A simulation test platform and method for autonomous attack planning function of unmanned aerial vehicle

Abstract

The present application provides a UAV autonomous attack planning function simulation test platform and method thereof, which constructs a digital simulation test environment with a modular and combined UAV autonomous attack planning function simulation test platform, and can conveniently and flexibly set the battlefield environment, mission objectives, injection of unexpected conditions, as well as the initial state of the UAV, parameters of weapons, etc., to efficiently simulate and verify the autonomous situation cognition and planning capabilities of the UAV autonomous situation cognition and planning module.

Description

Technical Field

[0001] The present application belongs to the technical field of autonomous attack planning function test of unmanned aerial vehicles, and specifically relates to a simulation test platform and method for autonomous attack planning function of unmanned aerial vehicles. Background Art

[0002] Using drones to perform attack missions does not require considering the pilot's physiological and psychological limits. It has performance advantages such as high overload, high maneuverability, and high stealth, and it is reusable.

[0003] For a drone to autonomously perform attack missions, its autonomous situation recognition and planning modules need to have strong adaptability and be able to cope with battlefield situations, communication denial environments, dynamic changes in missions, etc. Autonomous situation recognition and planning capabilities are of great significance to improving the survivability of drones.

[0004] Currently, there is a lack of a means to fully verify the autonomous situation awareness and planning capabilities of the autonomous situation awareness and planning module before it is applied onboard. In view of this, this application is proposed. Summary of the invention

[0005] The purpose of this application is to provide a UAV autonomous attack planning function simulation test platform and method, so as to fully verify its autonomous situation cognition and planning capabilities before the autonomous situation cognition and planning module is applied.

[0006] Overcome or alleviate at least one of the known technical deficiencies.

[0007] The technical solution of this application is:

[0008] On the one hand, a UAV autonomous attack planning function simulation test platform is provided, including:

[0009] UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and visual simulator, unexpected condition injection simulation module, autonomous situation recognition and planning digital prototype;

[0010] The UAV simulator is a digital simulation of the UAV itself, which can receive control instructions from the autonomous situation awareness and planning digital prototype to maneuver, and can feed back the status information of the airborne system to the autonomous situation awareness and planning digital prototype;

[0011] The weapon system simulator is a digital simulation of the UAV weapon system. It can receive control instructions from the autonomous situation awareness and planning digital prototype, control the weapon to be released, and can feedback the weapon status information to the autonomous situation awareness and planning digital prototype.

[0012] Weapon database module, used to configure the parameters of weapons in the weapon system simulator;

[0013] The photoelectric detection simulator is a digital simulation of the photoelectric detector of the UAV, which can detect and monitor the battlefield environment and mission target information, and transmit it to the autonomous situation awareness and planning digital prototype;

[0014] The mission target simulator is used to configure mission target information;

[0015] The battlefield environment simulator is used to configure battlefield environment information;

[0016] An unexpected condition injection simulation module is used to configure unexpected conditions and inject unexpected conditions into the visual simulator when triggered;

[0017] The situation and visual simulator integrates the status information of the airborne system, the status information of the weapon, the reconnaissance and surveillance information of the optoelectronic detection simulator, the mission target information that can be detected by the coordinated UAV, the battlefield environment information that can be detected by the coordinated UAV, and unexpected conditions, and evaluates the combat situation in real time, and displays it in real time through the visual scene, and transmits it to the autonomous situation cognition and planning digital prototype;

[0018] The autonomous situation awareness and planning digital prototype is the operating carrier of the autonomous situation awareness and planning module of the UAV. It is interconnected with the UAV simulator, weapon system simulator, optoelectronic detection simulator, situation and vision simulator through the bus to calculate control instructions.

[0019] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, the weapon database module configures the parameters of the weapons in the weapon system simulator, including the performance and type of the weapons.

[0020] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, the performance of the weapon includes attack mode, weapon speed, and damage radius;

[0021] Types of weapons include SDB bombs and LGB bombs.

[0022] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, the optoelectronic detection simulator conducts reconnaissance and monitoring of the battlefield environment and mission target information, including real-time detection and automatic warning of incoming missiles, and searches, captures, tracks and locates mission targets, and can provide real-time images and data.

[0023] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, the mission target simulator configures the mission target information, including the height, speed, threat level and type of the mission target.

[0024] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, the battlefield environment simulator is configured with battlefield environment information, including battlefield threats, weather conditions, electromagnetic environment, and mountain environment.

[0025] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, battlefield threats include ground radar, anti-aircraft artillery, and unmanned attack aircraft.

[0026] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, the unexpected condition injection simulation module configures unexpected conditions, including sudden threats / random targets, mission target changes / disappearance, and enemy surface-to-air missiles.

[0027] Optionally, in the above-mentioned UAV autonomous attack planning function simulation test platform, sudden threats / random targets include ground-based air defense missiles, dangerous weather areas, air defense radars, command posts, and command vehicles.

[0028] Optionally, the above-mentioned UAV autonomous attack planning function simulation test platform also includes a ground control station simulator;

[0029] The ground control station simulator is a digital simulation of the ground control station. It communicates with the autonomous situation awareness and planning digital prototype through a data link simulator, and can obtain mission target information that can be detected by the ground control station and some battlefield environment information that can be detected by the ground control station. It can display it in real time through the visual scene and can accept external commands. It can control the maneuverability of the UAV and the delivery of weapons through the autonomous situation awareness and planning digital prototype.

[0030] Optionally, the above-mentioned UAV autonomous attack planning function simulation test platform further includes a simulation evaluation unit;

[0031] The simulation evaluation unit includes a simulation data analysis module and a simulation result evaluation module, wherein:

[0032] The simulation data analysis module is used to record the simulation data of the UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and visual simulator, unexpected condition injection simulation module, autonomous situation recognition and planning digital prototype, data link simulator, and ground control station simulator, and process the simulation data and analyze the simulation results;

[0033] The simulation result evaluation module is used to evaluate the simulation results and determine whether the simulation results meet the index requirements.

[0034] Optionally, the above-mentioned UAV autonomous attack planning function simulation test platform also includes a master control console;

[0035] The main control console can initialize the UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and vision simulator, unexpected condition injection simulation module, autonomous situation awareness and planning digital prototype, data link simulator, ground control station simulator, and control the start, run, pause, and end of the UAV autonomous attack planning function simulation test platform.

[0036] On the other hand, a method for simulating the autonomous attack planning function of a UAV is provided, which is implemented based on the above-mentioned UAV autonomous attack planning function simulation test platform, and includes:

[0037] S1. Configure battlefield environment information with a battlefield environment simulator and set the battlefield environment;

[0038] S2. Configure the task target information with the task target simulator and set the task target;

[0039] S3, configuring the unexpected condition with the unexpected condition injection simulation module, and setting the unexpected condition injection;

[0040] S4. Use the drone simulator to set the initial state of the drone, including flight altitude, flight speed, angle of attack, sideslip angle, fuel quantity, N1 speed, and N2 speed;

[0041] S5. configuring the parameters of the weapons in the weapon system simulator using the weapon database module;

[0042] S6. Load the attack mission into the autonomous situation awareness and planning digital prototype;

[0043] S7, start simulation;

[0044] S8, use the autonomous situation recognition and planning digital prototype to calculate control instructions, control drones and weapons, and attack mission targets;

[0045] S9. Determine whether the drone has crashed:

[0046] If the UAV crashes, the calculation method of the autonomous situation recognition and planning digital prototype control instructions is updated, and the process returns to S1 to perform simulation again;

[0047] If the drone does not crash, determine whether the attack mission is completed:

[0048] If the attack task is not completed, return to S8;

[0049] If the attack mission is completed, the simulation evaluation unit analyzes the simulation results and evaluates the simulation results. If the simulation results meet the index requirements, the simulation is terminated. If the simulation results do not meet the index requirements, the calculation method of the autonomous situation recognition and planning digital prototype control instructions is updated, and S1 is returned to re-simulate.

[0050] This application has at least the following beneficial technical effects:

[0051] The invention provides a UAV autonomous attack planning function simulation test platform and a method thereof. A modular and combined UAV autonomous attack planning function simulation test platform is used to construct a digital simulation test environment, which can conveniently and flexibly set the battlefield environment, mission objectives, injection of unexpected conditions, as well as the initial state of the UAV and the parameters of the weapon, so as to perform efficient simulation verification on the autonomous situation cognition and planning capabilities of the UAV autonomous situation cognition and planning module. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 Schematic diagram of a simulation test platform for autonomous attack planning function of a UAV provided in an embodiment of the present application;

[0053] Figure 2 It is a schematic diagram of a simulation test method for the autonomous attack planning function of a drone provided in an embodiment of the present application.

[0054] In order to better illustrate the present embodiment, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product. In addition, the drawings are only used for illustrative purposes and should not be construed as limitations on the present application. DETAILED DESCRIPTION

[0055] In order to make the technical solution and advantages of the present application clearer, the technical solution of the present application will be described in further detail in detail and in detail with reference to the accompanying drawings. It can be understood that the specific embodiments described here are only partial embodiments of the present application, which are only used to explain the present application, not to limit the present application. It should be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, and other related parts can refer to the general design.

[0056] In addition, unless otherwise defined, the technical terms or scientific terms used in the description of this application shall have the usual meanings understood by those of ordinary skill in the art to which this application belongs. The words used in the description of this application to indicate orientation are only used to indicate relative directions or positional relationships. When the absolute position of the described object changes, its relative positional relationship may also change accordingly. The word "include" used in the description of this application indicates that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, but does not exclude other elements or objects.

[0057] In addition, it should be noted that, unless otherwise clearly specified and limited, the words "installation", "connection" and similar terms used in the description of this application should be understood in a broad sense. For example, the connection can be a fixed connection or a detachable connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. Technical personnel in the field can understand its specific meaning in this application according to the specific circumstances.

[0058] On the one hand, the present application provides a simulation test platform for autonomous attack planning functions of unmanned aerial vehicles, such as Figure 1 As shown, it includes UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and vision simulator, unexpected condition injection simulation module, autonomous situation awareness and planning digital prototype, data link simulator, ground control station simulator, simulation evaluation unit, and main control console.

[0059] The drone simulator is a digital simulation of the drone itself, including airborne systems such as the flight control system, power system, auxiliary power system, fuel system, landing gear brake and turning control system, fire protection system, lighting system, power supply system, environmental protection system, and hydraulic system. It can receive control instructions from the autonomous situation recognition and planning digital prototype to maneuver, and can feedback the status information of the airborne system to the autonomous situation recognition and planning digital prototype.

[0060] The weapon system simulator is a digital simulation of the UAV weapon system. It can receive control instructions from the autonomous situation awareness and planning digital prototype, control the weapon delivery, and feedback the weapon status information to the autonomous situation awareness and planning digital prototype.

[0061] The weapon database module can be embedded in the weapon system simulator to configure the parameters of the weapons in the weapon system simulator, including the performance and type of the weapons. The performance of the weapons includes the attack mode, weapon speed, damage radius, etc.; the types of weapons include SDB bombs, LGB bombs, etc.

[0062] The optoelectronic detection simulator is a digital simulation of the optoelectronic detector of a UAV. It can detect and monitor the battlefield environment and mission target information, and transmit it to the autonomous situation awareness and planning digital prototype. It can perform real-time detection and automatic warning of incoming missiles, search, capture, track and locate mission targets, and provide real-time images and data.

[0063] The mission target simulator is used to configure mission target information, including the altitude, speed, threat level and type of the mission target, wherein the type of the mission target may be an enemy command post.

[0064] The battlefield environment simulator is used to configure battlefield environment information, including battlefield threats, weather conditions, electromagnetic environment, mountain environment, etc. Among them, battlefield threats include ground radar, anti-aircraft artillery, unmanned attack aircraft, etc.

[0065] The unexpected condition injection simulation module can be embedded in the situation and visual simulator to configure unexpected conditions. When triggered, the unexpected conditions are injected into the visual simulator. The unexpected conditions include sudden threats / random targets, changes / disappearance of mission objectives, and enemy surface-to-air missiles. Among them, sudden threats / random targets include ground-based air defense missiles, dangerous weather areas, air defense radars, command posts, command vehicles, etc.

[0066] The situation and vision simulator integrates the status information of the airborne system, the status information of the weapons, the reconnaissance and surveillance information of the optoelectronic detection simulator, the mission target information that can be detected by the coordinated UAV, the battlefield environment information that can be detected by the coordinated UAV, and unexpected conditions, and evaluates the combat situation in real time. It displays it in real time through the vision and transmits it to the autonomous situation awareness and planning digital prototype.

[0067] The autonomous situation awareness and planning digital prototype is the operating carrier of the autonomous situation awareness and planning module of the UAV. It is interconnected with the UAV simulator, weapon system simulator, optoelectronic detection simulator, situation and vision simulator through the bus to calculate control instructions.

[0068] The ground control station simulator is a digital simulation of the ground control station. It communicates with the autonomous situation awareness and planning digital prototype through a data link simulator, and can obtain mission target information that can be detected by the ground control station and some battlefield environment information that can be detected by the ground control station. It can display it in real time through the visual scene and can accept external commands. It can control the maneuverability of the UAV and the delivery of weapons through the autonomous situation awareness and planning digital prototype, which may include joystick control commands, pedal control commands, throttle platform control commands, etc.

[0069] The simulation evaluation unit includes a simulation data analysis module and a simulation result evaluation module. The simulation data analysis module is used to record the simulation data of the UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and vision simulator, unexpected condition injection simulation module, autonomous situation recognition and planning digital prototype, data link simulator, and ground control station simulator, and processes the simulation data and analyzes the simulation results. The simulation result evaluation module is used to evaluate the simulation results and determine whether the simulation results meet the index requirements.

[0070] The main control console can initialize the UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and vision simulator, unexpected condition injection simulation module, autonomous situation awareness and planning digital prototype, data link simulator, and ground control station simulator, and control the start, run, pause, and end of the UAV autonomous attack planning function simulation test platform as a whole.

[0071] Those skilled in the art should also be able to appreciate that the various modules and units of the drone autonomous attack planning function simulation test platform disclosed in the embodiments of the present application can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, this application generally describes them according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can choose to adopt different methods to implement the described functions for each specific application and its actual constraints, but such implementation should not be considered to be beyond the scope of this application.

[0072] Based on the UAV autonomous attack planning function simulation test platform disclosed in the above embodiment, the present application also provides a UAV autonomous attack planning function simulation test method, such as Figure 2 shown.

[0073] S1. Configure battlefield environment information with a battlefield environment simulator and set the battlefield environment;

[0074] S2. Configure the task target information with the task target simulator and set the task target;

[0075] S3, configuring the unexpected condition with the unexpected condition injection simulation module, and setting the unexpected condition injection;

[0076] S4. Use the drone simulator to set the initial state of the drone, including flight altitude, flight speed, angle of attack, sideslip angle, fuel quantity, N1 speed, N2 speed, etc.;

[0077] S5. configuring the parameters of the weapons in the weapon system simulator using the weapon database module;

[0078] S6. Load the attack mission into the autonomous situation awareness and planning digital prototype;

[0079] S7, start simulation;

[0080] S8, use the autonomous situation recognition and planning digital prototype to calculate control instructions, control drones and weapons, and attack mission targets;

[0081] S9. Determine whether the drone has crashed:

[0082] If the UAV crashes, the calculation method of the autonomous situation recognition and planning digital prototype control instructions is updated, and the process returns to S1 to perform simulation again;

[0083] If the drone does not crash, determine whether the attack mission is completed:

[0084] If the attack task is not completed, return to S8;

[0085] If the attack mission is completed, the simulation evaluation unit analyzes the simulation results and evaluates the simulation results. If the simulation results meet the index requirements, the simulation is terminated. If the simulation results do not meet the index requirements, the calculation method of the autonomous situation recognition and planning digital prototype control instructions is updated, and S1 is returned to re-simulate.

[0086] The UAV autonomous attack planning function simulation test platform and method disclosed in the above-mentioned embodiment use a modular and combined UAV autonomous attack planning function simulation test platform to construct a digital simulation test environment, which can conveniently and flexibly set the battlefield environment, mission objectives, injection of unexpected conditions, as well as the initial state of the UAV, weapon parameters, etc., to efficiently simulate and verify the autonomous situation cognition and planning capabilities of the UAV autonomous situation cognition and planning module.

[0087] So far, the technical solution of the present application has been described in conjunction with the preferred embodiments shown in the accompanying drawings. Those skilled in the art should understand that the scope of protection of the present application is obviously not limited to these specific embodiments. Without departing from the principles of the present application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the scope of protection of the present application.

Claims

1. A UAV autonomous attack planning function simulation test platform, characterized in that: include: UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and visual simulator, unexpected condition injection simulation module, autonomous situation recognition and planning digital prototype; The UAV simulator is a digital simulation of the UAV itself, which can receive control instructions from the autonomous situation awareness and planning digital prototype to maneuver, and can feed back the status information of the airborne system to the autonomous situation awareness and planning digital prototype; The weapon system simulator is a digital simulation of the UAV weapon system. It can receive control instructions from the autonomous situation awareness and planning digital prototype, control the weapon to be released, and can feedback the weapon status information to the autonomous situation awareness and planning digital prototype. Weapon database module, used to configure the parameters of weapons in the weapon system simulator; The photoelectric detection simulator is a digital simulation of the photoelectric detector of the UAV, which can detect and monitor the battlefield environment and mission target information, and transmit it to the autonomous situation awareness and planning digital prototype; The mission target simulator is used to configure mission target information; The battlefield environment simulator is used to configure battlefield environment information; An unexpected condition injection simulation module is used to configure unexpected conditions and inject unexpected conditions into the visual simulator when triggered; The situation and visual simulator integrates the status information of the airborne system, the status information of the weapon, the reconnaissance and surveillance information of the optoelectronic detection simulator, the mission target information that can be detected by the coordinated UAV, the battlefield environment information that can be detected by the coordinated UAV, and unexpected conditions, and evaluates the combat situation in real time, and displays it in real time through the visual scene, and transmits it to the autonomous situation cognition and planning digital prototype; The autonomous situation awareness and planning digital prototype is the operating carrier of the autonomous situation awareness and planning module of the UAV. It is interconnected with the UAV simulator, weapon system simulator, optoelectronic detection simulator, situation and vision simulator through the bus to calculate control instructions.

2. The UAV autonomous attack planning function simulation test platform according to claim 1 is characterized in that: The weapon database module configures the parameters of the weapons in the weapon system simulator, including the performance and type of the weapons.

3. The UAV autonomous attack planning function simulation test platform according to claim 2 is characterized in that: Weapon performance includes attack mode, weapon speed, and damage radius; Types of weapons include SDB bombs and LGB bombs.

4. The UAV autonomous attack planning function simulation test platform according to claim 3 is characterized in that: The optoelectronic detection simulator conducts reconnaissance and monitoring of the battlefield environment and mission target information, including real-time detection and automatic warning of incoming missiles, searching, capturing, tracking and locating mission targets, and can provide real-time images and data.

5. The UAV autonomous attack planning function simulation test platform according to claim 4 is characterized in that: The mission target simulator configures mission target information, including the altitude, speed, threat level and type of the mission target.

6. The UAV autonomous attack planning function simulation test platform according to claim 5 is characterized in that: The battlefield environment simulator is configured with battlefield environment information, including battlefield threats, weather conditions, electromagnetic environment, and mountain environment.

7. The UAV autonomous attack planning function simulation test platform according to claim 6 is characterized in that: Battlefield threats include ground-based radars, anti-aircraft artillery, and unmanned attack aircraft.

8. The UAV autonomous attack planning function simulation test platform according to claim 7 is characterized in that: The unexpected condition injection simulation module configures unexpected conditions, including sudden threats / random targets, mission target changes / disappearance, and enemy surface-to-air missiles.

9. The UAV autonomous attack planning function simulation test platform according to claim 8 is characterized in that: Sudden threats / random targets include ground-based air defense missiles, dangerous weather areas, air defense radars, command posts, and command vehicles.

10. The UAV autonomous attack planning function simulation test platform according to claim 9 is characterized in that: Also included is a ground control station simulator; The ground control station simulator is a digital simulation of the ground control station. It communicates with the autonomous situation awareness and planning digital prototype through a data link simulator, and can obtain mission target information that can be detected by the ground control station and some battlefield environment information that can be detected by the ground control station. It can display it in real time through the visual scene and can accept external commands. It can control the maneuverability of the UAV and the delivery of weapons through the autonomous situation awareness and planning digital prototype.

11. The UAV autonomous attack planning function simulation test platform according to claim 10 is characterized in that: Also includes a simulation evaluation unit; The simulation evaluation unit includes a simulation data analysis module and a simulation result evaluation module, wherein: The simulation data analysis module is used to record the simulation data of the UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and visual simulator, unexpected condition injection simulation module, autonomous situation recognition and planning digital prototype, data link simulator, and ground control station simulator, and process the simulation data and analyze the simulation results; The simulation result evaluation module is used to evaluate the simulation results and determine whether the simulation results meet the index requirements.

12. The UAV autonomous attack planning function simulation test platform according to claim 11 is characterized in that: It also includes a master console; The main control console can initialize the UAV simulator, weapon system simulator, weapon database module, optoelectronic detection simulator, mission target simulator, battlefield environment simulator, situation and vision simulator, unexpected condition injection simulation module, autonomous situation awareness and planning digital prototype, data link simulator, ground control station simulator, and control the start, run, pause, and end of the UAV autonomous attack planning function simulation test platform.

13. A method for simulating the autonomous attack planning function of a drone, implemented based on the autonomous attack planning function simulation test platform of claim 12, characterized in that: include: S1. Configure battlefield environment information with a battlefield environment simulator and set the battlefield environment; S2. Configure the task target information with the task target simulator and set the task target; S3, configuring the unexpected condition with the unexpected condition injection simulation module, and setting the unexpected condition injection; S4. Use the drone simulator to set the initial state of the drone, including flight altitude, flight speed, angle of attack, sideslip angle, fuel quantity, N1 speed, and N2 speed; S5. configuring the parameters of the weapons in the weapon system simulator using the weapon database module; S6. Load the attack mission into the autonomous situation awareness and planning digital prototype; S7, start simulation; S8, use the autonomous situation recognition and planning digital prototype to calculate control instructions, control drones and weapons, and attack mission targets; S9. Determine whether the drone has crashed: If the UAV crashes, the calculation method of the autonomous situation recognition and planning digital prototype control instructions is updated, and the process returns to S1 to perform simulation again; If the drone does not crash, determine whether the attack mission is completed: If the attack task is not completed, return to S8; If the attack mission is completed, the simulation evaluation unit analyzes the simulation results and evaluates the simulation results. If the simulation results meet the index requirements, the simulation is terminated. If the simulation results do not meet the index requirements, the calculation method of the autonomous situation recognition and planning digital prototype control instructions is updated, and S1 is returned to re-simulate.

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