A drone flight plan pre-dispatch tool and method

Abstract

The application discloses a kind of unmanned plane flight plan pre-dispatching tool and method, wherein the tool includes: information input module, target constraint generation module, dispatching model establishment module, dispatching scheme generation module and dispatching scheme release module;The unmanned plane flight plan pre-dispatching method is realized using the above tool, including the following steps: step 1, receiving various information;Step 2, generating the target constraint of unmanned plane flight plan pre-dispatching;Step 3, establishing the target planning model of unmanned plane flight plan pre-dispatching;Step 4, solving the generation of unmanned plane flight plan pre-dispatching scheme;Step 5, release scheme, complete the unmanned plane flight plan pre-dispatching.The application provides implementation tool and technical basis for low-altitude flight service, urban air traffic management, unmanned plane command control.

Description

Technical Field

[0001] This invention belongs to the field of air traffic management and relates to a flight plan allocation tool and method, particularly a tool and method for pre-allocation of UAV flight plans. Background Technology

[0002] This section provides only background information relevant to this disclosure and is not necessarily prior art.

[0003] Pre-allocation of UAV flight plans is an effective means of scientifically planning UAV flight times and resolving airspace usage conflicts during the planning phase. It is one of the key technologies for air traffic management, low-altitude flight services, and command and control. Common flight plan allocation methods include first-come, first-served, allocation based on task priority, and minimizing total delay. Some technologies aim to minimize flight plan costs, establishing UAV flight plan pre-allocation models to generate conflict-free timetables. Other technologies associate flight operation areas or flight routes in the flight plan with airspace grids, determine the comprehensive priority of the flight plan, and establish a low-altitude airspace allocation model based on comprehensive priority under gridded airspace to achieve pre-allocation of flight plans. UAV flight missions are highly diversified, and flight demands are multifaceted. Different scenarios such as aerial logistics and emergency rescue have differentiated flight plan allocation requirements. Existing technologies have limited allocation targets and do not adequately consider the different flight interval requirements between UAVs belonging to different operators. Currently, there is a lack of a simple method suitable for rapid pre-allocation of UAV flight plans based on diversified allocation targets during the planning phase.

[0004] In terms of system tools, existing UAV operation management systems or low-altitude flight service systems have certain functions such as flight plan application and approval, information services, and UAV mission planning. However, they lack the functionality for pre-allocation of UAV flight plans, making it difficult to meet the air traffic control support needs for high-volume, high-density UAV flights and UAV public airway operation management. Currently, there is a lack of a universal, portable, and highly embeddable UAV flight plan pre-allocation tool.

[0005] The technologies and equipment for low-altitude air traffic management and unmanned aerial vehicle (UAV) traffic management are generally in the initial stages of development. There is still significant research and application potential to meet the development needs of UAV public airway networks and UAV transportation systems. Therefore, a new technical solution is needed to address these technical challenges.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] Purpose of the invention: The technical problem to be solved by the present invention is to provide a tool and method for pre-allocation of UAV flight plans, addressing the shortcomings of the existing technology.

[0008] To address the aforementioned technical problems, this invention discloses a tool and method for pre-planning unmanned aerial vehicle (UAV) flights, wherein the tool comprises:

[0009] The system comprises an information input module, a target constraint generation module, a deployment model establishment module, a deployment scheme generation module, and a deployment scheme publishing module; among which,

[0010] The information input module is used to receive various types of information, including: the UAV's flight path, take-off and landing points, flight plan, flight interval, and the target requirements pre-allocated by the UAV flight plan;

[0011] The target constraint generation module is used to generate target constraints pre-allocated to the UAV flight plan based on various types of information received by the information input module.

[0012] The allocation model establishment module is used to establish a target planning model for the pre-allocation of the UAV flight plan based on the target constraints pre-allocated by the UAV flight plan generated by the target constraint generation module.

[0013] The allocation scheme generation module is used to solve the target planning model for the pre-allocation of the UAV flight plan established by the allocation model establishment module, and generate a pre-allocation scheme for the UAV flight plan.

[0014] The allocation scheme publishing module is used to publish the pre-allocation scheme for the UAV flight plan generated by the allocation scheme generation module.

[0015] Furthermore, the tools also include: a server, a workstation, and an integrated information access device; wherein,

[0016] The server is used to perform calculations, storage, and management on the various types of information.

[0017] The workstation is used for graphic image processing, data computation, and human-computer interaction;

[0018] The integrated information access device serves as the information input interface for the tool.

[0019] This invention also proposes a method for pre-planning UAV flight schedules, implemented using the aforementioned tools, comprising the following steps:

[0020] Step 1: Receive various types of information, including: the UAV's flight path, take-off and landing points, flight plan, flight interval, and the target requirements pre-allocated in the UAV flight plan; among which, the target requirements pre-allocated in the UAV flight plan include target content and target priority;

[0021] Step 2: Based on the various types of information received in Step 1, generate the target constraints pre-allocated to the UAV flight plan;

[0022] Step 3: Based on the target constraints pre-allocated in the UAV flight plan generated in Step 2, establish a target planning model for the pre-allocation of the UAV flight plan.

[0023] Step 4: Solve the target planning model for pre-allocation of UAV flight plans established in Step 3 to generate a pre-allocation scheme for UAV flight plans;

[0024] Step 5: Publish the drone flight plan pre-allocation scheme generated in Step 4 to complete the drone flight plan pre-allocation.

[0025] Furthermore, step 2, which involves generating pre-allocated target constraints for the UAV flight plan, specifically includes the following steps:

[0026] Step 2-1: Extract the priority of each target based on the various types of information received in Step 1;

[0027] Step 2-2: Based on the priorities extracted in Step 2-1, sort the targets from highest to lowest priority as follows:

[0028] P1>>P2>>…P u …>>P U

[0029] Among them, P u The priority of target u (u = 1, 2, ..., U) is the total number of targets. >> indicates that the priority of the target to the left of the symbol is greater than the priority of the target to the right.

[0030] Step 2-3: Based on the sorting in Step 2-2, generate target constraints or absolute constraints for each target in turn.

[0031] Furthermore, the generation of target constraints for each target as described in steps 2-3 is represented as follows:

[0032]

[0033] i = 1, 2, ..., I

[0034] u = 1, 2, ..., U

[0035] m = 1, 2, ..., M

[0036]

[0037] Wherein, the target constraint represents achieving the target value. Flight delays in UAV flight plan i are allowed to have positive or negative deviations, where i is the total number of UAV flight plans. and Let U and V be the positive and negative deviation variables of the target u, respectively, where U represents the total number of targets. This indicates the time after the UAV passes waypoint m in flight plan i, following the rescheduling process. This represents the planned time when the UAV passes waypoint m in flight plan i. Here, takeoff and landing points are merged into waypoints, and the time of passing this waypoint is the takeoff or landing time. M is the sum of the number of merged waypoints and the number of takeoff and landing points. This represents the delay coefficient of the UAV passing through waypoint m in flight plan i under target u.

[0038] Furthermore, the delay coefficient of the UAV passing through waypoint m in the flight plan i under target u described in steps 2-3 is expressed as:

[0039]

[0040] Furthermore, the generation of absolute constraints for each objective described in steps 2-3 is as follows:

[0041]

[0042] i = 1, 2, ..., I

[0043] u = 1, 2, ..., U

[0044] The absolute constraint mentioned above refers to achieving the target value t. iu 0 The flight delay requirements that the UAV flight plan must meet.

[0045] Furthermore, step 3, which involves establishing a mathematical model for pre-planning UAV flight schedules, specifically includes the following steps:

[0046] Step 3-1: Based on the target constraints of the UAV flight plan pre-configured in Step 2, establish the objective function for the pre-configuration of the UAV flight plan;

[0047] Step 3-2: Based on the objective function established in Step 3-1, establish constraints, including: objective constraints, absolute constraints, and flight interval constraints. The flight interval constraint is expressed as follows:

[0048]

[0049] m = 1, 2, ..., M

[0050] The flight interval constraint means that two UAVs that pass through any waypoint or take off from or land from the same takeoff and landing point meet the flight interval requirement, where S represents the time interval between the two UAVs.

[0051] Step 3-3: Based on the objective function established in Step 3-1 and the constraints established in Step 3.2, establish a target planning model for the pre-allocation of UAV flight plans.

[0052] Furthermore, the objective function described in step 3-1 is expressed as follows:

[0053]

[0054] in, This indicates that the deviation between the drone flight delay and the target requirements is minimized.

[0055] Furthermore, the target planning model for the pre-allocation of the UAV flight plan described in step 3-3 is represented as follows:

[0056]

[0057] st

[0058]

[0059] i,j=1,2,…,I

[0060] m = 1, 2, ..., M

[0061] u = 1, 2, ..., U

[0062]

[0063] Beneficial effects:

[0064] 1. This invention provides an implementation tool for low-altitude flight services, urban air traffic management, and UAV command and control. It is easy to embed into air traffic control systems, low-altitude flight service systems, and UAV-related command and control systems, and provides technical support for the research and development and upgrading of air traffic control systems, low-altitude flight service systems, and UAV-related command and control systems.

[0065] 2. This invention provides a technical foundation for UAV flight plan management, flight time management, and public airway management, and the implementation method is simple, fast, and easy to operate;

[0066] 3. This invention provides a technical basis for low-altitude air traffic management and unmanned aerial vehicle (UAV) traffic management. Attached Figure Description

[0067] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, and the advantages of the present invention in the above and / or other aspects will become clearer.

[0068] Figure 1 This is a diagram showing the software module composition and internal information relationships of the UAV flight plan pre-allocation tool of the present invention.

[0069] Figure 2 This is a flowchart of the drone flight plan pre-allocation method of the present invention.

[0070] Figure 3 This is a flowchart of the target constraint generation method for pre-configured UAV flight plans according to the present invention.

[0071] Figure 4 A flowchart of the method for establishing a mathematical model for pre-configuration of the drone flight plan according to the present invention.

[0072] Figure 5 This is a schematic diagram of a drone route network in a specific embodiment. Detailed Implementation

[0073] This invention proposes a tool and method for pre-allocating UAV flight plans. Based on information such as the UAV's route, take-off and landing points, flight plan, flight interval, and target requirements for pre-allocating the UAV flight plan, while ensuring the flight interval between UAVs, the tool optimizes the time of passing waypoints for each UAV and proposes a satisfactory pre-allocation scheme for flight plans for various allocation targets.

[0074] The tools and methods proposed in this invention optimize the timing of waypoints for each UAV based on information such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and pre-allocated target requirements of the UAV flight plan, while ensuring the flight interval between UAVs, and propose a satisfactory pre-allocated flight plan scheme for each allocation target.

[0075] The specific technical solution of the present invention is as follows:

[0076] A tool for pre-allocation of UAV flight plans includes an information input module, a target constraint generation module, an allocation model establishment module, an allocation scheme generation module, an allocation scheme publishing module, a server, a workstation, and an integrated information access device. The information input module receives information such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and target requirements for pre-allocation of the UAV flight plan. The target constraint generation module generates target constraints for pre-allocation of the UAV flight plan based on the information received by the information input module. The allocation model establishment module establishes a target planning model for pre-allocation of the UAV flight plan based on the target constraints generated by the target constraint generation module. The allocation scheme generation module solves the target planning model established by the allocation model establishment module to generate a pre-allocation scheme for the UAV flight plan. The allocation scheme publishing module publishes the pre-allocation scheme for the UAV flight plan generated by the allocation scheme generation module.

[0077] The server is used to calculate, store, and manage various types of information for a drone flight plan pre-scheduling tool, and to complete the functional response of each module of the software; the workstation is used for various graphic image processing, data calculation, and human-computer interaction of the drone flight plan pre-scheduling tool; the integrated information access device is used as the interface for information input of the drone flight plan pre-scheduling tool.

[0078] This invention also proposes a method for pre-planning UAV flight schedules, comprising the following steps:

[0079] Step 1: Receive information such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and pre-allocated target requirements of the UAV flight plan. The flight plan generally includes, but is not limited to, information such as take-off time, take-off and landing points, landing time, and waypoint latitude and longitude. The flight interval is generally set according to conditions such as airspace capacity and low-altitude flight services. The pre-allocated target requirements of the UAV flight plan are generally requirements for the timeliness of the flight plan, as well as delay time and number of delayed flights.

[0080] Step 2: Based on the information received in Step 1, such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and the target requirements (including target content and target priority) pre-allocated to the UAV flight plan, generate the target constraints pre-allocated to the UAV flight plan.

[0081] Step 3: Based on the target constraints pre-allocated in the UAV flight plan generated in Step 2, establish a target planning model for the pre-allocation of the UAV flight plan;

[0082] Step 4: Use sequential algorithms and other methods to solve the target planning model for the pre-allocation of UAV flight plans established in Step 3, and generate a pre-allocation scheme for UAV flight plans. This scheme generally includes, but is not limited to, information such as the takeoff time, landing time, and waypoint overpass time of each UAV.

[0083] Step 5: Publish the drone flight plan pre-allocation scheme generated in Step 4. The target audience is generally air traffic control agencies, low-altitude flight service agencies, drone operators and other relevant parties.

[0084] Preferably, the method for generating target constraints for pre-configured UAV flight plans in step 2 includes the following steps:

[0085] Step 2.1: Based on the information received in Step 1, such as the UAV's flight path, take-off and landing point, flight plan, flight interval, and the target requirements pre-allocated in the UAV flight plan, extract the priority of each target (referring to the targets pre-allocated in the UAV flight plan);

[0086] Step 2.2: Based on the priorities extracted in Step 2.1, sort the targets in descending order of priority, satisfying P1 >> P2 >> ... >> P U P u Priority of target u (u = 1, 2, ..., U, where U is the total number of targets);

[0087] Step 2.3: Based on the order of the objectives arranged in Step 2.2, generate objective constraints or absolute constraints for each objective in turn, as shown below:

[0088]

[0089] i = 1, 2, ..., I

[0090] u = 1, 2, ..., U

[0091] m = 1, 2, ..., M

[0092]

[0093] Wherein, the target constraint represents achieving the target value. Flight delays in UAV flight plan i are allowed to have positive or negative deviations, where i is the total number of UAV flight plans. and Let be the positive and negative deviation variables of the target u, respectively. This indicates the time after the UAV passes waypoint m in flight plan i, following the rescheduling process. This represents the planned time when the UAV passes waypoint m in flight plan i. Here, takeoff and landing points are merged into waypoints, and the time of passing this waypoint is the takeoff or landing time. M is the sum of the number of merged waypoints and the number of takeoff and landing points. The delay coefficient for the UAV passing through waypoint m in flight plan i under target u is expressed as:

[0094]

[0095] Absolute constraints are expressed as:

[0096]

[0097] i = 1, 2, ..., I

[0098] u = 1, 2, ..., U

[0099] The absolute constraint mentioned above refers to achieving the target value t. iu 0 The flight delay requirements that the UAV flight plan must meet.

[0100] Preferably, the method for establishing the mathematical model for pre-configuration of the UAV flight plan in step 3 includes the following steps:

[0101] Step 3.1: Based on the target constraints of the UAV flight plan pre-configured in Step 2, establish the objective function for the UAV flight plan pre-configuration, expressed as:

[0102]

[0103] Step 3.2: Based on the objective function established in Step 3.1, establish constraints, including: objective constraints, absolute constraints, and flight interval constraints. The flight interval constraint is expressed as follows:

[0104]

[0105] i,j=1,2,…,I

[0106] m = 1, 2, ..., M

[0107] The flight interval constraint means that two UAVs that pass through any waypoint or take off from the same takeoff and landing point meet the flight interval requirement, where S represents the time interval between the two UAVs.

[0108] Step 3.3: Based on the objective function for pre-allocation of the UAV flight plan established in Step 3.1 and the constraints established in Step 3.2, establish the objective programming model for pre-allocation of the UAV flight plan, expressed as:

[0109]

[0110] i,j=1,2,…,I

[0111] m = 1, 2, ..., M

[0112] u = 1, 2, ..., U

[0113]

[0114] Example 1:

[0115] like Figure 1 As shown in a specific embodiment of the present invention, a UAV flight plan pre-allocation tool includes an information input module, a target constraint generation module, an allocation model establishment module, an allocation scheme generation module, an allocation scheme publishing module, a server, a workstation, and an integrated information access device. The information input module receives information such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and target requirements for UAV flight plan pre-allocation. The target constraint generation module generates target constraints for UAV flight plan pre-allocation based on the information received by the information input module. The allocation model establishment module establishes a target planning model for UAV flight plan pre-allocation based on the target constraints generated by the target constraint generation module. The allocation scheme generation module solves the target planning model established by the allocation model establishment module to generate a UAV flight plan pre-allocation scheme. The allocation scheme publishing module publishes the UAV flight plan pre-allocation scheme generated by the allocation scheme generation module.

[0116] The server is used to calculate, store, and manage various types of information for a drone flight plan pre-scheduling tool, and to complete the functional response of each module of the software; the workstation is used for various graphic image processing, data calculation, and human-computer interaction of the drone flight plan pre-scheduling tool; the integrated information access device is used as the interface for information input of the drone flight plan pre-scheduling tool.

[0117] like Figure 2 As shown, a method for pre-planning drone flight schedules includes the following steps:

[0118] Step 1: Receive information such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and pre-allocated target requirements of the UAV flight plan. Among them, the flight interval is generally set as a time interval.

[0119] Step 2: Based on the information received in Step 1, such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and the target requirements pre-allocated in the UAV flight plan, generate the target constraints for the pre-allocated UAV flight plan.

[0120] Step 3: Based on the target constraints pre-allocated in the UAV flight plan generated in Step 2, establish a target planning model for the pre-allocation of the UAV flight plan;

[0121] Step 4: Solve the target planning model for pre-allocation of UAV flight plans established in Step 3 to generate a pre-allocation scheme for UAV flight plans;

[0122] Step 5: Publish the pre-allocation scheme for the drone flight plan generated in Step 4.

[0123] like Figure 3 As shown, step 2 of the UAV flight plan pre-configuration method disclosed in this invention proposes a target constraint generation method for UAV flight plan pre-configuration, including the following steps:

[0124] Step 2.1: Based on the information received in Step 1, such as the UAV's flight path, take-off and landing points, flight plan, flight interval, and the target requirements pre-allocated in the UAV flight plan, extract the priority of each target;

[0125] Step 2.2: Based on the priorities extracted in Step 2.1, sort the targets in descending order of priority, satisfying P1 >> P2 >> ... >> P U P u Priority of target u (u = 1, 2, ..., U, where U is the total number of targets);

[0126] Step 2.3: Based on the order of the objectives arranged in Step 2.2, generate objective constraints or absolute constraints for each objective in turn, as shown below:

[0127]

[0128] i = 1, 2, ..., I

[0129] u = 1, 2, ..., U

[0130] m = 1, 2, ..., M

[0131]

[0132] Wherein, the target constraint represents achieving the target value. Flight delays in UAV flight plan i are allowed to have positive or negative deviations, where i is the total number of UAV flight plans. and Let be the positive and negative deviation variables of the target u, respectively. This indicates the time after the UAV passes waypoint m in flight plan i, following the rescheduling process. This represents the planned time when the UAV passes waypoint m in flight plan i. Here, takeoff and landing points are merged into waypoints, and the time of passing this waypoint is the takeoff or landing time. M is the sum of the number of merged waypoints and the number of takeoff and landing points. The delay coefficient for the UAV passing through waypoint m in flight plan i under target u is expressed as:

[0133]

[0134] Absolute constraints are expressed as:

[0135]

[0136] i = 1, 2, ..., I

[0137] u = 1, 2, ..., U

[0138] The absolute constraint mentioned above refers to achieving the target value t. iu 0 The flight delay requirements that the UAV flight plan must meet.

[0139] like Figure 4 As shown, step 3 of the UAV flight plan pre-deployment method disclosed in this invention proposes a mathematical model establishment method for UAV flight plan pre-deployment, including the following steps:

[0140] Step 3.1: Based on the target constraints of the UAV flight plan pre-configured in Step 2, establish the objective function for the UAV flight plan pre-configuration, expressed as:

[0141]

[0142] Step 3.2: Based on the objective function established in Step 3.1, establish the constraints.

[0143] The constraints include: target constraints, absolute constraints, and flight interval constraints, wherein the flight interval constraint is expressed as follows:

[0144]

[0145] i,j=1,2,…,I

[0146] m = 1, 2, ..., M

[0147] u = 1, 2, ..., U

[0148] The flight interval constraint means that two UAVs that pass through any waypoint or take off or land from the same takeoff and landing point meet the flight interval requirement, where S represents the time interval between the two UAVs.

[0149] Step 3.3: Based on the objective function for pre-allocation of the UAV flight plan established in Step 3.1 and the constraints established in Step 3.2, establish the objective programming model for pre-allocation of the UAV flight plan, expressed as:

[0150]

[0151] st

[0152]

[0153] i,j=1,2,…,I

[0154] m = 1, 2, ..., M

[0155] u = 1, 2, ..., U

[0156]

[0157] Example 2:

[0158] Taking flight simulation data of a certain UAV's flight airspace as an example, Figure 5 This is a flight path diagram of the airspace for the UAV. There are multiple flight path intersections and different types of UAVs. Based on UAV flight experience, the average cruising speeds of small, medium and large UAVs are set to 50km / h, 80km / h and 100km / h, respectively.

[0159] Step 1: Receive information such as the drone's flight path, take-off and landing point, flight plan, flight interval, and pre-allocated target requirements of the drone's flight plan, as shown in Tables 1 to 3. The flight interval between the two drones is 5 minutes.

[0160] Table 1. Drone route information

[0161]

[0162]

[0163] Table 2 Unmanned Aerial Vehicle Flight Plan

[0164]

[0165] Table 3. Target Requirements Information for Pre-allocation of Unmanned Aerial Vehicle Flight Plans

[0166]

[0167]

[0168] Step 2: Based on the information received in Step 1, such as the UAV's flight path, take-off and landing point, flight plan, flight interval, and target requirements pre-allocated in the UAV flight plan, generate target constraints for the pre-allocated UAV flight plan.

[0169] The objectives are sorted in descending order of priority, as shown in Table 4.

[0170] Table 4. Target Ranking Pre-allocated in UAV Flight Plans

[0171] Serial Number Target content Priority 1 Flight Plan 5 is an important mission and cannot be delayed. <![CDATA[P1]]> 2 Departure delays at landing point 2 can exceed 5 minutes, but should be kept to a minimum. <![CDATA[P2]]> 3 Flight Plan 3 is a critical mission; minimize delays. <![CDATA[P3]]> 4 Minimize the total delay time of all flight plans <![CDATA[P4]]>

[0172] The planned times for the UAV to pass waypoints in the flight plan are calculated by dividing the planned take-off time, planned landing time, and the distance between the two waypoints in the UAV flight plan received in step 1 by the average cruising speed of the UAV, as shown in Table 5.

[0173] Table 5 Planned times for UAVs to pass waypoints

[0174]

[0175]

[0176] In this embodiment, all objectives are related to delay time, so the delay coefficient is 1 for all objectives. Based on the objective order shown in Table 4, objective constraints or absolute constraints are generated for each objective in turn.

[0177] Objective 1 and Flight Plan 5 are critical and cannot be delayed. An absolute constraint is generated, represented as follows:

[0178]

[0179] For objective 2, the takeoff delay at takeoff and landing point 2 can exceed 5 minutes, but should be kept as low as possible. This generates a target constraint, represented as follows:

[0180]

[0181] Objective 3 and Flight Plan 3 are relatively important tasks. Minimize delays and generate objective constraints, represented as follows:

[0182]

[0183] Objective 4: Minimize the total delay time of all flight plans. This objective constraint is generated as follows:

[0184]

[0185] Step 3, establish a target planning model for pre-allocation of UAV flight plans, represented as:

[0186]

[0187]

[0188] Step 4: Use sequential algorithms and other methods to solve the target planning model for the pre-allocation of UAV flight plans established in Step 3, and generate the UAV flight plan pre-allocation scheme shown in Table 6.

[0189] Table 6. Pre-allocation Scheme for Unmanned Aerial Vehicle Flight Plans

[0190]

[0191]

[0192] Step 5: Publish the drone flight plan pre-allocation scheme generated in Step 4 to relevant parties such as air traffic control agencies, low-altitude flight service agencies, and drone operators involved in the flight plan in the airspace where the drone is flying.

[0193] In its specific implementation, this application provides a computer storage medium and a corresponding data processing unit. The computer storage medium is capable of storing a computer program, which, when executed by the data processing unit, can run the invention's content regarding a pre-allocation tool and method for UAV flight plans, as well as some or all of the steps in various embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0194] Those skilled in the art will clearly understand that the technical solutions in the embodiments of the present invention can be implemented using computer programs and their corresponding general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of computer programs, i.e., software products. These computer program software products can be stored in a storage medium and include several instructions to cause a device containing a data processing unit (which may be a personal computer, server, microcontroller, MCU, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.

[0195] This invention provides a method and approach for pre-planning flight schedules for unmanned aerial vehicles (UAVs). Many methods and approaches exist for implementing this technical solution; the above description is merely a preferred embodiment. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention. All components not explicitly stated in this embodiment can be implemented using existing technologies.

Claims

1. An unmanned aerial vehicle flight plan pre-dispatching tool, characterized in that, include: The system comprises an information input module, a target constraint generation module, a deployment model establishment module, a deployment scheme generation module, and a deployment scheme publishing module; among which, The information input module is used to receive various types of information, including: the UAV's flight path, take-off and landing points, flight plan, flight interval, and the target requirements pre-allocated by the UAV flight plan; The target constraint generation module is used to generate target constraints pre-allocated to the UAV flight plan based on various types of information received by the information input module. The allocation model establishment module is used to establish a target planning model for the pre-allocation of the UAV flight plan based on the target constraints pre-allocated by the UAV flight plan generated by the target constraint generation module. The allocation scheme generation module is used to solve the target planning model for the pre-allocation of the UAV flight plan established by the allocation model establishment module, and generate a pre-allocation scheme for the UAV flight plan. The allocation scheme publishing module is used to publish the pre-allocation scheme for the UAV flight plan generated by the allocation scheme generation module; The allocation model establishment module establishes a target planning model for the pre-allocation of UAV flight plans, as shown below: ； wherein, is an objective function representing minimization of the deviation of the UAV flight delay from the target requirement, is an objective priority, , is a total number of objectives, and are positive and negative deviation variables of the objective , , ; is a constraint condition symbol; For target constraints, it means achieving the target value. Time drone flight plan Flight delays in China are allowed to have positive or negative deviations. , The total number of drone flight plans, Indicates flight plan Chinese UAV waypoints After the allocation, , This is the sum of the number of waypoints and the number of takeoff and landing points after the merger. Indicates flight plan Chinese UAV waypoints The planned departure and arrival times are determined by combining the departure and arrival points into waypoints; the time at which a point is crossed is the departure or arrival time. Indicate target Next flight plan Chinese UAV waypoints The delay coefficient; For absolute constraints, it means reaching the target value. Time drone flight plan Flight delay requirements that must be met; The flight spacing constraint indicates that two UAVs that pass through any waypoint or take off from or land from the same takeoff and landing point must meet the required flight spacing. Indicates flight plan Chinese UAV waypoints After the allocation, , This indicates the time interval between the two drones.

2. The UAV flight plan pre-allocation tool according to claim 1, characterized in that, The tools also include: servers, workstations, and integrated information access devices; among which... The server is used to perform calculations, storage, and management on the various types of information. The workstation is used for graphic image processing, data computation, and human-computer interaction; The integrated information access device serves as the information input interface for the tool.

3. A method for pre-allocation of unmanned aerial vehicle (UAV) flight plans, characterized in that, Implemented using any of the tools described in claim 1 or 2, including the following steps: Step 1: Receive various types of information, including: the UAV's flight path, take-off and landing points, flight plan, flight interval, and the target requirements pre-allocated in the UAV flight plan; among which, the target requirements pre-allocated in the UAV flight plan include target content and target priority; Step 2: Based on the various types of information received in Step 1, generate the target constraints pre-allocated to the UAV flight plan; Step 3: Based on the target constraints pre-allocated in the UAV flight plan generated in Step 2, establish a target planning model for the pre-allocation of the UAV flight plan. Step 4: Solve the target planning model for pre-allocation of UAV flight plans established in Step 3 to generate a pre-allocation scheme for UAV flight plans; Step 5: Publish the drone flight plan pre-allocation scheme generated in Step 4 to complete the drone flight plan pre-allocation.

4. The method for pre-allocation of UAV flight plans according to claim 3, characterized in that, Step 2, which involves generating pre-allocated target constraints for the UAV flight plan, specifically includes the following steps: Step 2-1: Extract the priority of each target based on the various types of information received in Step 1; Step 2-2: Based on the priorities extracted in Step 2-1, sort the targets from highest to lowest priority as follows: ； in, For the goal priority, , For the target total number, This indicates that the target priority on the left of the symbol is greater than the target priority on the right. Step 2-3: Based on the sorting in Step 2-2, generate target constraints or absolute constraints for each target in turn.

5. The method for pre-allocation of UAV flight plans according to claim 4, characterized in that, The generation of target constraints for each target as described in steps 2-3 is as follows: ； Wherein, the target constraint represents achieving the target value. Time drone flight plan Flight delays in China are allowed to have positive or negative deviations. The total number of drone flight plans, and The target Positive and negative deviation variables, Indicates the total number of targets. Indicates flight plan Chinese UAV waypoints After the allocation, Indicates flight plan Chinese UAV waypoints The planned departure and arrival times are determined by combining the departure and arrival points into waypoints; the time at which a point is crossed is the departure or arrival time. This is the sum of the number of waypoints and the number of takeoff and landing points after the merger. Indicate target Next flight plan Chinese UAV waypoints The delay coefficient.

6. The method for pre-allocation of UAV flight plans according to claim 5, characterized in that, The objectives described in steps 2-3 Next flight plan Chinese UAV waypoints The delay coefficient is expressed as: 。 7. The method for pre-allocation of UAV flight plans according to claim 6, characterized in that, The generation of absolute constraints for each objective as described in steps 2-3 is as follows: ； The absolute constraint mentioned above refers to achieving the target value. Time drone flight plan The flight delay requirements that must be met.

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