A low-altitude flight route dynamic planning and simulation method, device and medium based on route network congestion degree evaluation

Abstract

The application discloses a kind of based on low-altitude flight route dynamic planning and simulation method, equipment and medium of route network congestion degree evaluation, the method includes: constructing low-altitude route network model, based on low-altitude route network model formation standardization low-altitude route network structure data, realize the digital expression of network topological relation between low-altitude route network elements;Based on low-altitude preflight plan, deduce calculation, form low-altitude route network congestion degree space-time distribution diagram;According to dynamically added flight demand, in combination with route network congestion degree distribution, real-time generation low-altitude flight route, and update low-altitude route network congestion degree space-time distribution diagram;Route network operation situation deduce prediction, simulate and visualize display route network congestion degree situation.The application can generate the flight route that avoids congestion section according to dynamically added flight demand, effectively cope with the characteristics that low-altitude flight route planning demand is dynamic, real-time, weak planning, meet the requirement of airspace efficient use of low-altitude high-density flight.

Description

Technical Field

[0001] This invention belongs to the field of air traffic control technology and relates to a method, equipment and medium for dynamic planning and simulation of low-altitude flight routes based on airway network congestion assessment. Background Technology

[0002] With the rapid development of the low-altitude economy, the volume of low-altitude flights continues to grow, and high-density, high-volume low-altitude flights are becoming the future trend. Problems such as low-altitude airspace utilization, flight congestion, and high conflict rates are gradually becoming prominent, placing higher demands on low-altitude flight route planning. First, traditional exclusive route planning has low airspace utilization, making it difficult to meet the demands of high-density flights. There is an urgent need for route planning based on airway networks to reuse basic routes and improve airspace utilization. Second, compared to traditional high-altitude flights, low-altitude flights are more dynamic, require more real-time updates, and have less planning capabilities. For example, online coffee delivery requires immediate route planning and takeoff, unlike traditional civil aviation where flight plans are determined the day before. Therefore, the dynamic and real-time requirements for flight route planning are higher. Third, high-density flights result in high conflict rates, necessitating rational route planning to dynamically avoid congested areas and improve flight efficiency. Currently, most low-altitude flight route planning is based on exclusive routes and static planning, failing to consider real-time congestion conditions in the flight environment. These planning methods are ill-suited to the future needs of high-density, high-volume, and dynamic flight demands. Summary of the Invention

[0003] Purpose of the invention: The purpose of this invention is to provide a method, device, and medium for dynamic planning and simulation of low-altitude flight routes based on airway network congestion assessment, in order to solve one or more problems existing in the prior art.

[0004] Technical solution: The present invention provides a method for dynamic planning and simulation of low-altitude flight routes based on airway network congestion assessment, comprising:

[0005] S1: Construct a low-altitude airway network model, and based on the low-altitude airway network model, form standardized low-altitude airway network structure data to realize the digital expression of the network topology relationship between low-altitude airway network elements;

[0006] S2: Based on the low-altitude pre-flight plan, extrapolation and calculation are performed to form a spatiotemporal distribution map of low-altitude airway network congestion.

[0007] S3: Based on dynamically added flight demand and combined with the airway network congestion distribution, generate low-altitude flight routes in real time and update the spatiotemporal distribution map of low-altitude airway network congestion.

[0008] S4: To predict and simulate the operational status of the airway network, and to visualize the congestion level of the airway network.

[0009] Further, step S1 includes:

[0010] S1-1: Set the length of the monitoring unit for the congestion assessment segment of the low-altitude airway network. Divide each physical segment in the low-altitude airway network according to the length of the monitoring unit. The segmented segment is defined as a meta-segment. Physical segments whose length is less than or equal to the length of the monitoring unit and are not divided are also classified as meta-segments. Add new waypoints at the division points and define them as virtual waypoints.

[0011] S1-2: The low-altitude airway network is decomposed into elements of takeoff and landing fields, physical waypoints, virtual waypoints, meta segments, and physical segments. Takeoff and landing fields, physical waypoints, and virtual waypoints are abstracted into point elements, and meta segments and physical segments are abstracted into line elements. The low-altitude airway network model is constructed by describing the five types of elements: takeoff and landing fields, physical waypoints, virtual waypoints, meta segments, and physical segments.

[0012] Further, steps S1-2 include:

[0013] S1-2-1: Takeoff and landing field elements Described as:

[0014]

[0015] in, This is the sequence number of the landing field element in the landing field data; Representing the The code name of each take-off and landing field; Representing the Basic information about each take-off and landing site, including the name, type, latitude and longitude location, and elevation of the take-off and landing site;

[0016] Representing the The network connectivity relationships of the takeoff and landing fields are described as follows:

[0017]

[0018] in, This refers to the number of connections between the takeoff and landing site and the low-altitude airway network. Representing the first takeoff and landing field The connection is established through the meta-segment. Connect to point elements Point elements Are they physical waypoints or virtual waypoints?

[0019] S1-2-2: Physical waypoint elements Described as:

[0020]

[0021] in, This is the sequence number of the physical waypoint element in the physical waypoint data; Representing the The code of each physical waypoint; Representing the Basic information about each physical waypoint, including the name and latitude / longitude of the physical waypoint;

[0022] Representing the The network connectivity relationships of the physical waypoints are described as follows:

[0023]

[0024] in, This represents the number of connections between the physical waypoint and the low-altitude airway network. Represents the physical waypoint number The connection is established through the meta-segment. Connect to point elements Point elements It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site;

[0025] S1-2-3: Incorporate virtual waypoint elements Described as:

[0026]

[0027] in, This is the sequence number of the virtual waypoint element in the virtual waypoint data; Representing the The code name of a virtual waypoint; Representing the Basic information about each virtual waypoint, including the name and latitude / longitude of the virtual waypoint;

[0028] Representing the The network connectivity relationships of the virtual waypoints are described as follows:

[0029]

[0030] in, This represents the number of connections between the virtual waypoint and the low-altitude airway network. Represents the virtual waypoint number The connection is established through the meta-segment. Connect to point elements Point elements It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site;

[0031] S1-2-4: Elements of the initial voyage segment Described as:

[0032]

[0033] in, This is the sequence number of the element in the meta-segment data; Representing the The code name for each segment of the flight; Representing the Basic information of each meta segment, including the physical length, altitude range, width, logical length, and applicable aircraft type of the meta segment;

[0034] Representing the The network connectivity relationships of each flight segment are described as follows:

[0035]

[0036] in, Point elements associated with the starting point of this meta-segment; The point element representing the endpoint of this meta-segment; This represents the physical segment to which the meta segment belongs, including its point elements. , It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site;

[0037] S1-2-5: Physical flight segment elements Described as:

[0038]

[0039] in, This is the sequence number of the physical segment element in the physical segment data; Representing the The code name for each physical flight segment; Representing the Basic information about each physical flight segment, including the length, altitude range, width, and applicable aircraft types of the physical flight segment;

[0040] Representing the The network connectivity relationships of each physical flight segment are described as follows:

[0041]

[0042] in, The number of meta segments associated with this physical segment, which is composed of... , … common It consists of several segments.

[0043] Further, step S2 includes:

[0044] S2-1: Based on the low-altitude pre-flight plan and the associated aircraft type, a discrete time step is set. Using a dynamic model, the meta-segment of the corresponding aircraft for each discrete time step in the low-altitude pre-flight plan is calculated. This allows for the unfolding of the low-altitude pre-flight plan's information in both time and space dimensions. The unfolded low-altitude pre-flight plan... Described as:

[0045]

[0046] in, This is the sequence number of the low-altitude pre-flight plan in the low-altitude pre-flight plan data; Representing the The code name for a low-altitude pre-flight plan; Representing the Basic information for a low-altitude pre-flight plan includes aircraft type, takeoff time, takeoff and landing sites, destination takeoff and landing sites, and physical waypoint sequence.

[0047] Representing the The meta-segment sequence data, after unfolding the time and spatial dimension information of the low-altitude pre-flight plan, is described as follows:

[0048]

[0049] in, The number of discrete moments spanned by the entire lifecycle of the low-altitude pre-flight plan, from takeoff to landing; This represents the low-altitude pre-flight plan in the The meta-segment where each discrete moment occurs;

[0050] S2-2: Traverse the meta-segment sequence data under each low-altitude pre-flight plan, and aggregate to form the flight plan association information of the meta-segment in the time dimension; The first segment of the journey was in the... The time-related sequence of low-altitude pre-flight plans is represented as follows:

[0051]

[0052] in, For the first The first segment of the journey was in the... The number of low-altitude pre-flight plans linked to specific times; For the first The first segment of the journey was in the... The first time associated with time A low-altitude pre-flight plan;

[0053] S2-3: Construct a congestion assessment model for each meta-segment, calculate the congestion degree of each meta-segment at each discrete time, and thus form a spatiotemporal distribution map of congestion degree of the low-altitude airway network.

[0054] Further, steps S2-3 include:

[0055] S2-3-1: A congestion assessment model for the metasegment is constructed by considering the number of low-altitude pre-flight plans associated with the metasegment at that moment, the metasegment's length, width, altitude range, and the aircraft types of the associated flight plans. The congestion level of the metasegment at that moment is... Represented as:

[0056]

[0057] in, This is the length of the meta-segment; This is the width of the current segment; This refers to the altitude range of this segment; This represents the number of low-altitude pre-flight plans associated with this segment at this time. , , For the first Each low-altitude preflight plan corresponds to the longitudinal, lateral, and vertical safety separations for the aircraft type.

[0058] S2-3-2: Traverse the low-altitude pre-flight plan sequence associated with each metasegment at each discrete time, and calculate the congestion degree of each metasegment at each discrete time based on the metasegment congestion assessment model.

[0059] Further, step S3 includes:

[0060] S3-1: Based on the time when the metasegment is used in the flight route, extract the congestion data of the metasegment at that time from the spatiotemporal distribution map of congestion in the low-altitude airway network. Based on the congestion data and the physical length of the metasegment, calculate the logical length of the metasegment at the corresponding time, thereby establishing a dynamic update mechanism for the logical length of the metasegment; the logical length calculation method is expressed as follows:

[0061]

[0062] in, This represents the logical length of the meta segment at that moment. This is the physical length of the meta-segment;

[0063] S3-2: Based on dynamically added flight requirements, extract information such as aircraft type, takeoff and landing sites, destination takeoff and landing sites, and takeoff time from the flight requirements, and calculate and update the logical length of the meta-segment;

[0064] S3-3: After all meta-segment logical lengths are updated, based on the digital representation of the network topology relationships between low-altitude airway network elements, the takeoff and landing fields and destination takeoff and landing fields in the newly added flight requirements are used as the start and end points of network path planning, and the updated meta-segment logical lengths are used as the edge lengths in the network structure. The algorithm generates paths between start and end points in this network, thereby constructing low-altitude flight routes under dynamic flight requirements;

[0065] S3-4: Combine the dynamic flight demand with the low-altitude flight path generated in step S3-3 to form a complete flight plan. Add the complete flight plan to the low-altitude pre-flight plan dataset and execute step S2 to update the spatiotemporal distribution map of low-altitude airway network congestion.

[0066] Further, step S3-2 includes:

[0067] S3-2-1: Traverse the aircraft type information of the meta segment. For meta segments whose aircraft type does not include the aircraft type corresponding to the flight requirements, set their logical length to infinity.

[0068] S3-2-2: For meta segments whose logical length is not set to infinite, combine the takeoff time information in the flight demand, extract the congestion data of the meta segment at that time from the spatiotemporal distribution map of low-altitude airway network congestion, and update the logical length of the meta segment using the logical length calculation method in step S3-1.

[0069] Further, step S4 includes:

[0070] S4-1: Set congestion level and configure the display style of meta segments under different congestion levels;

[0071] S4-2: Based on the set congestion level, calculate the congestion level of each meta-segment and at each time point in the updated spatiotemporal distribution map of low-altitude airway network congestion.

[0072] S4-3: Proceeding in discrete time sequence, displaying the congestion status of the airway network frame by frame, thereby predicting and verifying the availability of dynamic airway planning.

[0073] Based on the same inventive concept, the present invention provides a low-altitude flight route dynamic planning and simulation device based on airway network congestion assessment, comprising a processor and a memory. The memory stores computer instructions, and the processor executes the computer instructions stored in the memory. When the computer instructions are executed by the processor, the low-altitude flight route dynamic planning and simulation device based on airway network congestion assessment implements the steps of the low-altitude flight route dynamic planning and simulation method based on airway network congestion assessment.

[0074] Based on the same inventive concept, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for dynamic planning and simulation of low-altitude flight routes based on airway network congestion assessment as described above.

[0075] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0076] (1) The modeling and description method of the low-altitude airway network in this invention provides a more comprehensive and effective description of the network relationships between elements of the low-altitude airway network, and is more suitable for dynamic planning and simulation of flight routes under low-altitude high-density operation conditions.

[0077] (2) The virtual waypoints and meta-segments constructed in this invention divide the low-altitude physical segments, enabling more refined segment congestion calculation and prediction, and supporting more scientific flight route planning.

[0078] (3) This invention constructs and dynamically updates the spatiotemporal distribution map of low-altitude air route network congestion, and establishes a dynamic update mechanism for the logical length of the meta-segment. Based on this, according to the real-time newly added flight demand, low-altitude flight routes that avoid congested segments are dynamically generated, which is more in line with the characteristics of high dynamics, strong real-time performance and weak planning of low-altitude flight route planning, and meets the requirements of high-density low-altitude flight for efficient use of airspace.

[0079] (4) The method for airway network operation status simulation and visualization proposed in this invention improves the predictability of low-altitude airway network operation and better verifies the rationality of flight route planning. This invention can be used in low-altitude operator systems and low-altitude air traffic control systems. Attached Figure Description

[0080] Figure 1 This is a flowchart of a method for dynamic planning and simulation of low-altitude flight routes based on airway network congestion assessment provided by an embodiment of the present invention;

[0081] Figure 2 This is a schematic diagram of the low-altitude airway network in an embodiment of the present invention;

[0082] Figure 3 This is a flowchart illustrating the dynamic generation process of low-altitude flight routes in an embodiment of the present invention. Detailed Implementation

[0083] The invention will now be further described with reference to the accompanying drawings.

[0084] The present invention will now be described in detail with reference to specific embodiments. Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable by the present invention will become clearer from the following detailed description.

[0085] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application, design, and conditions of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0086] In this invention, the term "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this invention can be combined with other embodiments.

[0087] Example 1: As Figure 1 As shown, Example 1 provides a dynamic planning and simulation method for low-altitude flight routes based on route network congestion assessment, including the following steps:

[0088] S1: Construct a low-altitude airway network model, and based on the low-altitude airway network model, form standardized low-altitude airway network structure data to realize the digital expression of the network topology relationship between low-altitude airway network elements.

[0089] Step S1 includes:

[0090] S1-1: Set the length of the monitoring unit for the congestion assessment segment of the low-altitude airway network. Divide each physical segment in the low-altitude airway network according to the length of the monitoring unit. The segmented segment is defined as a meta segment. Physical segments whose length is less than or equal to the length of the monitoring unit and are not divided are also classified as meta segments. Add new waypoints at the division points and define them as virtual waypoints.

[0091] like Figure 2 The diagram of the low-altitude airway network shown is simplified for ease of explanation, idealizing it into four horizontal parallel routes and five vertical parallel routes (the actual low-altitude airway network is not necessarily parallel, but the subsequent processing method is the same), and assuming the area is [missing information]. (The distance between horizontal and vertical parallel routes is 2km), and the area includes to There are a total of 7 take-off and landing fields, including to There are a total of 20 physical waypoints. Physical waypoints are connected to each other, and physical waypoints are connected to takeoff and landing points, forming physical segments. part, Section, etc.

[0092] The length of the monitoring unit for congestion assessment of the low-altitude airway network is set to 1 km (the smaller the monitoring unit length, the higher the granularity of the congestion assessment). Each physical segment in the low-altitude airway network is divided according to the monitoring unit length. Specifically, a virtual waypoint is added every 1 km (monitoring unit length) from the start point to the end point of the physical segment until the remaining segment length is less than or equal to 1 km. The segment is at a distance from the starting point Add a virtual waypoint 1km away from the waypoint The remaining flight segments The length is 1km, no additional virtual waypoints are needed, physical flight segment Segmentation complete; no segmentation is needed for physical flight segments whose length is less than or equal to the monitoring unit length, such as... Segment. The segmented flight segment is defined as the meta-segment, such as the meta-segment. , Physical segments whose length is less than or equal to the length of the monitoring unit and have not been segmented are also classified as meta-segments, such as... The length of each flight segment is less than or equal to the length of the monitoring unit set.

[0093] S1-2: The low-altitude airway network is decomposed into elements of takeoff and landing fields, physical waypoints, virtual waypoints, meta segments, and physical segments. Takeoff and landing fields, physical waypoints, and virtual waypoints are abstracted into point elements, and meta segments and physical segments are abstracted into line elements. The low-altitude airway network model is constructed by describing the five types of elements: takeoff and landing fields, physical waypoints, virtual waypoints, meta segments, and physical segments.

[0094] Step S1-2 includes:

[0095] S1-2-1: Takeoff and landing field elements Described as:

[0096]

[0097] in, This is the sequence number of the takeoff and landing field element in the takeoff and landing field data; Representing the The code name of each take-off and landing field; Representing the Basic information about each take-off and landing site, including its name, type, latitude and longitude location, and elevation.

[0098] Representing the The network connectivity relationships of the takeoff and landing fields are described as follows:

[0099]

[0100] in, This refers to the number of connections between the takeoff and landing site and the low-altitude airway network. Representing the first takeoff and landing field The connection is established through the meta-segment. Connect to point elements Point elements It can be a physical waypoint or a virtual waypoint.

[0101] With take-off and landing field For example, suppose the sequence number of this takeoff and landing field in the takeoff and landing field data is 1. It can be described as: ,in This is the code name for the takeoff and landing field. Basic information about the takeoff and landing field. The network connectivity of this takeoff and landing field This indicates that the takeoff and landing field has only one network connection, namely through the meta-segment. Connect to point elements .

[0102] S1-2-2: Physical waypoint elements Described as:

[0103]

[0104] in, This is the sequence number of the physical waypoint element in the physical waypoint data; Representing the The code of each physical waypoint; Representing the Basic information about each physical waypoint, including its name and latitude / longitude.

[0105] Representing the The network connectivity relationships of the physical waypoints are described as follows:

[0106]

[0107] in, This represents the number of connections between the physical waypoint and the low-altitude airway network. Represents the physical waypoint number The connection is established through the meta-segment. Connect to point elements Point elements It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site.

[0108] By physical waypoints For example, suppose the physical waypoint's sequence number in the physical waypoint data is 1. It can be described as: ,in This is the designation of the physical waypoint. Basic information about the physical waypoint. The network connectivity of this physical waypoint This represents a total of 3 network connections for this physical waypoint, one of which is through the meta-segment. Connected to the take-off and landing field Secondly, through the Yuanhang segment Connect to virtual waypoint Thirdly, through the Yuanhang segment Connect to virtual waypoint .

[0109] S1-2-3: Incorporate virtual waypoint elements Described as:

[0110]

[0111] in, This is the sequence number of the virtual waypoint element in the virtual waypoint data; Representing the The code name of a virtual waypoint; Representing the Basic information about each virtual waypoint, including its name and latitude / longitude location.

[0112] Representing the The network connectivity relationships of the virtual waypoints are described as follows:

[0113]

[0114] in, This represents the number of connections between the virtual waypoint and the low-altitude airway network. Represents the virtual waypoint number The connection is established through the meta-segment. Connect to point elements Point elements It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site.

[0115] With virtual waypoints For example, suppose the virtual waypoint's index in the virtual waypoint data is 1. It can be described as: ,in This is the designation for the virtual waypoint. Basic information about the virtual waypoint. The network connectivity of this virtual waypoint This indicates that the virtual waypoint has two network connections, one through the meta segment. Connect to physical waypoint Secondly, through the Yuanhang segment Connect to physical waypoint .

[0116] S1-2-4: Elements of the initial voyage segment Described as:

[0117]

[0118] in, This is the sequence number of the element in the meta-segment data; Representing the The code name for each segment of the flight; Representing the Basic information for each meta segment, including the meta segment's physical length, altitude range, width, logical length, and applicable aircraft type.

[0119] Representing the The network connectivity relationships of each flight segment are described as follows:

[0120]

[0121] in, Point elements associated with the starting point of this meta-segment; The point element representing the endpoint of this meta-segment; This represents the physical segment to which the meta segment belongs, including its point elements. , It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site.

[0122] Yuanhangduan For example, suppose the sequence number of this meta segment in the meta segment data is 1, then the meta segment... It can be described as: ,in This is the code name for this meta-segment. Basic information about this meta-segment. The network connectivity of this segment. This indicates that the starting point of this voyage segment is The destination is The physical flight segment to which it belongs is .

[0123] S1-2-5: Physical flight segment elements Described as:

[0124]

[0125] in, This is the sequence number of the physical segment element in the physical segment data; Representing the The code name for each physical flight segment; Representing the Basic information about each physical flight segment, including its length, altitude range, width, and applicable aircraft types.

[0126] Representing the The network connectivity relationships of each physical flight segment are described as follows:

[0127]

[0128] in, The number of meta segments associated with this physical segment, which is composed of... , … common It consists of several segments.

[0129] Based on physical flight segments For example, suppose the sequence number of this physical segment in the physical segment data is 1, and the physical segment... Can be described as ,in This is the code name for the physical flight segment. Basic information about this physical flight segment. The network connectivity of this physical flight segment. This means that the physical flight segment consists of 2 meta-segments. and composition.

[0130] S2: Based on the low-altitude pre-flight plan, extrapolation and calculation are performed to form a spatiotemporal distribution map of low-altitude airway network congestion.

[0131] Step S2 includes:

[0132] S2-1: Based on the low-altitude pre-flight plan and the associated aircraft type, a discrete time step is set. Using a dynamic model, the meta-segment of the corresponding aircraft for each discrete time step in the low-altitude pre-flight plan is calculated. This allows for the unfolding of the low-altitude pre-flight plan's information in both time and space dimensions. The unfolded low-altitude pre-flight plan... Described as:

[0133]

[0134] in, This is the sequence number of the low-altitude pre-flight plan in the low-altitude pre-flight plan data; Representing the The code name for a low-altitude pre-flight plan; Representing the Basic information for a low-altitude pre-flight plan includes aircraft type, takeoff time, takeoff and landing sites, destination takeoff and landing sites, and physical waypoint sequence.

[0135] Representing the The meta-segment sequence data, after unfolding the time and spatial dimension information of the low-altitude pre-flight plan, is described as follows:

[0136]

[0137] in, The number of discrete moments spanned by the entire lifecycle of the low-altitude pre-flight plan, from takeoff to landing; This represents the low-altitude pre-flight plan in the The meta-segment at each discrete moment.

[0138] Table 1 shows some of the pre-flight plan data in the low-altitude pre-flight plan.

[0139] Table 1: Partial Pre-flight Plan Data

[0140]

[0141] Based on the takeoff times in the low-altitude pre-flight plan data, the earliest time in all low-altitude pre-flight plans is extracted, corresponding to time 0 of the discrete time. The discrete time step is set to 1 second (a smaller step provides more precision and can be set as needed). Combining the aircraft type in each low-altitude pre-flight plan, a dynamic model is used to calculate the meta-segment of each aircraft at each discrete time for each flight plan, thereby realizing the information unfolding of the pre-flight plan in the time and space dimensions. The correspondence between the planned spatiotemporal information and the meta-segment is shown in Table 2.

[0142] Table 2: Correspondence between planned spatiotemporal information unfolding and meta-segments

[0143]

[0144] by For example, the plan, once unfolded, can be described as follows: ,in This is the code name for the program. Basic information about the program. The plan's meta-segment sequence data after unfolding the temporal and spatial dimensions. , which represents the meta-segment in which the spacecraft is located at each discrete moment.

[0145] S2-2: Traverse the meta-segment sequence data under each low-altitude pre-flight plan, and aggregate to form the flight plan association information of the meta-segment in the time dimension; The first segment of the journey was in the... The time-related sequence of low-altitude pre-flight plans is represented as follows:

[0146]

[0147] in, For the first The first segment of the journey was in the... The number of low-altitude pre-flight plans linked to specific times; For the first The first segment of the journey was in the... The first time associated with time A low-altitude pre-flight plan.

[0148] Yuanhangduan For example, at the second discrete time step, this meta-segment has four plans. , , , If the corresponding aircraft is in use, then the sequence of pre-flight plans associated with that meta-segment at that discrete moment can be represented as follows: .

[0149] S2-3: Construct a congestion assessment model for each meta-segment, calculate the congestion degree of each meta-segment at each discrete time, and thus form a spatiotemporal distribution map of congestion degree of the low-altitude airway network.

[0150] Step S2-3 includes:

[0151] S2-3-1: A congestion assessment model for the metasegment is constructed by considering the number of low-altitude pre-flight plans associated with the metasegment at that moment, the metasegment's length, width, altitude range, and the aircraft types of the associated flight plans. The congestion level of the metasegment at that moment is... Represented as:

[0152]

[0153] in, This is the length of the meta-segment; This is the width of the current segment; This refers to the altitude range of this segment; This represents the number of low-altitude pre-flight plans associated with this segment at this time. , , For the first Each low-altitude preflight plan corresponds to the longitudinal, lateral, and vertical safety intervals for the aircraft type.

[0154] The meta segment at the second discrete time. For example, the flight segment is 1000 meters long, 350 meters wide, and has an altitude range of 300 meters - 120 meters = 180 meters. This moment is associated with 4 plans. , , , The corresponding aircraft models are all medium-sized drones, with longitudinal, lateral, and vertical safety intervals set at 670 meters, 170 meters, and 110 meters respectively. These parameters are then used in the formula for calculation.

[0155]

[0156] S2-3-2: Traverse the low-altitude pre-flight plan sequence associated with each metasegment at each discrete time, and calculate the congestion degree of each metasegment at each discrete time based on the metasegment congestion assessment model.

[0157] The congestion levels of each meta-segment at each discrete time point are shown in Table 3.

[0158] Table 3: Congestion degree of each meta-segment at each discrete time point

[0159]

[0160] S3: Based on dynamically added flight demand and combined with the congestion distribution of the airway network, generate low-altitude flight routes in real time and update the spatiotemporal distribution map of low-altitude airway network congestion.

[0161] Step S3 includes:

[0162] S3-1: Based on the time when the metasegment is used in the flight route, extract the congestion data of the metasegment at that time from the spatiotemporal distribution map of congestion in the low-altitude airway network. Based on the congestion data and the physical length of the metasegment, calculate the logical length of the metasegment at the corresponding time, thereby establishing a dynamic update mechanism for the logical length of the metasegment; the logical length calculation method is expressed as follows:

[0163]

[0164] in, This represents the logical length of the meta segment at that moment. This is the physical length of the meta-segment; This represents the congestion level of that segment at that moment.

[0165] The meta segment at the second discrete time. For example, if its physical length is 1000 meters and the congestion level at that moment is 0.7955, its logical length can be calculated as 1000. 0.7955 = 795.5 meters.

[0166] S3-2: As Figure 3 As shown, based on dynamically added flight requirements, the aircraft type, takeoff and landing sites, destination takeoff and landing sites, and takeoff time information are extracted from the flight requirements, and the logical length of the meta-segment is calculated and updated.

[0167] Step S3-2 includes:

[0168] S3-2-1: Traverse the aircraft type information of the meta segment. For meta segments whose aircraft type does not include the aircraft type corresponding to the flight requirements, set their logical length to infinity.

[0169] Add a new entry for discrete time 675. Take off to Taking the flight requirements of large aircraft as an example, the suitable aircraft type information of the original flight segment is traversed to determine whether it includes large aircraft. If it does not include large aircraft, its logical length is set to infinity. , The logical length of the equal segment is set to infinity.

[0170] S3-2-2: For meta segments whose logical length is not set to infinite, combine the takeoff time information in the flight demand, extract the congestion data of the meta segment at that time from the spatiotemporal distribution map of low-altitude airway network congestion, and update the logical length of the meta segment using the logical length calculation method in step S3-1.

[0171] S3-3: After all meta-segment logical lengths are updated, based on the digital representation of the network topology relationships between low-altitude airway network elements, the takeoff and landing fields and destination takeoff and landing fields in the newly added flight requirements are used as the start and end points of network path planning, and the updated meta-segment logical lengths are used as the edge lengths in the network structure. The algorithm generates paths between origin and destination points within this network, thereby constructing low-altitude flight routes under dynamic flight requirements. The waypoint sequence is as follows: Effectively avoid , Flight segments with incompatible aircraft types, and Wait for flight segments with high congestion.

[0172] S3-4: Combine the dynamic flight demand with the low-altitude flight path generated in step S3-3 to form a complete flight plan. Add the complete flight plan to the low-altitude pre-flight plan dataset and execute step S2 to update the spatiotemporal distribution map of low-altitude airway network congestion.

[0173] S4: To predict and simulate the operational status of the airway network, and to visualize the congestion level of the airway network.

[0174] Step S4 includes:

[0175] S4-1: Set congestion level and configure the display style of meta segments under different congestion levels;

[0176] Three congestion levels are set: smooth, mildly congested, and severely congested. A congestion level less than 0.4 is considered smooth, 0.4-0.7 is considered mildly congested, and greater than 0.7 is considered severely congested. The different congestion levels are displayed in green, yellow, and red, respectively.

[0177] S4-2: Based on the set congestion level, calculate the congestion level of each meta-segment and at each time point in the updated spatiotemporal distribution map of low-altitude airway network congestion.

[0178] S4-3: Proceeding in discrete time sequence, displaying the congestion status of the airway network frame by frame, thereby predicting and verifying the availability of dynamic airway planning.

[0179] In summary, this invention models the low-altitude airway network, calculates and describes the spatiotemporal distribution of congestion in the low-altitude airway network, and generates flight routes that avoid congested segments in real time based on dynamically added flight demands. This effectively addresses the characteristics of high dynamism, strong real-time requirements, and weak planning in low-altitude flight route planning, and meets the requirements of efficient airspace utilization for high-density low-altitude flights. Furthermore, by simulating the operation of the airway network through visualization, the predictability of the low-altitude airway network operation is improved.

[0180] Example 2: Example 2 provides a low-altitude flight route dynamic planning and simulation device based on airway network congestion assessment, including a processor and a memory. The memory stores computer instructions, and the processor executes the computer instructions stored in the memory. When the computer instructions are executed by the processor, the low-altitude flight route dynamic planning and simulation device based on airway network congestion assessment implements the steps of the low-altitude flight route dynamic planning and simulation method based on airway network congestion assessment as described in Example 1, and achieves the same technical effect.

[0181] The memory may include computer system readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory. The device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the memory may be used to read and write non-removable, non-volatile magnetic media (commonly referred to as a "hard disk drive"). A program / utility having a set (at least one) of program modules may be stored in, for example, memory. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules typically perform the functions and / or methods described in the embodiments of the present invention.

[0182] The processor executes various functional applications and data processing by running programs stored in memory, such as implementing the low-altitude flight route dynamic planning and simulation method based on airway network congestion assessment provided in Embodiment 1 of the present invention.

[0183] Example 3: Example 3 provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the low-altitude flight route dynamic planning and simulation method based on airway network congestion assessment as described in Example 1, and achieves the same technical effect.

[0184] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0185] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0186] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0187] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0188] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the above-described method operations, but can also perform related operations in the methods provided in any embodiment of the present invention.

[0189] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dynamic planning and simulation method for low-altitude flight routes based on route network congestion assessment, characterized in that, include: S1: Construct a low-altitude airway network model, and based on the low-altitude airway network model, form standardized low-altitude airway network structure data to realize the digital expression of the network topology relationship between low-altitude airway network elements; S2: Based on the low-altitude pre-flight plan, extrapolation and calculation are performed to form a spatiotemporal distribution map of low-altitude airway network congestion. S3: Based on dynamically added flight demand and combined with the airway network congestion distribution, generate low-altitude flight routes in real time and update the spatiotemporal distribution map of low-altitude airway network congestion. S4: To predict and simulate the operational status of the airway network, and to visualize the congestion of the airway network. Step S1 includes: S1-1: Set the length of the monitoring unit for the congestion assessment segment of the low-altitude airway network. Divide each physical segment in the low-altitude airway network according to the length of the monitoring unit. The segmented segment is defined as a meta-segment. Physical segments whose length is less than or equal to the length of the monitoring unit and are not divided are also classified as meta-segments. Add new waypoints at the division points and define them as virtual waypoints. S1-2: The low-altitude airway network is decomposed into elements of take-off and landing fields, physical waypoints, virtual waypoints, meta segments, and physical segments. Take-off and landing fields, physical waypoints, and virtual waypoints are abstracted into point elements, and meta segments and physical segments are abstracted into line elements. The low-altitude airway network model is constructed by describing the five types of elements: take-off and landing fields, physical waypoints, virtual waypoints, meta segments, and physical segments. Step S2 includes: S2-1: Based on the low-altitude pre-flight plan and the associated aircraft type, a discrete time step is set. Using a dynamic model, the meta-segment of the corresponding aircraft for each discrete time step in the low-altitude pre-flight plan is calculated. This allows for the unfolding of the low-altitude pre-flight plan's information in both time and space dimensions. The unfolded low-altitude pre-flight plan... Described as: in, This is the sequence number of the low-altitude pre-flight plan in the low-altitude pre-flight plan data; Representing the The code name for a low-altitude pre-flight plan; Representing the Basic information for a low-altitude pre-flight plan includes aircraft type, takeoff time, takeoff and landing sites, destination takeoff and landing sites, and physical waypoint sequence. Representing the The meta-segment sequence data, after unfolding the time and spatial dimension information of the low-altitude pre-flight plan, is described as follows: in, The number of discrete moments spanned by the entire lifecycle of the low-altitude pre-flight plan, from takeoff to landing; This represents the low-altitude pre-flight plan in the The meta-segment where each discrete moment occurs; S2-2: Traverse the meta-segment sequence data under each low-altitude pre-flight plan, and aggregate to form the flight plan association information of the meta-segment in the time dimension; The first segment of the journey was in the... The time-related sequence of low-altitude pre-flight plans is represented as follows: in, For the first The first segment of the journey was in the... The number of low-altitude pre-flight plans linked to specific times; For the first The first segment of the journey was in the... The first time associated with time A low-altitude pre-flight plan; S2-3: Construct a congestion assessment model for each meta-segment, calculate the congestion degree of each meta-segment at each discrete time, and thus form a spatiotemporal distribution map of congestion degree of the low-altitude airway network. Step S3 includes: S3-1: Based on the time when the metasegment is used in the flight route, extract the congestion data of the metasegment at that time from the spatiotemporal distribution map of congestion in the low-altitude airway network. Based on the congestion data and the physical length of the metasegment, calculate the logical length of the metasegment at the corresponding time, thereby establishing a dynamic update mechanism for the logical length of the metasegment; the logical length calculation method is expressed as follows: in, This represents the logical length of the meta segment at that moment. This is the physical length of the meta-segment; S3-2: Based on dynamically added flight requirements, extract information such as aircraft type, takeoff and landing sites, destination takeoff and landing sites, and takeoff time from the flight requirements, and calculate and update the logical length of the meta-segment; S3-3: After all meta-segment logical lengths are updated, based on the digital representation of the network topology relationships between low-altitude airway network elements, the takeoff and landing fields and destination takeoff and landing fields in the newly added flight requirements are used as the start and end points of network path planning, and the updated meta-segment logical lengths are used as the edge lengths in the network structure. The algorithm generates paths between start and end points in this network, thereby constructing low-altitude flight routes under dynamic flight requirements; S3-4: Combine the dynamic flight demand with the low-altitude flight path generated in step S3-3 to form a complete flight plan. Add the complete flight plan to the low-altitude pre-flight plan dataset and execute step S2 to update the spatiotemporal distribution map of low-altitude airway network congestion.

2. The method for dynamic planning and simulation of low-altitude flight routes based on route network congestion assessment according to claim 1, characterized in that, Step S1-2 includes: S1-2-1: Takeoff and landing field elements Described as: in, This is the sequence number of the takeoff and landing field element in the takeoff and landing field data; Representing the The code name of each take-off and landing field; Representing the Basic information about each take-off and landing site, including the name, type, latitude and longitude location, and elevation of the take-off and landing site; Representing the The network connectivity relationships of the takeoff and landing fields are described as follows: in, This refers to the number of connections between the takeoff and landing site and the low-altitude airway network. Representing the first takeoff and landing field The connection is established through the meta-segment. Connect to point elements Point elements Are they physical waypoints or virtual waypoints? S1-2-2: Physical waypoint elements Described as: in, This is the sequence number of the physical waypoint element in the physical waypoint data; Representing the The code of each physical waypoint; Representing the Basic information about each physical waypoint, including the name and latitude / longitude of the physical waypoint; Representing the The network connectivity relationships of the physical waypoints are described as follows: in, This represents the number of connections between the physical waypoint and the low-altitude airway network. Represents the physical waypoint number The connection is established through the meta-segment. Connect to point elements Point elements It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site; S1-2-3: Incorporate virtual waypoint elements Described as: in, This is the sequence number of the virtual waypoint element in the virtual waypoint data; Representing the The code name of a virtual waypoint; Representing the Basic information about each virtual waypoint, including the name and latitude / longitude of the virtual waypoint; Representing the The network connectivity relationships of the virtual waypoints are described as follows: in, This represents the number of connections between the virtual waypoint and the low-altitude airway network. Represents the virtual waypoint number The connection is established through the meta-segment. Connect to point elements Point elements It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site; S1-2-4: Elements of the initial voyage segment Described as: in, This is the sequence number of the element in the meta-segment data; Representing the The code name for each segment of the flight; Representing the Basic information of each meta segment, including the physical length, altitude range, width, logical length, and applicable aircraft type of the meta segment; Representing the The network connectivity relationships of each flight segment are described as follows: in, Point elements associated with the starting point of this meta-segment; The point element representing the endpoint of this meta-segment; This represents the physical segment to which the meta segment belongs, including its point elements. , It can be a physical waypoint, a virtual waypoint, or a takeoff and landing site; S1-2-5: Physical flight segment elements Described as: in, This is the sequence number of the physical segment element in the physical segment data; Representing the The code name for each physical flight segment; Representing the Basic information about each physical flight segment, including the length, altitude range, width, and applicable aircraft types of the physical flight segment; Representing the The network connectivity relationships of each physical flight segment are described as follows: in, The number of meta segments associated with this physical segment, which is composed of... , … common It consists of several segments.

3. The method for dynamic planning and simulation of low-altitude flight routes based on route network congestion assessment according to claim 1, characterized in that, Step S2-3 includes: S2-3-1: A congestion assessment model for the metasegment is constructed by considering the number of low-altitude pre-flight plans associated with the metasegment at that moment, the metasegment's length, width, altitude range, and the aircraft types of the associated flight plans. The congestion level of the metasegment at that moment is... Represented as: in, This is the length of the meta-segment; This is the width of the current segment; This refers to the altitude range of this segment; This represents the number of low-altitude pre-flight plans associated with this segment at this time. , , For the first Each low-altitude preflight plan corresponds to the longitudinal, lateral, and vertical safety separations for the aircraft type. S2-3-2: Traverse the low-altitude pre-flight plan sequence associated with each metasegment at each discrete time, and calculate the congestion degree of each metasegment at each discrete time based on the metasegment congestion assessment model.

4. The method for dynamic planning and simulation of low-altitude flight routes based on route network congestion assessment according to claim 1, characterized in that, Step S3-2 includes: S3-2-1: Traverse the aircraft type information of the meta segment. For meta segments whose aircraft type does not include the aircraft type corresponding to the flight requirements, set their logical length to infinity. S3-2-2: For meta segments whose logical length is not set to infinite, combine the takeoff time information in the flight demand, extract the congestion data of the meta segment at that time from the spatiotemporal distribution map of low-altitude airway network congestion, and update the logical length of the meta segment using the logical length calculation method in step S3-1.

5. The method for dynamic planning and simulation of low-altitude flight routes based on route network congestion assessment according to claim 4, characterized in that, Step S4 includes: S4-1: Set congestion level and configure the display style of meta segments under different congestion levels; S4-2: Based on the set congestion level, calculate the congestion level of each meta-segment and at each time point in the updated spatiotemporal distribution map of low-altitude airway network congestion. S4-3: Proceeding in discrete time sequence, displaying the congestion status of the airway network frame by frame, thereby predicting and verifying the availability of dynamic airway planning.

6. A dynamic planning and simulation device for low-altitude flight routes based on route network congestion assessment, characterized in that, The device includes a processor and a memory, wherein the memory stores computer instructions, and the processor executes the computer instructions stored in the memory. When the computer instructions are executed by the processor, the low-altitude flight route dynamic planning and simulation device based on airway network congestion assessment implements the steps of the low-altitude flight route dynamic planning and simulation method based on airway network congestion assessment as described in any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the low-altitude flight route dynamic planning and simulation method based on airway network congestion assessment as described in any one of claims 1 to 5.

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