capacity state of the low-altitude airspace can be reflected more accurately, a more reliable basis is provided for airspace management, the safety management of dynamic early warning optimization airspace can be realized, and the overall operation efficiency and performance of the system are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of low-altitude airspace management, and in particular to a low-altitude airspace saturation evaluation method and system. BACKGROUND

[0002] With the accelerated development and utilization of low-altitude airspace, low-altitude flight activities such as unmanned aerial vehicle logistics distribution, medical emergency transfer, and fire emergency rescue are becoming increasingly frequent, the airspace demand of general aviation and small aircraft is continuously growing, and the complexity and use intensity of low-altitude airspace are significantly increasing. However, the safe and efficient operation of low-altitude airspace is highly dependent on accurate control of airspace saturation, and if the real capacity state and risk level of the airspace cannot be grasped in a timely manner, it is easy to lead to waste of airspace resources or intensification of conflict risks, bringing serious challenges to low-altitude flight safety and management efficiency.

[0003] The existing method is only based on the number of aircraft or the number of radar tracking points in the overall airspace, and it is difficult to effectively evaluate the real risk and capacity state of the low-altitude complex dynamic environment, cannot accurately locate the saturation risk of the local area, and cannot meet the actual needs of fine management of low-altitude airspace. SUMMARY

[0004] Therefore, it is necessary to solve the above problems, and the present application provides a low-altitude airspace saturation evaluation method and system.

[0005] In a first aspect, the present application provides a low-altitude airspace saturation evaluation method, which comprises:

[0006] dividing the low-altitude airspace into a plurality of three-dimensional grid cells;

[0007] obtaining a static weighted number of each three-dimensional grid cell based on a static attribute parameter of an aircraft in each three-dimensional grid cell;

[0008] obtaining a situation complexity of each three-dimensional grid cell based on a dynamic correlation parameter between aircrafts in each three-dimensional grid cell;

[0009] obtaining an airspace use load of each three-dimensional grid cell based on a capacity attribute parameter of each three-dimensional grid cell;

[0010] obtaining a low-altitude airspace saturation based on the static weighted number, the situation complexity, and the airspace use load of each three-dimensional grid cell.

[0011] In some embodiments, the static attribute parameter includes task criticality, motion speed, aircraft type parameter, and controllability.

[0012] In some embodiments, the static weight quantity of each three-dimensional grid cell is obtained based on a static attribute parameter of the aircraft in each three-dimensional grid cell, and the static weight quantity of each three-dimensional grid cell comprises:

[0013] The static attribute parameter of each aircraft is graded based on quantifiable grading criteria;

[0014] The grading results of each static attribute parameter are assigned weights;

[0015] The individual weight of each aircraft is obtained based on the weight assignment;

[0016] The static weight quantity of each three-dimensional grid cell is obtained based on the individual weight of the aircraft in each three-dimensional grid cell.

[0017] In some embodiments, the dynamic correlation parameter comprises relative motion complexity, proximity complexity, and conflict point time complexity.

[0018] In some embodiments, the situation complexity of each three-dimensional grid cell is obtained based on a dynamic correlation parameter between the aircraft in each three-dimensional grid cell, and the situation complexity of each three-dimensional grid cell comprises:

[0019] All aircraft in each three-dimensional grid cell are paired in pairs;

[0020] The dynamic correlation parameter of each pair of aircraft is obtained;

[0021] The dynamic correlation parameter of each pair of aircraft is dimensionally scored;

[0022] The interaction complexity of each pair of aircraft is obtained based on the dimension score;

[0023] The situation complexity of each three-dimensional grid cell is obtained based on the interaction complexity of all pairs of aircraft in each three-dimensional grid cell.

[0024] In some embodiments, the airspace usage load of each three-dimensional grid cell is obtained based on a capacity attribute parameter of each three-dimensional grid cell, and the airspace usage load of each three-dimensional grid cell comprises:

[0025] The equivalent occupation quantity of each three-dimensional grid cell is obtained;

[0026] The current airspace resource utilization rate of each three-dimensional grid cell is obtained;

[0027] The airspace usage load of each three-dimensional grid cell is obtained based on the equivalent occupation rate and the current airspace resource utilization rate of each three-dimensional grid cell.

[0028] In some embodiments, the equivalent occupation quantity of each three-dimensional grid cell is obtained, and the equivalent occupation quantity of each three-dimensional grid cell comprises:

[0029] selecting a standard aircraft in each of the three-dimensional grid cells;

[0030] The equivalent coefficient of aircraft k in the three-dimensional grid cell to the standard aircraft is obtained based on the following formula :

[0031]

[0032] wherein, is the airspace occupation volume of aircraft k; is the airspace occupation volume of the standard aircraft; The equivalent occupation amount of the three-dimensional grid cell is obtained based on the following formula:

[0033]

[0034]

[0035] wherein, is the equivalent occupation amount of the three-dimensional grid cell at time t; is the number of aircraft k.

[0036] In some embodiments, the current airspace resource utilization of each of the three-dimensional grid cells is obtained based on the following formula:

[0037]

[0038] wherein, is the current airspace resource utilization of the three-dimensional grid cell ; is the space volume of a single grid; is the occupation volume of the standard aircraft; The airspace use load of the three-dimensional grid cell is obtained based on the following formula:

[0039]

[0040] . In some embodiments, the low-altitude airspace saturation S is obtained based on the following formula:

[0041]

[0042]

[0043] wherein, N is the number of three-dimensional grid cells; is the low-altitude airspace saturation of the i-th three-dimensional grid cell, Load is the airspace use load of the i-th three-dimensional grid cell, is the complexity influence coefficient, ​​is the situation complexity of the i th three-dimensional unit grid; S is the entire low-altitude airspace saturation; and N is the number of three-dimensional grid units.

[0044] In a second aspect, the application further provides a low-altitude airspace saturation evaluation system, which comprises:

[0045] a grid division module, configured to divide the low-altitude airspace into a plurality of three-dimensional grid units;

[0046] a static weighted quantity acquisition module, configured to obtain a static weighted quantity of each of the three-dimensional grid units based on a static attribute parameter of an aircraft in each of the three-dimensional grid units;

[0047] a situation complexity acquisition module, configured to obtain a situation complexity of each of the three-dimensional grid units based on a dynamic correlation parameter between the aircraft in each of the three-dimensional grid units;

[0048] an airspace usage load acquisition module, configured to obtain an airspace usage load of each of the three-dimensional grid units based on a capacity attribute parameter of each of the three-dimensional grid units;

[0049] a comprehensive evaluation module, configured to obtain a low-altitude airspace saturation based on the static weighted quantity, the situation complexity and the airspace usage load of each of the three-dimensional grid units.

[0050] The low-altitude airspace saturation evaluation method and system of the application comprehensively consider the static attribute parameter of the aircraft, the dynamic correlation parameter between the aircraft and the capacity attribute parameter of the three-dimensional grid unit, can more accurately reflect the real risk and capacity state of the low-altitude airspace, provide a more reliable basis for airspace management, can realize dynamic early warning and optimize the safety management of the airspace, and effectively improve the overall operation efficiency and performance of the system. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0052] Figure 1 a flowchart of the low-altitude airspace saturation evaluation method provided in an embodiment of the application;

[0053] Figure 2 a structural block diagram of the low-altitude airspace saturation evaluation system provided in another embodiment of the application.

[0054] Label explanation: 10, grid division module; 20, static weighted quantity acquisition module; 30, situation complexity acquisition module; 40, airspace use load acquisition module; 50, comprehensive evaluation module. DETAILED DESCRIPTION

[0055] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0056] In one embodiment, referring to Figure 1 The present application provides a low-altitude airspace saturation evaluation method, which comprises the following steps: S11-S15.

[0057] S11: dividing the low-altitude airspace into a plurality of three-dimensional grid cells.

[0058] S12: obtaining the static weighted quantity of each three-dimensional grid cell based on the static attribute parameters of the aircraft in each three-dimensional grid cell.

[0059] S13: obtaining the situation complexity of each three-dimensional grid cell based on the dynamic correlation parameters between the aircraft in each three-dimensional grid cell.

[0060] S14: obtaining the airspace use load of each three-dimensional grid cell based on the capacity attribute parameters of each three-dimensional grid cell.

[0061] S15: obtaining the low-altitude airspace saturation based on the static weighted quantity, the situation complexity and the airspace use load of each three-dimensional grid cell.

[0062] The low-altitude airspace saturation evaluation method of the present application comprehensively considers the static attribute parameters of the aircraft, the dynamic correlation parameters between the aircraft, and the capacity attribute parameters of the three-dimensional grid cell, can more accurately reflect the real risk and capacity state of the low-altitude airspace, provides a more reliable basis for airspace management, can realize dynamic early warning and optimize the safety management of the airspace, and effectively improves the overall operation efficiency and performance of the system.

[0063] In step S11, referring to Figure 1 S11 step, the low-altitude airspace is divided into a plurality of three-dimensional grid cells.

[0064] Specifically, first, the scope of three-dimensional grid division and the evaluation target are determined, the longitude and latitude (for example, longitude 113.5°-114.0°, latitude 22.5°-23.0° within the city around the highway) and height boundary (for example, 10-500 meters above the ground) of the target low-altitude airspace are determined based on the control requirements, and the evaluation accuracy requirement is determined according to the actual demand (for example, high accuracy is required for city consumer-level unmanned aerial vehicle risk warning, and medium accuracy is required for remote area cargo plane path planning).

[0065] Specifically, the three-dimensional dimension division granularity can be determined according to the scene characteristics and evaluation accuracy. For city low-altitude (high accuracy), the longitude and latitude interval is 50-100 meters, and the height layer interval is 20-50 meters. For remote areas (medium accuracy), the longitude and latitude interval is 300-500 meters, and the height layer interval is 100-200 meters. At the same time, fixed obstacles (for example, 300-meter-high television towers) in the airspace are separately divided into no-fly grids. Then, the grid boundary calibration and obstacle avoidance can be performed. The grid boundary can be adjusted by importing obstacle and no-fly zone data through GIS to ensure that there are no no-fly zones and obstacles with a height exceeding the grid in a single three-dimensional grid. At the same time, the three-dimensional grid granularity can be further reduced in obstacle-dense areas.

[0066] Specifically, then a unique code in the form of containing area identifier, longitude and latitude serial number, and height layer serial number can be assigned to each three-dimensional grid (for example, C i The spatial attributes and scene attributes of the grid are related, and a grid database is established to facilitate subsequent calling of grid data.

[0067] As an example, after the low-altitude airspace is successfully divided into a plurality of three-dimensional grid units in step S11, grid rationality verification and optimization can be carried out. The capture ability of the grid for interacting with the aircraft is simulated and tested by importing historical aircraft trajectory data. According to the test results, the grid is corrected (for example, to handle the cross-grid conflict problem). Finally, a landable three-dimensional grid system containing all grid unique identifiers, boundary ranges, and attribute information is output as a basic carrier for subsequent low-altitude airspace saturation evaluation.

[0068] In step S12, please refer to the S12 step in Figure 1 Based on the static attribute parameters of the aircraft in each of the three-dimensional grid units, the static weighted number of each of the three-dimensional grid units is obtained.

[0069] As an example, step S12 can include the following steps: S121-S124.

[0070] S121: The static attribute parameters of each of the aircraft are classified based on quantifiable classification standards.

[0071] S122: The classification results of each of the static attribute parameters are weighted.

[0072] S123: Based on the weight assignment, the individual weights of each of the aircraft are obtained.

[0073] S124: Based on the individual weights of the aircraft within each of the three-dimensional network units, obtain the static weighted number of each of the three-dimensional mesh units.

[0074] As an example, the static attribute parameters may include: task criticality, movement speed, machine parameters, and controllability.

[0075] Specifically, first extract the 3D mesh C. i At time t, each aircraft has four static attributes: mission criticality, speed, aircraft parameters, and controllability. Based on the grading standard combined with airspace scenario calibration, the fuzzy description of the attributes is transformed into a clear grade. For example, the criticality of a task can be classified as follows: consumer entertainment is Level 1, logistics and transportation is Level 2, fire rescue is Level 3, and medical emergency is Level 4; the speed of movement can be classified as follows: less than 50km / h is Level 1, 50-100km / h is Level 2, 100-200km / h is Level 3, and greater than 200km / h is Level 4; the aircraft parameters can be classified as follows: consumer aircraft weighing less than 5kg is Level 1, industrial aircraft weighing 5-25kg is Level 2, cargo aircraft weighing 25-150kg is Level 3, and special aircraft weighing greater than 150kg is Level 4; the controllability can be classified as follows: fully controllable (real-time trajectory adjustable) is Level 1, semi-controllable (only reported without trace) is Level 2, and uncontrollable (black flight / out of control) is Level 3.

[0076] Specifically, weights can then be assigned based on the contribution of each attribute level to risk or resources, and specific weight values ​​can be assigned according to the level-weight mapping. For example, task criticality level 1 = 1 (i.e., task criticality level 1 weight is assigned 1), level 2 = 3, level 3 = 5, level 4 = 8; movement speed level 1 = 1, level 2 = 2, level 3 = 4, level 4 = 6; aircraft parameters level 1 = 1, level 2 = 3, level 3 = 6, level 4 = 10; controllability level 1 = 1, level 2 = 4, level 3 = 9.

[0077] Specifically, after assigning weights to each level, the weight values ​​of the four major attributes of a single aircraft can be extracted. The individual weights are then calculated by weighted summation (additional dimensional weights can be assigned to highlight important attributes). Finally, all aircraft within the grid are traversed, and the individual weights of each aircraft are accumulated to obtain grid C. i The statically weighted quantity N (C) at time t it). For example, medical emergency task (task criticality = 8) + speed 150km / h (speed = 4) + large cargo aircraft (aircraft type parameter = 6) + fully controllable (controllability = 1) UAV, individual weight w = 8 + 4 + 6 + 1 = 19 (if need to highlight "controllability", can set the dimension weight: controllability x 2, then w = 8 + 4 + 6 + 1 x 2 = 20); traverse all aircraft in airspace grid C i at time t, add up the individual weight (w) of each aircraft, for example, grid C i has 2 UAVs (w = 19) + 1 consumer entertainment (task criticality = 1) + speed 40km / h (speed = 1) + small aircraft (aircraft type parameter = 1) + uncontrollable (controllability = 9) UAV (w = 1 + 1 + 1 + 9 = 12), then N(C i , t) = 19 + 19 + 12 = 50.

[0078] In step S13, please refer to the S13 step in Figure 1 , based on the dynamic correlation parameters between aircraft in each of the three-dimensional grid cells, the situation complexity of each of the three-dimensional grid cells is obtained.

[0079] As an example, step S13 can include the following steps: S131-S135.

[0080] S131: all aircraft in each of the three-dimensional grid cells are paired.

[0081] S132: obtain the dynamic correlation parameters of each pair of aircraft.

[0082] S133: dimensionally score the dynamic correlation parameters of each pair of aircraft.

[0083] S134: obtain the interaction complexity of each pair of aircraft based on the dimensionally scored.

[0084] S135: based on the interaction complexity of all pairs of aircraft in each of the three-dimensional grid cells, the situation complexity of each of the three-dimensional grid cells is obtained.

[0085] As an example, the dynamic correlation parameters can include: relative motion complexity , proximity complexity and conflict point time complexity .

[0086] Specifically, the relative motion complexity is used to quantify the combined influence of the relative speed and the heading angle on the conflict probability; the proximity complexity is used to quantify the influence of the gap between the actual physical distance and the safety distance threshold on the risk coefficient; and the conflict point time complexity is used to quantify the influence of the time difference between the two aircrafts reaching the potential conflict point in the future on the risk urgency.

[0087] As an example, for a three-dimensional grid C i For all aircrafts in the three-dimensional grid C

[0088] As an example, based on the interaction complexity of all aircrafts in each three-dimensional network unit, the formula for obtaining the situation complexity of each three-dimensional grid unit can be as follows:

[0089]

[0090] wherein, is the three-dimensional network unit C i The situation complexity at time t.

[0091] Specifically, quantifiable score rules for the relative motion complexity, the proximity complexity, and the conflict point time complexity can be subsequently formulated. For example, in the relative motion complexity, the dimension score can be assigned as follows: the heading angle is 170°-180° (head-on) = 8 points, 80°-100° (crossing) = 4 points, and 0°-30° (same direction) = 2 points; the relative speed is greater than 150 km / h = 6 points, 80-150 km / h = 4 points, and less than 80 km / h = 2 points; in the proximity complexity, the dimension score can be assigned as follows: the urban low-altitude safety distance threshold is 50 meters, less than 40 meters = 10 points, 40-50 meters = 8 points, 50-100 meters = 3 points, and greater than 100 meters = 1 point; the remote area safety distance threshold is 100 meters, less than 80 meters = 10 points, 80-100 meters = 8 points, 100-200 meters = 3 points, and greater than 200 meters = 1 point; in the conflict point time complexity, the full time threshold is 5 seconds, less than 3 seconds = 12 points, 3-5 seconds = 10 points, 5-20 seconds = 4 points, 20-40 seconds = 2 points, and greater than 40 seconds = 1 point.

[0092] As an example, based on the dimension score, the interaction complexity of each pair of aircraft is obtained, and the three sub-dimension complexity scores of a single pair of aircraft can be calculated according to the dimension score value. Taking aircraft pair A-B (i.e., a pair of aircraft A-B) as an example, the dynamic data of aircraft pair A-B is head-on heading 170°, relative speed 180 km / h, current distance 40 meters, and conflict time difference 3 seconds. At this time, the grid is urban low altitude (safety distance threshold 50 meters, safety time threshold 5 seconds), and the relative motion complexity score is heading angle 170° (8 points) + relative speed 180 km / h (6 points) = 14 points. The proximity complexity score is distance 40 meters (< 50 meters, dangerous level) = 10 points. The conflict point time complexity score is time difference 3 seconds (< 5 seconds, extremely urgent level) = 12 points. The interaction complexity of aircraft pair A-B can be obtained as C AB = 14 points + 10 points + 12 points = 36 points.

[0093] Taking aircraft pair A-C (i.e., a pair of aircraft A-C) as an example, the interaction complexity of aircraft pair A-C can be obtained as C AC = same direction heading (20°, score 2 points) + relative speed 30 km / h (score 2 points) + distance 200 meters (score 1 point) + conflict time difference 40 seconds (score 1 point) = 6 points, i.e., the interaction complexity of aircraft pair A-C is C AC = 6 points.

[0094] Taking aircraft pair B-C (i.e., a pair of aircraft B-C) as an example, the interaction complexity of aircraft pair B-C can be obtained as C BC = same direction heading (80°, score 4 points) + relative speed 80 km / h (score 4 points) + distance 120 meters (score 3 points) + conflict time difference 25 seconds (score 3 points) = 14 points, i.e., the interaction complexity of aircraft pair A-C is C AC = 14 points.

[0095] As an example, based on the interaction complexity of all pairs of aircraft in each of the three-dimensional network units, the situation complexity of each of the three-dimensional grid units is obtained respectively. All aircraft interaction pairs are traversed, and the single-pair complexity (C AB, C AC, C BC, etc.) of each pair is added up one by one to obtain the total situation complexity of the grid C i at time t. For example, there are three aircraft A, B, and C in the three-dimensional grid C i, and the interaction pairs and single-pair complexity are C AB = 36 points, C AC = 6 points, and C BC = 14 points. The total situation complexity Complexity (C i ,t) = 36 + 6 + 14 = 56 points.

[0096] In step S14, please refer to Figure 1 S14 step, based on the capacity attribute parameters of each of the three-dimensional grid units, the airspace usage load of each of the three-dimensional grid units is obtained.

[0097] As an example, in step S14, the following steps S141-S143 can be included.

[0098] S141: Obtain the equivalent occupancy of each of the three-dimensional mesh elements.

[0099] S142: Obtain the current spatial resource utilization rate of each of the three-dimensional mesh cells.

[0100] S143: Based on the equivalent occupancy rate of each of the three-dimensional grid cells and the current spatial resource utilization rate, the spatial utilization load of each of the three-dimensional grid cells is obtained.

[0101] As an example, in step S141, obtaining the equivalent occupancy of each of the three-dimensional mesh elements may include the following steps: S1411~S1143.

[0102] S1411: Select a standard aircraft from each of the three-dimensional mesh cells.

[0103] S1412: The equivalent coefficients of the aircraft k and the standard aircraft in the three-dimensional mesh element are obtained based on the following formula. :

[0104]

[0105] in, For aircraft The volume occupied by the airspace; The airspace volume occupied by a standard aircraft.

[0106] S1413: The formula for calculating the equivalent occupancy of a 3D mesh element can be:

[0107]

[0108] in, For three-dimensional mesh units The equivalent occupancy at time t; Let k be the number of aircraft.

[0109] As an example, in step S142, the formula for calculating the current spatial resource utilization rate of each of the three-dimensional mesh cells can be:

[0110]

[0111] in, For three-dimensional mesh units The current airspace resource utilization rate; The spatial volume of a single grid; This refers to the volume occupied by a standard aircraft.

[0112] As an example, in step S143, the formula for calculating the spatial usage load of the three-dimensional mesh element can be:

[0113] .

[0114] Specifically, when , the new flight plan is allowed to enter, but the remaining capacity needs to be prompted; when , a resource saturation warning is triggered, the new flight plan is prohibited from entering, and the existing aircraft is prompted to leave or adjust to an adjacent low-load grid as soon as possible.

[0115] In step S15, please refer to the S15 step in Figure 1 , based on the static weighted number, the situation complexity and the airspace usage load of each three-dimensional grid unit, the low-altitude airspace saturation is obtained.

[0116] As an example, in step S15, the calculation formula of the low-altitude airspace saturation S can be:

[0117]

[0118] Wherein, N is the number of three-dimensional grid units; is the low-altitude airspace saturation of the i-th three-dimensional grid unit, Load is the airspace usage load of the i-th three-dimensional grid unit, is the complexity influence coefficient, is the situation complexity of the i-th three-dimensional grid unit; S is the entire low-altitude airspace saturation; N is the number of three-dimensional grid units.

[0119] Specifically, the numerical value of the complexity influence coefficient can determine the influence degree of the situation complexity on the saturation. Among them, the larger, the higher the dynamic risk in the comprehensive evaluation, which is suitable for dense aircraft, conflict risk sensitive scenarios (such as urban low-altitude); the smaller, the more dominant the resource occupation, which is suitable for sparse aircraft, low dynamic risk scenarios (such as remote low-altitude). The value of can be calibrated according to the specific scene.

[0120] Specifically, the value of can be determined by historical data regression and expert review. First, collect the airspace usage load, situation complexity, actual conflict frequency / alarm frequency data of the three-dimensional grid in the target scene (such as the city low-altitude of a city) in the past 1-2 years to form a sample set; take the conflict mark as the dependent variable and as the independent variable, find the optimal through linear regression or logistic regression, which is positively correlated with the conflict probability.The value is determined, and then airspace control and unmanned aerial vehicle technology experts can be invited to determine the value finally in combination with actual risk preferences of the scene .

[0121] In another embodiment, the application further provides a low-altitude airspace saturation evaluation system, which can include a grid division module 10, a static weighted quantity acquisition module 20, a situation complexity acquisition module 30, an airspace use load acquisition module 40, and a comprehensive evaluation module 50. The grid division module 10 is configured to divide the low-altitude airspace into a plurality of three-dimensional grid units. The static weighted quantity acquisition module 20 is configured to obtain a static weighted quantity of each three-dimensional grid unit based on a static attribute parameter of an aircraft in each three-dimensional grid unit. The situation complexity acquisition module 30 is configured to obtain a situation complexity of each three-dimensional grid unit based on a dynamic correlation parameter between aircrafts in each three-dimensional grid unit. The airspace use load acquisition module 40 is configured to obtain an airspace use load of each three-dimensional grid unit based on a capacity attribute parameter of each three-dimensional grid unit. The comprehensive evaluation module 50 is configured to obtain a low-altitude airspace saturation based on the static weighted quantity, the situation complexity, and the airspace use load of each three-dimensional grid unit.

[0122] In the low-altitude airspace saturation evaluation system of the application, the static attribute parameter of the aircraft, the dynamic correlation parameter between the aircrafts, and the capacity attribute parameter of the three-dimensional grid unit are comprehensively considered by the grid division module 10, the static weighted quantity acquisition module 20, the situation complexity acquisition module 30, the airspace use load acquisition module 40, and the comprehensive evaluation module 50, so that the real risk and capacity state of the low-altitude airspace can be more accurately reflected, a more reliable basis can be provided for airspace management, dynamic early warning and optimization of the safety management of the airspace can be realized, and the overall operation efficiency and performance of the system are effectively improved.

[0123] As an example, the low-altitude airspace saturation evaluation system of the application can be used to perform the low-altitude airspace saturation evaluation method in the embodiments of the application and related embodiments. Figure 1 and related embodiments.

[0124] The technical features of the above embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features of the above embodiments are described, but as long as the combinations of the technical features do not exist contradictions, they should be considered as the scope of the description.

[0125] The above embodiments only express several implementation ways of the present application, and the description is specific and detailed, but it should not be understood as a limitation to the patent scope of the application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for assessing low-altitude airspace saturation, characterized in that, The low-altitude airspace is divided into multiple three-dimensional grid units; Based on the static attribute parameters of the aircraft within each of the three-dimensional mesh cells, the static weighted number of each of the three-dimensional mesh cells is obtained; Based on the dynamic correlation parameters between the aircraft within each of the three-dimensional grid cells, the situational complexity of each of the three-dimensional grid cells is obtained. Based on the capacity attribute parameters of each of the three-dimensional mesh cells, the spatial usage load of each of the three-dimensional mesh cells is obtained; Based on the static weighted number of each three-dimensional mesh cell, the situational complexity, and the airspace usage load, the low-altitude airspace saturation is obtained.

2. The method according to claim 1, characterized in that, The static attribute parameters include: task criticality, movement speed, machine parameters, and controllability.

3. The method according to claim 1, characterized in that, Based on the static attribute parameters of the aircraft within each of the three-dimensional mesh cells, the static weighted quantity of each of the three-dimensional mesh cells is obtained, including: The static attribute parameters of each of the aforementioned aircraft are classified based on quantifiable classification criteria. The grading results of each static attribute parameter are weighted and assigned values. Based on the weight assignment, the individual weights of each of the aforementioned aircraft are obtained; Based on the individual weights of the aircraft within each of the three-dimensional network units, the static weighted number of each of the three-dimensional mesh units is obtained.

4. The method according to claim 1, characterized in that, The dynamic association parameters include: relative motion complexity, proximity complexity, and conflict point time complexity.

5. The method according to claim 1, characterized in that, Based on the dynamic correlation parameters between aircraft within each of the three-dimensional mesh cells, the situational complexity of each of the three-dimensional mesh cells is obtained, including: All aircraft within each of the three-dimensional grid cells are paired up in pairs. Obtain the dynamic correlation parameters of each pair of aircraft; Dimensional scoring is assigned to the dynamic correlation parameters of each pair of aircraft; The interaction complexity of each pair of aircraft is obtained based on the dimensional scoring. Based on the interaction complexity of all pairs of aircraft within each of the three-dimensional network units, the situational complexity of each of the three-dimensional mesh units is obtained.

6. The method according to claim 1, characterized in that, Based on the capacity attribute parameters of each of the three-dimensional mesh elements, the spatial usage load of each of the three-dimensional mesh elements is obtained, including: Obtain the equivalent occupancy of each of the three-dimensional mesh units; Obtain the current spatial resource utilization rate of each of the three-dimensional mesh cells; Based on the equivalent occupancy rate of each three-dimensional grid cell and the current spatial resource utilization rate, the spatial utilization load of each three-dimensional grid cell is obtained.

7. The method according to claim 6, characterized in that, Obtaining the equivalent occupancy of each of the three-dimensional mesh elements includes: A standard aircraft is selected from each of the aforementioned three-dimensional mesh cells; The equivalent coefficients of the aircraft k and the standard aircraft in the three-dimensional mesh element are obtained based on the following formula. : in, For aircraft The volume occupied by the airspace; The airspace volume occupied by a standard aircraft; The equivalent occupancy of a 3D mesh element is obtained based on the following formula: in, For three-dimensional mesh units The equivalent occupancy at time t; Let k be the number of aircraft.

8. The method according to claim 7, characterized in that, The current spatial resource utilization rate of each of the three-dimensional mesh elements is obtained based on the following formula: in, For three-dimensional mesh units The current airspace resource utilization rate; The spatial volume of a single grid; This refers to the volume occupied by a standard aircraft. The spatial utilization load of the three-dimensional mesh element is obtained based on the following formula: 。 9. The method according to claim 1, characterized in that, The low-altitude airspace saturation S is obtained based on the following formula: Where N is the number of three-dimensional mesh elements; Let i be the low-altitude airspace saturation of the i-th 3D mesh cell. Load is the spatial usage load of the i-th 3D mesh element. This is the complexity impact coefficient. S represents the situational complexity of the i-th 3D cell grid; S represents the saturation of the entire low-altitude airspace; and N represents the number of 3D cell grids.

10. A low-altitude airspace saturation assessment system, characterized in that, The low-altitude airspace saturation assessment system includes: The mesh generation module is used to divide the low-altitude airspace into multiple three-dimensional mesh units; The static weighted quantity acquisition module is used to obtain the static weighted quantity of each three-dimensional mesh cell based on the static attribute parameters of the aircraft within each three-dimensional mesh cell; The situation complexity acquisition module is used to obtain the situation complexity of each three-dimensional grid cell based on the dynamic correlation parameters between the aircraft in each three-dimensional grid cell. The airspace usage load acquisition module is used to obtain the airspace usage load of each of the three-dimensional mesh cells based on the capacity attribute parameters of each of the three-dimensional mesh cells; The comprehensive evaluation module is used to obtain the low-altitude airspace saturation based on the static weighted number of each of the three-dimensional grid cells, the situational complexity, and the airspace usage load.

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