Aircraft operation simulation method, system and equipment based on cellular automaton

Abstract

The invention discloses an aircraft operation simulation method, system and device based on a cellular automaton, and the method comprises the steps: obtaining air route network information, and constructing a cell according to the air route network information; determining a position identifier corresponding to each cell according to the route of each cell and the position of each cell on the route, and determining the state of the cell according to the aircraft running in the cell; determining operation parameters corresponding to a to-be-simulated target aircraft, and performing normalization processing on the operation parameters according to the length of the leg cell; detecting an operation scene where the target aircraft is located, and simulating operation of the target aircraft according to the operation scene; wherein the types of the operation scenes comprise a conflict-free scene, an afflux scene, a shunting scene and an interleaving scene. According to the method, small-range parallel operation of simulation can be supported, tedious re-calculation and synchronization processes are avoided, and the simulation cost is effectively reduced. The method can be widely applied to operation simulation.

Description

Technical Field

[0001] The present application relates to operation simulation, and in particular to an aircraft operation simulation method, system and device based on cellular automata. Background Art

[0002] In order to solve the problem of urban traffic congestion, the three-dimensional application of urban space will become one of the key ways. In recent years, with the development of low-altitude transportation services, the concept of UAM (Urban Air Mobility) has been proposed, which uses eVTOL (electric vertical take-off and landing) type vehicles in cities for manned and cargo transportation, and uses the vast low-altitude airspace as a new carrier for urban transportation.

[0003] With the promotion of the low-altitude concept, the urban low-altitude logistics system in the near future and the urban low-altitude traffic passenger flow system in the long term will develop rapidly, and the channel-level refined low-altitude aircraft operation simulation technology will become a research hotspot. At present, there are many simulation architectures for low-altitude aircraft, such as MATSim-UAM and Opensky for urban low-altitude traffic operation and evaluation, MATLAB, Simulink UAM Toolbox and SUMO-UAM modules for aircraft microdynamics modeling, and some researchers have built a more efficient simulation framework based on multi-agent simulation technology. However, these current simulation technologies all use a graph-based network, that is, a network composed of nodes and edges for simulation. During the movement, the simulation object follows the queue model on the edge and the rule-based release model on the node to realize the continuous simulation of traffic flow. The computational complexity is high, and it is difficult to respond to dynamic changes such as traffic accidents and road control. The simulation efficiency and degree of freedom are poor, and often fail to meet expectations.

[0004] In summary, the problems existing in related technologies need to be solved urgently. Summary of the invention

[0005] The purpose of this application is to solve one of the technical problems existing in the related art to at least a certain extent.

[0006] To this end, an object of an embodiment of the present application is to provide an aircraft operation simulation method, system and device based on cellular automata.

[0007] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present application include:

[0008] On the one hand, an embodiment of the present application provides an aircraft operation simulation method based on cellular automata, the method comprising:

[0009] Acquire route network information, and construct cells according to the route network information; wherein the types of cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circular, and the cells are used to accommodate at most one aircraft in the running simulation;

[0010] Determine the position identifier corresponding to each cell according to the route and the position of each cell on the route, and determine the state of the cell according to the aircraft running in the cell;

[0011] Determine the operating parameters corresponding to the target aircraft to be simulated, and normalize the operating parameters according to the length of the flight segment cell; wherein the operating parameters include the expected flight speed, the maximum flight speed, the starting acceleration and the braking acceleration;

[0012] The operation scenario of the target aircraft is detected, and the operation of the target aircraft is simulated according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenarios, merging scenarios, diversion scenarios, and interweaving scenarios.

[0013] In addition, the aircraft operation simulation method based on cellular automata according to the above embodiment of the present application may also have the following additional technical features:

[0014] Furthermore, in one embodiment of the present application, simulating the operation of the target aircraft according to the operation scenario includes:

[0015] If the target aircraft is in a non-conflict scenario, an acceleration is performed based on the speed corresponding to the previous simulation step according to the startup acceleration to obtain a first speed;

[0016] Detecting the speed of a previous flight of aircraft corresponding to the target aircraft and the relative distance between the target aircraft and the previous flight of aircraft, and determining a safe distance according to the speed of the previous flight of aircraft and the relative distance;

[0017] According to the safety distance, deceleration determination is performed on the target aircraft based on the first speed to obtain a second speed;

[0018] If the relative distance is greater than the product of the predetermined aircraft departure interval and the desired flight speed, performing secondary acceleration on the target aircraft based on the second speed to obtain a third speed;

[0019] The position of the target aircraft in the cell is updated according to the third speed.

[0020] Further, in one embodiment of the present application, determining the safety distance according to the speed of the previous flight aircraft and the relative distance includes:

[0021] If the speed of the aircraft of the previous flight is 0, the safety distance is determined as a predetermined minimum safety distance;

[0022] Alternatively, if the speed of the previous flight of aircraft is greater than the speed of the target aircraft, the safety distance is determined according to the product of the aircraft departure interval and the speed of the target aircraft;

[0023] Alternatively, if the speed of the previous flight of aircraft is greater than 0 and less than or equal to the speed of the target aircraft, the safety distance is determined according to the difference between the relative distance and the flight distance of the previous flight of aircraft in a single simulation step.

[0024] Furthermore, in one embodiment of the present application, the detecting the operation scenario of the target aircraft and simulating the operation of the target aircraft according to the operation scenario includes:

[0025] If it is detected that the target aircraft enters the merging range, it is determined that the target aircraft is in the merging scene, and the merging route, target route and merging point corresponding to the current route of the target aircraft are determined;

[0026] Determine the corresponding merging priorities of other aircraft on the merging route and the target aircraft;

[0027] If the merging priority of the target aircraft is lower than the merging priority of the other aircraft, the relative distance between the target aircraft and the other aircraft after merging into the target route is detected. If the relative distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

[0028] Further, in one embodiment of the present application, the determining of the merging priorities of other aircraft on the merging route and the target aircraft includes:

[0029] detecting a speed of the target aircraft and a first merging distance between the target aircraft and the merging point;

[0030] detecting a speed of the other aircraft and a second merging distance between the other aircraft and the merging point;

[0031] determining a first merging time corresponding to the target aircraft according to the speed of the target aircraft and the first merging distance;

[0032] determining a second merging time corresponding to the other aircraft according to the speed of the other aircraft and the second merging distance;

[0033] If the first import time is less than the second import time, it is determined that the import priority of the target aircraft is higher than the import priority of the other aircraft; or, if the first import time is greater than the second import time, it is determined that the import priority of the target aircraft is lower than the import priority of the other aircraft.

[0034] Furthermore, in one embodiment of the present application, simulating the operation of the target aircraft according to the operation scenario includes:

[0035] If the target aircraft is in a diversion scenario, determining the last flight aircraft on the route to which the target aircraft is diverted;

[0036] Detecting a first distance between the target aircraft and a diversion point and a second distance between the previous flight aircraft and the diversion point;

[0037] If the sum of the first distance and the second distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

[0038] Further, simulating the operation of the target aircraft according to the operation scenario includes:

[0039] If the target aircraft is in an interweaving scene, the interweaving route and the interweaving point corresponding to the current route of the target aircraft are determined;

[0040] Determining the interleaving priorities of other aircraft on the interleaving route and the target aircraft;

[0041] If the interleaving priority of the target aircraft is higher than the interleaving priority of the other aircraft, detecting whether a conflict occurs between the target aircraft and the other aircraft;

[0042] If the target aircraft and the other aircraft do not conflict, detecting a third distance between the target aircraft and the intersecting point and a fourth distance between the previous flight of the target aircraft and the intersecting point;

[0043] If the sum of the third distance and the fourth distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

[0044] On the other hand, an embodiment of the present application provides an aircraft operation simulation system based on cellular automata, the system comprising:

[0045] An acquisition unit, used to acquire route network information, and construct cells according to the route network information; wherein the types of cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circular, and the cells are used to accommodate at most one aircraft in the running simulation;

[0046] an identification unit, used to determine a position identification corresponding to each of the cells according to the route on which each of the cells is located and the position on the route, and to determine the state of the cell according to the aircraft running in the cell;

[0047] A processing unit, used for determining operating parameters corresponding to the target aircraft to be simulated, and normalizing the operating parameters according to the length of the flight segment cell; wherein the operating parameters include expected flight speed, maximum flight speed, starting acceleration and braking acceleration;

[0048] An execution unit is used to detect the operation scenario of the target aircraft and simulate the operation of the target aircraft according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenarios, merging scenarios, diversion scenarios and interweaving scenarios.

[0049] On the other hand, an embodiment of the present application provides an electronic device, including:

[0050] at least one processor;

[0051] at least one memory for storing at least one program;

[0052] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned aircraft operation simulation method based on cellular automation.

[0053] On the other hand, an embodiment of the present application further provides a computer-readable storage medium, which stores a program executable by a processor. When the program executable by the processor is executed by the processor, it is used to implement the above-mentioned cellular automaton-based aircraft operation simulation method.

[0054] The advantages and benefits of the present application will be partially given in the following description, and partially become apparent from the following description, or be understood through the practice of the present application:

[0055] The aircraft operation simulation method, system and device based on cellular automata disclosed in the embodiments of the present application obtain route network information and construct cells according to the route network information; wherein the types of cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circles, and the cells are used to accommodate at most one aircraft in the operation simulation; according to the route on which each cell is located and the position on the route, the position identifier corresponding to each cell is determined, and the state of the cell is determined according to the aircraft running in the cell; the operation parameters corresponding to the target aircraft to be simulated are determined, and the operation parameters are normalized according to the length of the segment cell; wherein the operation parameters include expected flight speed, maximum flight speed, starting acceleration and braking acceleration; the operation scenario of the target aircraft is detected, and the operation of the target aircraft is simulated according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenario, merging scenario, diversion scenario and interweaving scenario. This method is based on the simulation logic of cellular state update. It evolves the specific actions of the simulation object through a small number of neighborhood cellular states. It can support small-scale parallel operation of the simulation and avoid tedious recalculation and synchronization processes, effectively reducing the simulation cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following introduction is made to the drawings of the embodiments of the present application or the related technical solutions in the prior art. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present application. For technical personnel in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0057] Figure 1 A schematic diagram of an implementation environment of an aircraft operation simulation method based on cellular automata provided in an embodiment of the present application;

[0058] Figure 2 A schematic diagram of a flow chart of an aircraft operation simulation method based on cellular automata provided in an embodiment of the present application;

[0059] Figure 3 A schematic diagram of a flight segment cell provided in an embodiment of the present application;

[0060] Figure 4 A schematic diagram of an inflow cell and a diversion cell provided in an embodiment of the present application;

[0061] Figure 5 A schematic diagram of a non-vertical interlaced cell provided in an embodiment of the present application;

[0062] Figure 6 A schematic diagram of a vertically interwoven cell provided in an embodiment of the present application;

[0063] Figure 7 A schematic diagram of a cellular neighborhood provided in an embodiment of the present application;

[0064] Figure 8 A schematic diagram of an aircraft motion evolution rule in a non-conflict scenario provided in an embodiment of the present application;

[0065] Fig. 9 A schematic diagram of an import scenario provided in an embodiment of the present application;

[0066] Fig.10 A schematic diagram of an aircraft motion evolution rule in a merge scenario provided in an embodiment of the present application;

[0067] Fig.11 A schematic diagram of a traffic diversion scenario provided in an embodiment of the present application;

[0068] Fig.12 A schematic diagram of an aircraft motion evolution rule in a diversion scenario provided in an embodiment of the present application;

[0069] Fig.13 A schematic diagram of an interweaving scenario provided in an embodiment of the present application;

[0070] Fig.14 A schematic diagram of the evolution rules of aircraft motion in an interweaving scenario provided in an embodiment of the present application. DETAILED DESCRIPTION

[0071] The present application is further described below in conjunction with the accompanying drawings and specific embodiments. The described embodiments should not be regarded as limiting the present application, and all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0072] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0073] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0074] In order to solve the problem of urban traffic congestion, the three-dimensional application of urban space will become one of the key ways. In recent years, with the development of low-altitude transportation services, the concept of UAM (Urban Air Mobility) has been proposed, which uses eVTOL (electric vertical take-off and landing) type vehicles in cities for manned and cargo transportation, and uses the vast low-altitude airspace as a new carrier for urban transportation.

[0075] With the promotion of the low-altitude concept, the urban low-altitude logistics system in the near future and the urban low-altitude traffic passenger flow system in the long term will develop rapidly, and the channel-level refined low-altitude aircraft operation simulation technology will become a research hotspot. At present, there are many simulation architectures for low-altitude aircraft, such as MATSim-UAM and Opensky for urban low-altitude traffic operation and evaluation, MATLAB, Simulink UAM Toolbox and SUMO-UAM modules for aircraft microdynamics modeling, and some researchers have built a more efficient simulation framework based on multi-agent simulation technology. However, these current simulation technologies all use a graph-based network, that is, a network composed of nodes and edges for simulation. During the movement, the simulation object follows the queue model on the edge and the rule-based release model on the node to realize the continuous simulation of traffic flow. The computational complexity is high, and it is difficult to respond to dynamic changes such as traffic accidents and road control.

[0076] Specifically, the traffic network based on the graph structure is composed of nodes and edges connecting the nodes. The edges have attributes such as maximum capacity, free flow speed, length, number of lanes, etc., which can be used to represent road sections, lanes, and tracks in the traffic system; nodes release and allocate traffic through relevant rules, and can be used to represent intersections and stations in the traffic system. The simulation of graph structure networks mainly relies on path search algorithms and network flow analysis. Dijkstra and A* algorithms are usually used to search for the shortest path, and then the dynamic simulation of traffic flow is realized by simulation step by step. The simulation output will be determined by the simulation framework used. Traditional simulation and event-based simulation will output the status information of traffic participants such as location, speed, time, etc. for each simulation step and key event node.

[0077] The network model based on the graph structure can clearly represent and distinguish the different elements and element relationships in the traffic network, and is easy to integrate with the path planning algorithm, which is suitable for large-scale network analysis. Correspondingly, the queue-based road section simulation increases the computational complexity of the model, and the model is difficult to respond to dynamic changes in the road caused by traffic accidents, one-way control, etc., which reduces the simulation efficiency and degree of freedom. In addition, this implementation method also has the following problems:

[0078] 1) The network construction process is complex and requires consideration of the interaction between different elements. It is only suitable for irregular and complex networks with multiple connection relationships between nodes.

[0079] 2) Limited simulation efficiency: The dynamic processing in path planning and simulation relies on complex rules and algorithms, which consume a lot of computing power and are only suitable for scenarios that do not emphasize real-time performance.

[0080] 3) Low degree of simulation parallelization: Limited by the dependency relationship between nodes and edges, the network data of the graph structure is irregular and continuous, making it difficult to effectively divide parallel tasks within a small range. Frequent recalculation and synchronization are required, resulting in a high simulation cost.

[0081] In view of this, an embodiment of the present application provides an aircraft operation simulation method based on cellular automata, which obtains route network information and constructs cells according to the route network information; wherein the types of cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circles, and the cells are used to accommodate at most one aircraft in the operation simulation; according to the route on which each cell is located and the position on the route, the position identifier corresponding to each cell is determined, and the state of the cell is determined according to the aircraft running in the cell; the operation parameters corresponding to the target aircraft to be simulated are determined, and the operation parameters are normalized according to the length of the segment cell; wherein the operation parameters include expected flight speed, maximum flight speed, starting acceleration and braking acceleration; the operation scenario of the target aircraft is detected, and the operation of the target aircraft is simulated according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenarios, merging scenarios, diversion scenarios and interweaving scenarios. This method is based on the simulation logic of cellular state update. It evolves the specific actions of the simulation object through a small number of neighborhood cellular states. It can support small-scale parallel operation of the simulation and avoid tedious recalculation and synchronization processes, effectively reducing the simulation cost.

[0082] Please refer to Figure 1 , Figure 1 The schematic diagram of the implementation environment of an aircraft operation simulation method based on cellular automata provided in the embodiment of the present application is shown. In the implementation environment, the main hardware and software entities involved include a terminal device 110 and a backend server 120. The terminal device 110 and the backend server 120 are connected in communication.

[0083] Specifically, the aircraft operation simulation method based on cellular automata provided in the embodiments of the present application can be configured on the background server 120 side and executed based on the data interaction between the terminal device 110 and the background server 120. Among them, the terminal device 110 of the above embodiment may include a mobile phone, a computer, a smart wearable device, an intelligent voice interaction device, a vehicle terminal, etc., but is not limited to this. The background server 120 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0084] The terminal device 110 and the backend server 120 may establish a communication connection via a wireless network or a wired network. The wireless network or wired network uses standard communication technology and / or protocols, and the network may be set to the Internet or any other network, such as but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or any combination of a virtual private network.

[0085] Of course, it is understandable that Figure 1 The implementation environment in the embodiment of the present application is only some optional application scenarios of the aircraft operation simulation method based on cellular automation, and the actual application is not fixed. Figure 1 The hardware and software environment shown.

[0086] Below, in combination with the introduction of the aforementioned implementation environment, an aircraft operation simulation method based on cellular automata provided in an embodiment of the present application is introduced and explained.

[0087] Please refer to Figure 2 , Figure 2 is a schematic diagram of an aircraft operation simulation method based on cellular automata provided in an embodiment of the present application. Specifically, the aircraft operation simulation method based on cellular automata provided in an embodiment of the present application includes but is not limited to:

[0088] Step 210: Acquire route network information, and construct cells according to the route network information; wherein the types of cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circular, and the cells are used to accommodate at most one aircraft in the running simulation;

[0089] Step 220: determining a position identifier corresponding to each cell according to the route and the position of each cell on the route, and determining the state of the cell according to the aircraft running in the cell;

[0090] Step 230, determining the operating parameters corresponding to the target aircraft to be simulated, and normalizing the operating parameters according to the length of the flight segment cell; wherein the operating parameters include the expected flight speed, the maximum flight speed, the starting acceleration and the braking acceleration;

[0091] Step 240, detecting the operation scenario of the target aircraft, and simulating the operation of the target aircraft according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenarios, merging scenarios, diversion scenarios, and interweaving scenarios.

[0092] In an embodiment of the present application, a method for simulating the operation of an aircraft based on cellular automata is provided. The method constructs a low-altitude traffic network model based on cellular automata, uses cells of a specific size to construct a network and a traffic rule system, and realizes continuous simulation of the operation of low-altitude aircraft through cellular state updates. The interaction relationship between cells is simple, and the network construction is efficient. The core of the simulation logic based on cellular state updates is to rely on local rules to confirm the state of the cell in the next simulation step. The update rules are simple and the simulation speed is fast. Moreover, the state update design based on the state of the neighborhood cells can evolve the specific actions of the simulation object through a small number of neighborhood cell states, which can support small-scale parallel operation of the simulation and avoid cumbersome recalculation and synchronization processes, effectively reducing the simulation cost.

[0093] Specifically, in the embodiment of the present application, the route network information can be first obtained, and cells can be constructed based on the route network information. In the embodiment of the present application, the types of cells can include two types: segment cells and node cells, which respectively constitute the route network of the non-conflict scenario and the special nodes such as confluence, diversion, and interweaving in the conflict scenario. A single aircraft only occupies one cell at a time. Please refer to Figure 3 , Figure 3 A schematic diagram of a flight segment cell provided in an embodiment of the present application is shown. In the embodiment of the present application, the flight segment cell is a square of the same size, which can be used for flight simulation of a single aircraft. A single channel allows at most one aircraft to fly in the same section, so the width of a single channel is 1 cell width. The number of cells that make up the channel depends on the length of the channel. If the channel is 10 km long and the side length L of a single cell is 20 m, the channel is composed of 500 cells arranged in sequence.

[0094] The node cell is circular, and the radius depends on the scene type where the cell is located and the angle of the interweaving routes. Node cells are used to simulate the flight segments where conflicts occur between aircraft. There are three types of aircraft conflicts in routes. Aircraft on multiple routes merge into one route at the same time, which is a merging conflict. Aircraft on one route flow into multiple routes at the same time, which is a diversion conflict. Aircraft on two routes are close to each other or overlap at the same altitude and time, which is an interweaving conflict. In the embodiment of the present application, the three conflicts are respectively managed by merging cells, diversion cells, and interweaving cells. These three types of cells are all node cells. For example, please refer to Figures 4 to 6 , Figure 4 Schematic diagram of the inflow cell and the diversion cell provided in the embodiment of the present application is shown, Figure 5 Schematic diagram of non-vertical interlaced cells provided in an embodiment of the present application is shown, Figure 6 A schematic diagram of a vertical interleaving cell provided in an embodiment of the present application is shown. In the embodiment of the present application, the confluence cell, the diversion cell and the interleaving cell are circular, and the cell radius depends on the interleaving type and the interleaving angle. For non-vertical interleaving cells, the smaller the interleaving angle of the two lines, the larger the cell radius, and the larger the detection area and conflict range of the cell; for vertical interleaving cells, the detection area and conflict range are fixed values.

[0095] In the embodiment of the present application, for each cell, the position identifier corresponding to each cell can be determined according to their position. Specifically, it is the route and the position on the route. For example, if a cell is on the i-th route and the j-th cell position (i and j are both positive integers), it can be represented by the two-dimensional coordinates (i, j). In the embodiment of the present application, the state of the cell can also be determined according to the situation of the aircraft running in each cell. For example, A can be used to represent the state of the cell, and A ij ∈{0, 1..V exp , V exp +1, ..V max}, when A ij = 0, indicating that the cell corresponding to the two-dimensional coordinate (i, j) is currently empty, and there is no aircraft in it; when A ij =V, V∈{1..V exp , V exp +1, ..V max}, it means that the cell corresponding to the two-dimensional coordinates (i, j) is occupied by a flying vehicle with a speed of V.

[0096] In the embodiment of the present application, in order to facilitate the subsequent data processing, the corresponding operating parameters of the aircraft to be simulated (referred to as the target aircraft) can be obtained. The operating parameters here can include the expected flight speed, maximum flight speed, starting acceleration and braking acceleration. Then, the operating parameters can be normalized according to the length of the flight segment cell. Specifically, in the embodiment of the present application, the flight speed of the aircraft in the cellular space is represented by the number of cells that can pass through per unit time. Let the actual expected flight speed of the aircraft be V rea_des , the maximum flight speed is V rea_max , in m / s, the cellular flight speed of the aircraft in the flight segment can be calculated by the following formula:

[0097] V exp =V rea_des / / L

[0098] V max =V rea_max / / L

[0099] Where L is the length of the flight segment cell.

[0100] Similarly, let the actual starting acceleration of the aircraft be a rea_acc , the braking acceleration is a rea_dec , unit is m / s 2 , are all positive values, then the calculation of the starting acceleration and braking acceleration of the aircraft in the cellular network is as follows:

[0101] a acc =a rea_acc / L

[0102] a dec =a rea_dec / L

[0103] For example, the current maximum flight speed of a certain aircraft is 220km / h, the expected flight speed is 150km / h, and the startup and running acceleration is 7.5m / s 2 , braking acceleration is 10m / s 2 , assuming that the length of the flight segment cell side L is 20m. The above formula shows that the theoretical maximum speed of the aircraft in the cellular space is about 60m / s, which is three cell lengths, and the theoretical expected speed is about 40m / s, which is two cell lengths. Therefore, it can be concluded that the corresponding maximum speed and expected speed are V max =3, V exp =2, the starting acceleration and braking acceleration are a respectively acc =0.375 and a dec =0.5.

[0104] In addition, in the embodiments of the present application, a cell domain can also be defined. Figure 7 , Figure 7 A schematic diagram of a cellular neighborhood provided in an embodiment of the present application is shown. Figure 7 In the figure, the dark cells represent the current cell position of the target aircraft, and the light cells are the movable neighborhood of the target aircraft in the next second. Considering that there is only one route in a single channel and the maximum flight speed of the target aircraft, the neighborhood of each flight segment cell is set as the V after the current cell and the travel direction. max A cell.

[0105] In the embodiment of the present application, after the above-mentioned model parameters are established, the operation of the target aircraft can be simulated by cellular automata. Specifically, the operation scenario of the target aircraft can be detected, and then the operation of the target aircraft can be simulated according to the operation scenario, so as to achieve the state control of the aircraft. In the embodiment of the present application, the types of operation scenarios can include conflict scenarios, merging scenarios, diversion scenarios, and interweaving scenarios.

[0106] The simulation process in each of the above scenarios is introduced and explained below.

[0107] Specifically, in some embodiments, simulating the operation of the target aircraft according to the operation scenario includes:

[0108] If the target aircraft is in a non-conflict scenario, an acceleration is performed based on the speed corresponding to the previous simulation step according to the startup acceleration to obtain a first speed;

[0109] Detecting the speed of a previous flight of aircraft corresponding to the target aircraft and the relative distance between the target aircraft and the previous flight of aircraft, and determining a safe distance according to the speed of the previous flight of aircraft and the relative distance;

[0110] According to the safety distance, deceleration determination is performed on the target aircraft based on the first speed to obtain a second speed;

[0111] If the relative distance is greater than the product of the predetermined aircraft departure interval and the desired flight speed, performing secondary acceleration on the target aircraft based on the second speed to obtain a third speed;

[0112] The position of the target aircraft in the cell is updated according to the third speed.

[0113] In the embodiment of the present application, the non-conflict scenario is the basic scenario for the aircraft to move, which refers to the flight process of the route far away from the conflict point. If the target aircraft is in a non-conflict scenario, the cell position of the current aircraft at time t is Xi,j (t), X i,j (t)≥0, the speed of the aircraft at time t is V i，j (t). Without special circumstances, the aircraft moves along the route at the expected speed V exp When the distance is too large or too small, the aircraft can be allowed to slow down or speed up to the maximum speed V max Run, the evolution parameters and rules of the current cell are as follows:

[0114] X i,j (t+1)=f(X i,j (t), V i，j (t), D i , T i ,d,T,V exp , V max , N i , a)

[0115] X i,j (t)——The cell position of the jth aircraft on route i at time t

[0116] V i，j (t)——the flight speed of the jth aircraft on route i at time t;

[0117] D i ——The minimum safe distance between two aircraft on route i;

[0118] T i - minimum safe time interval for aircraft operation;

[0119] d——The actual distance between the cell where the current aircraft is located and the nearest non-empty cell in the direction of travel;

[0120] T——Time to make up the distance. When the time between the aircraft and the previous aircraft exceeds this value, the current aircraft will accelerate to make up the distance difference.

[0121] V exp ——The expected flight speed of the aircraft in the cellular network;

[0122] V max ——The maximum flight speed of the aircraft in the cellular network;

[0123] t——simulation step time;

[0124] N i --The minimum safe distance of the next aircraft when the speed of the previous aircraft is 0;

[0125] a——The acceleration of the aircraft in the cellular network, which represents the change in the aircraft speed in a single simulation step. According to the judgment of the acceleration or deceleration state of the aircraft in the evolution rule, the acceleration of the aircraft when starting and accelerating is a. acc The braking and deceleration acceleration of the aircraft is a dec , both of which are positive values.

[0126] Reference Figure 8 , Figure 8 A schematic diagram of an aircraft motion evolution rule in a non-conflict scenario provided in an embodiment of the present application is shown. In the embodiment of the present application, the essence of the motion evolution rule is to comprehensively consider factors such as the aircraft's safety distance, flight speed, and cell state in the current simulation step to determine the moving distance (i.e., speed) of the target aircraft in the next simulation step. In a non-conflict scenario, the judgment is divided into the following four steps:

[0127] Step 1: One-time acceleration

[0128] By default, the speed of the target aircraft is increased by a based on the speed of the previous simulation step to obtain the first speed. Here, if the aircraft has reached the desired speed, the speed remains unchanged. The purpose of this step is to make the aircraft fly as fast as possible but not exceeding the desired speed.

[0129] Step 2: Slow down

[0130] The deceleration process is divided into two steps. First, the safe distance of the target aircraft is determined according to different situations. Then, the new flight speed is calculated based on one acceleration to obtain the second speed.

[0131] Specifically, the judgment of the safe distance needs to consider the speed and relative distance between the target aircraft and the previous flight aircraft. If the current speed of the previous flight aircraft is 0, the safe distance D between the two aircraft is N i cells, which is the predetermined minimum safety distance; if the flight speed of the previous flight is greater than the flight speed of the target aircraft, the safety distance D is the time interval multiplied by the flight speed of the target aircraft; otherwise, when the flight speed of the previous flight is between 0 and the flight speed of the target aircraft, the safety distance D is the difference between the current actual distance and the flight distance of the previous flight in a single simulation step. Finally, the smaller value is selected as the aircraft speed of the next simulation step between the current speed and the actual distance d minus the safety distance D, so as to ensure that the target aircraft will not collide with the previous aircraft in the next simulation step.

[0132] Step 3: Secondary acceleration

[0133] Determine whether the actual distance d between the target aircraft and the previous flight exceeds the product of the aircraft departure interval and the expected aircraft speed. If it exceeds, it means that the distance between the aircraft is too far. You can accelerate based on the current speed to shorten the intermediate distance to ensure the flight space of the subsequent flight aircraft, that is, get the third speed. If it does not exceed, no adjustment is made.

[0134] Step 4: Location Update

[0135] Through Step 1-Step 3, the aircraft already has a certain speed that can be used for simulation. Based on this speed value, the aircraft will update its position in the one-dimensional cellular network, that is, the original position plus the speed of the target aircraft multiplied by a unit simulation step.

[0136] It is understandable that during low-altitude operation, the distance between the aircraft itself is relatively long, and the safety tolerance space is relatively large. Unlike ground traffic that allows queuing, low-altitude aircraft are more expected not to queue or stop during the entire operation process. Therefore, it is particularly important to maintain the relative distance between aircraft on a straight route. The distance between aircraft will not cause safety risks due to being too close, nor will it cause uneven distribution of aircraft on the route due to being too far, thereby affecting the efficiency of passing through the conflict point. Based on the above reasons, this application is improved on the basis of traditional CTM, and the "random slowing down" link of road traffic is replaced by "secondary acceleration", which is used to determine whether to speed up the target aircraft a second time based on the distance between the target aircraft and the previous aircraft, and at the same time, the direct speed update is corrected to affect the speed update by updating the acceleration. So that the aircraft are as close as possible on the basis of a safe distance, and the update granularity is more detailed, ensuring the operation density of aircraft on the route and the continuity of simulation.

[0137] Specifically, in some embodiments, detecting the operation scenario of the target aircraft and simulating the operation of the target aircraft according to the operation scenario includes:

[0138] If it is detected that the target aircraft enters the merging range, it is determined that the target aircraft is in the merging scene, and the merging route, target route and merging point corresponding to the current route of the target aircraft are determined;

[0139] Determine the corresponding merging priorities of other aircraft on the merging route and the target aircraft;

[0140] If the merging priority of the target aircraft is lower than the merging priority of the other aircraft, the relative distance between the target aircraft and the other aircraft after merging into the target route is detected. If the relative distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

[0141] In the embodiment of the present application, in the merging scenario, a one-way route scenario where two routes merge into one route is discussed. Fig. 9 , Fig. 9 A schematic diagram of a merging scenario provided in an embodiment of the present application is shown. In the embodiment of the present application, the model under the merging scenario is used to simulate the scenario where aircraft on multiple routes converge on a main channel, mainly considering the flight status of the aircraft on each route and the distance from the nearest aircraft passing on the main channel. First, under the premise that the aircraft on all routes are in a normal flight state and within a safe distance, the distance from each aircraft on the route to the merging cell is monitored. When an aircraft is detected to enter the merging range, the merging judgment algorithm is executed. Fig. 9 For example, assuming that the aircraft AVeh 1,5 First, once the aircraft enters the detection range, it is necessary to determine the distance, speed and other travel conditions of the aircraft. The determination formula and evolution rules are as follows:

[0142] X i,j (t+1)=f(X i,j (t), V i，j (t), d1, d2, d3, D i , V exp , V max , a, p)

[0143] X i,j (t)——the cell position of the jth aircraft on route i at time t;

[0144] AV i，j ——jth aircraft on route i;

[0145] V i，j (t)——the flight speed of the jth aircraft on route i at time t;

[0146] d1——the cellular distance between the nearest merging aircraft and the merging point on route 1;

[0147] d2——the cellular distance between the nearest merging aircraft and the merging point on route 2;

[0148] d3——the cellular distance between the nearest merging aircraft and the merging point on the main route;

[0149] D i ——The minimum safe travel distance of the aircraft on route i;

[0150] V exp ——The expected flight speed of the aircraft in the cellular network;

[0151] V max——The maximum flight speed of the aircraft in the cellular network;

[0152] a——The acceleration of the aircraft in the cellular network, which represents the maximum value of the change in the aircraft speed in a single simulation step. According to the judgment of the acceleration or deceleration state of the aircraft in the evolution rule, when the aircraft is about to start and accelerate, the acceleration is a. acc When the aircraft is braking or decelerating, the acceleration is a dec ;

[0153] P——The probability of the aircraft randomly speeding up or slowing down, the default value is 0.5. When two aircraft arrive at the conflict point at the same time, the system will increase or decrease the speed of one of the aircraft according to the conditions to distinguish the arrival priority of the aircraft.

[0154] Reference Fig.10 , Fig.10 A schematic diagram of the evolution rules of aircraft motion in a merging scenario provided in an embodiment of the present application is shown. In the embodiment of the present application, when the detector finds that the target aircraft has entered the merging range, it will first determine the entry priority of each aircraft based on the distance between the aircraft in the current range and the merging cell and the degree of congestion in the queue where the aircraft is located; then, based on factors such as the aircraft spacing between the merging route and the main route, the flight speed, and the position difference of the aircraft on the merging route, the merging is achieved by controlling the flight speed of the aircraft. In addition to allowing aircraft to pass under normal circumstances, there are also situations where the merging section is found to be more crowded, in which case it will be determined to reduce the overall speed of the crowded route, delay departure, and other operations. The specific judgment process is as follows:

[0155] Priority judgment: When the aircraft of multiple routes converge into one route, firstly, the time for the aircraft to reach the confluence point shall be calculated according to the current simulation step flight speed of the aircraft and the distance from the confluence point, and the confluence priority shall be determined according to the length of time. The priority of the confluence shall be the highest if the time distance is short, and vice versa. For the target aircraft, the confluence route, target route and confluence point corresponding to the route where it is located can be detected, and the route where the target aircraft is located and the confluence route are confluenced into the target route at the confluence point. Then, the confluence priority corresponding to other aircraft and the target aircraft on the confluence route can be determined. Specifically, the speed of the target aircraft and the first confluence distance between the target aircraft and the confluence point are detected, and the first confluence time corresponding to the target aircraft is determined according to the first confluence distance and the speed of the target aircraft, and the speed of other aircraft and the second confluence distance between other aircraft and the confluence point are detected, and the second confluence time corresponding to other aircraft is determined according to the second confluence distance and the speed of other aircraft. The two are compared, and the aircraft with the smaller confluence time is determined as the aircraft with high priority.

[0156] Speed ​​judgment:

[0157] ① Assuming that the target aircraft will reach the merging point first, the highest priority it obtains must ensure that the target aircraft can maintain the required minimum safety distance to enter the merging route when passing through the merging point in turn. Therefore, the relative distance between the two aircraft is judged here. If the distance is greater than the minimum safety distance to merge into the target route, other aircraft can maintain the original speed and pass freely; if the distance does not meet the minimum safety distance condition, other aircraft need to slow down.

[0158] ② Assuming that the target aircraft is currently judged to arrive at the merging point later: its passage priority is lower than other aircraft on other routes. The relative distance between the two aircraft is also judged. If the distance is greater than the minimum safe distance to merge into the target route, the target aircraft can maintain the original speed and pass normally; otherwise, the target aircraft needs to slow down to make way for other aircraft with higher priority to leave the minimum safe distance and provide deceleration space.

[0159] Position movement: Perform displacement operation on the aircraft according to the final speed result obtained in the above judgment process.

[0160] Specifically, in some embodiments, simulating the operation of the target aircraft according to the operation scenario includes:

[0161] If the target aircraft is in a diversion scenario, determining the last flight aircraft on the route to which the target aircraft is diverted;

[0162] Detecting a first distance between the target aircraft and a diversion point and a second distance between the previous flight aircraft and the diversion point;

[0163] If the sum of the first distance and the second distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

[0164] In the embodiment of the present application, the model in the diversion scenario is used to handle the scenario where the main channel aircraft is about to sail to a different route. The aircraft needs to be released based on the flight status of the main channel aircraft and the existing path planning results, mainly considering the distance factor between the current main channel aircraft and the nearest general aircraft on the route to be diverted. First, under the premise that all aircraft on the route are in normal flight status and within a safe distance, the distance from each aircraft on the route involved to the diversion cell is monitored. When an aircraft is detected to enter the diversion management range, the diversion determination algorithm is executed. Refer to Fig.11 , Fig.11 FIG. 1 is a schematic diagram of a traffic diversion scenario provided in an embodiment of the present application. Fig.11 For example, assuming that the aircraft AVeh 1,6First, once the aircraft enters the detection range, it is necessary to determine the distance, speed and other travel conditions of the aircraft. The determination formula and evolution rules are as follows:

[0165] X i，j (t+1)=f(X i，j (t), V i，j (t), d1, d2, d3, D i , a)

[0166] X i，j (t)——the cell position of the jth aircraft on route i at time t;

[0167] AV i，j ——jth aircraft on route i;

[0168] V i，j (t)——the flight speed of the jth aircraft on route i at time t;

[0169] d1——the cell distance from the aircraft to be diverted on the main channel to the diversion point;

[0170] d2——the cellular distance between the nearest diversion aircraft and the diversion point on route 2;

[0171] d3——the cellular distance between the nearest diversion aircraft on route 1 and the diversion point;

[0172] D i ——The minimum safe travel distance of the aircraft on route i;

[0173] a——The acceleration of the aircraft in the cellular network, which represents the maximum value of the change in the aircraft speed in a single simulation step. According to the judgment of the acceleration or deceleration state of the aircraft in the evolution rule, when the aircraft is about to start and accelerate, the acceleration is a. acc When the aircraft is braking or decelerating, the acceleration is a dec ;

[0174] i ob ——The target route number of the current aircraft.

[0175] Reference Fig.12 , Fig.12A schematic diagram of the evolution rules of aircraft motion in a diversion scenario provided in an embodiment of the present application is shown. In the embodiment of the present application, the specific release judgment process of the diversion model is as follows: first, the number of the route to which the target aircraft is diverted is obtained, assuming that the target aircraft is the aircraft closest to the diversion point and is about to be diverted to route 1. Then the distance between the target aircraft and the previous aircraft on route 1 is summed, that is, the first distance between the target aircraft and the diversion point and the second distance between the previous aircraft and the diversion point are detected. If the sum of the two distances is greater than the minimum safety distance, the aircraft can maintain the original speed and pass safely; if it is less than the minimum safety distance, the target aircraft is decelerated. Compared with the merging process, the diversion process mostly belongs to the process of aircraft density from high to low, the judgment process is simple, and there are relatively few conflicts.

[0176] Specifically, in some embodiments, simulating the operation of the target aircraft according to the operation scenario includes:

[0177] If the target aircraft is in an interweaving scene, the interweaving route and the interweaving point corresponding to the current route of the target aircraft are determined;

[0178] Determining the interleaving priorities of other aircraft on the interleaving route and the target aircraft;

[0179] If the interleaving priority of the target aircraft is higher than the interleaving priority of the other aircraft, detecting whether a conflict occurs between the target aircraft and the other aircraft;

[0180] If the target aircraft and the other aircraft do not conflict, detecting a third distance between the target aircraft and the intersecting point and a fourth distance between the previous flight of the target aircraft and the intersecting point;

[0181] If the sum of the third distance and the fourth distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

[0182] In the embodiment of the present application, the model in the interweaving scenario is used to simulate the process of aircraft on two routes traveling at the intersection of the routes. Fig.13 , Fig.13 A schematic diagram of an interleaving scenario provided in an embodiment of the present application is shown. Fig.13 In the figure, the outer light-colored circle represents the monitoring range of the weaving area, and the inner dark-colored circle represents the conflict range. Under the assumption that all aircraft on the route are in normal flight status and within a safe distance, when an aircraft enters the weaving monitoring range, the model implements algorithms such as priority determination and speed determination to enable the aircraft to pass through the weaving area. Fig.13 For example, assuming that the aircraft AVeh 1，4First, once the aircraft enters the detection range, it is necessary to determine the distance, speed and other travel conditions of the aircraft. The determination formula and evolution rules are as follows:

[0183] X i,j (t+1)=f(X i,j (t), V i，j (t),d1,d2,d3,d4,D,D i , V exp , V max , d, a, p)

[0184] X i,j (t)——the cell position of the jth aircraft on route i at time t;

[0185] AV i，j ——jth aircraft on route i;

[0186] V i，j (t)——the flight speed of the jth aircraft on route i at time t;

[0187] d1——the cellular distance between the target aircraft entering the monitoring range on route 1 and the intersection point;

[0188] d2——the cellular distance between the aircraft on route 2 that is about to reach the intersection point and the intersection point;

[0189] d3——the cellular distance between the last aircraft leaving the intersection point on route 1 and the intersection point;

[0190] d4——the cellular distance between the last aircraft leaving the intersection point on route 2 and the intersection point;

[0191] D——Cell radius of aircraft conflict zone in interweaving scenario;

[0192] D i ——safe flight interval for route i;

[0193] V exp ——The expected flight speed of the aircraft in the cellular network;

[0194] V max ——The maximum flight speed of the aircraft in the cellular network;

[0195] d——cell radius of the aircraft monitoring area in the interweaving scenario;

[0196] a——The acceleration of the aircraft in the cellular network, which represents the maximum value of the change in the aircraft speed in a single simulation step. According to the judgment of the acceleration or deceleration state of the aircraft in the evolution rule, when the aircraft is about to start and accelerate, the acceleration is a. acc, when the aircraft needs to brake or decelerate, the acceleration is taken as a dec ;

[0197] p—the probability of the aircraft randomly increasing or decreasing speed, with a default value of 0.5. When two aircraft will reach the conflict point simultaneously, the system increases or decreases the speed of one of the aircraft according to the conditions to distinguish the arrival priority of the aircraft.

[0198] Refer to Fig.14 , Fig.14 shows a schematic diagram of the motion evolution rule of an aircraft in an interleaved scenario provided in an embodiment of the present application. In the embodiment of the present application, when an aircraft enters the monitoring area, it is detected and identified as an interleaved object by the system, and then the interleaving priority is judged; when two aircraft appear in the conflict area at the same time, it is determined that a conflict occurs. According to the design of the motion evolution rule of the aircraft in the interleaving model in this study, when the aircraft enters the interleaving area, the following judgment process will be carried out:

[0199] Priority confirmation: When multiple flight routes are interleaved, first calculate the time for the aircraft to reach the interleaving point according to the current simulation step flight speed of the aircraft and the distance from the interleaving point at the interleaving point, and determine the priority of passing through the interleaving point according to the length of the time. The highest priority is given to the one with the shortest time distance, and the lowest priority is given to the one with the longest time distance.

[0200] Speed judgment:

[0201] Assume that the current target object aircraft AVdh 1，4 will reach the confluence point first: Then it obtains the highest passing priority, and determines the interleaved flight route and the interleaving point corresponding to the current flight route of the target aircraft. First, judge whether the target aircraft and other aircraft on the interleaved flight route will appear in the conflict area with a radius of D around the interleaving point when passing through the interleaving point in turn through V2*(d1 + D) / V1 + D < d2. If this condition is met, no conflict will occur; if not, a conflict will occur. When no conflict will occur, it is necessary to judge whether the current safety distance of the limited passing route meets the condition of d1 + d3 > D1. If it meets, the target aircraft can pass at the original speed; if not, the target aircraft decelerates; when a conflict will occur, also judge the condition of d1 + d3 > D1. If it meets, the target aircraft accelerates through to widen the safety distance from the next passing flight; if not, the target aircraft maintains the original speed and the line may conflict.

[0202] Assume that the current judgment object aircraft AVdh 1，4Arriving at the intersection after the meeting: Its traffic priority is lower than that of other routes. At this time, the flight safety distance judgment of another route is carried out: V1*(d2 + D) / V2 + D < d1. If this condition is met, there will be no conflict; otherwise, there will be a conflict. When there is no conflict, it is judged whether the current aircraft AVdh on another airway 2，6 meets the safety distance by judging d2 + d4 > D2. If it meets, the aircraft can pass freely at the original speed, and the original judgment target aircraft AVdh 1，4 does not need to change its flight state; if it does not meet, the target aircraft AVdh 1，4 decelerates to provide deceleration space for high-priority aircraft. When there is a conflict, the target aircraft AVdh 1，4 decelerates to avoid the conflict and at the same time provides deceleration space for high-priority aircraft.

[0203] Position movement: According to the final speed result obtained from the above judgment process, displacement operation is carried out on the target aircraft AVdh 1，4

[0204] It can be understood that the technical solutions provided in the embodiments of the present application at least have the following technical effects:

[0205] 1. The model based on cellular automata replaces the update of the state of the simulation object by updating the state of cells, and at the same time supports parallel simulation, which can effectively improve the operation speed of large-scale simulation.

[0206] 2. The simulation based on cellular automata is realized by the state evolution update of cells according to corresponding rules. An individual can make the next simulation operation decision only based on its local environment and the states of adjacent cells, making the model have high self-organization and robustness, and being able to more naturally simulate the route interaction and conflict resolution process of large-scale aircraft.

[0207] 3. The network structure of the cell space and the aircraft operation process can be directly visualized according to the cell state, with higher visualization efficiency and more intuitiveness, especially when reflecting the dynamic changes of large-scale low-altitude aircraft clusters.

[0208] In the embodiments of the present application, a flight simulation system based on cellular automata is also provided. The flight simulation system based on cellular automata includes:

[0209] An acquisition unit, configured to acquire airway network information and construct cells according to the airway network information; wherein, the types of the cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circles, and the cells are used to accommodate at most one aircraft in the operation simulation;

[0210] ​an identification unit, used to determine a position identification corresponding to each of the cells according to the route on which each of the cells is located and the position on the route, and to determine the state of the cell according to the aircraft running in the cell;

[0211] A processing unit, used for determining operating parameters corresponding to the target aircraft to be simulated, and normalizing the operating parameters according to the length of the flight segment cell; wherein the operating parameters include expected flight speed, maximum flight speed, starting acceleration and braking acceleration;

[0212] An execution unit is used to detect the operation scenario of the target aircraft and simulate the operation of the target aircraft according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenarios, merging scenarios, diversion scenarios and interweaving scenarios.

[0213] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0214] The present application also provides an electronic device, including:

[0215] at least one processor;

[0216] at least one memory for storing at least one program;

[0217] When at least one program is executed by at least one processor, the at least one processor implements the above-mentioned aircraft operation simulation method based on cellular automation.

[0218] The electronic device of the embodiment of the present application may be a terminal device, a computer device or a server device.

[0219] Similarly, the contents of the above method embodiments are all applicable to the electronic device embodiments. The functions specifically implemented by the electronic device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0220] An embodiment of the present application also provides a computer-readable storage medium, in which a program executable by a central processing unit is stored. When the program executable by the central processing unit is executed by the central processing unit, it is used to execute the above-mentioned cellular automaton-based aircraft operation simulation method.

[0221] Similarly, the contents of the above method embodiments are all applicable to the computer-readable storage medium embodiments. The functions specifically implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0222] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part described as a larger operation is performed independently.

[0223] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0224] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0225] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0226] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0227] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0228] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0229] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0230] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the embodiments. Technical personnel familiar with the field can make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A method for simulating aircraft operation based on cellular automata, characterized in that: The method comprises: Acquire route network information, and construct cells according to the route network information; wherein the types of cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circular, and the cells are used to accommodate at most one aircraft in the running simulation; Determine the position identifier corresponding to each cell according to the route and the position of each cell on the route, and determine the state of the cell according to the aircraft running in the cell; Determine the operating parameters corresponding to the target aircraft to be simulated, and normalize the operating parameters according to the length of the flight segment cell; wherein the operating parameters include the expected flight speed, the maximum flight speed, the starting acceleration and the braking acceleration; The operation scenario of the target aircraft is detected, and the operation of the target aircraft is simulated according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenarios, merging scenarios, diversion scenarios, and interweaving scenarios.

2. The method for simulating aircraft operation based on cellular automata according to claim 1, characterized in that: The simulating the operation of the target aircraft according to the operation scenario includes: If the target aircraft is in a non-conflict scenario, an acceleration is performed based on the speed corresponding to the previous simulation step according to the startup acceleration to obtain a first speed; Detecting the speed of a previous flight of aircraft corresponding to the target aircraft and the relative distance between the target aircraft and the previous flight of aircraft, and determining a safe distance according to the speed of the previous flight of aircraft and the relative distance; According to the safety distance, deceleration determination is performed on the target aircraft based on the first speed to obtain a second speed; If the relative distance is greater than the product of the predetermined aircraft departure interval and the desired flight speed, performing secondary acceleration on the target aircraft based on the second speed to obtain a third speed; The position of the target aircraft in the cell is updated according to the third speed.

3. The method for simulating aircraft operation based on cellular automata according to claim 2, characterized in that: Determining the safety distance according to the speed of the previous flight aircraft and the relative distance comprises: If the speed of the aircraft of the previous flight is 0, the safety distance is determined as a predetermined minimum safety distance; Alternatively, if the speed of the previous flight of aircraft is greater than the speed of the target aircraft, the safety distance is determined according to the product of the aircraft departure interval and the speed of the target aircraft; Alternatively, if the speed of the previous flight of aircraft is greater than 0 and less than or equal to the speed of the target aircraft, the safety distance is determined according to the difference between the relative distance and the flight distance of the previous flight of aircraft in a single simulation step.

4. The method for simulating aircraft operation based on cellular automata according to claim 1, characterized in that: The detecting the operation scenario of the target aircraft and simulating the operation of the target aircraft according to the operation scenario includes: If it is detected that the target aircraft enters the merging range, it is determined that the target aircraft is in the merging scene, and the merging route, target route and merging point corresponding to the current route of the target aircraft are determined; Determine the corresponding merging priorities of other aircraft on the merging route and the target aircraft; If the merging priority of the target aircraft is lower than the merging priority of the other aircraft, the relative distance between the target aircraft and the other aircraft after merging into the target route is detected. If the relative distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

5. The method for simulating aircraft operation based on cellular automata according to claim 4, characterized in that: The determining of the corresponding merging priorities of other aircraft on the merging route and the target aircraft includes: detecting a speed of the target aircraft and a first merging distance between the target aircraft and the merging point; detecting a speed of the other aircraft and a second merging distance between the other aircraft and the merging point; determining a first merging time corresponding to the target aircraft according to the speed of the target aircraft and the first merging distance; determining a second merging time corresponding to the other aircraft according to the speed of the other aircraft and the second merging distance; If the first import time is less than the second import time, it is determined that the import priority of the target aircraft is higher than the import priority of the other aircraft; or, if the first import time is greater than the second import time, it is determined that the import priority of the target aircraft is lower than the import priority of the other aircraft.

6. The method for simulating aircraft operation based on cellular automata according to claim 1, characterized in that: The simulating the operation of the target aircraft according to the operation scenario includes: If the target aircraft is in a diversion scenario, determining the last flight aircraft on the route to which the target aircraft is diverted; Detecting a first distance between the target aircraft and a diversion point and a second distance between the previous flight aircraft and the diversion point; If the sum of the first distance and the second distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

7. The method for simulating aircraft operation based on cellular automata according to claim 1, characterized in that: The simulating the operation of the target aircraft according to the operation scenario includes: If the target aircraft is in an interweaving scene, the interweaving route and the interweaving point corresponding to the current route of the target aircraft are determined; Determining the interleaving priorities of other aircraft on the interleaving route and the target aircraft; If the interleaving priority of the target aircraft is higher than the interleaving priority of the other aircraft, detecting whether a conflict occurs between the target aircraft and the other aircraft; If the target aircraft and the other aircraft do not conflict, detecting a third distance between the target aircraft and the intersecting point and a fourth distance between the previous flight of the target aircraft and the intersecting point; If the sum of the third distance and the fourth distance is less than a predetermined minimum safety distance, the target aircraft is decelerated.

8. An aircraft operation simulation system based on cellular automata, characterized in that: The system comprises: An acquisition unit, used to acquire route network information, and construct cells according to the route network information; wherein the types of cells include segment cells and node cells, the segment cells are squares of the same size, the node cells are circular, and the cells are used to accommodate at most one aircraft in the running simulation; an identification unit, used to determine a position identification corresponding to each of the cells according to the route on which each of the cells is located and the position on the route, and to determine the state of the cell according to the aircraft running in the cell; A processing unit, used for determining operating parameters corresponding to the target aircraft to be simulated, and normalizing the operating parameters according to the length of the flight segment cell; wherein the operating parameters include expected flight speed, maximum flight speed, starting acceleration and braking acceleration; An execution unit is used to detect the operation scenario of the target aircraft and simulate the operation of the target aircraft according to the operation scenario; wherein the types of the operation scenarios include non-conflict scenarios, merging scenarios, diversion scenarios and interweaving scenarios.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements an aircraft operation simulation method based on cellular automation as described in any one of claims 1-7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to implement an aircraft operation simulation method based on cellular automation as described in any one of claims 1 to 7 when executed by the processor.

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