CN116734849A

CN116734849A - Method, system, electronic equipment and medium for route planning in special scene

Info

Publication number: CN116734849A
Application number: CN202310183251.7A
Authority: CN
Inventors: 李佳林; 邹小忠; 林志文; 欧阳嘉兰
Original assignee: Beijing Zhongbing Digital Technology Group Co ltd; China Southern Airlines Co Ltd
Current assignee: Beijing Zhongbing Digital Technology Group Co ltd; China Southern Airlines Co Ltd
Priority date: 2023-02-27
Filing date: 2023-02-27
Publication date: 2023-09-12

Abstract

A method, system, electronic device and medium for route planning in special scenarios are provided. The method comprises the following steps: predicting flight profile data of an aircraft based on the weight, altitude, and ambient temperature of the aircraft in a particular scenario; obtaining terrain elevation data surrounding a predetermined course of the aircraft; planning a course of the aircraft based on the flight profile data and the terrain elevation data. Therefore, the automatic route planning under the special condition of the aircraft can be realized, and related personnel can more quickly and better optimize the dispatching.

Description

Method, system, electronic equipment and medium for route planning in special scene

Technical Field

The present application relates to the field of aerospace, and more particularly to aircraft routings methods, systems, electronic devices, and non-transitory storage media in special scenarios.

Background

Emergency programs such as a take-off failure emergency program, a course failure drift descent emergency program, a cabin pressure release emergency program and the like are manufactured according to civil aviation regulation requirements, and the aircraft can be safely returned to the ground or lowered in order to avoid dangerous terrains in emergency situations.

At present, the emergency programs are manually manufactured by aircraft performance personnel, the manual calculation amount is large, the emergency programs are unavoidable, and the planned aviation route does not necessarily achieve the optimal effect.

It is desirable to be able to plan the way of the aircraft reasonably under special circumstances in order to avoid dangerous terrain, prevent collisions and to safely return to ground or fall.

Disclosure of Invention

According to one aspect of the present application, there is provided a method for planning a route of an aircraft in a special scenario, comprising: predicting flight profile data of an aircraft based on the weight, altitude, and ambient temperature of the aircraft in a particular scenario; obtaining terrain elevation data surrounding a predetermined course of the aircraft; planning a course of the aircraft based on the flight profile data and the terrain elevation data.

According to another aspect of the application, there is provided an aircraft routings system in a special scenario, comprising: a prediction device configured to predict flight profile data of an aircraft according to weight, flight altitude and ambient temperature of the aircraft in a special scene; obtaining means configured to obtain terrain elevation data around a predetermined course of the aircraft; planning means configured to plan a course of the aircraft based on the flight profile data and the terrain elevation data.

According to another aspect of the present application, there is provided an electronic apparatus including: a memory for storing instructions; a processor for reading the instructions in the memory and performing a method according to an embodiment of the application.

According to another aspect of the application, there is provided a non-transitory storage medium having instructions stored thereon, wherein the instructions, when read by a processor, cause the processor to perform a method according to an embodiment of the application.

Therefore, the automatic route planning under the special condition of the aircraft can be realized, and related personnel can more quickly and better optimize the dispatching.

Drawings

In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort to a person of ordinary skill in the art.

Fig. 1 shows a flow chart of an aircraft routings method in a special scenario according to an embodiment of the present application.

Fig. 2 shows a schematic illustration of the course of an aircraft according to an embodiment of the application, as well as flight profile data and said terrain elevation data.

Fig. 3 shows a specific process of step 110 of predicting flight profile data of an aircraft according to its weight, altitude and ambient temperature in a particular scenario, according to an embodiment of the application.

FIG. 4 shows an exemplary aircraft manufacturer provided fault profile curve table.

FIG. 5 illustrates an example flight profile of a drift down due to a fault provided by a model vendor of an aircraft in accordance with an embodiment of the application.

Fig. 6 shows a schematic view of a flight profile of the aircraft based on the planned profile data according to a set flat flight duration and descent duration, according to an embodiment of the application.

FIG. 7 illustrates an example terrain elevation curve plotted with terrain elevation data near a course of an aircraft in one example, in accordance with an embodiment of the application.

Fig. 8 shows a flow chart of steps for planning a course of the aircraft based on the flight profile data and the terrain elevation data, according to an embodiment of the application.

Fig. 9 shows a schematic diagram of overlaying a flight profile as shown in fig. 6 and a terrain elevation as shown in fig. 7, in accordance with an embodiment of the present application.

Fig. 10 illustrates the difference between the conventional a-algorithm and the hybrid a-algorithm.

Fig. 11A-11D illustrate examples of paths generated by two heuristic functions of a hybrid a-algorithm according to an embodiment of the present application.

Fig. 12 shows a process of path node expansion for the hybrid a-algorithm according to an embodiment of the application.

Fig. 13 shows an example roadmap planned by the hybrid a-algorithm according to an embodiment of the application.

Fig. 14 shows a block diagram of an aircraft routings system in a special scenario according to an embodiment of the present application.

FIG. 15 illustrates a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the application.

Fig. 16 shows a schematic diagram of a non-transitory computer-readable storage medium according to an embodiment of the disclosure.

Detailed Description

Reference will now be made in detail to the present embodiments of the application, examples of which are illustrated in the accompanying drawings. While the application will be described in conjunction with the specific embodiments, it will be understood that it is not intended to limit the application to the described embodiments. On the contrary, it is intended to cover alternatives, modifications, and equivalents as may be included within the spirit and scope of the application as defined by the appended claims. It should be noted that the method steps described herein may be implemented by any functional block or arrangement of functions, and any functional block or arrangement of functions may be implemented as a physical entity or a logical entity, or a combination of both.

At present, the emergency programs are manually manufactured by aircraft performance personnel, the manual calculation amount is large, the emergency programs are unavoidable, and the program route does not necessarily reach the optimal effect.

If the electronic map is used for manufacturing, there is still room for improving performance and reducing the load of flights. Meanwhile, the number of machine types is huge, the program production is time-consuming and labor-consuming, the efficiency is low, and the time requirement of temporary airlines for voyage cannot be met frequently. In addition, because of lacking simulation verification tools, the emergency program cannot pass once during verification of the simulation machine, multiple times of verification are needed, and verification cost is increased.

Advanced emergency program analysis systems exist for aviation related enterprises in the world, the program is accurate and quick to manufacture, such as a Hansa system company, and the rapid and automatic generation of simple emergency programs for the failure and drop of a route and the pressure release of a passenger cabin are realized. Therefore, in order to compare international first-class and increase efficiency, the technology of combining the airplane performance analysis with the technology of electronic maps, electronic airlines and the like needs to be researched, an intelligent analysis system applied to airplane emergency programs is researched and established, the efficiency and the precision of program manufacturing are improved, and the safety level of flight is improved.

When the civil aviation flight executes the release program, factors such as a take-off airport runway, local temperature, model thrust, obstacle crossing conditions of a single departure after take-off, a flying and descending program of a special high-altitude way and the like are required to be considered, so that the optimal allocation scheme of the civil aviation flight can be adjusted by providing the single departure program under a special scene, the path planning of the standby descending way under the release of a passenger cabin of the high-altitude way and the flying and descending program of the high-altitude way after fine calculation of the flight conditions and the special environment limit.

The course of the route planning of the flight is equivalent to the route planning of making a point on a two-dimensional or three-dimensional plane, and the plane obstacle and limitation can be obtained by only analyzing the motion attribute of the point. And acquiring aircraft flight parameters, flight plans, airports and meteorological conditions on the airlines, analyzing the terrain to acquire barrier information, and generating a planning path by using a path planning algorithm.

Fig. 1 shows a flow chart of an aircraft routings method 100 in a special scenario according to an embodiment of the present application.

As shown in fig. 1, the aircraft routing method 100 in a special scenario includes the following steps.

Step 110, predicting flight profile data of the aircraft according to weight, flight altitude and ambient temperature of the aircraft in a special scene.

A special scenario refers to the situation where the aircraft needs to initiate an emergency procedure. For example, the special scene includes at least one of: take-off failure, route failure, cabin pressure relief, aircraft failure, aircraft drift down, etc. In such special scenarios, the aircraft may need to initiate an emergency procedure and perform a fly-down.

If one engine fails, the climbing performance of the engine is reduced by half, and if the aircraft flies according to the departure procedure published by the civil aviation administration, the aircraft cannot climb over the obstacle according to the normal climbing gradient, and is highly likely to collide with the obstacle below the route. When the engine fails, the flying personnel shall descend to a proper height according to the topography of the route by adopting obstacle surmounting or standard drifting mode to fly to the nearby available standby airport or continue to the destination airport.

At this point, it is important to surmount the obstacle and descend and avoid colliding with obstacles below the course. At this time, the flight profile data during the flying down of the aircraft in a special scenario, i.e. how much the aircraft will drop in altitude after how much distance it has flown, can be predicted from the weight of the aircraft, the flying altitude and the ambient temperature. It is also contemplated herein that the ambient temperature of the aircraft is primarily used to correct the altitude measured by barometric altimeters commonly used by aircraft. As will be described in more detail hereinafter.

In this way, after the aircraft's flight profile data is predicted, it is known about what curve the aircraft will fly down in the air.

Step 120 obtains terrain elevation data surrounding a predetermined course of the aircraft.

The predetermined route of the aircraft is a route the aircraft is scheduled to fly, and can be, for example, a broken line from Beijing to Shanghai, and then from Shanghai to Shenzhen.

In this case, it is possible to draw a 2-or 3-dimensional graph of the terrain around the predetermined course of the aircraft by collecting altitude data of the terrain around the predetermined course of the aircraft, for example in the range of 400 km, in order to intuitively see whether there is a region above the aircraft flight altitude (after the addition of the obstacle avoidance margin), which is then an obstacle region. The obstacle avoidance margin herein may be a 2000 foot margin, or other value.

The terrain elevation map may be drawn here by a meshing process.

Step 130, planning a course of the aircraft based on the flight profile data and the terrain elevation data.

In this way, knowing the projected flight profile data (which may be visually represented as a flight level curve, for example) of the aircraft, and the terrain elevation data (which may be visually represented as a terrain level curve, for example) around the course, the course of the aircraft may be planned to avoid the aircraft hitting ground obstacles.

As shown in the map on the left side of fig. 2, a predetermined course of the aircraft is marked. As shown on the right side of fig. 2, the lower curve represents a terrain elevation curve plotted with terrain elevation data. Whereas the upper right hand curve of fig. 2 represents a flight altitude curve plotted with predicted aircraft flight profile data. It can be seen that to avoid the aircraft hitting ground obstacles, i.e. to avoid the flight level profile of the aircraft (e.g. minus a certain margin) falling below the terrain level data.

Of course the drawing of fig. 2 is only an example, and the relation between the flight profile data and the terrain elevation data of the aircraft can be seen intuitively, but this is not a limitation, and indeed the flight profile data and the terrain elevation data of the aircraft can also be utilized in other forms, for example in three-dimensional graphics or other transformations.

In one embodiment, the step 110 of predicting the flight profile data of the aircraft according to the weight, the altitude and the ambient temperature of the aircraft in the special scene includes:

step 111, obtaining the barometric altitude by using a barometer altimeter.

Barometer altimeters commonly used on aircraft include:

standard barometric pressure altitude (HQNE). Altimeters represent the vertical distance of an aircraft from a standard barometric pressure plane using the altitude calculated and indicated at standard barometric pressure (760 mmHg or 1013mb or 29.92 inHg) values. Used on airlines. Special name-flight level or altitude level.

The sea pressure height (HQNH) is corrected. The altimeter uses the altitude calculated and indicated when correcting the sea level barometric pressure value somewhere to represent the vertical distance of the aircraft to a certain corrected sea level barometric pressure surface. The aircraft is used when taking off and landing. Specially called Altitude (Altitude) or Altitude.

The barometer is in fact a barometer. This pressure difference represents the difference in height between you and the reference air pressure, since the higher the height, the smaller the air pressure. The barometer measures the air pressure around the aircraft and then subtracts the measured air pressure from a reference air pressure to obtain a pressure difference. This pressure difference represents the difference between the altitude of the aircraft and the reference altitude at which the reference air pressure is located. Here, the reference air pressure may be set to an air pressure 1013hPa of a standard atmosphere (ISA). Therefore, the barometric altitude of an aircraft is measured indirectly by measuring the barometric pressure of the altitude at which the aircraft is located, which is a solution for altitude from the measured barometric pressure value.

The atmosphere adopted by the international civil aviation organization is completely the same as the corresponding part below 32km of standard atmosphere ISA in the us 1976. The partial characteristics are defined as follows:

a. sea level air temperature t0=288.15k=15 ℃;

b. sea level pressure p0=1013.25 hpa=760 mmHg;

c. under the altitude of 11km, the air temperature direct reduction rate is 0.65 ℃/100m;

d. altitude is 11-20km, air temperature is unchanged and is-56.5 ℃;

since the barometric altimeter is designed according to the standard atmosphere ISA environment, that is, the barometric pressure reduction rate is fixed at-8.25 m/hPa, but the actual atmosphere environment is not the standard atmosphere ISA in most cases, the altimeter indication may deviate from the actual altitude. The actual barometric pressure at that time is affected by the ambient temperature of the environment in which the aircraft is located, and therefore it is necessary to correct the barometric altitude to the actual flying altitude of the aircraft based on the ambient temperature of the aircraft.

That is, at step 112, the barometric altitude is corrected to the flying altitude based on the ambient temperature of the aircraft.

Specifically, assuming that the barometer measures 700hPa, a pressure differential of 300hPa, and under ISA atmospheric conditions, a rough calculation may be considered to be 30ft/1hPa, then a differential of 300hPa means that the barometric altitude is 9000ft. But this 9000ft represents the true altitude of the aircraft only if the atmospheric temperature of the aircraft flight environment is the same as or close to ISA atmospheric temperature. When the temperature of the flight environment of the aircraft differs greatly from the ISA atmospheric temperature, a temperature correction is required to know the actual flight altitude of the aircraft.

Specifically, the ISA atmosphere is assumed to be at 15 degrees sea level temperature, 2 degrees lower per 1000ft rise. The 9000ft of the aircraft is the true fly height only when the temperature around the aircraft is very close to-3 degrees (15-2 x 9000/1000 = -3).

The effect of temperature on the air layer thickness can be considered as a 1 degree change resulting in a change in air layer thickness (height) of about 0.4%. The temperature increases and the air layer becomes thicker (the total mass is unchanged) because of expansion, while the temperature decreases and the air layer becomes thinner because of contraction. This makes the same pressure difference represent a relatively small height difference in cold air and a relatively large height difference in hot air.

If the actual ambient temperature of the aircraft is 10 degrees cooler than the standard ambient temperature measured by ISA model, i.e., the temperature around the aircraft is in fact-13 degrees, then the air altitude shrinkage ratio is 10 x 0.4% = 4%, and thus the corrected aircraft's actual altitude is 9000 x (1-4%) = 8640ft.

In summary, the formula for correcting the height according to the temperature is: ia=ta x t° std/t°

IA = barometer altimeter indication altitude

TA = true height

T°std=standard temperature (° K)

T+=actual temperature (° K)

Thus, based on the barometer altitude indication altitude as well as the standard temperature and the actual temperature, the actual altitude of the aircraft can be calculated.

Of course, the above-mentioned method of correcting fly height based on temperature is merely an example, and other correction methods may be employed.

Step 113, obtaining planned profile data of the aircraft based on a fault profile curve table provided by a model manufacturer of the aircraft according to the weight and the flying height of the aircraft in a special scene;

typically, a manufacturer of an aircraft will provide a fault profile table. FIG. 4 shows an exemplary aircraft manufacturer provided fault profile curve table.

The aircraft model manufacturer may provide flight profile data for the aircraft model that is dropped due to a fault in a particular scenario. Specifically, as shown in fig. 4, the model 737-800W is data of pressure height, weight, remaining time, vacuum speed, and the like. From this data, a flight profile may be drawn, which is a drawing of the aircraft track for a particular mission.

As shown in fig. 5, it can be seen that the aircraft flying down due to a fault is highly declining with flight distance or time of flight according to data provided by the model manufacturer of the aircraft.

And 114, obtaining flight profile data of the aircraft based on the planned profile data according to the set flat flight duration and descent duration.

Here, in order to make the taxiing time longer and the taxiing distance longer for the failed aircraft in the special scene, the flat flight time and the descent time of the aircraft are set, assuming that the aircraft can keep the flat flight for the set flat flight time and then descend for the set descent time. For example, each time the time period of the flat fly is 6 minutes, the time period of the descent is 1 minute, then the time period of the flat fly is 6 minutes, and the time period of the descent is 1 minute.

For example, the planned profile data may be looked up every 7 minutes period to obtain the altitude H1 of the aircraft at the present time, assuming that the altitude of the aircraft remains at H1 for a period of 6 minutes of flat flight, and then after a period of 1 minute of descent, the planned profile data is looked up to obtain a 1 minute decrease in altitude of the aircraft from H1 to H2. Continuing to assume that the altitude of the aircraft remains at H2 for 6 minutes of flat flight, then after 1 minute of descent, the planned profile data is looked up to obtain 1 minute later the altitude of the aircraft decreases from H2 to H3. And so on.

Of course, the flat flight time and the descent time are only examples, other values may be taken, and the flat flight time and the descent time may be set to be different each time, depending on the performance of the aircraft and the descent time.

And finally, obtaining flight profile data of the aircraft based on the planned profile data according to the set flat flight duration and the set descent duration.

As shown in fig. 6, the aircraft flies 3 minutes at the height FL390 (39000 feet), then descends 1 minute to the height FL290, then flies 6 minutes at the height FL290, then descends 1 minute to the height FL250, then flies 6 minutes at the height FL250, then descends 1 minute to FL140, then flies 6 minutes at the height FL140, then descends 1 minute to FL100, then flies 6 minutes at the height FL100, then descends 1 minute to FL50, then flies 6 minutes at the height FL50, then descends 1 minute to FL20, and so on.

Of course the flight profile shown in fig. 6 is only exemplary and not limiting.

Assume that the solid line in fig. 7 is an example terrain elevation curve plotted with terrain elevation data near the course of the aircraft. It can be seen that the terrain has peaks at FL180 (18000 feet, about 5486.4 meters), FL130, FL30, FL80, etc., respectively.

Suppose the obstacle avoidance margin may be a FL20 (2000 feet) margin. Then, the dashed line in fig. 7 is a schematic curve after adding the FL20 (2000 feet) margin to the terrain elevation curve. The peaks of the dotted lines are at FL200, FL150, FL50, FL100, etc., respectively.

Fig. 8 shows a flowchart of step 130 of planning a course of the aircraft based on the flight profile data and the terrain elevation data, according to an embodiment of the application.

As shown in fig. 8, the step 130 of planning a course of the aircraft based on the flight profile data and the terrain elevation data includes: step 131, determining an obstacle region of the aircraft, which is lower than the terrain elevation during the flight, based on the flight profile data and the terrain elevation data; step 132, planning a course of the aircraft to avoid the obstacle region based on the obstacle region.

In step 131, an obstacle region is determined for the aircraft that would be below the terrain elevation during flight based on the flight profile data and the terrain elevation data.

After the flight profile shown in fig. 6 and the terrain elevation shown in fig. 7 are obtained, they can be superimposed, and it can be intuitively seen that the aircraft may be below the obstacle area of the terrain elevation (e.g., plus an obstacle avoidance margin) during flight.

Wherein although the abscissa of the flight profile shown in fig. 6 is minutes, the flight profile shown in fig. 6 can be converted by using the flight speed of the aircraft to find the distance the aircraft is flying. The converted flight profile is then superimposed on the terrain elevation map shown in fig. 7.

As shown in fig. 9, it can be seen that the gray circular box marks an obstacle region where the aircraft would have a flight level below the terrain level (e.g., plus an obstacle avoidance margin). The obstacle region may be represented by two-dimensional coordinates or three-dimensional coordinates.

Then the course of the aircraft may be planned to avoid the obstacle region based on the obstacle region.

Note that only two-dimensional flight profiles and terrain elevations are shown in the examples and figures of the present application, but those skilled in the art will appreciate that three-dimensional flight profiles and terrain elevations are possible and that the principles disclosed and taught in the present application may be used to plan three-dimensional flight paths for an aircraft as well.

In step 132, a course of the aircraft is planned to avoid the obstacle region based on the obstacle region.

In this way, the course of the aircraft may be planned to avoid the obstacle region based on the determined obstacle region.

In this step, the course of the aircraft may be planned to avoid the obstacle region using a hybrid a algorithm or an artificial potential field method.

First, an embodiment is described in which a hybrid a-algorithm is used to plan the way of the aircraft to avoid the obstacle region.

Unlike the conventional a algorithm, which is an improvement over the conventional a algorithm, the hybrid a is a heuristic search in a continuous coordinate system and ensures that the generated trajectory satisfies the non-integrity constraint, but the path is not necessarily globally optimal during the operation of the algorithm, but is nevertheless "near" the globally optimal solution.

The mixed A planning path consists of two parts, wherein the first part is a path formed by connecting exploration nodes taking kinematics into consideration; the second part is a path connecting the intermediate point pose with the target pose using a Reeds-Shepp curve or Dubins curve. The search space of the mixed A is not only considered for expansion of the x and y directions, but also considered for exploration of the theta direction. Compared with the traditional A exploration space, the node expansion of the mixed A is three-dimensional, so that more calculation amount is needed.

Fig. 10 illustrates the difference between the conventional a-algorithm and the hybrid a-algorithm. The left diagram of fig. 10 is a schematic diagram of a conventional A9 algorithm implementation, the middle diagram is a schematic diagram of other a variant algorithm implementations, and the right diagram is a schematic diagram of a hybrid a algorithm implementation.

Both conventional a and hybrid a algorithms are based on grid world (grid world), the a algorithm is a penalty assigned to the center points of each grid and the algorithm only accesses those center points. As shown in the left-hand diagram of fig. 10, the planned trajectory of the moving object passes through only the center point of each grid.

The mixing a is to select points satisfying the three-dimensional continuous state of the moving object from the grids, and assign losses to the points. As shown in the right-hand diagram of fig. 10, the planned trajectory of the moving object is continuous. The mixed A is used for heuristic search under a continuous coordinate system, and the generated track can be ensured to meet the non-integrity constraint of the moving object.

The hybrid a algorithm constructs two heuristic functions (heuristic function).

The first heuristic is a constraint heuristic (Constrained heuristics) that considers only non-integrity constraints and not obstacles and terrain, considering only the course of the endpoint.

Non-integrity constraints refer to constraints in which constraint equations contain derivatives of coordinates that determine the position of the system and cannot be directly integrated into a system without derivatives of coordinates without using kinetic equations. That is, if the constraint equation contains a derivative of coordinates with respect to time (e.g., a motion constraint), and the equation cannot be integrated into a finite form, such a constraint is referred to as an incomplete constraint. The non-integrity constraint equation is always in the form of a differential equation.

The basic configuration space for the non-integrity constraint is:where (x, y) is the position of the node and θ is the orientation of the object,>representing a two-dimensional space>Representing an angular space. Assuming that the speed of the object isFor example, in actual motion, the object cannot translate directly to the left and right, the object can move with rounded corners, that is, the velocity perpendicular to the direction of the object head is 0 (of course, this is only an example, and constraints can be added, such as adding latitude limits, etc., and changing the constraint equation of the non-integrity constraint accordingly), v in the following figure _⊥ The decomposition to X and Y coordinates can be achieved:

the two can be obtained by combining:

the non-integrity constraints that can be obtained for an object are:

the heuristic function ignores information such as obstacles in the environment and only considers kinematic characteristics. From the point of termination (x _g ,y _g ,θ _g ) Starting with = (0, 0), the shortest path from this point to the other point is calculated. Its return value is the maximum of non-holonomic-no-obstacles-cost and 2-dimensional euclidean distance loss. Its advantage is high Euclidean distance lossAnd is of an order of magnitude.

2. The second heuristic is the first pair, called unconstrained heuristic (Unconstrained heuristics), which considers only obstacle information and does not consider the non-integrity constraints of the aircraft. The shortest path to the endpoint for each node is then calculated using a 2-dimensional dynamic programming approach (i.e., a conventional 2-dimensional a-x algorithm). The heuristic function utilizes the obstacle map to dynamically plan in a two-dimensional space, calculates the shortest distance to the target, and the heuristic function considering the obstacle can guide the object to bypass the obstacle or the U-shaped curve. The advantage is that after the heuristic function is introduced, all obstacles and dead ends in the 2-dimensional space can be found.

Here, the information of the obstacle region obtained in the embodiment according to the present application may be taken into the calculation as the obstacle information here.

FIGS. 11A and 11C are paths generated under a first heuristic function that can be seen to be continuous; while fig. 11B and 11D are discrete paths generated under a second heuristic function (similar to the result obtained by the conventional a-algorithm).

The design of the loss function of the hybrid a-algorithm needs to meet the following requirements: the path length or loss should be near optimal; the path should be smooth; the resulting path should be kept at a distance from the obstacle. Thus, the loss function used by the hybrid a-algorithm may be the maximum of the two heuristic functions above.

The hybrid a algorithm may use the Reeds-Shepp curve or Dubins curve to attempt to connect to the current node (x _s ) And the end node (x) _g )。

Assuming that the environment is not considered (corresponding to the first heuristic function), the hybrid a algorithm will regenerate an additional child node by calculating the optimal Reed-Shepp curve from the start point to the end point; then, the hybrid a algorithm performs collision detection on the path based on the existing obstacle map, and points corresponding to the collision-free path are added to the expansion tree. The Reed-Shepp curves are computationally intensive compared to straight lines. Using a simple selection rule, a calculated Reed-Shepp curve is selected for every N nodes (N is a positive integer) (where N decreases with decreasing heuristic function, i.e., the closer to the endpoint, the smaller N). Fig. 12 shows a process of path node expansion for the hybrid a-algorithm according to an embodiment of the application.

Similar to the a algorithm, the hybrid a algorithm also maintains two lists, one Open List (Open List, or O List) and one closed List (closed List, or C List). The Open list is a priority queue that provides the best node for each search. The closed list is a common queue, which stores the accessed nodes and avoids repeated access of a node. The end conditions of the algorithm are: the open list is empty or the endpoint has been searched. The algorithm does not have to search exactly for the endpoint and therefore introduces a round state function that is evaluated before determining if the current node has reached the endpoint. If the endpoint is not reached, the algorithm expands the path nodes by performing all actions in the action space. If the generated node is not in the C list (i.e., not traversed by the algorithm), then the cost-so-far is calculated; if the generated node is not in the O list (has been traversed) or the resulting cost so far is less than the cost already available to the current node, then the cost so far is updated with the smaller cost currently available.

The specific process of searching comprises the following steps:

firstly, sampling is carried out to obtain a plurality of discrete track points, and the speed and acceleration of the starting point, so as to obtain a node point set (point_set), namely, an open list is created.

And converting the three-dimensional positions of the starting point and the target point into indexes of the grid map. And calculates a Heuristic cost (heuristics cost) for the first expansion point.

Iterative loop searches for expansion nodes, and continuously performs direct curve calculation of two-point boundaries while expanding the nodes:

taking out from the open_list priority queue the node with the smallest cost value f (n) =g (n) +h (n), where f (n) is the valuation function from the initial point a via the node n to the target point B, g (n) is the actual cost from the initial point a to the node n in the state space, and h (n) is the estimated cost of the best path from n to the target point B.

Judging whether the current node exceeds the level or is nearer to the end point, calculating a direct curve, and checking whether the direct curve exists on the curve. If the path point exists, the searching is completed, and the path point is returned.

If the current node does not reach the endpoint, the algorithm will expand-prune the path nodes by performing all actions in the action space: 1. the nodes are deleted in the open list and the nodes are added in close_list. 2. State transfer is initialized. 3. The decision node is already extended. 4. The state transfer loop iterates, checks the speed constraint, checks if an obstacle is hit, calculates the g-score (g_score, i.e. the cost of moving the current point to the point a along the path generated by the initial point a) and the f-score (f_score, i.e. the cost of theoretical movement of the current point to the target point B without considering the area of non-trafficability (obstacle area)) of the current node, and prunes the repeated extended nodes: if the judging node is not in the close_list. And judging the maximum speed of the node. The nodes are judged not to be in the same grid. Whether the node collides with the obstacle region is judged. State transfer, the position and speed stateTransit () of the extended node is obtained by forward integration. And calculating the true cost G value of the current node. And calculating a heuristic cost H value. And comparing the expansion nodes in the circulation, and pruning the nodes.

If the open list has been traversed, no paths are searched, then the open set is empty, i.e., no paths.

Then, an embodiment will be described in which the course of the aircraft is planned to avoid the obstacle region by using an artificial potential field method.

The artificial potential field path planning is a virtual force method proposed by Khatib (eussama Khatib, real-Time Obstacle Avoidance for Manipulators and Mobile robots. Proc of The 1985 IEEE.). The basic idea is to design the motion of the object in the surrounding environment into an abstract artificial gravitational field, the target point generates 'attraction' to the object, the obstacle generates 'repulsion' to the object, and finally the motion of the object is controlled by solving the resultant force. The path planned by the potential field method is generally smooth and safe, but the method has the problem of local optimal point.

The artificial potential field method is a relatively common method for local path planning. This method assumes that the object is moving under a virtual force field.

The artificial potential field is established by means of a potential function U. The potential (field) function is a microtransaction, and the magnitude of the potential function value at a point in space represents the potential field strength at that point. The simplest potential function is the attraction/repulsion potential function. The action thought is very simple: the target point is made to generate attractive force to the object, and the obstacle (region) 0 generates repulsive force to the object. The potential function U (q) at a point q is expressed as the gravitational potential U _att (q) and repulsive force potential U _rep Sum of (q):

U(g)＝U _att (q)+U _rep (q)

of these, the most common potential U _att The functional expression of (q) is as follows:

zeta-gravitational gain

d(q，q _goal ) -current point q to target point q _goal Distance between

The most common repulsive force potential U _rep The functional expression of (q) is as follows:

d (q) -distance of point q from its nearest obstacle

Eta-repulsive force gain

Q ^* -a threshold distance of action of the obstacle, an obstacle greater than this distanceThe object does not generate repulsive force to affect

The result of the route planning is from the planning of the fault point on the route to the selection of the route with the best descent.

In connection with the present application, it is possible to generate a repulsive force to an aircraft using the obstacle region obtained according to the embodiment of the present application as an obstacle, thereby planning a course of the aircraft to avoid the obstacle region.

While the above describes planning the path of the aircraft to avoid the obstacle region using a hybrid a-algorithm and artificial potential field method, the present application is not limited thereto, and other algorithms may be used to plan the path of the aircraft to avoid the obstacle region after determining the obstacle region.

Note that the aircraft mentioned herein may include an aircraft in the present disclosure, but is not limited thereto, and other aircraft, such as balloons, gliders, airships, helicopters, etc., may also be suitable for use in the present application in certain situations.

Fig. 14 shows a block diagram of an aircraft routings system 1400 in a special scenario according to an embodiment of the present application.

As shown in fig. 14, the aircraft routings system 1400 in a special scenario includes: a prediction device 1401 configured to predict flight profile data of an aircraft according to its weight, its altitude and its ambient temperature in a specific scenario; an obtaining means 1402 configured to obtain terrain elevation data around a predetermined course of the aircraft; planning means 1403 is configured to plan a course of the aircraft based on the flight profile data and the terrain elevation data.

In one embodiment, the special scene may include at least one of: take-off failure, route failure, cabin pressure relief, aircraft failure, aircraft drift down, etc.

In one embodiment, the predictive device includes: a measuring device configured to obtain an air pressure measured height using an air pressure gauge; a correction device configured to correct the barometric altitude to the flying altitude according to an ambient temperature of the aircraft; a first obtaining device configured to obtain planned profile data of an aircraft based on a fault profile curve table provided by a model manufacturer of the aircraft according to the weight and the flying height of the aircraft in a special scene; and second obtaining means configured to obtain flight profile data of the aircraft based on the planned profile data according to the set flat flight duration and descent duration.

In one embodiment, the planning apparatus includes: a determining device configured to determine an obstacle region of the aircraft that would be below a terrain elevation during flight based on the flight profile data and the terrain elevation data; an avoidance device configured to plan a course of the aircraft to avoid the obstacle region based on the obstacle region.

In one embodiment, the avoidance device is configured to: based on the obstacle region, planning a course of the aircraft using a hybrid a-algorithm or an artificial potential field method to avoid the obstacle region.

The electronic device may include a processor (H1); a storage medium (H2) coupled to the processor (H1) and having stored therein computer executable instructions for performing the steps of the methods of embodiments of the present application when executed by the processor.

The processor (H1) may include, but is not limited to, for example, one or more processors or microprocessors or the like.

The storage medium (H2) may include, for example, but is not limited to, random Access Memory (RAM), read Only Memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, a computer storage medium (e.g., hard disk, a floppy disk, a solid state disk, a removable disk, a CD-ROM, a DVD-ROM, a blu-ray disc, etc.).

In addition, the electronic device may include, but is not limited to, a data bus (H3), an input/output (I/O) bus (H4), a display (H5), and an input/output device (H6) (e.g., keyboard, mouse, speaker, etc.), among others.

The processor (H1) may communicate with external devices (H5, H6, etc.) via a wired or wireless network (not shown) through an I/O bus (H4).

The storage medium (H2) may also store at least one computer executable instruction for performing the functions and/or steps of the methods in the embodiments described in the present technology when executed by the processor (H1).

In one embodiment, the at least one computer-executable instruction may also be compiled or otherwise formed into a software product in which one or more computer-executable instructions, when executed by a processor, perform the functions and/or steps of the methods described in the embodiments of the technology.

As shown in fig. 16, the computer-readable storage medium 1620 has stored thereon instructions, such as computer-readable instructions 1610. When the computer-readable instructions 1610 are executed by a processor, the various methods described with reference to the above may be performed. Computer-readable storage media include, but are not limited to, volatile memory and/or nonvolatile memory, for example. Volatile memory can include, for example, random Access Memory (RAM) and/or cache memory (cache) and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. For example, the computer-readable storage medium 1620 may be connected to a computing device such as a computer, and then the various methods described above may be performed where the computing device runs the computer-readable instructions 1610 stored on the computer-readable storage medium 1620.

Of course, the above-described specific embodiments are merely examples, and those skilled in the art may combine and combine some steps and means from the above-described embodiments separately to achieve the effects of the present application according to the concept of the present application, and such combined and combined embodiments are also included in the present application, and such combination and combination are not described herein one by one.

Note that advantages, effects, and the like mentioned in this disclosure are merely examples and are not to be construed as necessarily essential to the various embodiments of the application. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, as the application is not necessarily limited to practice with the above described specific details.

The block diagrams of the devices, apparatuses, devices, systems referred to in this disclosure are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.

The step flow diagrams in this disclosure and the above method descriptions are merely illustrative examples and are not intended to require or imply that the steps of the various embodiments must be performed in the order presented. The order of steps in the above embodiments may be performed in any order, as will be appreciated by those skilled in the art. Words such as "thereafter," "then," "next," and the like are not intended to limit the order of the steps; these words are simply used to guide the reader through the description of these methods. Furthermore, any reference to an element in the singular, for example, using the articles "a," "an," or "the," is not to be construed as limiting the element to the singular.

In addition, the steps and means in the various embodiments herein are not limited to practice in a certain embodiment, and indeed, some of the steps and some of the means associated with the various embodiments herein may be combined according to the concepts of the present application to contemplate new embodiments, which are also included within the scope of the present application.

The individual operations of the above-described method may be performed by any suitable means capable of performing the corresponding functions. The means may include various hardware and/or software components and/or modules including, but not limited to, circuitry for hardware, an Application Specific Integrated Circuit (ASIC), or a processor.

The various illustrative logical blocks, modules, and circuits described herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an ASIC, a field programmable gate array signal (FPGA) or other Programmable Logic Device (PLD), discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any commercially available processor, controller, microcontroller or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, microprocessors in conjunction with a DSP core, or any other such configuration.

The steps of a method or algorithm described in connection with the disclosure herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may reside in any form of tangible storage medium. Some examples of storage media that may be used include Random Access Memory (RAM), read Only Memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, and so forth. A storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. A software module may be a single instruction, or many instructions, and may be distributed over several different code segments, among different programs, and across several storage media.

The methods disclosed herein include acts for implementing the described methods. The methods and/or acts may be interchanged with one another without departing from the scope of the claims. In other words, unless a specific order of acts is specified, the order and/or use of specific acts may be modified without departing from the scope of the claims.

The functions described above may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as instructions on a tangible computer-readable medium. A storage media may be any available tangible media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other tangible medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. As used herein, discs (disks) and disks include Compact Disks (CDs), laser disks, optical disks, digital Versatile Disks (DVDs), floppy disks, and blu-ray disks where disks usually reproduce data magnetically, while disks reproduce data optically with lasers.

Thus, the computer program product may perform the operations presented herein. For example, such a computer program product may be a computer-readable tangible medium having instructions tangibly stored (and/or encoded) thereon, the instructions being executable by a processor to perform operations described herein. The computer program product may comprise packaged material.

The software or instructions may also be transmitted over a transmission medium. For example, software may be transmitted from a website, server, or other remote source using a transmission medium such as a coaxial cable, fiber optic cable, twisted pair, digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, or microwave.

Furthermore, modules and/or other suitable means for performing the methods and techniques described herein may be downloaded and/or otherwise obtained by the user terminal and/or base station as appropriate. For example, such a device may be coupled to a server to facilitate the transfer of means for performing the methods described herein. Alternatively, the various methods described herein may be provided via storage means (e.g., RAM, ROM, a physical storage medium such as a CD or floppy disk, etc.) so that the user terminal and/or base station can obtain the various methods when coupled to or providing storage means to the device. Further, any other suitable technique for providing the methods and techniques described herein to a device may be utilized.

Other examples and implementations are within the scope and spirit of the disclosure and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwired or any combination of these. Features that implement the functions may also be physically located at various locations including being distributed such that portions of the functions are implemented at different physical locations. Also, as used herein, including in the claims, the use of "or" in the recitation of items beginning with "at least one" indicates a separate recitation, such that recitation of "at least one of A, B or C" means a or B or C, or AB or AC or BC, or ABC (i.e., a and B and C), for example. Furthermore, the term "exemplary" does not mean that the described example is preferred or better than other examples.

Various changes, substitutions, and alterations are possible to the techniques described herein without departing from the techniques of the teachings, as defined by the appended claims. Furthermore, the scope of the claims of the present disclosure is not limited to the particular aspects of the process, machine, manufacture, composition of matter, means, methods and acts described above. The processes, machines, manufacture, compositions of matter, means, methods, or acts, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein may be utilized. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or acts.

The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit embodiments of the application to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.

Claims

1. An aircraft routing method in a special scenario, comprising:

predicting flight profile data of an aircraft based on the weight, altitude, and ambient temperature of the aircraft in a particular scenario;

obtaining terrain elevation data surrounding a predetermined course of the aircraft;

planning a course of the aircraft based on the flight profile data and the terrain elevation data.

2. The method of claim 1, wherein predicting flight profile data for an aircraft based on weight, altitude, and ambient temperature of the aircraft in a particular scenario comprises:

obtaining an air pressure measurement height by using an air pressure gauge;

correcting the barometric altitude measured as the flying altitude according to the ambient temperature of the aircraft;

obtaining planned section data of the aircraft based on a fault section curve table provided by a model manufacturer of the aircraft according to the weight and the flying height of the aircraft in a special scene;

and obtaining flight profile data of the aircraft based on the planned profile data according to the set flat flight duration and descent duration.

3. The method of claim 1, wherein the planning the path of the aircraft based on the flight profile data and the terrain elevation data comprises:

determining an obstacle region of the aircraft that would be below a terrain elevation during flight based on the flight profile data and the terrain elevation data;

based on the obstacle region, a course of the aircraft is planned to avoid the obstacle region.

4. The method of claim 3, wherein the planning a course of the aircraft to avoid the obstacle region based on the obstacle region comprises:

Based on the obstacle region, planning a course of the aircraft using a hybrid a-algorithm or an artificial potential field method to avoid the obstacle region.

5. The method of claim 1, wherein the special scene comprises at least one of: take-off failure, route failure, cabin pressure relief, aircraft failure, and aircraft drift.

6. An aircraft routing system in a special scenario, comprising:

a prediction device configured to predict flight profile data of an aircraft according to weight, flight altitude and ambient temperature of the aircraft in a special scene;

obtaining means configured to obtain terrain elevation data around a predetermined course of the aircraft;

planning means configured to plan a course of the aircraft based on the flight profile data and the terrain elevation data.

7. The system of claim 6, wherein the predictive device comprises:

a measuring device configured to obtain an air pressure measured height using an air pressure gauge;

a correction device configured to correct the barometric altitude to the flying altitude according to an ambient temperature of the aircraft;

A first obtaining device configured to obtain planned profile data of an aircraft based on a fault profile curve table provided by a model manufacturer of the aircraft according to the weight and the flying height of the aircraft in a special scene;

and second obtaining means configured to obtain flight profile data of the aircraft based on the planned profile data according to the set flat flight duration and descent duration.

8. The system of claim 6, wherein the planning device comprises:

a determining device configured to determine an obstacle region of the aircraft that would be below a terrain elevation during flight based on the flight profile data and the terrain elevation data;

an avoidance device configured to plan a course of the aircraft to avoid the obstacle region based on the obstacle region.

9. The system of claim 8, wherein the avoidance device is configured to:

10. The system of claim 6, wherein the special scene comprises at least one of: take-off failure, route failure, cabin pressure relief, aircraft failure, and aircraft drift.

11. An electronic device, comprising:

a memory for storing instructions;

a processor for reading instructions in said memory and performing the method of any of claims 1-5.

12. A non-transitory storage medium having instructions stored thereon,

wherein the instructions, when read by a processor, cause the processor to perform the method of any of claims 1-5.