A method for designing a departure flight procedure in a terminal area considering noise reduction and emission reduction in coordination

Abstract

The application belongs to the technical field of traffic control, and particularly relates to a terminal area departure flight procedure design method considering noise reduction and emission reduction in coordination, and aims to solve the problem of insufficient consideration of environmental protection factors in current flight procedure design. The application comprises: taking the end of the runway in the departure direction of the target airport terminal area as the starting point, taking the flight limiting area and the noise sensitive area as the circling area, and generating the initial departure flight procedure of the target aircraft; based on the initial departure flight procedure, reading the matching target decision in the decision knowledge base; based on the noise value, fuel consumption and obstacle region height of each point in the terminal area, and in combination with the target decision, generating a plurality of segment departure flight procedures in sequence until the route connection is completed. The application can timely adjust the climb path of the aircraft, avoid the noise sensitive area and reduce the pollutant emission as much as possible, so as to achieve the purpose of multi-objective coordinated design of environmental protection elements and safety factors.

Description

Technical Field

[0001] This application belongs to the field of traffic control technology, and specifically relates to a method, device and equipment for designing departure flight procedures for terminal areas that consider noise reduction and emission reduction in a coordinated manner. Background Technology

[0002] Within the approach (terminal) controlled airspace, flight procedures are an important form of airspace resource utilization that can regulate aircraft flight activities and ensure aircraft flight safety.

[0003] With the rapid development of the civil aviation industry, the complexity of approach control airspace structure and traffic flow is increasing day by day, and flight procedures have a significant impact on the safety, economy and environmental benefits of aviation operations.

[0004] In recent years, airport environmental management has received increasing attention, with noise pollution and pollutant emissions becoming common environmental issues. Flight procedures, as a crucial operational resource in the airspace of an airport, not only need to ensure aircraft fly safely and orderly along prescribed routes but also significantly impact the economic and environmental efficiency of flight operations. However, current departure flight procedure designs often prioritize safety, neglecting the need for coordinated environmental considerations. Summary of the Invention

[0005] To address the aforementioned problems in existing technologies, namely the insufficient consideration of environmental factors in current flight procedure design, this application, in its first aspect, proposes a method for designing departure flight procedures in the terminal area that synergistically considers noise reduction and emission reduction, including:

[0006] Starting from the end of the departure runway in the terminal area of ​​the target airport, and using restricted flight areas and noise-sensitive areas as bypass areas, the initial departure flight procedure for the target aircraft is generated.

[0007] Based on the initial departure flight procedure, the matching target decision is read from the decision knowledge base. The decision knowledge base is constructed based on the decisions of the historical flight procedure. The historical flight procedure is determined by classifying multiple actual flight tracks in the target airport. The target decision is used to control flight data. The flight data includes at least flight altitude, flight speed, flight roll angle, fuel consumption value and engine thrust.

[0008] Based on the noise levels, fuel consumption, and obstacle heights at various points in the terminal area, and combined with target decisions, multiple departure flight procedures are generated sequentially until the route connection is completed.

[0009] As a preferred implementation method, the process of constructing a decision knowledge base includes:

[0010] Multiple flight tracks of different aircraft types at the target airport are obtained. The flight tracks are displayed on a geographic information system digital map according to latitude and longitude coordinates by reading data from the fast access recorder.

[0011] Based on aircraft type, flight time period, and flight origin and destination, the actual flight tracks are classified, and the average flight procedure for each category is determined;

[0012] Based on flight data of each average flight procedure at different geographical locations, predictive flight data is generated to serve as the basis for decision-making at the corresponding geographical locations.

[0013] The decision knowledge base consists of all decisions.

[0014] As a preferred implementation, predictive flight data is generated based on flight data from each average flight procedure at different geographical locations, including:

[0015] Based on the data characteristics of flight data, a corresponding neural network model is constructed for any flight data. The input of the neural network model is the impact data of any flight data, and the output is the predicted flight data of any flight data.

[0016] Predictive flight data for different geographical locations is generated using a neural network model.

[0017] As a preferred implementation method, the flight tracks are classified according to aircraft type, flight time period, and flight origin and destination, including:

[0018] The actual flight tracks are classified by using aircraft type and flight time period as identifiers, and by using the start and end points of the actual flight tracks as classification criteria. The actual flight tracks are classified by combining rapid dynamic time warping with hierarchical clustering.

[0019] As a preferred implementation, multiple departure flight procedures are generated sequentially, including:

[0020] If the noise value is lower than the noise threshold of the point and the difference between the obstacle area and the flight altitude included in the target decision meets the safety margin, the flight procedure determined by the target decision shall be used as the next departure flight procedure.

[0021] If the noise value is higher than or equal to the noise threshold of the location, the location is divided into a noise-sensitive area. The next departure flight procedure is generated by flying around the noise-sensitive area.

[0022] If the difference between the obstacle zone and the flight altitude included in the target decision is less than the safety margin, the next departure flight segment should be replanned.

[0023] As a preferred implementation, when there are multiple flight procedures determined by the target decision, the flight procedure with the shortest horizontal path is selected as the next departure flight procedure, wherein the flight procedure determined by the target decision passes through a preset mandatory point.

[0024] As a preferred embodiment, the process of obtaining the noise value includes:

[0025] Based on target decision-making, obtain the engine thrust of the target aircraft at each point;

[0026] Obtain the shortest distance between the noise-sensitive area and the track corresponding to the initial departure flight procedure;

[0027] Based on engine thrust and the closest distance, the noise level of the target aircraft at the location is determined.

[0028] As a preferred implementation, based on the initial departure flight procedure, a matching target decision is retrieved from the decision knowledge base, including:

[0029] Determine the geographical locations involved in the initial departure flight procedure under the preset length unit;

[0030] Retrieve target decisions that match geographical location from the decision knowledge base.

[0031] A second aspect of this application proposes a device for designing departure flight procedures that collaboratively considers noise reduction and emission reduction in the terminal area, comprising:

[0032] The initial design module is used to generate the initial departure flight procedure for the target aircraft, starting from the end of the departure runway in the departure direction of the target airport terminal area and using restricted flight areas and noise-sensitive areas as bypass areas.

[0033] The target decision matching module is used to read the matching target decision from the decision knowledge base based on the initial departure flight procedure. The decision knowledge base is constructed based on the decisions of the historical flight procedure. The historical flight procedure is determined by classifying multiple actual flight tracks in the target airport. The target decision is used to control flight data, which includes at least flight altitude, flight speed, flight roll angle, fuel consumption value and engine thrust.

[0034] The departure flight procedure design module is used to generate multiple departure flight procedures sequentially based on the noise value, fuel consumption value, and obstacle area height of each point in the terminal area, combined with target decisions, until the route connection is completed.

[0035] A third aspect of this application proposes an electronic device comprising:

[0036] At least one processor; and

[0037] A memory communicatively connected to at least one of the processors; wherein,

[0038] The memory stores instructions that can be executed by the processor to implement the aforementioned collaborative noise reduction and emission reduction terminal area departure flight procedure design method.

[0039] The beneficial effects of this application are:

[0040] By constructing a decision knowledge base, flight data for subsequent moments can be predicted based on historical flight procedures. This serves as the basis for flight procedure design. When flying around noise-sensitive areas, an initial departure flight procedure can be set to avoid noise from the source of aircraft departure. Then, based on noise values, fuel consumption values, and obstacle area heights during the flight procedure design process, combined with the target decisions predicted by the decision knowledge base, a continuous path is generated segment by segment to form a departure flight procedure. During the generation of the departure flight procedure, decisions can be made in real time, and the aircraft's climb path can be adjusted in a timely manner to avoid noise-sensitive areas while minimizing pollutant emissions. This achieves the goal of multi-objective collaborative design of environmental protection and safety factors, reduces the impact of noise and pollutants on the environment, and provides strong support for the prevention and control of noise and emissions pollution. Attached Figure Description

[0041] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0042] Figure 1 This is a flowchart of a method for designing a departure flight procedure in a terminal area that considers noise reduction and emission reduction, according to an embodiment of this application.

[0043] Figure 2 This is a rasterized example diagram provided in one embodiment of this application;

[0044] Figure 3 This is a logic block diagram of a device for designing a departure flight procedure in a terminal area that considers noise reduction and emission reduction, according to one embodiment of this application.

[0045] Figure 4 This is a schematic diagram of the structure of a computer system used to implement the methods, apparatus, and devices of this application. Detailed Implementation

[0046] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0047] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0048] This application provides a method for designing departure flight procedures in a terminal area that considers noise reduction and emission reduction. The method starts at the end of the departure runway in the departure direction of the target airport terminal area and uses restricted flight areas and noise-sensitive areas as bypass zones to generate an initial departure flight procedure for the target aircraft. Based on the initial departure flight procedure, matching target decisions are retrieved from a decision knowledge base. This decision knowledge base is constructed based on decisions from historical flight procedures, which are determined by classifying multiple actual flight paths in the target airport. Target decisions are used to control flight data, which includes at least flight altitude, flight speed, flight roll angle, fuel consumption, and engine thrust. Based on the noise levels, fuel consumption, and obstacle heights at various points in the terminal area, and in conjunction with the target decisions, multiple departure flight procedures are generated sequentially until the route connection is completed. By constructing a decision knowledge base, flight data for subsequent moments can be predicted based on historical flight procedures. This serves as the basis for flight procedure design. When flying around noise-sensitive areas, an initial departure flight procedure can be set to avoid noise from the source of aircraft departure. Then, based on the noise values ​​and obstacle area heights during the flight procedure design process, combined with the target decisions predicted by the decision knowledge base, a continuous path is generated segment by segment to form a departure flight procedure. During the generation of the departure flight procedure, decisions can be made in real time to adjust the aircraft's climb path in a timely manner to avoid noise-sensitive areas. This achieves the goal of multi-objective collaborative design of environmental protection and safety factors, reduces the impact of noise on the environment, and provides strong support for noise pollution prevention and control.

[0049] To more clearly explain the collaborative noise reduction and emission reduction end-zone departure flight procedure design method of this application, the following will combine... Figure 1 The steps in the embodiments of this application are described in detail.

[0050] The first embodiment of this application provides a method for designing a departure flight procedure in a terminal area that considers noise reduction and emission reduction in collaboration, including steps S10-S30, each of which is described in detail below:

[0051] Step S10: Starting from the end of the departure runway in the departure direction of the target airport terminal area, and using the restricted flight area and noise-sensitive area as the bypass area, the initial departure flight procedure of the target aircraft is generated.

[0052] Optionally, the airport terminal area is a specific controlled area designated around one or more busy airports, primarily used to coordinate aircraft approaches, departures, and transition flights to ensure safe and orderly takeoffs and landings. The end of the departure runway is the physical starting point of the departure procedure and a critical location where aircraft finish ground taxiing and enter the departure climb phase. The noise-sensitive area is the region surrounding the target airport (e.g., within 100 kilometers or the terminal area) where noise levels must be below a noise threshold, which is determined based on the specific scenario and could be, for example, 80 decibels.

[0053] It should be noted that the above-mentioned areas can be determined by obtaining geographical information around the target airport terminal area, such as points selected in previous years' airport monitoring or points with high noise sensitivity, such as schools and residential areas, which can be read on the map.

[0054] Furthermore, after determining the detour area, an initial departure flight procedure with an initial partial path can be generated through the flight procedure already designed for the target airport. Alternatively, the initial departure flight procedure with an initial partial path can be generated based on a decision knowledge base using the method of this application. For example, the detour area and restricted flight area of ​​the target airport terminal area can be used as the constraint area, the end of the departure direction runway can be used as the starting point, and the exit of the target airport departure corridor can be used as the ending point. The initial departure flight procedure can be generated by reading the decision corresponding to the geographical location in the decision knowledge base.

[0055] Step S20: Based on the initial departure flight procedure, read the matching target decision from the decision knowledge base. The decision knowledge base is constructed based on the decisions of the historical flight procedure. The historical flight procedure is determined by classifying multiple actual flight tracks in the target airport. The target decision is used to control flight data. The flight data includes at least flight altitude, flight speed, flight roll angle, fuel consumption value and engine thrust.

[0056] Optionally, after generating the initial departure flight procedure, the target aircraft departs and climbs according to the initial departure flight procedure, and obtains target decisions through the decision knowledge base as the basis for the next departure flight procedure.

[0057] In this embodiment of the application, the geographical locations involved in the initial departure flight procedure under a preset length unit are determined; and the target decision matching the geographical location is read from the decision knowledge base.

[0058] As an example, please see Figure 2 After removing restricted airspace, the entire process from the end of the departure runway to the departure corridor entrance is gridded into multiple points with 1 kilometer as the preset length unit. The geographical location corresponding to each grid position involved in the initial departure flight procedure is determined. Furthermore, the target decision matching the geographical location is read from the decision knowledge base.

[0059] Geographical location includes latitude, longitude, and altitude.

[0060] It should be noted that each decision in the decision knowledge base is based on flight data at various geographical locations predicted from historical flight procedures, which can guide the design of the next flight procedure.

[0061] As one possible implementation method, the process of constructing the decision knowledge base includes: acquiring multiple flight tracks of different aircraft types at the target airport, wherein the flight tracks are displayed on a geographic information system digital map according to latitude and longitude coordinates by reading data from the fast access recorder; classifying the flight tracks according to aircraft type, flight time period, and flight origin and destination, and determining the average flight procedure for each category; generating predicted flight data based on flight data of each average flight procedure at different geographical locations, as the basis for decision-making at the corresponding geographical locations; and forming a decision knowledge base from all the decisions.

[0062] In this embodiment of the application, to ensure sufficient data support for the analysis, during peak flight periods with high capacity in summer and winter, 12,000 Quick Access Recorder (QAR) records of the main aircraft type at the target airport were selected as the actual flight tracks. The QAR data includes aircraft type, flight time, latitude and longitude, altitude, ground speed, engine speed, roll angle, instantaneous fuel consumption, etc.

[0063] It should be noted that QAR data is time-series data at the second level. By reading the latitude and longitude in the QAR data, the horizontal trajectory of the actual flight path can be displayed on a Geographic Information System (GIS) digital map according to the latitude and longitude coordinates. For any latitude and longitude in the actual flight path, there are corresponding QAR data such as altitude, ground speed, and engine speed.

[0064] Furthermore, the actual flight tracks are identified by aircraft type and flight time period, and classified by the start and end points of the actual flight tracks. The actual flight tracks are classified by combining rapid dynamic time warping with hierarchical clustering.

[0065] Understandably, aircraft type and flight time can be used as identifiers to distinguish different flight tracks. By identifying the start and end points of flight tracks, similar flight paths can be identified and analyzed from a large number of flight tracks.

[0066] In some embodiments, the flight track data can be preprocessed, for example, by removing invalid data through data cleaning, smoothing jitter through filtering, unifying the dimensions of each flight data through normalization, and segmenting the track according to event nodes through key point extraction. Preprocessed data can make the clustering results more accurate.

[0067] Since the above preprocessing methods are all conventional techniques in the field of data processing, they will not be described in detail in this application.

[0068] Furthermore, the preprocessed flight data is processed using Fast Dynamic Event Warping (Fast-DTW) to calculate a similarity matrix of latitude and longitude distributions. The similarity matrix is ​​then filtered using preset track deviation values ​​to identify similar tracks. These track deviation values ​​can be set based on the degree of regularity in different directions.

[0069] Fast-DTW can solve the problem of local time offset caused by inconsistent track lengths or differences in pilot operating speed, thus quickly and accurately dividing similar tracks.

[0070] Furthermore, the tracks segmented by Fast-DTW are used to construct a clustering tree through hierarchical clustering, thereby building a multi-level track category system and automatically classifying the categories.

[0071] In some embodiments, the clustering tree can be pruned during multi-level clustering to improve clustering efficiency and enhance robustness.

[0072] By combining Fast-DTW and hierarchical clustering, and by combining local and global approaches, more intelligent track management can be achieved.

[0073] After clustering the actual flight tracks, the average flight procedure of each category is obtained as the representative track of the corresponding category.

[0074] Furthermore, based on the data characteristics of flight data from each average flight procedure at different geographical locations, a corresponding neural network model is constructed for any flight data. The input of the neural network model is the influence data of any flight data, and the output is the predicted flight data of any flight data. Predicted flight data at different geographical locations is generated through the neural network model.

[0075] When constructing a neural network model for each flight data, the input data includes aircraft type, departure and destination airports, flight time, geographic information, program type, and magnetic heading, and consists of multiple layers of neurons.

[0076] As one possible implementation, when the flight data is flight altitude, the corresponding data features also include barometric altitude, engine gear, and weight. The constructed neural network model can be a multilayer perceptron (MLP), trained using the mean squared error loss function.

[0077] In other embodiments, flight altitude decisions can also be obtained by constructing other network models, such as recurrent neural networks, that can perform data prediction based on hierarchical information processing.

[0078] As one possible implementation, when the flight data is flight speed, the corresponding data features also include vacuum speed, ground speed, wind speed, and flaps, and the constructed neural network model is a transformer model.

[0079] In other embodiments, a prediction tree can be constructed from the data features of flight speed using a random forest ensemble learning method, and the prediction results of the tree can be aggregated (i.e., the average of multiple regression results) to generate predicted flight speed data.

[0080] As one possible implementation, when the flight data is the flight roll angle, the corresponding data features also include flaps, vacuum speed, ground speed, barometric altitude, and weight. The constructed neural network is a backpropagation neural network (BP neural network), which is trained using the mean square error loss function.

[0081] In other embodiments, the decision on the flight roll angle can also be obtained by constructing other supervised learning models such as long short-term memory networks.

[0082] As one possible implementation, when the flight data is engine thrust, the corresponding data features also include engine operating status, engine gear, and throttle lever position. The constructed neural network is a fusion model of MLP and random forest, and the gradient of the loss function with respect to the network parameters is calculated through the backpropagation algorithm.

[0083] In other embodiments, engine thrust decisions can also be obtained by constructing other network models, such as gated loop units, that can perform data prediction based on phased information filtering and integration.

[0084] As one possible implementation, when the flight data is fuel consumption value, the corresponding data features also include engine operating status, aircraft weight, engine gear, and fuel flow. The output data is the instantaneous value of fuel consumption, and the constructed neural network is a recurrent neural network, which is trained using the mean squared error loss function.

[0085] In other embodiments, fuel consumption values ​​can also be determined using an MLP network model.

[0086] By constructing neural network models for data prediction based on various flight data, predicted flight data for different geographical locations is generated. The predicted flight data obtained from these models are then used as decisions for each geographical location, and all decisions constitute a decision knowledge base.

[0087] The decision knowledge base can learn the correlation between actual flight tracks and flight data based on prediction models of various flight data, obtain prediction results for different flight stages, and make decision recommendations for each geographical location.

[0088] Based on the geographical location of the initial departure flight procedure, a target decision matching it is selected from the decision knowledge base. The target decision includes the predicted flight data.

[0089] Step S30: Based on the noise value, fuel consumption value and obstacle area height of each point in the terminal area, and combined with target decision, multiple departure flight procedures are generated sequentially until the route connection is completed.

[0090] Optionally, without considering noise impact, fuel consumption value, and obstacle area, the departure flight procedure can be generated directly based on the target decision. In this embodiment, considering the impact of environmental factors on the surrounding area, it is necessary to calculate the noise value of each geographical location as a design factor for the departure flight procedure.

[0091] As one possible implementation method, the engine thrust of the target aircraft at each location is obtained based on the target decision; the shortest distance between the noise-sensitive area and the flight path corresponding to the initial departure flight procedure is obtained; and the noise value of the target aircraft at each location is determined based on the engine thrust and the shortest distance.

[0092] Understandably, target decision-making involves various flight data, including engine thrust. By reading the target decision, the engine thrust at the corresponding geographical location when the target aircraft passes through each point can be obtained.

[0093] Furthermore, the spatial index optimization method is used to calculate the shortest distance from the noise-sensitive area to the generated track. In this embodiment, the generated track is the initial departure flight procedure.

[0094] As an example, in this embodiment, a quadtree is used as a spatial index to calculate the nearest distance. The spatial index optimization method is a conventional technique and will not be described in detail in this embodiment.

[0095] Furthermore, by combining engine thrust and closest distance, approximate noise values ​​are extracted from the Noise-Power-Distance (NPD) database, and then the noise values ​​of the target aircraft at each point are obtained through interpolation.

[0096] Since the data in the NPD database are discrete points, it is not possible to directly read the real-time engine thrust and the noise value corresponding to the nearest distance. Therefore, discrete points with approximate data are selected for interpolation calculation to obtain the noise value of the target aircraft at each point.

[0097] As an example, when calculating the noise level of a target aircraft at 87% thrust and a minimum distance of 1200 meters to a certain point, the noise levels at 85% and 90% thrust at distances of 1000m and 1500m are extracted. The final noise level is calculated by first interpolating based on distance and then based on thrust, and can be determined using the following formula:

[0098]

[0099] Wherein, SEL represents the noise value to be calculated, SEL1 represents the noise value at a distance of 85% of the thrust from D1 (i.e., 1000 meters), D represents the closest distance between the target aircraft and a certain point (i.e., 1200 meters), and SEL2 represents the noise value at a distance of 90% of the thrust from D2 (i.e., 1500 meters).

[0100] As an example, in this embodiment of the application, after calculating the single noise value using the above formula, the equivalent sound level for day and night is calculated based on the flight time of the main aircraft type, with one week as a cycle. Weighted averages are then applied for day and night to determine the cumulative noise value at each location. If the cumulative noise value exceeds a certain noise threshold, the corresponding location is designated as a noise-sensitive area.

[0101] It should be noted that the calculation of the cumulative noise value is a conventional calculation method in the field of aircraft, and will not be described again in the embodiments of this application.

[0102] Furthermore, if the noise level is below the noise threshold of the location and the difference between the obstacle area and the flight altitude included in the target decision meets the safety margin, the flight procedure determined by the target decision is used as the next departure flight procedure; if the noise level is higher than or equal to the noise threshold of the location, the location is divided into a noise-sensitive area, and the next departure flight procedure is generated by flying around the noise-sensitive area; if the difference between the obstacle area and the flight altitude included in the target decision is lower than the safety margin, the next departure flight procedure is replanned.

[0103] In this application embodiment, the noise threshold is set based on the actual situation. For example, in a commercial area, the noise threshold can be set to 80 decibels, and in a residential area or school area, the noise threshold can be set to 65 decibels.

[0104] As one possible implementation, if the noise value is lower than the noise threshold of the point and the difference between the obstacle area and the flight altitude included in the target decision meets the safety margin, the result of the target decision will not cause noise impact and there is no safety hazard to the obstacle area. In this case, the flight procedure with the lowest fuel consumption can be selected from the flight procedures determined by the target decision as the next departure flight procedure.

[0105] It is understandable that there may be multiple flight procedures for determining the target. By selecting the flight procedure with the lowest fuel consumption, while avoiding noise, the flight procedure with the lowest pollutant emissions can be selected as the next departure flight procedure. This can satisfy both the noise reduction purpose and the emission reduction effect, taking multiple environmental factors into consideration in a coordinated manner to maximize the environmental protection effect.

[0106] It should be noted that the main aircraft type has different fuel consumption at different stages. For example, a certain flight route may be relatively long, but the fuel consumption is low because the flight is level. On the other hand, a flight segment with a shorter horizontal route but requiring continuous climb has a higher fuel consumption during the climb phase, even though the route is shorter. By selecting the flight procedure with the lowest fuel consumption, although it is not the flight procedure with the shortest horizontal path, it is possible to minimize the pollutant emissions during the flight phase, and further consider environmental factors.

[0107] In this embodiment, obstacles are categorized into straight-line obstacles, initial turning area obstacles, and turning area obstacles based on their location. The difference between the flight altitude and the obstacle altitude in the target decision is compared to determine whether it meets the safety margin, i.e., whether the altitude difference exceeds the preset safety margin.

[0108] As another possible implementation, if the noise value is higher than or equal to the noise threshold of the point, according to the design of the target decision, the noise during the aircraft's climb will affect the point. In this case, the point is divided into a noise-sensitive area, and the next departure flight procedure is generated by flying around the noise-sensitive area.

[0109] As an example, the process of bypassing noise-sensitive areas can be achieved by specifying the radiation range of noise-sensitive points during the pathfinding process using an improved Dijkstra algorithm. A two-dimensional optimization solution model is then established, with the restricted flight area and the locations of surrounding noise-sensitive points set as constraint areas. Horizontal and vertical safety margins are reserved for airspace obstacles. The solution path comprehensively judges the noise level of the noise-sensitive area and the distance of the flight path. Under the requirements of the restricted airspace, the horizontal path with the minimum fuel consumption that meets the safety margin and noise level requirements of sensitive points is selected. The start and end points of the next departure flight procedure are selected, and the mandatory reporting points that the flight procedure must pass through are set as mandatory points. Penalty values ​​are assigned to the noise-sensitive points in the area expanding outward from the center point according to their distance. With the flight procedure design criteria as an additional condition, the corresponding optimal decision path is generated under the condition of selecting different noise-sensitive points.

[0110] As another possible implementation, if the difference between the obstacle area and the flight altitude included in the target decision is less than the safety margin, the aircraft may face safety risks when flying over the obstacle area according to the design of the target decision. In this case, the obstacle overpass area is set as a clear obstacle with a safety margin, and the next departure flight procedure is replanned according to the above steps.

[0111] In this embodiment of the application, multiple departure flight procedures are generated at once according to the above steps. It should be noted that when generating the next departure flight procedure, the shortest distance calculated is the shortest distance between the point and all generated flight paths.

[0112] The departure flight procedure must follow the access route when it is designed. Therefore, the mandatory reporting points on the route must be passed. In other words, the flight procedure with the target decision must pass through the preset mandatory points.

[0113] Understandably, the target aircraft only needs to avoid noise during the climb phase. After the climb phase, the target aircraft's altitude will no longer be affected by noise, so there is no need to consider noise factors. The target decision is used as the guide to generate the departure flight procedure until the route connection is completed.

[0114] Although the steps in the above embodiments are described in the above order, those skilled in the art will understand that in order to achieve the effect of this embodiment, different steps do not need to be executed in such order. They can be executed simultaneously (in parallel) or in reverse order. These simple changes are all within the protection scope of this application.

[0115] Please see Figure 3 The second embodiment of this application provides a collaborative noise reduction and emission reduction terminal area departure flight procedure design device, which includes: an initial design module 100, a target decision matching module 200, and a departure flight procedure design module 300.

[0116] The initial design module 100 is used to generate the initial departure flight procedure of the target aircraft, starting from the end of the departure direction runway in the terminal area of ​​the target airport and using the restricted flight area and the noise-sensitive area as the bypass area.

[0117] The target decision matching module 200 is used to read the matching target decision from the decision knowledge base based on the initial departure flight procedure. The decision knowledge base is constructed based on the decision of the historical flight procedure. The historical flight procedure is determined by classifying multiple actual flight tracks in the target airport. The target decision is used to control flight data. The flight data includes at least flight altitude, flight speed, flight roll angle, fuel consumption and engine thrust.

[0118] The departure flight procedure design module 300 is used to generate multiple departure flight procedures sequentially based on the noise value, fuel consumption and obstacle area height of each point in the terminal area, combined with target decision, until the route connection is completed.

[0119] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the system described above can be found in the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0120] It should be noted that the above-described embodiment of the collaborative noise reduction and emission reduction terminal area departure flight procedure design device is merely an example of the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of this application can be further decomposed or combined. For example, the modules in the above embodiments can be merged into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of this application are merely for distinguishing the various modules or steps and are not considered as an improper limitation of this application.

[0121] An electronic device according to a third embodiment of this application includes:

[0122] At least one processor; and

[0123] A memory communicatively connected to at least one of the processors; wherein,

[0124] The memory stores instructions that can be executed by the processor to implement the aforementioned collaborative noise reduction and emission reduction terminal area departure flight procedure design method.

[0125] A computer-readable storage medium according to a fourth embodiment of this application stores computer instructions, which are executed by the computer to implement the above-described collaborative noise reduction and emission reduction terminal area departure flight procedure design method.

[0126] A computer program product according to the fifth embodiment of this application, when run on an electronic device, causes the electronic device to execute the above-described collaborative noise reduction and emission reduction terminal area departure flight procedure design method.

[0127] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes and related descriptions of the electronic devices, computer-readable storage media, and computer program products described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0128] Those skilled in the art will recognize that the modules and method steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. The programs corresponding to the software modules and method steps can be placed in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art. To clearly illustrate the interchangeability of electronic hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0129] The following is for reference. Figure 4 It shows a schematic diagram of the structure of a computer system for implementing the methods, systems, and devices of this application. Figure 4 The server shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0130] like Figure 4 As shown, the computer system includes a Central Processing Unit (CPU) 401, which can perform various appropriate actions and processes based on programs stored in Read Only Memory (ROM) 402 or programs loaded from storage section 408 into Random Access Memory (RAM) 403. RAM 403 also stores various programs and data required for system operation. The CPU 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0131] The following components are connected to I / O interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to I / O interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 410 as needed so that computer programs read from it can be installed into storage section 408 as needed.

[0132] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit (CPU) 401, it performs the functions defined in the methods of this application. It should be noted that the computer-readable medium described above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on a computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0133] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0134] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0135] The terms “first”, “second”, etc., are used to distinguish similar objects, not to describe or indicate a specific order or sequence.

[0136] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent in such process, method, article, or apparatus / device.

[0137] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.

Claims

1. A method for designing departure flight procedures that collaboratively consider noise reduction and emission reduction in the terminal area, characterized in that, include: Starting from the end of the departure runway in the terminal area of ​​the target airport, and using restricted flight areas and noise-sensitive areas as bypass areas, the initial departure flight procedure for the target aircraft is generated. Based on the initial departure flight procedure, a matching target decision is read from the decision knowledge base, wherein the decision knowledge base is constructed based on the decisions of historical flight procedures, which are determined by classifying multiple actual flight tracks in the target airport, and the target decision is used to control flight data, wherein the flight data includes at least flight altitude, flight speed, flight roll angle, fuel consumption value and engine thrust; Based on the noise level, fuel consumption, and obstacle height at each point in the terminal area, and in conjunction with the target decision, multiple departure flight procedures are generated sequentially until the route connection is completed. The sequential generation of multiple departure flight procedures includes: If the noise value is lower than the noise threshold of the location, and the difference between the obstacle area and the flight altitude included in the target decision meets the safety margin, the flight procedure with the lowest fuel consumption value is selected as the next departure flight procedure from the flight procedures determined by the target decision. If the noise value is higher than or equal to the noise threshold of the location, the location is divided into a noise-sensitive area, and the next departure flight procedure is generated by flying around the noise-sensitive area. If the difference between the obstacle area and the flight altitude included in the target decision is less than the safety margin, the next departure flight segment will be replanned.

2. The method for designing a departure flight procedure in the terminal area that collaboratively considers noise reduction and emission reduction, as described in claim 1, is characterized in that... The process of constructing the decision knowledge base includes: Multiple flight tracks of different aircraft types at the target airport are obtained, wherein the flight tracks are displayed on a geographic information system digital map according to latitude and longitude coordinates by reading data from the fast access recorder. Based on the aircraft type, flight time period, and flight origin and destination, the actual flight tracks are classified, and the average flight procedure for each category is determined; Based on flight data of each average flight procedure at different geographical locations, predictive flight data is generated to serve as the basis for decision-making at the corresponding geographical locations. The decision knowledge base consists of all decisions.

3. The method for designing a departure flight procedure in the terminal area that collaboratively considers noise reduction and emission reduction, as described in claim 2, is characterized in that... The generation of predicted flight data based on flight data from various average flight procedures at different geographical locations includes: Based on the data characteristics of flight data, a corresponding neural network model is constructed for any flight data, wherein the input of the neural network model is the influence data of any flight data, and the output is the predicted flight data of any flight data; The neural network model generates predicted flight data for different geographical locations.

4. The method for designing a departure flight procedure in the terminal area that collaboratively considers noise reduction and emission reduction, as described in claim 2, is characterized in that... The classification of the actual flight tracks based on aircraft type, flight time period, and flight origin and destination includes: The actual flight track is identified by the aircraft type and the flight time period, and classified by the start and end points of the actual flight track. The actual flight track is classified by combining rapid dynamic time warping with hierarchical clustering.

5. The method for designing a departure flight procedure in the terminal area that collaboratively considers noise reduction and emission reduction, as described in claim 1, is characterized in that... The flight procedure determined by the target decision passes through a pre-set mandatory point.

6. The method for designing a departure flight procedure in the terminal area that collaboratively considers noise reduction and emission reduction, as described in claim 1, is characterized in that... The process of obtaining the noise value includes: Based on the target decision, the engine thrust of the target aircraft at each point is obtained; Obtain the closest distance between the noise-sensitive region and the flight path corresponding to the initial departure flight procedure; Based on the engine thrust and the nearest distance, the noise level of the target aircraft at that location is determined.

7. The method for designing a departure flight procedure in the terminal area that collaboratively considers noise reduction and emission reduction, as described in claim 1, is characterized in that... The step of retrieving a matching target decision from the decision knowledge base based on the initial departure flight procedure includes: Determine the geographical locations involved in the initial departure flight procedure under the preset length unit; From the decision knowledge base, retrieve the target decision that matches the geographical location.

8. A device for designing departure flight procedures that collaboratively considers noise reduction and emission reduction in the terminal area, characterized in that, include: The initial design module is used to generate the initial departure flight procedure for the target aircraft, starting from the end of the departure runway in the departure direction of the target airport terminal area and using restricted flight areas and noise-sensitive areas as bypass areas. The target decision matching module is used to read the matching target decision from the decision knowledge base based on the initial departure flight procedure. The decision knowledge base is constructed based on the decisions of historical flight procedures. The historical flight procedures are determined by classifying multiple actual flight tracks in the target airport. The target decision is used to control flight data. The flight data includes at least flight altitude, flight speed, flight roll angle, fuel consumption value and engine thrust. The departure flight procedure design module is used to generate multiple departure flight procedures sequentially based on the noise value, fuel consumption value and obstacle area height of each point in the terminal area, combined with the target decision, until the route connection is completed. The sequential generation of multiple departure flight procedures includes: If the noise value is lower than the noise threshold of the location, and the difference between the obstacle area and the flight altitude included in the target decision meets the safety margin, the flight procedure with the lowest fuel consumption value is selected as the next departure flight procedure from the flight procedures determined by the target decision. If the noise value is higher than or equal to the noise threshold of the location, the location is divided into a noise-sensitive area, and the next departure flight procedure is generated by flying around the noise-sensitive area. If the difference between the obstacle area and the flight altitude included in the target decision is less than the safety margin, the next departure flight segment will be replanned.

9. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to at least one of the processors; wherein, The memory stores instructions that can be executed by the processor to implement the collaborative noise reduction and emission reduction terminal area departure flight procedure design method according to any one of claims 1-7.

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