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

Abstract

The application discloses an aircraft operation simulation method, system and device based on a cellular automaton, acquires air route network information, constructs a cell according to the air route network information; determines a position identifier corresponding to each cell according to an air route where each cell is located and a position on the air route where each cell is located, and determines a state of the cell according to an aircraft running in the cell; determines an operation parameter corresponding to a target aircraft to be simulated, and performs normalization processing on the operation parameter according to the length of a section cell; detects an operation scene where the target aircraft is located, and simulates the operation of the target aircraft according to the operation scene; wherein the type of the operation scene includes a conflict-free scene, a merging scene, a diverging scene and an interleaving scene. The method can support small-range parallel operation of simulation and avoid complicated recalculation and synchronization processes, thereby effectively reducing the simulation cost. The application can be widely applied in 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 a cellular automaton. BACKGROUND

[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 to transport passengers and goods by using eVTOL (electric vertical take-off and landing) type vehicles in the city, and to use the vast low-altitude airspace as a new carrier for urban transportation.

[0003] With the popularization of the low-altitude concept, the urban low-altitude logistics system in the near future and the urban low-altitude 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 various simulation architectures for low-altitude aircraft, such as MATSim-UAM and Opensky for urban low-altitude transportation operation and evaluation, MATLAB, Simulink UAM Toolbox and SUMO-UAM module for aircraft micro-dynamics modeling, and researchers have also constructed more efficient simulation frameworks based on multi-agent simulation technology. However, the current simulation technologies all use network based on graph structure, i.e. network composed of nodes and edges, for simulation, and the simulation objects follow the queue model on the edge and the release model based on rules on the node to realize continuous simulation of traffic flow in the moving process, which has high computational complexity and is difficult to respond to dynamic changes such as traffic accidents and road regulations, and has poor simulation efficiency and freedom, and often cannot achieve the expected results.

[0004] In summary, the problems in the related art need to be solved urgently. SUMMARY

[0005] The present application aims to at least partly solve one of the problems in the related art.

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

[0007] To achieve the above technical purpose, the technical solutions adopted by the embodiments of the present application include:

[0008] On the one hand, the embodiments of the present application provide an aircraft operation simulation method based on a cellular automaton, which comprises:

[0009] Obtaining air route network information, and constructing cells according to the air route network information; wherein types of the cells include air segment cells and node cells, the air segment cells are squares with the same size, and the node cells are circles, and the cells are used for accommodating at most one aircraft in running simulation;

[0010] Determining position identifiers corresponding to each of the cells according to air routes where the cells are located and positions of the cells on the air routes, and determining states of the cells according to aircrafts running in the cells;

[0011] Determining running parameters corresponding to a target aircraft to be simulated, and performing normalization processing on the running parameters according to lengths of the air segment cells; wherein the running parameters include an expected flight speed, a maximum flight speed, a start-up acceleration, and a braking acceleration;

[0012] Detecting a running scenario where the target aircraft is located, and simulating running of the target aircraft according to the running scenario; wherein types of the running scenario include a conflict-free scenario, a merging scenario, a diverging scenario, and an interleaving scenario.

[0013] In addition, the aircraft running simulation method based on the cellular automaton according to the above-mentioned embodiments of the application can have the following additional technical features:

[0014] Further, in an embodiment of the application, the simulating running of the target aircraft according to the running scenario comprises:

[0015] If the target aircraft is in the conflict-free scenario, performing once acceleration on a speed corresponding to a previous simulation step on the basis of the start-up acceleration to obtain a first speed;

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

[0017] Performing deceleration determination on the target aircraft on the basis of the first speed according to the safety distance to obtain a second speed;

[0018] If the relative distance is greater than a product of a predetermined aircraft batch interval and the expected flight speed, performing twice acceleration on the target aircraft on the basis of the second speed to obtain a third speed;

[0019] Updating a position of the target aircraft in the cells according to the third speed.

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

[0021] if the speed of the previous aircraft is 0, determining the safety distance as a predetermined minimum safety distance;

[0022] or, if the speed of the previous aircraft is greater than the speed of the target aircraft, determining the safety distance according to a product of the aircraft departure interval and the speed of the target aircraft;

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

[0024] Further, in an embodiment of the present application, the detecting the operation scenario in which the target aircraft is located and simulating the operation of the target aircraft according to the operation scenario comprises:

[0025] if it is detected that the target aircraft enters a merging range, determining that the target aircraft is in a merging scenario, and determining a merging route, a target route and a merging point corresponding to the route on which the target aircraft is currently located;

[0026] judging a merging priority of the target aircraft and other aircraft on the merging route;

[0027] if the merging priority of the target aircraft is lower than the merging priority of the other aircraft, detecting a relative distance between the target aircraft and the other aircraft after the target aircraft and the other aircraft merge into the target route, and decelerating the target aircraft if the relative distance is less than a predetermined minimum safety distance.

[0028] Further, in an embodiment of the present application, the judging the merging priority of the target aircraft and the other aircraft on the merging route comprises:

[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] determine 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 merging time is less than the second merging time, determine that the merging priority of the target aircraft is higher than the merging priority of the other aircraft; or if the first merging time is greater than the second merging time, determine that the merging priority of the target aircraft is lower than the merging priority of the other aircraft.

[0034] Further, in an embodiment of the present application, the simulating the operation of the target aircraft according to the operation scenario comprises:

[0035] if the target aircraft is in a splitting scenario, determine a last flight on a route to which the target aircraft is split;

[0036] detect a first distance of the target aircraft from a splitting point and a second distance of a last flight of the target aircraft from the splitting point;

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

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

[0039] if the target aircraft is in an interweaving scenario, determine an interweaving route corresponding to a route on which the target aircraft is currently located and an interweaving point;

[0040] determine an interweaving priority corresponding to the target aircraft and other aircraft on the interweaving route;

[0041] if the interweaving priority of the target aircraft is higher than the interweaving priority of the other aircraft, detect whether the target aircraft and the other aircraft collide;

[0042] if the target aircraft and the other aircraft do not collide, detect a third distance of the target aircraft from the interweaving point and a fourth distance of a last flight of the target aircraft from the interweaving point;

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

[0044] In another aspect, an embodiment of the present application provides a flight operation simulation system based on a cellular automaton, the system comprising:

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

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

[0047] A processing unit is configured to determine a running parameter corresponding to a target aircraft to be simulated, and normalize the running parameter according to a length of the air segment cell; wherein, the running parameter includes an expected flight speed, a maximum flight speed, a start-up acceleration and a braking acceleration;

[0048] An execution unit is configured to detect a running scenario where the target aircraft is located, and simulate a running of the target aircraft according to the running scenario; wherein, the types of the running scenario include a conflict-free scenario, a merging scenario, a diverging scenario and an interleaving scenario.

[0049] In another aspect, an embodiment of the present application provides an electronic device, comprising:

[0050] at least one processor;

[0051] at least one memory configured to store at least one program;

[0052] When the at least one program is executed by the at least one processor, the at least one processor is caused to implement the above-mentioned aircraft running simulation method based on a cellular automaton.

[0053] In another aspect, an embodiment of the present application further provides a computer readable storage medium, wherein a processor executable program is stored, and the above-mentioned processor executable program is used to implement the above-mentioned aircraft running simulation method based on a cellular automaton when executed by a processor.

[0054] The advantages and beneficial effects of the present application will be partially given in the following description, partially will become obvious from the following description, or will be understood by the practice of the present application:

[0055] The aircraft operation simulation method, system and device based on the cellular automaton disclosed in the embodiments of the present application obtain air route network information, and construct cells according to the air route network information; wherein the types of the cells include air segment cells and node cells, the air segment cells are squares with the same size, the node cells are circles, and the cells are used to accommodate at most one aircraft in operation simulation; the position identifiers corresponding to each of the cells are determined according to the air routes where the cells are located and the positions of the cells on the air routes, and the states of the cells are determined according to the aircrafts running in the cells; the operation parameters corresponding to a target aircraft to be simulated are determined, and the operation parameters are normalized according to the lengths of the air segment cells; wherein the operation parameters include expected flight speed, maximum flight speed, start-up acceleration and braking acceleration; the operation scene where the target aircraft is located is detected, and the operation of the target aircraft is simulated according to the operation scene; wherein the types of the operation scene include a conflict-free scene, a merging scene, a diverging scene and an interleaving scene. The method is based on the simulation logic of cell state updating, and the specific actions of the simulation objects are evolved through a small number of neighbor cell states, which can support small-range parallel operation of simulation and avoid cumbersome recalculation and synchronization process, thereby effectively reducing the simulation cost. BRIEF DESCRIPTION OF DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following introduces the drawings of the related technical solutions in the embodiments of the present application or the prior art. It should be understood that the drawings in the following introduction are only for the convenience of clearly describing some embodiments of the technical solutions in the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0057] Figure 1 An implementation environment diagram of the aircraft operation simulation method based on the cellular automaton provided in the embodiments of the present application;

[0058] Figure 2 A flowchart of the aircraft operation simulation method based on the cellular automaton provided in the embodiments of the present application;

[0059] Figure 3 A schematic diagram of an air segment cell provided in the embodiments of the present application;

[0060] Figure 4 A schematic diagram of a merging cell and a diverging cell provided in the embodiments of the present application;

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

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

[0063] Figure 7 A schematic diagram of a cell 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] Figure 9 A schematic diagram of a merge scenario provided in an embodiment of the present application;

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

[0067] Figure 11 A schematic diagram of a split scenario provided in an embodiment of the present application;

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

[0069] Figure 13 A schematic diagram of an interleaving scenario provided in an embodiment of the present application;

[0070] Figure 14 A schematic diagram of an aircraft motion evolution rule in an interleaving scenario provided in an embodiment of the present application. DETAILED DESCRIPTION

[0071] The present application will be further described with reference to the drawings and specific embodiments described below. The described embodiments should not be considered limiting the present application, all other embodiments obtained by those skilled in the art without creative effort under the premise of the described embodiments, are within the scope of protection of the present application.

[0072] In the following description, "some embodiments" are described, which describe a subset of all possible embodiments, but it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0073] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present 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 to use eVTOL (electric vertical take-off and landing) type vehicles for passenger and cargo transportation in the city, and to use the vast low-altitude airspace as a new carrier for urban transportation.

[0075] With the popularization of the low-altitude concept, the urban low-altitude logistics system in the near future and the urban low-altitude 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. There are currently various simulation architectures for low-altitude aircraft, such as MATSim-UAM and Opensky for urban low-altitude transportation operation and evaluation, MATLAB, Simulink UAM Toolbox, and SUMO-UAM module for aircraft micro-dynamics modeling, and researchers have also built more efficient simulation frameworks based on multi-agent simulation technology. However, the current simulation technologies use a network based on a graph structure, i.e., a network composed of nodes and edges, to simulate the simulation objects following the queue model on the edge and the release model based on rules on the node to realize continuous simulation of traffic flow. The calculation complexity is high, and it is difficult to respond to dynamic changes such as traffic accidents and road regulations.

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

[0077] The network model based on the graph structure can clearly represent and distinguish different elements and element relationships in the traffic network, and is easy to integrate with path planning algorithms, suitable for large-scale network analysis. Correspondingly, the queue-based road segment 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 regulations, etc., reducing the simulation efficiency and freedom. Moreover, this implementation approach also has the following problems:

[0078] 1) Network construction process is complex, and the action relationship between different elements needs to be considered, which is only suitable for irregular and complex networks with multiple connection relationships between nodes.

[0079] 2) Simulation efficiency is limited: the dynamic processing in path planning and simulation process depends on complex rules and algorithms, which will consume a lot of computing power, and is only suitable for scenarios that do not emphasize real-time performance.

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

[0081] Therefore, in the embodiments of the present application, a flight vehicle operation simulation method based on cellular automata is provided, which acquires air route network information and constructs cells according to the air route network information. The types of the cells include flight segment cells and node cells. The flight segment cells are squares of the same size, and the node cells are circles. The cells are used to accommodate at most one flight vehicle in the operation simulation. The position identifier corresponding to each cell is determined according to the air route where the cell is located and the position of the cell on the air route, and the state of the cell is determined according to the flight vehicle running in the cell. The running parameters corresponding to the target flight vehicle to be simulated are determined, and the running parameters are normalized according to the length of the flight segment cell. The running parameters include expected flight speed, maximum flight speed, start-up acceleration and braking acceleration. The running scene of the target flight vehicle is detected, and the running of the target flight vehicle is simulated according to the running scene. The types of the running scene include conflict-free scene, merging scene, splitting scene and interleaving scene. This method is based on the simulation logic of cell state update, and the specific actions of the simulation object are evolved through a small number of neighbor cell states, which can support small-range parallel operation of simulation and avoid tedious recalculation and synchronization process, thereby effectively reducing the simulation cost.

[0082] Please refer to Figure 1 , Figure 1 An implementation environment schematic diagram of a flight vehicle operation simulation method based on cellular automata provided in the embodiments of the present application is shown. In this implementation environment, the main hardware and software subjects involved include terminal device 110 and background server 120. The terminal device 110 and the background server 120 are in communication connection.

[0083] Specifically, the aircraft operation simulation method based on the cellular automaton provided in the embodiments of the present application can be configured on the background server 120 side and executed based on data interaction between the terminal device 110 and the background server 120. The terminal device 110 in the above embodiments can include a mobile phone, a computer, a smart wearable device, a smart voice interaction device, a vehicle-mounted terminal, and the like, but is not limited thereto. The background server 120 can be a standalone physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and basic cloud computing services such as big data and artificial intelligence platforms.

[0084] The terminal device 110 and the background server 120 can establish a communication connection through a wireless network or a wired network. The wireless network or the wired network uses standard communication technology and / or protocols, and the network can be set as the Internet or any other network, for example, including 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 can be understood that the implementation environment in Figure 1 is only some optional application scenarios of the aircraft operation simulation method based on the cellular automaton provided in the embodiments of the present application, and the actual application is not fixed to the software and hardware environment shown in Figure 1 .

[0086] Next, in combination with the introduction of the foregoing implementation environment, an aircraft operation simulation method based on a cellular automaton provided in the embodiments of the present application is introduced and described.

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

[0088] Step 210, obtaining air route network information, and constructing cells according to the air route network information; wherein the types of the cells include leg cells and node cells, the leg 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;

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

[0090] Step 230, determining the running parameter corresponding to the target aircraft to be simulated, and performing normalization processing on the running parameter according to the length of the leg cell; wherein the running parameter includes expected flight speed, maximum flight speed, start-up acceleration and braking acceleration;

[0091] Step 240, detecting the running scene where the target aircraft is located, and simulating the running of the target aircraft according to the running scene; wherein the type of the running scene includes a conflict-free scene, a merging scene, a diverging scene and an interleaving scene.

[0092] In the embodiments of the present application, a flight vehicle running simulation method based on a cellular automaton is provided. The method constructs a low-altitude traffic network model based on a cellular automaton, uses a specific size of cells to construct a network and a traffic rule system, and realizes continuous simulation of low-altitude flight vehicle running through cell state updating. The interaction relationship between cells is simple, the network construction is efficient, the simulation logic based on cell state updating depends on local rules to confirm the state of the next simulation step of the cell, the updating rule is simple, and the simulation speed is fast. Moreover, based on the state updating design of the state of the neighborhood cells, the specific actions of the simulation object are evolved through a small number of neighborhood cell states, which can support small-range parallel running of the simulation and avoid cumbersome recalculation and synchronization processes, thereby effectively reducing the simulation cost.

[0093] Specifically, in the embodiments of the present application, first, route network information can be acquired, and cells can be constructed according to the route network information. In the embodiments of the present application, the types of cells can include two types of leg cells and node cells, which constitute the route network of the conflict-free scene and the special nodes such as merging, diverging and interleaving in the conflict scene, and a single flight vehicle occupies only one cell at the same time. Please refer to Figure 3 , Figure 3 A schematic diagram of a leg cell provided in the embodiments of the present application is shown. In the embodiments of the present application, the leg cell is a square with the same size, which can be used for flight simulation of a single flight vehicle. A single flight vehicle is allowed to fly on a single flight path at the same cross section, and therefore the width of a single flight path is 1 cell width. The number of cells constituting the flight path depends on the length of the flight path. If the length of the flight path is 10 km and the side length L of a single cell is 20 m, the flight path is composed of 500 cells arranged in sequence.

[0094] The node cell is circular, and the radius depends on the type of scenario where the cell is located and the included angle of the interlaced route. The node cell is used to simulate the flight segment where conflicts occur between aircraft. There are three types of aircraft conflicts in the flight path: aircraft on multiple routes converging to one route at the same time, which is a converging conflict; aircraft on one route flowing to multiple routes at the same time, which is a diverging conflict; and aircraft on two routes being close to each other or overlapping at the same time and at the same height, which is an interlaced conflict. In the embodiments of the present application, the three types of conflicts are guided by converging cells, diverging cells and interlaced cells, and the three types of cells belong to node cells. Exemplarily, please refer to Figures 4 to 6 , Figure 4 FIG. 1 shows a schematic diagram of a converging cell and a diverging cell provided in the embodiments of the present application, Figure 5 FIG. 2 shows a schematic diagram of a non-vertical interlaced cell provided in the embodiments of the present application, Figure 6 FIG. 3 shows a schematic diagram of a vertical interlaced cell provided in the embodiments of the present application. In the embodiments of the present application, the converging cell, the diverging cell and the interlaced cell are circular, and the cell radius depends on the interlacing type and the interlacing angle. For the non-vertical interlaced cell, the smaller the interlacing angle of the two routes, the larger the cell radius, and the larger the detection area and the conflict range of the cell; for the vertical interlaced cell, the detection area and the conflict range are fixed values.

[0095] In the embodiments of the present application, for each cell, the position identifier corresponding to each cell can be determined according to the position of the cell. Specifically, the route where the cell is located and the position of the cell on the route, for example, a certain cell is located on the i th route, and the j th cell is located on the i th route (i and j are positive integers), which can be represented by a two-dimensional coordinate (i, j). In the embodiments 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, A ij ∈{0,1..V exp ,V exp +1,..V max},when A ij = 0, it means that the cell corresponding to the two-dimensional coordinate (i, j) is currently empty, that is, there is no aircraft; when A ij = V, V ∈ {1..V exp ,V exp +1,..V max}, it means that the cell corresponding to the two-dimensional coordinate (i, j) is occupied by an aircraft with a speed of V.

[0096] In the embodiments of the present application, in order to facilitate subsequent processing of data, for the aircraft to be simulated (denoted as target aircraft), the corresponding operating parameters thereof can be acquired, which can include expected flight speed, maximum flight speed, start-up acceleration and braking acceleration. Then, the operating parameters can be normalized according to the length of the leg cell. Specifically, in the embodiments of the present application, the flight speed of the aircraft in the cell space is represented by the number of cells that can be passed through per unit time, assuming that the actual expected flight speed of the aircraft is V rea_des , the maximum flight speed is V rea_max , and the unit is m / s, then the cell flight speed of the aircraft in the leg can be calculated by the following formula:

[0097] V exp =V rea_des / / L

[0098] V max =V rea_max / / L

[0099] In the formula, L is the length of the leg cell.

[0100] Similarly, assuming that the actual start-up acceleration of the aircraft is a rea_acc , and the braking acceleration is a rea_dec , the unit is m / s 2 , and all are positive values, then the start-up acceleration and braking acceleration of the aircraft in the cell network can be calculated as follows:

[0101] a acc =a rea_acc / L

[0102] a dec =a rea_dec / L

[0103] For example, the maximum flight speed of a certain aircraft is 220 km / h, the expected flight speed is 150 km / h, the start-up and running acceleration is 7.5 m / s 2 , and the braking acceleration is 10 m / s 2 , assuming that the leg cell edge length L is 20 m. Through the calculation of the above formula, it can be obtained that the theoretical maximum speed of the aircraft in the cell space is about 60 m / s, i.e. three cell lengths, and the theoretical expected speed is about 40 m / s, i.e. two cell lengths. Therefore, it can be obtained that the corresponding maximum speed and expected speed are V max = 3, V exp = 2, the start-up acceleration and braking acceleration are a acc = 0.375 and a dec = 0.5, respectively.

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

[0105] In the embodiments of the present application, after the model parameters are established, the running of the target aircraft can be simulated by a cellular automaton. Specifically, the running scenario of the target aircraft can be detected, and then the running of the target aircraft is simulated according to the running scenario, so as to realize the state control of the aircraft. In the embodiments of the present application, the types of the running scenario can include a conflict-free scenario, a merging scenario, a diverging scenario, and an interleaving scenario.

[0106] The simulation process under each of the above scenarios will be introduced and described below.

[0107] Specifically, in some embodiments, the simulation of the running of the target aircraft according to the running scenario comprises:

[0108] If the target aircraft is in a conflict-free scenario, the target aircraft is accelerated once based on the speed corresponding to the previous simulation step according to the start acceleration, to obtain a first speed;

[0109] The speed of a previous flight aircraft corresponding to the target aircraft and the relative distance between the target aircraft and the previous flight aircraft are detected, and a safety distance is determined according to the speed of the previous flight aircraft and the relative distance;

[0110] The target aircraft is decelerated based on the first speed according to the safety distance, to obtain a second speed;

[0111] If the relative distance is greater than the product of a predetermined flight interval and the expected flight speed, the target aircraft is accelerated twice 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 embodiments of the present application, the conflict-free scenario is the basic scenario of the flight of the aircraft, which refers to the flight process of the route far away from the conflict point. If the target aircraft is in a conflict-free scenario, the current cell position of the aircraft at time t is Xi,j (t), X i,j (t) ≥ 0, the movement speed of the aircraft at time t is V i，j (t). In the absence of special circumstances, the aircraft runs at the desired speed V exp on the route, when the distance is too large or too small, the aircraft can be allowed to decelerate or speed up to the maximum speed V max , then 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 aircrafts on route i;

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

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

[0120] T - the time distance to be made up, when the time distance between the current aircraft and the previous aircraft exceeds this value, the current aircraft accelerates to make up the distance gap;

[0121] V exp - the desired flight speed of the aircraft in the cell network;

[0122] V max - the maximum flight speed of the aircraft in the cell 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 - aircraft acceleration in the cellular network, representing the amount of change in aircraft speed in a single simulation step, according to the judgment of the evolution rule on the acceleration state or deceleration state of the aircraft, the acceleration takes a when the aircraft starts and runs at acceleration acc , the acceleration takes a when the aircraft brakes and decelerates dec , both of which take positive values.

[0126] Referring to Figure 8 , Figure 8 Fig. 1 shows a schematic diagram of an aircraft motion evolution rule in a conflict-free scenario according to an embodiment of the present application. In the embodiment of the present application, the essence of the motion evolution rule is to comprehensively consider the safety distance, flight speed and cell state of the aircraft in the current simulation step, and to judge the moving distance (i.e. speed) of the target aircraft in the next simulation step. In the conflict-free scenario, the judgment is divided into the following four steps:

[0127] Step 1: Acceleration

[0128] The speed of the target aircraft is increased by a on the basis of the speed in the last simulation step to obtain the first speed. Here, if the aircraft has reached the desired speed, the speed remains unchanged, and the purpose of this step is to let the aircraft fly at the fastest possible speed without exceeding the desired speed.

[0129] Step 2: Deceleration

[0130] The deceleration process is divided into two steps. First, the safety distance of the target aircraft is judged according to different situations, and then the new flight speed is calculated on the basis of the acceleration to obtain the second speed.

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

[0132] Step 3: Second acceleration

[0133] determine whether the actual distance d between the target aircraft and the previous aircraft exceeds the product of the aircraft departure interval and the aircraft expected speed, and if so, it means that the distance between the aircrafts is too far, and the subsequent aircraft can speed up on the basis of the current speed to reduce the intermediate distance to ensure the flight space of the subsequent aircraft, i.e., to obtain a third speed, and if not, no adjustment is made.

[0134] Step 4: position update

[0135] Through the steps of Step 1-Step 3, the aircraft has a determined speed that can be used for simulation, and based on the speed value, the aircraft will update the position in the one-dimensional cellular network, i.e., the original position plus the speed of the target aircraft multiplied by a unit simulation step.

[0136] It can be understood that during low-altitude operation, the distance interval of the aircraft itself is relatively long, and the fault tolerance space is relatively large. Unlike ground traffic, which allows queuing, low-altitude aircrafts are more expected not to queue during the entire operation. Therefore, it is particularly important to maintain the relative distance between the aircrafts on the straight route. The distance between the aircrafts will not pose a safety risk due to being too close, nor will it cause uneven distribution of line aircrafts due to being too far, thereby affecting the efficiency of passing through the conflict point. Based on the above reasons, the application improves the traditional CTM by replacing the "random slowing down" link of road traffic with "second acceleration" to determine whether to accelerate the target aircraft twice according to the distance between the target aircraft and the previous aircraft, and by updating the acceleration instead of directly updating the speed to affect the update of the speed. In this way, the aircrafts are as close as possible based on a safe distance, the update granularity is more detailed, and the running density and simulation continuity of the aircrafts on the airway are ensured.

[0137] Specifically, in some embodiments, the detecting the running scenario in which the target aircraft is located and simulating the running of the target aircraft according to the running scenario comprises:

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

[0139] determine the merging priorities of the other aircrafts on the merging airway and the target aircraft;

[0140] If the merging priority of the target aircraft is lower than the merging priority of the other aircrafts, detect the relative distance between the target aircraft and the other aircrafts after merging into the target airway, and if the relative distance is less than a predetermined minimum safety distance, decelerate the target aircraft.

[0141] In this embodiment, the merging scenario is discussed using a one-way route scenario where two routes merge into one route. For example, please refer to... Figure 9 , Figure 9 This illustration shows a schematic diagram of a merging scenario provided in an embodiment of this application. In this embodiment, the model in the merging scenario simulates a situation where aircraft from multiple flight paths converge onto a main channel. It primarily considers the flight status of aircraft on each flight path and their distance to the nearest passing aircraft on the main channel. First, assuming all aircraft on all flight paths are in normal flight status and within safe distance, the distance from each aircraft on the relevant flight path to the merging cell is monitored. When an aircraft is detected entering the merging range, a merging determination algorithm is executed. Figure 9 For example, suppose the aircraft AVeh 1,5 Once the aircraft enters the detection range, its distance, speed, and other passage conditions need to be assessed. The assessment 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 j-th flight on route i at time t;

[0144] AVdh i，j —The j-th flight on route i;

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

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

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

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

[0149] D i —Minimum safe travel distance for aircraft on route i;

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

[0151] V maxThe maximum flight speed of the aircraft in the cell network;

[0152] a The acceleration of the aircraft in the cell network, representing the maximum value of the change in the speed of the aircraft in a single simulation step, according to the judgment of the acceleration state or deceleration state in the evolution rule, when the aircraft is to start and run acceleration, the acceleration takes a acc , when the aircraft is to brake or decelerate, the acceleration takes a dec ;

[0153] P The probability of random acceleration or deceleration of the aircraft, which is 0.5 by default. When two aircrafts will arrive at the conflict point at the same time, the system will give one of the aircrafts a speed increase or decrease according to the conditions to distinguish the arrival priority of the aircraft.

[0154] Referring to Figure 10 , Figure 10 A schematic diagram of an aircraft motion evolution rule in a merging scenario provided in an embodiment of the present application is shown. In an embodiment of the present application, when the detector finds that the target aircraft enters the merging range, first, the entering priority of each aircraft is determined according to the distance between the aircraft in the current range and the merging cell and the congestion degree of the queue where the aircraft is located; then, according to the aircraft spacing, flight speed, and body position difference of the aircraft on the merging route and the main route, the merging is realized by controlling the flight speed of the aircraft. In addition to allowing the aircraft to pass under normal circumstances, there are also situations where the merging section is found to be congested, and then operations such as overall speed reduction, delay of departure, etc. on the congested line are judged. The specific judgment process is as follows:

[0155] Priority judgment: when the aircrafts of multiple routes converge into one route, first, the time for the aircraft to arrive at the merging point is calculated according to the current simulation step flight speed of the aircraft and the distance from the merging point, and the merging priority is determined according to the time length, the shortest time distance has the highest priority, and vice versa. For the target aircraft, the merging route corresponding to the route where it is located, the target route, and the merging point can be detected, and the route where the target aircraft is located and the merging route merge together at the merging point to the target route. Then, the merging priority of other aircrafts on the merging route and the target aircraft can be judged. Specifically, the speed of the target aircraft and the first merging distance between the target aircraft and the merging point are detected, the first merging time corresponding to the target aircraft is determined according to the first merging distance and the speed of the target aircraft, the speed of the other aircrafts and the second merging distance between the other aircrafts and the merging point are detected, the second merging time corresponding to the other aircrafts is determined according to the second merging distance and the speed of the other aircrafts, and the two are compared. The aircraft with a smaller merging time is determined as a high-priority aircraft.

[0156] Speed judgment:

[0157] ①Assume that the current target aircraft will arrive at the merging point first: then the highest priority it gets needs to ensure that the target aircraft can maintain the required minimum safety distance when passing through the merging point in turn. Therefore, the relative distance between the two aircrafts is judged here, if the distance is greater than the minimum safety distance of the target route, then the other aircraft can pass freely at the original speed; if the distance does not meet the minimum safety distance condition, then the other aircraft needs to slow down.

[0158] ②Assume that the current target aircraft will arrive at the merging point later: then its priority is lower than that of other aircrafts on other routes, and the relative distance between the two aircrafts is also judged, if the distance is greater than the minimum safety distance of the target route, then the target aircraft can pass normally at the original speed; otherwise, the target aircraft needs to slow down to facilitate the priority higher aircraft to give way out of the minimum safety distance and provide deceleration space.

[0159] Position movement: according to the final speed result obtained by the above judgment process, the aircraft is displaced.

[0160] Specifically, in some embodiments, the simulation of the operation of the target aircraft according to the running scene includes:

[0161] If the target aircraft is in a split scene, determine the last batch of aircrafts on the route to which the target aircraft is split;

[0162] Detect the first distance of the target aircraft from the split point and the second distance of the last batch of aircrafts from the split point;

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

[0164] In the embodiments of the present application, the model in the split scene is used to process the scene where the main channel aircrafts want to go to different routes, and needs to release the aircrafts based on the flight state of the main channel aircrafts and the existing path planning result, mainly considering the distance factor of the current main channel aircraft and the nearest general aircraft on the route to which the aircraft is split. First, under the premise that all aircrafts on the route are in normal flight state and within the safety distance, the distance of each aircraft on the route to the split cell is monitored. When a aircraft enters the split management range, the split determination algorithm is executed. Referring to Figure 11 , Figure 11 A schematic diagram in a split scene provided by an embodiment of the present application is shown. Taking Figure 11 for example, assume that the aircraft AVeh 1,6First into the detection range, the need to determine the distance of the aircraft, speed and other traffic conditions, judgment formula and evolution rules 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 jth aircraft on the i route at time t cell position;

[0167] AVdh i，j - the jth aircraft on the i route;

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

[0169] d1 - the cell distance from the main channel to the shunt point of the aircraft to be shunted;

[0170] d2 - the cell distance from the nearest shunt aircraft on route 2 to the shunt point;

[0171] d3 - the cell distance from the nearest shunt aircraft on route 1 to the shunt point;

[0172] D i - the minimum safe distance of the aircraft on the i route;

[0173] a - the acceleration of the aircraft in the cell network, representing the maximum value of the change in aircraft speed in a single simulation step, according to the evolution rule for the acceleration state or deceleration state of the aircraft, when the aircraft is to start and run acceleration, the acceleration takes a acc , when the aircraft is to brake or decelerate, the acceleration takes a dec ;

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

[0175] Referring Figure 12 , Figure 12A schematic diagram of an aircraft motion evolution rule in a flow splitting scenario provided in an embodiment of the present application is shown. In an embodiment of the present application, the specific release judgment process of the flow splitting model is as follows: first, the number of the route to which the target aircraft is split is obtained, assuming that the target aircraft is the closest aircraft to the flow splitting point and is about to be split onto route 1. Then, the distance between the target aircraft and the last aircraft on route 1 is summed, that is, the first distance of the target aircraft from the flow splitting point and the second distance of the last aircraft from the flow splitting point are detected, and if the sum of the two distances is greater than the minimum safety distance, the aircraft can maintain the original speed to pass safely; if it is less than the minimum safety distance, the target aircraft is slowed down. Compared with the merging process, the flow splitting process is mostly from high to low aircraft density, the judgment process is simple, and the conflict is relatively less.

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

[0177] If the target aircraft is in an interleaving scenario, and the interleaving route and the interleaving point corresponding to the route where the target aircraft is currently located are determined;

[0178] The interleaving priorities of the other aircraft on the interleaving route and the target aircraft are determined;

[0179] If the interleaving priority of the target aircraft is higher than the interleaving priority of the other aircraft, it is detected whether the target aircraft and the other aircraft conflict;

[0180] If the target aircraft and the other aircraft do not conflict, the third distance of the target aircraft from the interleaving point and the fourth distance of the last aircraft of the target aircraft from the interleaving point are detected;

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

[0182] In an embodiment of the present application, the model in the interleaving scenario is used to simulate the travel process of the aircrafts on two routes at the route interleaving point, and reference is made to Figure 13 , Figure 13 A schematic diagram of an interleaving scenario provided in an embodiment of the present application is shown, and Figure 13 In the default premise that all aircrafts on the route are in a normal flight state and within a safety distance, when the aircraft enters the interleaving monitoring range, the model realizes the passage of the aircraft in the interleaving area by performing priority judgment, speed judgment and other algorithms. Taking Figure 13 for example, assuming that the aircraft AVeh 1，4First into the detection range, the need to determine the distance of the aircraft, speed and other traffic conditions, judgment formula and evolution rules 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 the i route at time t;

[0185] AVdh i，j - the jth aircraft on the i route;

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

[0187] d1 - the cell distance between the target aircraft entering the monitoring range on route 1 and the interlacing point;

[0188] d2 - the cell distance between the aircraft about to reach the interlacing point on route 2 and the interlacing point;

[0189] d3 - the cell distance between the last aircraft leaving the interlacing point on route 1 and the interlacing point;

[0190] d4 - the cell distance between the last aircraft leaving the interlacing point on route 2 and the interlacing point;

[0191] D - the cell radius of the conflict area of the interlacing scenario aircraft;

[0192] D i - the safe flight interval of the i route;

[0193] V exp - the desired flight speed of the aircraft in the cell network;

[0194] V max - the maximum flight speed of the aircraft in the cell network;

[0195] d - the cell radius of the monitoring area of the interlacing scenario aircraft;

[0196] a - the acceleration of the aircraft in the cell network, representing the maximum value of the change in speed of the aircraft in a single simulation step, according to the judgment of the acceleration state or deceleration state in the evolution rule, when the aircraft is to start and run acceleration, the acceleration takes a accThe acceleration takes a when the aircraft is to be braked or decelerated dec ;

[0197] p - the probability of the aircraft randomly increasing or decreasing speed, by default 0.5. When two aircrafts will arrive at the conflict point at the same time, the system gives one of the aircrafts to increase or decrease speed according to the conditions, so as to distinguish the arrival priority of the aircrafts.

[0198] Referring to Figure 14 , Figure 14 A schematic diagram of the aircraft motion evolution rule in the interleaving scenario provided in the embodiment of the application is shown. In the embodiment of the application, the aircraft entering the monitoring area is detected and identified as an interleaving object by the system, so as to perform interleaving priority judgment; when two aircrafts appear in the conflict area at the same time, it is determined that a conflict occurs. According to the interleaving model aircraft motion evolution rule design in the present research, the aircraft entering the interleaving area will perform the following judgment process:

[0199] Priority confirmation: when multiple routes are interleaved, first, the time for the aircraft to arrive at the interleaving point is calculated according to the current simulation step flight speed of the aircraft and the distance from the interleaving point, and the priority of passing through the interleaving point is determined according to the time length, the priority is the highest when the time distance is the closest, and vice versa.

[0200] Speed judgment:

[0201] Suppose the current target object aircraft AVdh 1，4 will arrive at the merging point first: it obtains the highest priority of passing through, determines the interleaving route and the interleaving point corresponding to the route where the target aircraft is currently located. First, it is determined whether the target aircraft and other aircrafts on the interleaving route will appear in the conflict area with a radius of D around the interleaving point at the same time when they pass through the interleaving point in turn, by V2*(d1+D) / V1+D<d2, if the condition is met, no conflict will occur, if not, a conflict will occur. When no conflict occurs, it is necessary to determine whether the current safety distance of the limited passing route satisfies the condition d1+d3>D1, if it satisfies, the target aircraft can pass through at the original speed; if it does not satisfy, the target aircraft needs to be decelerated; when a conflict occurs, it is also necessary to determine the condition d1+d3>D1, if it satisfies, the target aircraft needs to be accelerated to pass through to pull away the safety distance from the next passing aircraft; if it does not satisfy, the target aircraft needs to keep the original speed, and the route may conflict.

[0202] Suppose the current judgment object aircraft AVdh 1，4Arrive at the interlaced point after the meeting: the priority is lower than other lines, at this time, the flight safety distance judgment V1*(d2+D) / V2+D<d1 of another route is carried out, if the condition is met, no conflict occurs, if not met, conflict occurs. When no conflict occurs, the current aircraft AVdh 2，6 of another route is carried out, if the condition is met, the aircraft can pass freely at the original speed, the original judgment target aircraft AVdh 1，4 does not need to change the flight state; if not met, the target aircraft AVdh 1，4 is decelerated to provide deceleration space for the high-priority aircraft. When conflict occurs, the target aircraft AVdh 1，4 decelerates to avoid conflict while providing deceleration space for the high-priority aircraft.

[0203] Position movement: the final speed result obtained according to the above judgment process, the target aircraft AVdh 1，4 is subjected to a displacement operation.

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

[0205] 1. The model based on the cellular automaton replaces the update of the state of the simulation object by the update of the state of the cell, while supporting parallel simulation, which can effectively improve the running speed of large-scale simulation.

[0206] 2. The simulation based on the cellular automaton is realized by the state evolution update of the cell according to the corresponding rules, and the individual can only make the next simulation operation decision according to the local environment and the state of the adjacent cell, so that the model has high self-organization and robustness, and can 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 running process of the aircraft can be directly visualized according to the state of the cell, which is more efficient and more intuitive, especially when reflecting the dynamic changes of large-scale low-altitude aircraft clusters.

[0208] In the embodiments of the application, a flight vehicle running simulation system based on a cellular automaton is also provided, which comprises:

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

[0210] An identification unit is configured to determine a position identifier corresponding to each of the cells according to a route where each of the cells is located and a position on the route where each of the cells is located, and determine a state of each of the cells according to an aircraft running in each of the cells;

[0211] A processing unit is configured to determine a running parameter corresponding to a target aircraft to be simulated, and perform normalization processing on the running parameter according to a length of the route cell; wherein the running parameter includes an expected flight speed, a maximum flight speed, a start-up acceleration, and a braking acceleration.

[0212] An execution unit is configured to detect a running scenario where the target aircraft is located, and simulate running of the target aircraft according to the running scenario; wherein a type of the running scenario includes a conflict-free scenario, a merging scenario, a diverging scenario, and an interleaving scenario.

[0213] It can be understood that the content in the above method embodiments is applicable to the present system embodiments, the present system embodiments specifically implement the functions of the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

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

[0215] at least one processor;

[0216] at least one memory configured to store at least one program;

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

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

[0219] Similarly, the content in the above method embodiments is applicable to the present electronic device embodiments, the present electronic device embodiments specifically implement the functions of the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0220] The present application also provides a computer readable storage medium, which stores a program executable by a central processing unit, and the program executable by the central processing unit is used to execute the above-mentioned aircraft running simulation method based on a cellular automaton when executed by the central processing unit.

[0221] Similarly, the contents of the above method embodiments are applicable to the computer readable storage medium embodiments, the computer readable storage medium embodiments specifically implement the functions of the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0222] In some alternative embodiments, the functions / operations mentioned in the block diagrams can not occur in the order mentioned in the operation diagrams. For example, depending on the functions / operations involved, two blocks shown in succession can actually be executed substantially concurrently with each other, or sometimes the blocks can be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts in this application are provided by way of example, and are intended to provide a more thorough and complete understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented in this application. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of a larger operation are independently executed.

[0223] Furthermore, although the present application is described in the context of functional modules, it is to be understood that one or more of the functions and / or features can be integrated in a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules, unless otherwise specified. It is also to be understood that detailed discussion of the actual implementation of each module is unnecessary to an understanding of the present application. Rather, the actual implementation of the modules is within the ordinary skill in the art, given the nature of the attributes, functions and internal relationships of the various functional modules disclosed herein. Therefore, the present application is not limited to the specific embodiments disclosed herein, but rather, the scope of the present application is to be determined entirely by the claims and the equivalents thereof, which are to be accorded the full scope of equivalents to which they are entitled.

[0224] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, and includes a number of instructions for causing an apparatus (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0225] The logic and / or steps represented in the flow diagrams or otherwise described herein, for example, can be embodied in non-transitory computer- readable media, executed by an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions, or in conjunction with which the instructions can be executed. In the context of this specification, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium.

[0226] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can also be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example, via an optical scanner, then compiled, interpreted, or otherwise processed, and stored in a computer memory in a form that is then employable by a computer. In some embodiments, the computer-readable medium can be a non-transitory computer-readable medium.

[0227] It should be understood that aspects of the present application can be implemented in hardware, software, firmware, or combinations thereof. In the above-described embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any of the following technologies, or combinations thereof, can be used with the necessary logic gates and circuitry for implementing logic functions on data signals: discrete logic circuitry having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and so forth.

[0228] In the above-described description of the present specification, the description referring to the terms "one embodiment," "another embodiment," or "some embodiments," and the like, means that the particular feature, structure, material, or characteristic being described is included in at least one embodiment or example of the present application. The illustrative appearances of the above- described terms in the description are not necessarily all referring to the same embodiment or example of the present application. Furthermore, the particular features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0229] While the embodiments of the present application have been shown and described, it is to be understood that the embodiments can be varied, modified, substituted and changed by those skilled in the art without departing from the principles and spirit of the present application, the scope of which is defined by the claims and their equivalents.

[0230] The above is a specific description of the preferred embodiments of the present application, but the present application is not limited to the embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present application, and 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 includes: Obtain route network information and construct cells based on the route network information; wherein, the cell types 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 a maximum of one aircraft in the simulation. Based on the flight path and position of each cell, determine the position identifier corresponding to each cell, and determine the state of the cell based on the aircraft running in the cell. The operating parameters corresponding to the target aircraft to be simulated are determined, and the operating parameters are normalized according to the length of the segment cell; wherein, the operating parameters include the desired flight speed, maximum flight speed, start-up acceleration, and braking acceleration; The operating scenario of the target aircraft is detected, and the operation of the target aircraft is simulated based on the operating scenario; wherein, the types of operating scenarios include conflict-free scenarios, merging scenarios, splitting scenarios, and interleaving scenarios; The process of detecting the operating scenario of the target aircraft and simulating the operation of the target aircraft based on the operating scenario includes: If the target aircraft is detected to enter the merging range, it is determined that the target aircraft is in the merging scenario, and the merging route, target route, and merging point corresponding to the current route of the target aircraft are determined; Determine the merging priority of other aircraft on the merging route and the target aircraft; If the merging priority of the target aircraft is lower than that of the other aircraft, the relative distance between the target aircraft and the other aircraft after merging into the target flight path is detected. If the relative distance is less than a predetermined minimum safe distance, the target aircraft is decelerated.

2. The aircraft operation simulation method based on cellular automata according to claim 1, characterized in that, The simulation of the target aircraft's operation based on the operating scenario includes: If the target aircraft is in a conflict-free scenario, it accelerates once based on the speed corresponding to the previous simulation step according to the start-up acceleration to obtain the first speed; The speed of the previous flight corresponding to the target aircraft and the relative distance between the target aircraft and the previous flight aircraft are detected, and a safe distance is determined based on the speed of the previous flight aircraft and the relative distance. Based on the safe distance, the target aircraft is decelerated according to the first speed to obtain the second speed; If the relative distance is greater than the product of the predetermined aircraft departure interval and the desired flight speed, the target aircraft is accelerated a second time based on the second speed to obtain the third speed; The position of the target aircraft in the cell is updated based on the third velocity.

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

4. The aircraft operation simulation method based on cellular automata according to claim 1, characterized in that, The determination of the merging priority of other aircraft on the merging route and the target aircraft includes: Detect the speed of the target aircraft and the first merging distance between the target aircraft and the merging point; Detect the speed of the other aircraft and the second merging distance between the other aircraft and the merging point; Based on the speed of the target aircraft and the first merging distance, the first merging time corresponding to the target aircraft is determined; Based on the speed of the other aircraft and the second merging distance, the second merging time corresponding to the other aircraft is determined; If the first inbound time is less than the second inbound time, the inbound priority of the target aircraft is determined to be higher than that of the other aircraft; or, if the first inbound time is greater than the second inbound time, the inbound priority of the target aircraft is determined to be lower than that of the other aircraft.

5. The aircraft operation simulation method based on cellular automata according to claim 1, characterized in that, The simulation of the target aircraft's operation based on the operating scenario includes: If the target aircraft is in a diversion scenario, determine the previous aircraft on the route to which the target aircraft is diverted; Detect the first distance between the target aircraft and the diversion point and the 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 the predetermined minimum safe distance, the target aircraft will be decelerated.

6. The aircraft operation simulation method based on cellular automata according to claim 1, characterized in that, The simulation of the target aircraft's operation based on the operating scenario includes: If the target aircraft is in an interleaving scenario, determine the interleaving route and interleaving point corresponding to the current route of the target aircraft; Determine the interleaving priority of other aircraft on the interleaving route and the target aircraft; If the interleaving priority of the target aircraft is higher than that of the other aircraft, detect whether a conflict occurs between the target aircraft and the other aircraft; If the target aircraft does not collide with the other aircraft, detect the third distance of the target aircraft from the interleaving point and the fourth distance of the target aircraft's previous flight aircraft from the interleaving point; If the sum of the third distance and the fourth distance is less than the predetermined minimum safe distance, the target aircraft will be decelerated.

7. A flight operation simulation system based on cellular automata, characterized in that, The system includes: An acquisition unit is used to acquire route network information and construct cells based on the route network information; wherein, the cell types 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 a maximum of one aircraft in the simulation. The identification unit is used to determine the position identifier corresponding to each cell based on the flight path and its position on the flight path, and to determine the state of the cell based on the aircraft running in the cell. The processing unit is used to determine the operating parameters corresponding to the target aircraft to be simulated, and to normalize the operating parameters according to the length of the segment cell; wherein, the operating parameters include the desired flight speed, the maximum flight speed, the start-up acceleration, and the braking acceleration; An execution unit is used to detect the operating scenario of the target aircraft and simulate the operation of the target aircraft according to the operating scenario; wherein, the types of operating scenarios include conflict-free scenarios, merging scenarios, splitting scenarios, and interleaving scenarios; The process of detecting the operating scenario of the target aircraft and simulating the operation of the target aircraft based on the operating scenario includes: If the target aircraft is detected to enter the merging range, it is determined that the target aircraft is in the merging scenario, and the merging route, target route, and merging point corresponding to the current route of the target aircraft are determined; Determine the merging priority of other aircraft on the merging route and the target aircraft; If the merging priority of the target aircraft is lower than that of the other aircraft, the relative distance between the target aircraft and the other aircraft after merging into the target flight path is detected. If the relative distance is less than a predetermined minimum safe distance, the target aircraft is decelerated.

8. 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 a cellular automaton-based aircraft operation simulation method as described in any one of claims 1-6.

9. A computer-readable storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to implement a cellular automaton-based aircraft operation simulation method as described in any one of claims 1-6.

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