Event-driven low-altitude transportation system rapid simulation method

Abstract

The invention relates to the technical field of urban traffic planning simulation, and particularly discloses a low-altitude transportation system rapid simulation method based on event driving, comprising the following steps: S1, a simulator analyzes and preloads a configuration file and a method module, and loads first data in the configuration file into a simulation environment; s2, the simulator configures first data and a travel calculation dependency module for the simulation model, and calculates a simulated initial travel plan; s3, the simulator initializes the simulation time and the simulation object state; s4, the simulation model performs simulation on the travel plan of the simulation object according to the simulation step to obtain a simulation result, and performs state updating and time recording on the simulation object according to the simulation result; and S5, the simulation model outputs a simulation result to a corresponding address in a file format according to an output directory in the configuration file. According to the method, parallel loading operation of large-scale simulation can be realized, calculation of an unnecessary simulation process is reduced, and the simulation efficiency is effectively improved.

Description

Technical Field

[0001] The invention relates to the technical field of urban traffic planning simulation, and in particular to an event-driven low-altitude transportation system rapid simulation method. Background Art

[0002] The problem of traffic congestion in urban space is becoming increasingly prominent. Traditional urban traffic management methods such as controlling demand, expanding roads, and developing public transportation have been unable to meet the growing traffic demand of large cities. Compared with traditional ground transportation, low-altitude transportation has the advantages of fewer obstacles, fewer restrictions, and more levels, but it also has higher requirements in terms of communication, scheduling, and safety. The common low-altitude traffic planning simulation software currently has the following problems:

[0003] (1) Simulation based on preset time steps requires processing a lot of invalid intermediate process information, which is time-consuming and inefficient, and cannot meet the high timeliness requirements of urban traffic operation;

[0004] (2) Path solving: Most simulation path solving processes use the Dijkstra algorithm, which traverses all nodes in the network to solve the shortest path. The solving process consumes a lot of time and computing power.

[0005] (3) Traditional simulation is limited by road space and rules and cannot realize parallel simulation of a large range of traffic behaviors. The simulation calculation process is time-consuming and inefficient. Summary of the invention

[0006] In order to solve the problems existing in the above-mentioned prior art, the present invention designs an event-driven low-altitude transportation system fast simulation method, which can realize parallel loading operation of large-scale simulation, reduce the calculation of unnecessary simulation process, and effectively improve the simulation efficiency. The specific technical scheme is as follows:

[0007] A fast simulation method for a low-altitude transportation system based on event-driven includes the following steps:

[0008] S1. The simulator parses and preloads the configuration file and the method module, and loads the first data in the configuration file into the simulation environment; the configuration file at least includes the output directory and the network data file, vehicle data file, infrastructure data file, travel plan data file of the simulation object running the simulation model, and the control parameter data file of the simulation model running; the first data at least includes network data, vehicle data, infrastructure data, travel plan data and control parameter data; a variable parameter table corresponding to the first data is provided in the simulation environment, and the variable parameter table at least includes a network attribute table, a vehicle attribute table and a simulation parameter table, the network attribute table corresponds to the network data of the simulation object, the vehicle attribute table corresponds to the vehicle data of the simulation object, and the simulation parameter table corresponds to the control parameter data of the simulation object;

[0009] S2, the simulator configures the first data and a travel calculation dependency module for a simulation model according to the first data, and calculates an initial travel plan for the simulation;

[0010] S3, the simulator initializes the simulation time and the simulation object state, and activates the monitoring call function;

[0011] S4, the simulation model simulates the travel plan of the simulation object according to the simulation steps to obtain a simulation result, and updates the state of the simulation object and records the time according to the simulation result;

[0012] S5. The simulation model outputs the simulation results in a file format to a corresponding address according to the output directory in the configuration file.

[0013] Preferably, the S1 specifically includes:

[0014] S11, inputting the configuration file address into the simulation model in the form of command line parameters, the simulation framework automatically parses the configuration file in the corresponding address, and after parsing, puts the first data in the configuration file into the corresponding scene container and loads it into the memory; the scene container is a collection of variables in the configuration file;

[0015] S12, the simulation framework parses the parameters of the running module in the configuration file and loads them into the running controller of the simulation model;

[0016] S13, the simulation framework verifies the field name and data format in the configuration file according to the preset data format;

[0017] S14. The simulation framework initializes the parameters and behaviors of the listener module and integrates it into the simulation model.

[0018] Preferably, the network data file at least includes a road network data file and a low-altitude airway network data file;

[0019] The vehicle data file includes at least the type, performance parameters, number, and capacity of cars, buses, ferries, subways, trains, and aircraft;

[0020] The infrastructure data file contains various behavior parameters in the infrastructure, and the behavior parameters at least include passengers entering and leaving the station, waiting for a flight, boarding a plane, and aircraft take-off, landing, and cruising;

[0021] The travel plan data file at least includes the travel number, starting and ending points, mode, and time;

[0022] The control parameter data file includes at least the total simulation duration, simulation step length, simulation random seed, simulation start time, end time, vehicle fare cost, distance cost and waiting cost.

[0023] Preferably, the calculation steps of the initial travel plan are as follows:

[0024] S21, injecting the method module and parameter configuration used in the simulation into the simulation model;

[0025] S22, injecting the first data in the configuration file into a unified scene container;

[0026] S23, calling the activity planner of the simulation model, calculating the specific path of the travel in the travel plan based on the A* algorithm, and configuring the specific path of the travel into the scene container.

[0027] Furthermore, the S3 specifically includes:

[0028] S31, initializing the simulation time according to the first data in the configuration file;

[0029] S32, judging the spatiotemporal correlation of the travel plans calculated by the activity planner: first, the travel plans are divided according to time periods, and the travel plans in the same time period are judged by cruise line interweaving, cruise line overlap and common take-off and landing sites, and the travel plans without spatiotemporal correlation are assigned to different plan pools for initial classification;

[0030] S33, initializing the state of the object whose state is constantly updated in the simulation;

[0031] S34. Activate the listener module.

[0032] Preferably, the S4 specifically includes:

[0033] S41, simulation step is an object state update cycle of simulation. The realization of travel plan is composed of events in simulation step. The object state is updated according to the events in simulation step. Each time a simulation iteration is performed, the state of the simulation object will be updated and advanced to the next simulation step. At the same time, the update of simulation step will filter and use the events in the corresponding simulation step stage;

[0034] S42. After determining the current simulation step, the simulation model determines whether the simulation is executed according to the current state of the object and obtains a judgment result, and updates or maintains the object state according to the judgment result:

[0035] S43, the simulation model calls the event manager in the simulator to detect whether all travel plans have completed simulation at the end of the simulation step, and calls the thread synchronization tool in the simulator after the simulation is completed;

[0036] S44, the simulation model determines the travel status of all objects. First, it determines whether the simulation process of all travel plans has ended, and at the same time determines whether the simulation has reached the preset deadline. If both are met, the simulation is terminated, otherwise the simulation step is updated to perform the next simulation.

[0037] Furthermore, the simulation execution specific steps are as follows:

[0038] S421, the simulation model obtains the initialization state of the vehicle, calls the state judgment module in the simulator, judges the vehicle state according to the current parameters of the vehicle, and calls the standard state list in the simulation environment to obtain the current state of the vehicle;

[0039] S422, the simulation model obtains the network initialization status, calculates the road network capacity, and determines whether other vehicles are currently allowed to enter;

[0040] S423. Call the network access judgment result in the network attribute table to judge the next state of the vehicle: if the network is allowed, the vehicle enters the new network and updates the node queue state, vehicle state and network state at the same time; if the network is saturated, the vehicle waits at the current node, and the state of the vehicle and the network remains unchanged. The simulation model will determine the state advancement of the vehicle according to the new state of the target network in the next simulation step.

[0041] Preferably, the simulation result includes at least the first data input into the configuration file of the simulation model and the travel time, activity time and travel path data output by the activity planner.

[0042] Preferably, after the simulation is finished, the listener module is closed, and exception troubleshooting and memory release are performed.

[0043] A computer-readable storage medium is also disclosed. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the event-driven low-altitude transportation system rapid simulation method is implemented.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The present invention adopts event-responsive simulation design to build an efficient event-based simulation framework. The A* algorithm is used in the simulation startup phase to speed up the pathfinding operation to support the flexible adjustment of the flight plan. At the same time, based on the independent layered characteristics of the route, the task is divided into subtask groups through the time-space correlation judgment of the task, and the parallel loading operation of large-scale simulation is realized. Through the above improvements, the present invention can realize the rapid simulation and evaluation of low-altitude high-frequency, heterogeneous, and high-complexity large-scale systems at any time point, reduce the calculation of unnecessary simulation processes, reduce the space and time complexity of the search, and greatly improve the simulation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0047] Figure 1 It is a flow chart of the simulation method of the present invention.

[0048] Figure 2 It is the overall flow chart of the present invention.

[0049] Figure 3 It is a simulation operation flow chart of the present invention.

[0050] Figure 4 It is a flow chart of judging the spatiotemporal correlation of travel plans according to the present invention.

[0051] Figure 5 It is a simulation execution flow chart of the present invention. DETAILED DESCRIPTION

[0052] The present invention is further illustrated below through the description of specific implementation methods, but this is not a limitation of the present invention. Those skilled in the art can make various modifications or improvements based on the basic idea of ​​the present invention, but as long as they do not deviate from the basic idea of ​​the present invention, they are all within the protection scope of the present invention.

[0053] The present invention aims to realize the simulation modeling of the urban low-altitude traffic system by constructing a clear "input-simulation-output" process framework. The framework is mainly divided into three main processes: input, simulation, and output. The input is responsible for configuring and controlling the simulation input information and model operation; the simulation process is responsible for the pre-configuration of the simulation, simulation step iteration, information monitoring and collection of the simulation process, etc.; the output is responsible for the cleaning, slicing, and standardization of the output data.

[0054] Description of the overall simulation process: Data in standard input format is passed into the configuration file in the form of a data file path, and is read and parsed by the simulator together with the key simulation parameters stored in the controller, and then called during the simulation process. Each intermediate step in the simulation process will be monitored by the listener and recorded by the event manager, and the intermediate results will be updated in the form of logs. After the simulation run is completed, the simulation results will generate corresponding output files according to the instructions of the controller, and generate results in the corresponding location according to the configuration path. The following will describe this process and the specific links involved.

[0055] See also Figures 1 to 5 , an embodiment provided by the present invention is as follows:

[0056] The present invention discloses a method for rapid simulation of a low-altitude transportation system based on event-driven, comprising the following steps:

[0057] S1. Simulation preloading: The simulator parses and preloads the configuration file and method module, and loads the first data in the configuration file into the simulation environment. The method module includes simulation preprocessing, input, operation and output program modules; the configuration file at least includes the output directory and the network data file, vehicle data file, infrastructure data file, travel plan data file of the simulation object running the simulation model, and the control parameter data file of the simulation model running; the first data at least includes network data, vehicle data, infrastructure data, travel plan data and control parameter data; a variable parameter table corresponding to the first data is provided in the simulation environment, and the variable parameter table at least includes a network attribute table, a vehicle attribute table and a simulation parameter table, the network attribute table corresponds to the network data of the simulation object, the vehicle attribute table corresponds to the vehicle data of the simulation object, and the simulation parameter table corresponds to the control parameter data of the simulation object:

[0058] The simulation process is the process of updating these tables multiple times, so it will be necessary to refresh the table data, create new tables, and overwrite old tables multiple times. This is a process of efficiently updating, iterating, transferring, and storing the variable space. The configuration file specifies everything used in the entire simulation, including the path where the input data is located, simulation control, traffic decisions, benefit calculations, mode selection and other parameters. The simulator is a complex code method library that processes and calculates the input files. This process uses various parameters, all of which come from the configuration file;

[0059] The network data file is a spatial carrier file that all kinds of travel modes in urban traffic need to complete travel. It is composed of nodes with spatial attributes and the connections between nodes, and is the basis for traffic simulation. The network data file includes at least a road network data file and a low-altitude airway network data file. The present invention integrates the road network and the low-altitude airway network into a unified network data file. In addition to acting on ground transportation, the road network is also designed to act on low-altitude travel needs and serve the air-to-ground transfer process;

[0060] Low-altitude transportation requires the use of aircraft of different types and parameters as transportation tools. The vehicle data file shall at least include the types, performance parameters, numbers, and capacities of cars, buses, ferries, subways, trains, and aircraft.

[0061] Low-altitude traffic needs to use road foundation design to simulate docking and transfer. The infrastructure data file contains various behavior parameters within the infrastructure. The behavior parameters at least include passengers entering and exiting the station, waiting, boarding, and aircraft take-off, landing, and cruising.

[0062] The travel plan data file is a file used to initialize the travel path parameter information during the simulator simulation process. The travel plan data file at least includes the travel number, starting and ending points, mode, and time;

[0063] The control parameter data file includes at least the total simulation duration, simulation step length, simulation random seed, simulation start time, end time, vehicle fare cost, distance cost and waiting cost.

[0064] S1 specifically includes:

[0065] S11, configuration injection: input the configuration file address into the simulation model in the form of command line parameters, the simulation framework automatically parses the configuration file in the corresponding address, and after parsing, puts the first data in the configuration file into the corresponding scene container and loads it into the memory for the simulation model to run and call; the scene container is a collection of variables in the configuration file;

[0066] S12, controller loading: the simulation framework parses the parameters of the running module in the configuration file and loads them into the running controller of the simulation model to control the running of the simulation model;

[0067] S13, input verification: the simulation framework verifies the field name and data format in the configuration file according to the preset data format to ensure that the input data meets the simulation model operation requirements and excludes missing or erroneous data;

[0068] S14. Listener loading: The simulation framework initializes the parameters and behaviors of the listener module and integrates it into the simulation model to ensure that the listener can correctly capture and process events during the simulation process.

[0069] S2, simulation start: the simulator configures the first data and the travel calculation dependency module for the simulation model according to the first data, and calculates the initial travel plan of the simulation; the calculation steps of the initial travel plan are as follows:

[0070] S21, simulation resource configuration: inject the method module and parameter configuration used in the simulation into the simulation model to ensure the smooth calling of the simulation model;

[0071] S22, simulation input configuration: injecting the first data in the configuration file into a unified scene container to facilitate unified calling;

[0072] S23, travel path calculation: call the activity planner of the simulation model, calculate the specific travel path in the travel plan based on the A* algorithm, and configure the specific travel path into the scene container as direct input data of the simulation model.

[0073] A* search algorithm is commonly known as A star algorithm. A* algorithm is one of the more popular heuristic search algorithms and is widely used in the field of path optimization. Its uniqueness is that it introduces global information when checking each possible node in the shortest path, estimates the distance between the current node and the end point, and uses it as a measure to evaluate the possibility of the node being on the shortest path.

[0074] S3, state initialization: the simulation model simulates the travel plan according to the simulation steps to obtain the simulation results, and updates the state of the simulation object and records the time according to the simulation results;

[0075] S3 specifically includes:

[0076] S31, initializing simulation time: initializing the simulation time according to the first data in the configuration file to ensure that the simulation runs according to the start time configured by the simulation model;

[0077] S32, subtask initialization: perform spatiotemporal correlation judgment on the travel plan calculated by the activity planner: first, divide the travel plan according to time periods, perform cruise line interweaving judgment, cruise line overlap judgment and take-off and landing shared site judgment on the travel plans in the same time period, and allocate the travel plans without spatiotemporal correlation to different plan pools for initialization and classification, so as to facilitate the use of different threads for simulation calculations;

[0078] S33, object state initialization: initializing the state of objects that are constantly updating their states in the simulation, ensuring that at the beginning of each simulation, all simulation objects are in the state at the end of the simulation activity in the previous simulation step;

[0079] S34, listener activation: Activate the listener module to ensure that the simulation can call the listener at any stage to monitor the simulation environment and record events.

[0080] S4, simulation operation: the simulation model simulates the travel plan according to the simulation steps to obtain simulation results, and updates the status of the simulation object and records the time according to the simulation results;

[0081] S4 specifically includes:

[0082] S41, simulation step update: a simulation step is an object state update cycle of the simulation. The realization of the travel plan is composed of events in the simulation step. The object state is updated according to the events in the simulation step. Each time a simulation iteration is performed, the state of the simulation object will be updated and advanced to the next simulation step. At the same time, the update of the simulation step will filter and use the events in the corresponding simulation step stage;

[0083] S42, simulation execution: After determining the current simulation step, the simulation model determines whether the simulation is executed according to the current state of the object and obtains a judgment result, and updates or maintains the object state according to the judgment result:

[0084] S43, simulation synchronization: the simulation model calls the event manager in the simulator to detect whether all travel plans have been simulated at the end of the simulation step, and calls the thread synchronization tool in the simulator after the simulation is completed to ensure that all threads are in the initial state before the next round of simulation iteration starts;

[0085] S44, iterative judgment: The simulation model judges the travel status of all objects. First, it judges whether the simulation process of all travel plans has ended, and at the same time, it judges whether the simulation has reached the preset deadline. If both are met, the simulation is terminated, otherwise the simulation step is updated to perform the next simulation.

[0086] Furthermore, the simulation execution specific steps are as follows:

[0087] S421, the simulation model obtains the initialization state of the vehicle, calls the state judgment module in the simulator, judges the vehicle state according to the current parameters of the vehicle, and calls the standard state list in the simulation environment to obtain the current state of the vehicle;

[0088] S422, the simulation model obtains the network initialization status, calculates the road network capacity, and determines whether other vehicles are currently allowed to enter;

[0089] S423. Call the network access judgment result in the network attribute table to judge the next state of the vehicle: if the network is allowed, the vehicle enters the new network and updates the node queue state, vehicle state and network state at the same time; if the network is saturated, the vehicle waits at the current node, and the state of the vehicle and the network remains unchanged. The simulation model will determine the state advancement of the vehicle according to the new state of the target network in the next simulation step.

[0090] Here we only take the interaction between the vehicle and the network as an example. The other examples are similar and will not be elaborated here.

[0091] S5. Output results: The simulation model outputs the simulation results in a file format to the corresponding address according to the output directory in the configuration file, and cleans, filters and statistically analyzes the simulation results. The simulation results at least include the data input into the configuration file of the simulation model, the travel information with specific details added by the activity planner, and the intermediate result events generated during the simulation process. The specific output content and format of the simulation results are controlled by adjusting the corresponding parameters in the configuration file.

[0092] Finally, after the simulation is completed, check whether there is a simulation process being executed in the current simulator, as well as the remaining processes waiting to enter the simulator. If not, close the listener module, end the iteration, terminate the simulation process, and perform exception troubleshooting and memory release.

[0093] Exception troubleshooting is to troubleshoot and record the exceptions that occur during the simulation process.

[0094] Memory release is to clear variables and instances during the simulation process, release memory, and ensure a clean environment for the next simulation.

[0095] The present invention also discloses a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned event-driven low-altitude transportation system rapid simulation method is implemented.

[0096] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present invention. Therefore, all equivalent modifications or changes made by a person with ordinary knowledge in the technical field without departing from the spirit and technical ideas disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A fast simulation method for low-altitude transportation system based on event-driven, characterized in that: The following steps are involved: S1. The simulator parses and preloads the configuration file and the method module, and loads the first data in the configuration file into the simulation environment; the configuration file at least includes the output directory and the network data file, vehicle data file, infrastructure data file, travel plan data file of the simulation object running the simulation model, and the control parameter data file of the simulation model running; the first data at least includes network data, vehicle data, infrastructure data, travel plan data and control parameter data; a variable parameter table corresponding to the first data is provided in the simulation environment, and the variable parameter table at least includes a network attribute table, a vehicle attribute table and a simulation parameter table, the network attribute table corresponds to the network data of the simulation object, the vehicle attribute table corresponds to the vehicle data of the simulation object, and the simulation parameter table corresponds to the control parameter data of the simulation object; S2, the simulator configures the first data and a travel calculation dependency module for a simulation model according to the first data, and calculates an initial travel plan for simulation; S3, the simulator initializes the simulation time and the simulation object state, and activates the monitoring call function; S4, the simulation model simulates the travel plan of the simulation object according to the simulation steps to obtain a simulation result, and updates the state of the simulation object and records the time according to the simulation result; S5. The simulation model outputs the simulation results in a file format to a corresponding address according to the output directory in the configuration file.

2. The event-driven low-altitude transportation system rapid simulation method according to claim 1 is characterized in that: The S1 specifically includes: S11, inputting the configuration file address into the simulation model in the form of command line parameters, the simulation framework automatically parses the configuration file in the corresponding address, and after parsing, puts the first data in the configuration file into the corresponding scene container and loads it into the memory; the scene container is a collection of variables in the configuration file; S12, the simulation framework parses the parameters of the running module in the configuration file and loads them into the running controller of the simulation model; S13, the simulation framework verifies the field name and data format in the configuration file according to the preset data format; S14. The simulation framework initializes the parameters and behaviors of the listener module and integrates it into the simulation model.

3. The event-driven low-altitude transportation system rapid simulation method according to claim 1 is characterized in that: The network data files at least include a road network data file and a low-altitude airway network data file; The vehicle data file includes at least the type, performance parameters, number, and capacity of cars, buses, ferries, subways, trains, and aircraft; The infrastructure data file contains various behavior parameters in the infrastructure, and the behavior parameters at least include passengers entering and leaving the station, waiting for a flight, boarding a plane, and aircraft take-off, landing, and cruising; The travel plan data file at least includes the travel number, starting and ending points, mode, and time; The control parameter data file includes at least the total simulation duration, simulation step length, simulation random seed, simulation start time, end time, vehicle fare cost, distance cost and waiting cost.

4. The event-driven low-altitude transportation system rapid simulation method according to claim 1 is characterized in that: The calculation steps of the initial travel plan are as follows: S21, injecting the method module and parameter configuration used in the simulation into the simulation model; S22, injecting the first data in the configuration file into a unified scene container; S23, calling the activity planner of the simulation model, calculating the specific path of the travel in the travel plan based on the A* algorithm, and configuring the specific path of the travel into the scene container.

5. The event-driven low-altitude transportation system rapid simulation method according to claim 4 is characterized in that: The S3 specifically includes: S31, initializing the simulation time according to the first data in the configuration file; S32, judging the spatiotemporal correlation of the travel plans calculated by the activity planner: first, the travel plans are divided according to time periods, and the travel plans in the same time period are judged by cruise line interweaving, cruise line overlap and common take-off and landing sites, and the travel plans without spatiotemporal correlation are assigned to different plan pools for initial classification; S33, initializing the state of the object whose state is constantly updated in the simulation; S34. Activate the listener module.

6. The event-driven low-altitude transportation system rapid simulation method according to claim 1 is characterized in that: The S4 specifically includes: S41, simulation step is an object state update cycle of simulation. The realization of travel plan is composed of events in simulation step. The object state is updated according to the events in simulation step. Each time a simulation iteration is performed, the state of the simulation object will be updated and advanced to the next simulation step. At the same time, the update of simulation step will filter and use the events in the corresponding simulation step stage; S42. After determining the current simulation step, the simulation model determines whether the simulation is executed according to the current state of the object and obtains a judgment result, and updates or maintains the object state according to the judgment result: S43, the simulation model calls the event manager in the simulator to detect whether all travel plans have completed simulation at the end of the simulation step, and calls the thread synchronization tool in the simulator after the simulation is completed; S44, the simulation model determines the travel status of all objects. First, it determines whether the simulation process of all travel plans has ended, and at the same time determines whether the simulation has reached the preset deadline. If both are met, the simulation is terminated, otherwise the simulation step is updated to perform the next simulation.

7. The event-driven low-altitude transportation system rapid simulation method according to claim 6 is characterized in that: The specific steps of simulation execution are as follows: S421, the simulation model obtains the initialization state of the vehicle, calls the state judgment module in the simulator, judges the vehicle state according to the current parameters of the vehicle, and calls the standard state list in the simulation environment to obtain the current state of the vehicle; S422, the simulation model obtains the network initialization status, calculates the road network capacity, and determines whether other vehicles are currently allowed to enter; S423. Call the network access judgment result in the network attribute table to judge the next state of the vehicle: if the network is allowed, the vehicle enters the new network and updates the node queue state, vehicle state and network state at the same time; if the network is saturated, the vehicle waits at the current node, and the state of the vehicle and the network remains unchanged. The simulation model will determine the state advancement of the vehicle according to the new state of the target network in the next simulation step.

8. The event-driven low-altitude transportation system rapid simulation method according to claim 1 is characterized in that: The simulation result includes at least the first data input into the configuration file of the simulation model and the travel time, activity time and travel path data output by the activity planner.

9. The event-driven low-altitude transportation system rapid simulation method according to claim 1 is characterized in that: After the simulation is finished, close the listener module, and perform exception troubleshooting and memory release.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the event-driven low-altitude transportation system rapid simulation method according to any one of claims 1 to 9 is implemented.

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