A method and device for switching a control architecture of an urban air mobility system

Abstract

The application discloses a city air traffic system control architecture switching method and device, relates to the technical field of system engineering and automatic control, and is based on an adaptive architecture switching control model constructed based on adaptive control theory and fuzzy logic control. Based on state variable values and performance index values of the system, the adaptive architecture switching control model is used to switch the type of the city air traffic control system architecture and the corresponding model structure in real time, so that the operation efficiency of the city air traffic system can be effectively improved, and the loss caused by the safety risk can be reduced. The application designs three types of city air traffic control system architectures for the city air traffic system, can meet the command and control requirements of different scenes, and provides a reference for the design of the city air traffic system control architecture.

Description

Technical Field

[0001] The present application relates to the field of system engineering and automatic control technology, and in particular to a method and device for switching the control architecture of an urban air traffic system based on adaptive control. Background Art

[0002] Urban air mobility (UAM) is an innovative way to achieve air travel within and between cities through new aviation technologies, such as electric vertical take-off and landing (eVTOL) vehicles. This system can effectively alleviate ground traffic congestion and improve urban transportation efficiency. Because UAM systems operate within urban areas, they face stricter efficiency and safety requirements than traditional civil aviation and general aviation systems. In terms of efficiency, UAM systems must handle a massive volume of flight requests and provide passenger and logistics services to tens of thousands of urban residents. A study based on population and traffic data from 1,200 cities worldwide suggests that by 2050, there will be 160,000 passenger-carrying unmanned aerial vehicles (UAVs) serving urban transportation worldwide, generating $90 billion in annual revenue. Furthermore, international research institutions have estimated that under a best-case (unconstrained) scenario, the potential demand for air taxis and airport shuttles is 11 million daily trips (accounting for 20% of all daily work trips in the United States). In terms of safety, the huge passenger volume of urban air traffic in the future may bring more safety hazards. At the same time, the urban environment is more complex. For example, as the pressure gradient, surface friction and air density decrease, the wind speed increases with altitude. The higher wind speed in the city makes the take-off and landing operations of aircraft more difficult and dangerous. In addition, buildings will block the wireless signals required for urban air traffic operations, including navigation and most forms of surveillance communications. These will further increase the operational safety risks of the system.

[0003] However, the existing aviation system control architecture is unable to fully cope with the above two challenges. A single architecture is unable to meet the needs of urban air traffic scenarios. Therefore, it is necessary to design a flexible architecture switching method that can quickly switch the architecture operation mode according to the needs of different scenarios. Summary of the Invention

[0004] The purpose of this application is to provide a method and device for switching the control architecture of an urban air traffic system, which can utilize an adaptive architecture switching control model to autonomously switch the control architecture type of the urban air traffic system according to internal and external risk situations and different scenario requirements, thereby improving the operating efficiency and system safety level of the urban air traffic system.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for switching a control architecture of an urban air traffic system, comprising:

[0007] Obtain the state variable values ​​and performance index values ​​of the urban air traffic control system at the current stage, where the state variables are used to reflect the system status; the performance indexes are used to reflect the system capabilities;

[0008] determining a state variable error based on the state variable value and the state variable expected value;

[0009] Determining a performance indicator error based on the performance indicator value and the performance indicator expected value;

[0010] The state variable error and the performance indicator error are used as inputs, and an adaptive architecture switching control model is used to output the optimal type and adjustment plan of the urban air traffic control system architecture, wherein the adaptive architecture switching control model includes an architecture switching fuzzy rule base and architecture control variables, the architecture switching fuzzy rule base includes a rule set, each rule in the rule set includes a condition and a corresponding result, the condition is a condition determined according to the state variable and the performance indicator, and the corresponding result represents the type of the urban air traffic control system architecture corresponding to the condition; the architecture control variable includes a type variable and an edge relationship variable, the type variable is used to represent the type of the urban air traffic control system architecture, and the edge relationship variable is used to represent whether edges are established between elements in the model of the urban air traffic control system architecture; the types of the urban air traffic control system architecture include a centralized urban air traffic control system architecture, a distributed urban air traffic control system architecture, and a semi-distributed urban air traffic control system architecture;

[0011] According to the adjustment plan, the model structure of the urban air traffic control system architecture in the previous stage is adjusted accordingly.

[0012] In a second aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the urban air traffic system control architecture switching method described in the first aspect above.

[0013] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the urban air traffic system control architecture switching method described in the first aspect above.

[0014] In a fourth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the urban air traffic system control architecture switching method described in the first aspect above.

[0015] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0016] The present application provides a method and device for switching the control architecture of an urban air traffic system. The method is based on an adaptive architecture switching control model constructed based on adaptive control theory and fuzzy logic control, and based on the state variable values ​​and performance index values ​​of the system, utilizes the adaptive architecture switching control model to switch the type of urban air traffic control system architecture and the corresponding model structure in real time, which can effectively improve the operating efficiency of the urban air traffic system and reduce the losses caused by safety risks. The present application designs three types of urban air traffic control system architectures for the urban air traffic system, which can meet the command and control requirements of different scenarios and provide a reference for the design of the control architecture of the urban air traffic system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 This is an application environment diagram of a method for switching the control architecture of an urban air traffic system in Example 1 of the present application;

[0019] Figure 2 A flowchart of a method for switching the control architecture of an urban air traffic system provided in Example 1 of the present application;

[0020] Figure 3 This is a schematic diagram of the structure of the centralized urban air traffic control system architecture model in Example 1 of the present application;

[0021] Figure 4 This is a schematic diagram of the structure of the distributed urban air traffic control system architecture model in Example 1 of the present application;

[0022] Figure 5 This is a structural diagram of the semi-distributed urban air traffic control system architecture model in Example 1 of the present application;

[0023] Figure 6 This is a flowchart of the process of building an adaptive architecture switching control model in Example 1 of the present application;

[0024] Figure 7 A schematic diagram of the structure of a computer device provided in Example 2 of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0026] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0027] Example 1

[0028] The urban air traffic system control architecture switching method and device provided in the embodiments of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the state variable values ​​and performance index values ​​of the current stage of the urban air traffic control system to be processed to the server 104. After receiving the state variable values ​​and performance index values, the server 104 determines the state variable error based on the state variable value and the expected value of the state variable; determines the performance index error based on the performance index value and the expected value of the performance index; uses the state variable error and the performance index error as input, and uses the adaptive architecture switching control model to output the optimal type and adjustment plan of the urban air traffic control system architecture. The server 104 can feedback the obtained optimal type and adjustment plan of the urban air traffic control system architecture to the terminal 102. In addition, in some embodiments, the urban air traffic system control architecture switching method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly use the urban air traffic system control architecture switching method to process the state variable values ​​and performance indicator values ​​to be processed, or the server 104 can obtain the state variable values ​​and performance indicator values ​​to be processed from the data storage system and use the urban air traffic system control architecture switching method to process them.

[0029] Terminal 102 may include, but is not limited to, various desktop computers, laptops, smartphones, tablet computers, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, and smart car devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Server 104 may be implemented as a standalone server or a server cluster consisting of multiple servers, or may be a cloud server.

[0030] The traditional civil aviation system utilizes a centralized control architecture, where all aircraft follow flight plans and control instructions provided by airports, regional air traffic control, and airlines. This architecture maintains extremely high safety levels. For example, the 2023 Global Commercial Aviation Safety Report shows a global commercial civil aviation accident rate of 0.8 accidents per million flights. However, this high level of safety comes with a side effect: overburdened central command and control units, leading to inefficiencies and high delays. Data shows that in 2023, over 45% of flights in the United States were delayed. Another typical aviation control architecture is the distributed control architecture of the general aviation system. This architecture is primarily based on manual control. Regional flight service stations independently control helicopters and drones within their area, without a clear central command and control unit. This distributed architecture, lacking layered safety audits and high-level dispatch and control, results in lower safety levels. For example, from 2012 to 2021, there were 12,368 non-fatal accidents and 2,269 fatal accidents worldwide. However, due to its more flexible operations, flight service efficiency is higher. Data shows that the US general aviation system boasts over 26 million flight hours annually. It can be seen that these system control architectures each have their own advantages, but a single architecture is difficult to meet the needs of urban air traffic scenarios. Therefore, it is necessary to design a flexible architecture switching method that can quickly switch the architecture operation mode according to the requirements of different scenarios.

[0031] To address the above issues, this embodiment proposes an effective method for switching the urban air traffic system architecture. By considering the performance and safety requirements of different urban air traffic scenarios, three typical urban air traffic system control architectures are designed. Based on these architectures, an adaptive architecture switching control model is constructed. This method can autonomously switch the urban air traffic system control architecture based on internal and external risk situations, and adaptively adjust the control model parameters to ensure optimal control results, thereby improving the operational efficiency and system safety level of the urban air traffic system.

[0032] In an exemplary embodiment, a method for switching the control architecture of an urban air traffic system is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the process, including the following steps 201 to 208.

[0033] Step 201: Obtain state variable values ​​and performance index values ​​of the urban air traffic control system at the current stage, wherein the state variables are used to reflect the system state; and the performance indexes are used to reflect the system capability.

[0034] Step 202: Determine a state variable error based on the state variable value and the state variable expected value.

[0035] Step 203: Determine a performance indicator error according to the performance indicator value and the performance indicator expected value.

[0036] Step 204: Using the state variable error and the performance indicator error as input, an adaptive architecture switching control model is used to output an optimal urban air traffic control system architecture type and adjustment plan. The adaptive architecture switching control model includes an architecture switching fuzzy rule base and architecture control variables. The architecture switching fuzzy rule base includes a rule set. Each rule in the rule set includes a condition and a corresponding result. The condition is determined based on the state variable and the performance indicator, and the corresponding result represents the type of urban air traffic control system architecture corresponding to the condition. The architecture control variable includes a type variable and an edge relationship variable. The type variable is used to represent the type of the urban air traffic control system architecture. The edge relationship variable is used to represent whether edges are established between elements in the urban air traffic control system architecture model. The types of urban air traffic control system architectures include centralized urban air traffic control system architectures, distributed urban air traffic control system architectures, and semi-distributed urban air traffic control system architectures.

[0037] Step 205 : adjusting the model structure of the urban air traffic control system architecture of the previous stage according to the adjustment plan.

[0038] This embodiment considers the safety and efficiency requirements of UAM operations and designs three typical UAM control architectures: centralized, distributed, and semi-distributed. Based on adaptive control theory, an adaptive architecture switching control model is then established. This model can autonomously switch the UAM control architecture based on internal and external risk dynamics and the capabilities of different architecture types. This approach considers the capabilities and characteristics of different control architectures, as well as the adaptability and resilience of the UAM system in uncertain operating environments. It can effectively improve the operational efficiency of the UAM system and reduce the losses caused by safety risks.

[0039] In order to make those skilled in the art more clear about the specific implementation process of the urban air traffic system control architecture switching method provided by this embodiment, a specific explanation is given below.

[0040] This embodiment provides a method for switching the control architecture of an urban air traffic system. Figure 2 As shown, specifically including:

[0041] Step A: Design different types of urban air traffic control architectures.

[0042] Designing different types of UAT system architectures involves analyzing the components and interactions within the UAT system and designing three types of UAT system architecture models: centralized, distributed, and semi-distributed. This step A includes the following four steps:

[0043] Starting from the requirements of the urban air traffic system's airspace management, operational services, safety supervision, air transport, communications, navigation, and surveillance capabilities, we analyze the systems or subsystems required to support different capabilities and form a set of system components. The elements of this scenario include: 1) a national safety brain (including the national air traffic control system, the central service platform of manned service operator A, and the national safety supervision system); 2) edge management centers in Regions 1, 2, and 3 (including the provincial air traffic control system, provincial operational management platform, and airports within each region); 3) N aircraft; and 4) various infrastructure, including M meteorological sensors, R navigation satellites, S surveillance radars, T surveillance cameras, U navigation base stations, V communications satellites, W 5G communication base stations, and third-party data service providers. Based on this, we analyze the possible interactions between these elements and form a set of relationships between them. Table 1 shows some of the relationships in this set.

[0044] Table 1 Schematic diagram of some relations in the relation set

[0045] Feature name Feature name relation Regional Operators Regional Air Traffic Control Flight plan submission Regional Operators Regional Air Traffic Control Risk information reporting Regional Air Traffic Control Regional Operators Risk management plan issued Regional Air Traffic Control Regional Operators Flight plan approval … … …

[0046] Step A2: Design a centralized urban air traffic control system architecture model.

[0047] First, based on the characteristics of centralized command and control, the interaction relationship between elements in different levels of the system and between different levels is designed. Then, the centralized control process of the urban air traffic system is designed. Finally, based on complex network theory, the established system architecture is modeled as a centralized urban air traffic control system architecture super network model. In the super network, the elements and interaction relationships in different levels correspond to the network nodes and edges of the corresponding levels respectively, and the interaction relationships between elements at different levels correspond to the coupling edges between networks at different levels, such as Figure 3The centralized urban air traffic control system architecture model shown in Figure 2 is shown. The "layer" here refers to the decision-making level of the urban air traffic control system architecture, which is divided into three layers: cloud, edge, and end. In a centralized architecture, cloud elements reside in central cloud servers or server clusters, receiving data on regional risk status and operational indicators, and making decisions on macro-level airspace management, traffic control, safety assessments, and operational scheduling. Examples include the national air traffic control system and the national urban air traffic operation management center platform. Edge elements reside in edge cloud servers or server clusters in specific regions, sharing regional risk status and operational indicator data and making decisions on operational planning, airport operations, plan approval, route planning, and emergency management within a specific region. Examples include a provincial air traffic control system, regional operators, and airports. End elements are various manned and unmanned aircraft, which fly only under instructions from edge elements.

[0048] Among them, the so-called "centralized command and control" means that in the urban air traffic control system, various types of aircraft at the end level are centrally commanded by the edge-level management system, and there is no collaboration between the aircraft.

[0049] Step A3: Design a distributed urban air traffic control system architecture model.

[0050] First, based on the characteristics of distributed command and control, the interaction relationship between elements in different levels of the system and between different levels is designed. Then, the distributed control process of the urban air traffic system is designed. Finally, based on the complex network theory, the established system architecture is modeled as a distributed urban air traffic control system architecture super network model, such as Figure 4 The distributed urban air traffic control system architecture model shown in Figure 2 is shown. In a distributed architecture, cloud-based elements no longer manage or control edge elements. Edge elements no longer exchange information or collaborate, but instead receive data from aircraft in their area and provide basic information support, such as weather, terrain, and flight intelligence. Aircraft on the edge communicate via the communication network, exchanging flight plans, route information, and flight intelligence, and developing and adjusting flight plans and routes.

[0051] Among them, the so-called "distributed command and control" means that in the urban air traffic control system, the cloud-level and edge-level systems no longer directly command and control aircraft. Aircraft collaborate through information sharing, and aircraft formulate and adjust flight plans and routes themselves.

[0052] Step A4: Design a semi-distributed urban air traffic control system architecture model.

[0053] First, based on the characteristics of semi-distributed command and control, the interaction relationship between elements in different levels of the system and between different levels is designed. Then, the semi-distributed control process of the urban air traffic system is designed. Finally, based on complex network theory, the established system architecture is modeled as a semi-distributed urban air traffic control system architecture super network model, such as Figure 5 The semi-distributed urban air traffic control system architecture model shown in Figure 1 is shown in Figure 2. In a semi-distributed architecture, cloud-based elements do not manage or control edge elements. Edge elements can exchange information and collaborate with each other. At the same time, some edge-level elements command a small number of aircraft in their respective areas, providing them with basic information, flight plans, and routes. Some aircraft on the end upload flight status, flight intelligence, and risk status to edge elements, while receiving flight plans and routes issued by the edges. Other aircraft do not interact with edge elements, but only share information and collaborate with each other, independently developing and adjusting flight plans and routes.

[0054] Among them, the "semi-distributed command and control" is a form of command and control between "centralized command and control" and "distributed command and control". It means that in the urban air traffic control system, the systems at the cloud level do not perform command and control, and some systems at the edge level directly command and control some aircraft. A small number of aircraft accept the command of the edge and pass the command and control information to other aircraft. Other aircraft formulate and adjust their flight plans and routes based on the information.

[0055] Step B: Construct an adaptive architecture switching control model.

[0056] Constructing an adaptive architecture switching control model, which specifically means: according to the three types of system architecture super network models designed in step A, determine the state variables and performance indicators that need to be paid attention to in the system, and construct an architecture switching control model that can switch the architecture type according to the changes in state variables and performance indicators, and adjust the structure of the architecture super network. Figure 6 As shown, the specific implementation of step B includes the following four steps:

[0057] Step B1: Determine the state variables in the system according to scenario requirements.

[0058] From the system architecture hypernetwork model, select elements that are highly relevant to scenario requirements and design their state variables, such as aircraft flight health levels, maximum aircraft density within each airspace, and weather conditions. The system's state variables reflect the state of the system at any given moment. Changes in these state variables immediately reflect changes in the system's state, making them a useful control basis in scenarios requiring high real-time control.

[0059] Step B2: Determine system performance indicators based on scenario requirements.

[0060] According to the scene requirements, analyze the system capacity corresponding to the demand, and design and select the index that can quantitatively evaluate the system capacity according to the system capacity, such as the request satisfaction rate, the average flight time, etc. can be selected as the index in the urban air passenger transport scene.

[0061] Step B3: Constructing the architecture control variable.

[0062] The architecture control variable is the edge relationship of the urban air traffic control architecture type and the architecture super network model, wherein the urban air traffic control architecture type X is an integer variable with a value of 1-3, respectively corresponding to "centralized", "distributed" and "semi-distributed" architecture, and the edge relationship of the architecture super network model is an adjacency matrix E between elements, wherein each element e ij is an integer variable of 0-1, and if it is 1, it represents that there is an interaction relationship (control or information interaction) between the elements, and if it is 0, there is no interaction relationship.

[0063] Step B4: Fuzzy processing of the error of the state variable and the error value of the performance index.

[0064] According to the fuzzy theory, the error level membership function of each state variable and the index error is set, and the error value range is fuzzy processed. The membership function is used to describe the degree of error value belonging to a certain error level, and the independent variable of the membership function is the accurate error value, and the dependent variable is the degree of error value belonging to the error level. Error refers to the difference between the current actual value (measured value) and the expected value (target value). For example, the error of the maximum aircraft density in the airspace can be divided into five levels: negative large, negative small, zero, positive small and positive large, which respectively correspond to less than 10 aircraft per cubic kilometer than the expected value, 5-10 aircraft per cubic kilometer than the expected value, 0-5 aircraft per cubic kilometer than the expected value, 5-10 aircraft per cubic kilometer than the expected value, and more than 10 aircraft per cubic kilometer than the expected value. If the current error is 15 more than the expected value, the membership degree of the positive large level is the highest, and it belongs to the positive large. In practical application, the specific level division rule can be determined according to the scene requirements and expert experience.

[0065] Step B5: Establishing the architecture switching fuzzy rule base.

[0066] According to the expert experience, the fuzzy rule base is established, and each rule in the rule set is represented in the form of "if-then". For example, one of the rules is that if the maximum aircraft density in the airspace is positive large and the weather condition is extremely poor, then switch to the centralized control architecture. The specific setting of the fuzzy rule can be determined according to the scene requirements and expert experience.

[0067] Step B6: Inference of the architecture type according to the fuzzy rule base.

[0068] According to the error level of the input state variable and the error level of the performance index value, the fuzzy rules are queried by substituting all the fuzzy rules, and if there is a rule that meets the condition, the corresponding switching result is output.

[0069] Step B7: Adjust the structure of the architecture super network.

[0070] According to the switched architecture type, the edges of the super network are adjusted. If the switched architecture is centralized, edges are constructed between all cloud-level elements and edge-level elements in the super network, and edges are constructed between all edge-level elements and aircraft elements (i.e., end-level) in the corresponding region, the corresponding elements in the adjacency matrix E are set to 1, and the edges between all aircraft elements are disconnected, the corresponding elements in the adjacency matrix E are set to 0; if the switched architecture is distributed, all cloud-level elements and edge-level elements in the super network are disconnected, all edge-level elements and aircraft elements in the corresponding region are disconnected, the corresponding elements in the adjacency matrix E are set to 0, and all aircraft elements establish edges with aircraft within their communication range, the corresponding elements in the adjacency matrix E are set to 1; if the switched architecture is semi-distributed, all cloud-level elements and edge-level elements in the super network are disconnected, the corresponding elements in the adjacency matrix E are set to 0, and the adjustment of other edges can be modeled as a network structure optimization problem, which can be solved by designing a target function according to the scene requirements and using an optimization algorithm.

[0071] Step B8: Self-adaptively adjust the membership function parameter of the error level according to the performance index error threshold.

[0072] Set the error threshold of each performance index i as Q i , if the error of any performance index exceeds the threshold, use the standard genetic algorithm to optimize the error level of all state variables and the membership function parameter value of the performance index error level, the goal is to minimize the error value of the performance index, each individual in the algorithm represents a set of membership function parameters, the iteration number is T, and the final output is the adjusted membership function parameter value.

[0073] Step C: Switch the optimal architecture according to the risk situation and the operation index.

[0074] Switching the optimal architecture according to the risk situation and the operation index, which specifically means: obtaining the current state variable data of the system through radar, weather sensor, satellite, aircraft state sensor and other sensing devices, and calculating the current performance index value according to operator data and safety monitoring data, comparing the state variable and the performance index value with their expected values to obtain error values and inputting them into the architecture switching control model described in step B to calculate the switching architecture type and adjust the structure of the architecture super network.

[0075] The embodiment has the following beneficial effects:

[0076] 1) This embodiment designs three types of control architectures for urban air traffic systems, which can meet the command and control requirements of different scenarios and provide a reference for the design of urban air traffic system control architectures;

[0077] 2) This embodiment uses a hypernetwork model to model the system control architecture, effectively characterizing the interactions between elements within and between different layers of the urban air traffic system. It also provides a quantitative calculation model foundation for adjusting the system control architecture.

[0078] 3) Once the traditional aviation system control architecture is put into use, it will not change. It is difficult to adaptively adjust the architecture according to changes in scenarios and give full play to the respective advantages of different architectures. The architecture switching control model proposed in this embodiment based on adaptive control theory and fuzzy logic control can switch the system control architecture type and specific structure in real time according to system state variables and performance indicator values. At the same time, it can adaptively adjust the control model parameters, which can effectively improve the operating efficiency of the urban air traffic system and reduce the losses caused by safety risks.

[0079] In summary, this adaptive control-based urban air traffic system control architecture switching method can improve the flexibility of system control in practice and provide good support for the management and control of the urban air traffic system.

[0080] This application also provides an application scenario that utilizes the aforementioned urban air traffic system control architecture switching method. Specifically, the urban air traffic system control architecture switching method provided in this embodiment can be applied in air traffic operations scenarios. Air traffic operations scenarios include content data processing, flight scheduling, and real-time monitoring. The urban air traffic system control architecture switching method provided in this embodiment is a key step in the flight scheduling process.

[0081] Example 2

[0082] This embodiment provides a computer device, which can be a server or a terminal. Its internal structure diagram can be as follows: Figure 7As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store any data in the urban air traffic system control architecture switching method. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements the urban air traffic system control architecture switching method provided in Example 1.

[0083] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0084] Example 3

[0085] This embodiment provides a computer device including a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the urban air traffic system control architecture switching method provided in Example 1 is implemented.

[0086] Example 4

[0087] This embodiment provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method for switching the urban air traffic system control architecture provided in Example 1 is implemented.

[0088] Example 5

[0089] This embodiment provides a computer program product, including a computer program. When the computer program is executed by a processor, the urban air traffic system control architecture switching method provided in Example 1 is implemented.

[0090] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0091] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0092] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0093] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0094] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for switching control architecture of an urban air traffic system, characterized in that: The urban air traffic system control architecture switching method includes: Obtain the state variable values ​​and performance index values ​​of the urban air traffic control system at the current stage, where the state variables are used to reflect the system status; the performance indexes are used to reflect the system capabilities; determining a state variable error based on the state variable value and the state variable expected value; Determining a performance indicator error based on the performance indicator value and the performance indicator expected value; The state variable error and the performance indicator error are used as inputs, and an adaptive architecture switching control model is used to output the optimal type and adjustment plan of the urban air traffic control system architecture, wherein the adaptive architecture switching control model includes an architecture switching fuzzy rule base and architecture control variables, the architecture switching fuzzy rule base includes a rule set, each rule in the rule set includes a condition and a corresponding result, the condition is a condition determined according to the state variable and the performance indicator, and the corresponding result represents the type of the urban air traffic control system architecture corresponding to the condition; the architecture control variable includes a type variable and an edge relationship variable, the type variable is used to represent the type of the urban air traffic control system architecture, and the edge relationship variable is used to represent whether edges are established between elements in the model of the urban air traffic control system architecture; the types of the urban air traffic control system architecture include a centralized urban air traffic control system architecture, a distributed urban air traffic control system architecture, and a semi-distributed urban air traffic control system architecture; According to the adjustment plan, the model structure of the urban air traffic control system architecture of the previous stage is adjusted accordingly.

2. The urban air traffic system control architecture switching method according to claim 1, characterized in that: Before executing the step of "obtaining state variable values ​​and performance indicator values ​​of the urban air traffic control system at the current stage", the urban air traffic system control architecture switching method further includes: Obtaining an element set and an element relationship set in the urban air traffic control system, wherein the elements in the element set refer to various types of systems, subsystems, or devices required to support the capabilities of the urban air traffic control system; and the element relationships in the element relationship set refer to the interactive relationships between the elements; According to the element set and the element relationship set, a model of the urban air traffic control system architecture is constructed, wherein the model of the urban air traffic control system architecture includes a centralized urban air traffic control system architecture model, a distributed urban air traffic control system architecture model and a semi-distributed urban air traffic control system architecture model; the model of the urban air traffic control system architecture is divided into cloud layer, end layer and edge layer according to the decision-making level, the decision-making level of the elements of the cloud layer is the highest, and the decision-making level of the elements of the edge layer is the lowest; in the centralized urban air traffic control system architecture model, the elements of the cloud layer control the elements of the edge layer, the elements of the end layer control the elements of the edge layer of the corresponding area, and the elements in the edge layer communicate with each other. Information interaction is performed between elements at the edge level, and no information interaction is performed between elements at the end level; in the distributed urban air traffic control system architecture model, elements at the cloud level do not control elements at the edge level, elements at the end level do not control elements at the edge level of the corresponding region, there is no information interaction between elements at the edge level, and information interaction is performed between elements at the end level; in the semi-distributed urban air traffic control system architecture model, elements at the cloud level do not control elements at the edge level, some elements at the end level control elements at the edge level of the corresponding region, and another part of elements at the end level do not control elements at the edge level of the corresponding region, there is information interaction between elements at the edge level, some elements at the end level interact with each other, and no information interaction is performed between other parts of elements at the end level.

3. The urban air traffic system control architecture switching method according to claim 1, characterized in that: The process of constructing the adaptive architecture switching control model specifically includes: Determine the state variables and performance indicators of the urban air traffic control system based on scenario requirements; Constructing architectural control variables; Determining the error level membership function of each state variable and the error level membership function of each performance indicator according to fuzzy theory, wherein the error refers to the difference between the measured value of the state variable or the performance indicator and the corresponding expected value; Determining the error level of the state variable and the error level of the performance indicator according to the error level membership function of the state variable and the error level membership function of the performance indicator; Establishing a fuzzy rule base for architecture switching based on the error level of the state variable and the error level of the performance indicator as conditions and the type of the urban air traffic control system architecture as a result; determining the type of traffic control system architecture according to the architecture switching fuzzy rule base; Determining the value of the architecture control variable according to the type of the traffic control system architecture; adjusting the model structure of the urban air traffic control system architecture according to the values ​​of the architecture control variables; Determine whether an error of any of the performance indicators exceeds an error threshold, and obtain a first determination result; If the first judgment result is yes, a genetic algorithm is used to optimize the parameters of the error level membership function of all the state variables and the error level membership function of the performance index, wherein the objective function in the genetic algorithm is a function constructed with the goal of minimizing a target error, and the target error refers to the error of the performance index that exceeds an error threshold; The error level membership function of the state variable and the error level membership function of the performance index corresponding to the optimized parameters are used as the new error level membership function of the state variable and the error level membership function of the performance index, and the process returns to the step of "determining the error level of the state variable and the error level of the performance index according to the error level membership function of the state variable and the error level membership function of the performance index"; If the first judgment result is no, the construction of the adaptive architecture switching control model is completed.

4. The urban air traffic system control architecture switching method according to claim 1, characterized in that: The adjustment plan specifically includes: When the optimal urban air traffic control system architecture is the centralized urban air traffic control system architecture, the adjustment scheme is to establish edges between all cloud-level elements and edge-level elements in the centralized urban air traffic control system architecture model, establish edges between all edge-level elements and end-level elements in the corresponding region, establish edges between all edge-level elements, and disconnect all end-level elements from each other. When the type of the optimal urban air traffic control system architecture is the distributed urban air traffic control system architecture, the adjustment solution is to disconnect all cloud-level elements and edge-level elements in the distributed urban air traffic control system architecture model, disconnect all edge-level elements from the end-level elements in the corresponding region, disconnect all edge-level elements from each other, and establish connections between all end-level elements within a preset communication range. When the type of the optimal urban air traffic control system architecture is the semi-distributed urban air traffic control system architecture, the adjustment plan is to disconnect the connections between all cloud-level elements and edge-level elements in the model of the semi-distributed urban air traffic control system architecture, establish connections between some elements in the end level and elements in the edge level in the corresponding area, disconnect the connections between another part of the elements in the end level and elements in the edge level in the corresponding area, establish connections between all elements in the edge level, establish connections between some elements in the end level, and disconnect the connections between another part of the elements in the end level.

5. The urban air traffic system control architecture switching method according to claim 1, characterized in that: The edge relationship variables are represented in the form of an adjacency matrix.

6. The urban air traffic system control architecture switching method according to claim 1, characterized in that: The rules are expressed in the form of "if-then" and are set according to expert experience and scenario requirements.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the urban air traffic system control architecture switching method according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the urban air traffic system control architecture switching method according to any one of claims 1 to 6 is implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the urban air traffic system control architecture switching method according to any one of claims 1 to 6 is implemented.

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