Post-fault processing method and system for unmanned mine car, and storage medium
By working together with the fault diagnosis system and the unmanned driving system, faults in unmanned mining trucks are automatically handled, ensuring the timeliness and accuracy of fault handling and improving the safety of unmanned mining trucks.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SANY INTELLIGENT MINING TECH CO LTD
- Filing Date
- 2023-04-03
- Publication Date
- 2026-05-29
AI Technical Summary
In existing technologies, when unmanned mining trucks malfunction, the faults cannot be handled in a timely and accurate manner, resulting in a lack of safety assurance.
A post-fault handling method and system are provided. The system receives fault data reported by the functional system through a fault diagnosis system, determines the target fault handling measures, and generates a list of measures to be executed by the autonomous driving system. These measures are executed in sequence according to the processing priority, including deceleration, stopping, self-repair and scheduling measures.
It enables timely and accurate handling of malfunctions in unmanned mining trucks, thus improving safety.
Smart Images
Figure CN116424355B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of post-fault processing technology, and in particular to a post-fault processing method and system, storage medium, and computer equipment for unmanned mining trucks. Background Technology
[0002] With the continuous development of autonomous driving technology and increasingly stringent national requirements for intelligent and unmanned operations in mining, driverless mining trucks have become an inevitable trend in mining. In future smart mines, the entire mining operation will increasingly require no human intervention, thus placing higher demands on the safety of driverless mining trucks. Among these demands, the post-fault handling function after a malfunction is one of the key factors ensuring the safety of driverless mining trucks.
[0003] In existing technologies, when unmanned mining trucks malfunction, post-malfunction control and diagnosis are typically performed manually. This method not only fails to guarantee timely handling of malfunctions, but the effectiveness is also affected by human experience. Therefore, the safety of unmanned mining trucks after malfunctions is often not guaranteed. Summary of the Invention
[0004] In view of this, this application provides a method and system for post-fault handling of unmanned mining trucks, a storage medium, and a computer device, which on the one hand ensures the timeliness of fault handling after a fault occurs in the unmanned mining truck, and on the other hand ensures the accuracy of fault handling, thereby greatly improving the safety of the unmanned mining truck.
[0005] According to one aspect of this application, a post-fault handling method for an unmanned mining truck is provided, comprising:
[0006] When the fault diagnosis system receives fault data reported by any functional system of the unmanned mining truck, it determines the corresponding target fault handling measure from the preset fault handling measures based on the fault data, and sends the target fault handling measure to the unmanned driving system.
[0007] The autonomous driving system receives multiple target fault handling measures, generates a list of measures to be executed based on the multiple target fault handling measures, and executes the measures to be executed sequentially based on the processing priority of the measures to be executed in the list of measures to be executed.
[0008] According to another aspect of this application, a fault post-processing system for an unmanned mining truck is provided, including a fault diagnosis system and an unmanned driving system;
[0009] The fault diagnosis system is used to determine the corresponding target fault handling measure from the preset fault handling measures based on the fault data when it receives fault data reported by any functional system of the unmanned mining vehicle, and to send the target fault handling measure to the unmanned driving system.
[0010] The autonomous driving system is configured to receive multiple target fault handling measures, generate a list of measures to be executed based on the multiple target fault handling measures, and execute the measures to be executed sequentially based on the processing priority of the measures to be executed in the list of measures to be executed.
[0011] According to another aspect of this application, a storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the above-described post-fault handling method for unmanned mining trucks.
[0012] According to another aspect of this application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the program to implement the above-described post-fault handling method for unmanned mining trucks.
[0013] By employing the above technical solution, this application provides a post-fault handling method and system, storage medium, and computer equipment for unmanned mining trucks. When the fault diagnosis system receives fault data reported by any functional system, it directly finds the corresponding target fault handling measures based on the fault data and sends the target fault handling measures to the unmanned driving system. This allows the unmanned driving system to generate a list of measures to be executed based on the target fault handling measures and execute these measures according to their processing priority. This achieves the technical effect of automatically handling post-faults of unmanned mining trucks, ensuring both the timeliness and accuracy of fault handling after a fault occurs, thereby greatly improving the safety of unmanned mining trucks.
[0014] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description
[0015] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:
[0016] Figure 1A schematic flowchart of a post-fault handling method for an unmanned mining truck provided in an embodiment of this application is shown.
[0017] Figure 2 The diagram shows a schematic of each functional system in the driverless mining truck provided in the embodiments of this application;
[0018] Figure 3 A schematic diagram illustrating the types of preset fault handling measures provided in the embodiments of this application is shown;
[0019] Figure 4 A flowchart illustrating another post-fault handling method for unmanned mining trucks provided in an embodiment of this application is shown.
[0020] Figure 5 A schematic diagram of a fault post-processing system for an unmanned mining truck provided in an embodiment of this application is shown. Detailed Implementation
[0021] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.
[0022] This embodiment provides a post-fault handling method for unmanned mining trucks, such as... Figure 1 As shown, the method includes:
[0023] Step 101: When the fault diagnosis system receives fault data reported by any functional system of the unmanned mining truck, it determines the corresponding target fault handling measure from the preset fault handling measures based on the fault data, and sends the target fault handling measure to the unmanned driving system.
[0024] Step 102: The autonomous driving system receives multiple target fault handling measures and generates a list of measures to be executed based on the multiple target fault handling measures. Based on the processing priority of the measures to be executed in the list of measures to be executed, the measures to be executed are executed in sequence.
[0025] The fault post-processing method for unmanned mining trucks provided in this application embodiment can be implemented based on a fault post-processing system. This system can be applied to unmanned mining trucks and may include two systems: a fault diagnosis system and an unmanned driving system. In addition to the fault post-processing system, the unmanned mining truck may also include several other functional systems, such as... Figure 2As shown, examples include the battery system, vehicle powertrain system, vehicle steering system, body system, etc. Each functional system can diagnose faults in its corresponding function and generate fault data upon diagnosis. Each functional system is connected to the fault diagnosis system in the fault post-processing system, specifically through a CAN bus for communication between the functional systems and the fault diagnosis system. After generating fault data, each functional system can report the fault data to the fault diagnosis system. Upon receiving fault data reported by any functional system, the fault diagnosis system can find the corresponding target fault handling measure from multiple preset fault handling measures. Here, the fault data can be fault codes in the format specified by the Society of Automotive Engineers (SAE), and the preset fault handling measures can be those corresponding to the fault codes. After determining the target fault handling measure, the fault diagnosis system can distribute it to the autonomous driving system. It is important to note that the fault diagnosis system can simultaneously receive fault data reported by multiple functional systems and find the corresponding target fault handling measure for each piece of fault data. Figure 3 As shown, the preset fault handling measures can be deceleration measures, stopping measures, self-repair measures, scheduling measures, etc.
[0026] After receiving fault data reported by various functional systems, the fault diagnosis system can clean each piece of fault data. Specifically, it can compare the received fault data with preset data. When the comparison result shows that the received fault data belongs to the preset data, the system executes the step of determining the target fault handling measures; otherwise, it can directly process the error and send the generated error information to the preset management terminal corresponding to the staff, so that the staff can carry out subsequent processing in a timely manner. Here, the preset data can be data on faults that are currently known and have preset fault handling measures.
[0027] After receiving the target fault handling measures, the autonomous driving system can generate a list of measures to be executed, which may include multiple target fault handling measures. Then, these measures can be executed according to their processing priority. Once any measure has been executed, it can be removed from the list.
[0028] By applying the technical solution of this embodiment, when the fault diagnosis system receives fault data reported by any functional system, it directly finds the corresponding target fault handling measures based on the fault data and sends the target fault handling measures to the unmanned driving system. The unmanned driving system then generates a list of measures to be executed based on the target fault handling measures and executes these measures according to their processing priority. This achieves the technical effect of automatically handling faults in unmanned mining trucks, ensuring both the timeliness and accuracy of fault handling after a fault occurs in the unmanned mining truck, thereby greatly improving the safety of the unmanned mining truck.
[0029] Optionally, after generating a list of measures to be executed based on multiple target fault handling measures, the method further includes: when the autonomous driving system receives a new target fault handling measure, updating the list of measures to be executed based on the new target fault handling measure, determining the processing priority of the measures to be executed included in the updated list of measures to be executed, and executing the measures to be executed in the updated list of measures to be executed in sequence according to the processing priority.
[0030] In this embodiment, if the unmanned mining truck experiences other malfunctions while the unmanned driving system is executing pending measures, the unmanned driving system can receive new target fault handling measures sent by the fault diagnosis system and add them to the pending measures list to update the list. The execution order of the pending measures in the updated list is still determined by their respective processing priorities. For example, if the processing priority of the newly added target fault handling measure is higher than the processing priority of all previous pending measures, then this new target fault handling measure can be executed first. This embodiment, by setting processing priorities, ensures that when there are multiple pending measures, each measure is executed in priority order, while avoiding omissions.
[0031] In this embodiment of the application, optionally, the preset fault handling measures include deceleration measures, stopping measures, self-repair measures and scheduling measures, wherein each preset fault handling measure is marked with an urgency level label, and the handling priority is determined based on the urgency level label.
[0032] In this embodiment, such as Figure 3As shown, preset fault handling measures can include deceleration measures, parking measures, self-repair measures, and scheduling measures. To identify the processing priority of each preset fault handling measure, an urgency level label can be assigned to each measure. The urgency level label can be determined based on the urgency of each type of preset fault handling measure. For example, a parking measure has an urgency level label of 1, indicating the highest urgency; a deceleration measure has an urgency level label of 2, indicating the next highest urgency; a self-repair measure has an urgency level label of 3; and a scheduling measure has an urgency level label of 4. The higher the number of the urgency level label, the lower the urgency.
[0033] Optionally, in this embodiment of the application, when the list of measures to be executed includes multiple deceleration measures but does not include parking measures, the minimum throttle value, the minimum expected speed value, and the maximum braking speed value corresponding to the multiple deceleration measures are obtained, and the unmanned mining truck is controlled based on the minimum throttle value, the minimum expected speed value, and the maximum braking speed value; when the list of measures to be executed includes parking measures, the unmanned mining truck is controlled based on the parking measures, and the throttle of the unmanned mining truck is reset to zero.
[0034] In this embodiment, the list of measures to be executed may include multiple measures, which may include measures of the same type. For example, multiple deceleration measures may be included simultaneously. It should be noted that each type of preset fault handling measure may include multiple fault handling measures with different requirements. For example, for deceleration measures, there may be gradual deceleration measures, immediate deceleration measures, etc.; for parking measures, there may be sidewalk parking measures, immediate parking measures, etc. When the list of measures to be executed includes multiple deceleration measures but does not include parking measures, since the deceleration requirements corresponding to different deceleration measures may be different, but the processing priority of deceleration measures is the same, the required minimum throttle value, the desired minimum speed value, and the maximum braking speed value can be determined from the multiple deceleration measures when processing deceleration measures. Then, the unmanned mining truck is controlled according to the minimum throttle value, the desired minimum speed value, and the maximum braking speed value to realize the execution of deceleration measures. When the list of measures to be executed includes parking measures, since parking measures have a higher processing priority, parking measures can be executed first, and the throttle of the unmanned mining truck can be reset to zero.
[0035] Optionally, in this embodiment of the application, the method further includes: when the measure to be executed is a self-repairing measure, the unmanned driving system identifies action control data and self-repairing code from the self-repairing measure, and performs self-repairing processing on the unmanned mining truck based on the action control data and self-repairing code.
[0036] In this embodiment, if the measure to be executed is a self-repairing measure, it means that in addition to controlling the movement of the unmanned mining truck, self-repair can also be performed after the unmanned mining truck stops. At this time, the unmanned driving system can identify action control data and self-repair codes from the self-repairing measures. The action control data can be used to instruct the unmanned mining truck on how to act, such as reducing speed from a certain point to another, or changing gears from one position to another. The self-repair codes can be used to instruct the unmanned mining truck on how to perform self-repair. Different self-repair codes can correspond to different self-repair tools, which can perform self-repair processing on the corresponding faults of the unmanned mining truck. After identifying the action control data and self-repair codes from the self-repairing measures, on the one hand, the action control data can be used to control the movement of the unmanned mining truck; on the other hand, after the unmanned mining truck stops, the self-repair code can be used to call the self-repair tool, and then the self-repair tool can be used to perform self-repair processing on the unmanned mining truck. By performing action control and self-repair processing on the unmanned mining truck, post-fault processing of the unmanned mining truck is achieved. When the measure to be executed in this embodiment is a self-repairing measure, the driverless mining truck can be automatically self-repaired, which is simple and convenient, and the processing is timely.
[0037] Optionally, in this embodiment of the application, the method further includes: when the measure to be executed is a scheduling measure, the autonomous driving system sends the scheduling measure to the cloud platform so that the cloud platform can establish a scheduling task based on the scheduling measure.
[0038] In this embodiment, the measures to be executed may further include scheduling measures. When the measures to be executed are scheduling measures, the autonomous driving system can send the scheduling measures to the cloud platform. After receiving the scheduling measures, the cloud platform can establish corresponding scheduling tasks. The scheduling tasks may be tasks such as scheduling vehicles to perform maintenance or charging for the autonomous mining truck. In this way, the autonomous driving system can receive subsequent services provided by the scheduling vehicles according to the scheduling measures. In this embodiment, when the autonomous mining truck has a fault that cannot be self-repaired, the cloud platform is promptly notified to establish a scheduling task, thereby repairing the fault of the autonomous mining truck, which can greatly improve the safety of the autonomous mining truck.
[0039] Optionally, in this embodiment of the application, the method further includes: the unmanned driving system obtains the current operating status of the unmanned mining truck, and determines the task category of the current operation task based on the current operating status. When the task category is a safety-related operation task, the latest operating status is updated to the suspended operation status, and the steps of the pending measures are executed sequentially based on the processing priority of the pending measures in the pending measures list.
[0040] In this embodiment, the autonomous driving system can also acquire the current operating status of the autonomous mining truck in real time, and further determine the current operation task based on the current operating status. Each operation task can be pre-defined with a task category, and different task categories correspond to different levels of task safety. Specifically, task categories can include safe operation tasks, unsafe operation tasks, etc. Safe operation tasks refer to situations where the autonomous mining truck is safe when switching from the current operating status to the suspended operation status; unsafe operation tasks refer to situations where there may be safety risks when switching from the current operating status to the suspended operation status. The autonomous driving system can also determine the task category corresponding to the current operation task. Then, the latest operating status of the autonomous mining truck can be determined based on the task category. When the current task is classified as a safety-related task, suspending the task will not pose a safety risk to the unmanned mining truck. In this case, the latest task status can be updated to "suspended," and then the pending measures in the list can be executed. Conversely, when the current task is classified as a non-safety-related task, suspending the task is likely to pose a safety risk to the unmanned mining truck. In this case, the pending measures should be executed only after the unmanned mining truck completes the current task. For example, operating a cargo container can be a non-safety-related task. If the current task is operating a cargo container, to ensure unloading safety, the pending measures should only be executed after unloading is completed, i.e., after the cargo container operation task is finished.
[0041] In this embodiment, optionally, the unmanned driving system includes a perception layer, a planning layer, a decision-making layer, and a control layer; the perception layer acquires real-time environmental data of the unmanned mining truck; the planning layer performs path planning based on the measures to be executed and the surrounding environmental data to obtain target planned path data; the decision-making layer acquires the current operating status of the unmanned mining truck and determines the latest operating status of the unmanned mining truck based on the current operating status; the control layer identifies action control data from the measures to be executed and performs post-fault processing on the unmanned mining truck based on the action control data, the latest operating status, and the target planned path data.
[0042] In this embodiment, the autonomous driving system may include a perception layer, a planning layer, a decision-making layer, and a control layer. The perception layer can acquire real-time environmental data of the autonomous mining truck's surroundings. Specifically, the autonomous mining truck may be equipped with millimeter-wave radar, lidar, etc. The perception layer collects the surrounding environmental data of the autonomous mining truck in real time through millimeter-wave radar, lidar, etc., and then sends the surrounding environmental data to the planning layer. Next, the planning layer can perform path planning based on the measures to be executed and the surrounding environmental data, thereby obtaining the target planned path data. Here, the target planned path data can be data corresponding to global path planning or data corresponding to local path planning. For example, when the measures to be executed are parking measures, the target planned path data can be the path data corresponding to the autonomous mining truck from its current position to the parking position; when the measures to be executed are self-repair measures, the target planned path data can be the path data corresponding to the autonomous mining truck from its current position to the self-repair destination position. The decision-making layer can acquire the current operating status of the unmanned mining truck and, based on this status, determine its latest operating status. It's important to note that the latest operating status can be the current status or a completely new one, determined specifically based on the current status. Finally, the control layer can identify action control data from the pending measures and, using this data, the latest operating status, and the target planned path data, implement post-fault handling for the unmanned mining truck. Here, action control data can include data controlling the unmanned mining truck's speed, deceleration speed, and braking gear to control its movement. The control layer can control the unmanned mining truck's movement based on the action control data; determine whether the current operating status needs to be changed based on the latest operating status; and determine the corresponding travel path for the unmanned mining truck when executing pending measures based on the target planned path data.
[0043] In the embodiments of this application, optionally, as shown... Figure 4As shown, the autonomous driving system is also used for: when receiving a target fault handling measure, if there is only one target fault handling measure, it can be executed directly according to its content. Afterwards, a DDS (Data Distribution Service) message is published to notify the fault diagnosis system of the specific fault handling status. If there are multiple target fault handling measures, newly added measures can be inserted into the map queue, while already executed measures can be removed from the map queue, leaving unexecuted measures in the map queue. Then, the map queue can be traversed, and pre-control measures can be extracted. Specifically, the extraction strategy for pre-control measures may include: handling the throttle at its minimum value; if braking or parking is required, the throttle is reset to zero; handling the brake at its maximum value; handling parking requests according to parking requests; and handling neutral requests, cargo box lowering requests, or unloading human driving commands after stopping. Afterwards, pre-control instructions are issued according to the extracted pre-control measures to pre-control the unmanned mining truck. Then, each target fault handling measure is executed in sequence, and the corresponding fault handling status is published as a DDS message, which can notify the fault diagnosis system of the specific fault handling status.
[0044] Furthermore, as Figure 1 In terms of specific implementation, this application provides a fault post-processing system for unmanned mining trucks, such as... Figure 5 As shown, it includes a fault diagnosis system and an autonomous driving system;
[0045] The fault diagnosis system is used to determine the corresponding target fault handling measures from the preset fault handling measures based on the fault data when it receives fault data reported by any functional system of the unmanned mining truck, and to send the target fault handling measures to the unmanned driving system.
[0046] The autonomous driving system is used to receive multiple target fault handling measures, generate a list of measures to be executed based on the multiple target fault handling measures, and execute the measures to be executed in sequence according to the processing priority of the measures to be executed in the list.
[0047] Optionally, the autonomous driving system is also used to update the list of measures to be executed based on the new target fault handling measures when a new target fault handling measure is received, and to determine the processing priority of the measures to be executed included in the updated list of measures to be executed, and to execute the measures to be executed in the updated list of measures to be executed in sequence according to the processing priority.
[0048] Optionally, the preset fault handling measures include deceleration measures, stopping measures, self-repair measures, and scheduling measures. Each preset fault handling measure is marked with an urgency level label, and the handling priority is determined based on the urgency level label.
[0049] Optionally, the unmanned driving system is also used to obtain the minimum throttle value, the minimum expected speed value, and the maximum braking speed corresponding to the multiple deceleration measures when the list of measures to be executed includes multiple deceleration measures but does not include parking measures, and to control the unmanned mining truck based on the minimum throttle value, the minimum expected speed value, and the maximum braking speed value.
[0050] The unmanned driving system is also used to control the unmanned mining truck based on parking measures when the list of measures to be executed includes parking measures, and to reset the throttle of the unmanned mining truck to zero.
[0051] Optionally, the unmanned driving system is also used to identify action control data and self-repair code from self-repair measures when the measure to be executed is a self-repair measure, and to perform self-repair processing on the unmanned mining truck based on the action control data and self-repair code.
[0052] Optionally, the autonomous driving system is also used to send scheduling measures to the cloud platform when the measures to be executed are scheduling measures, so that the cloud platform can create scheduling tasks based on the scheduling measures.
[0053] Optionally, the unmanned driving system is also used to obtain the current operating status of the unmanned mining truck, and determine the task category of the current operation based on the current operating status. When the task category is a safety-related operation, the latest operating status is updated to the suspended operation status, and the steps of the pending measures are executed sequentially based on the processing priority of the pending measures in the pending measures list.
[0054] It should be noted that other corresponding descriptions of the functional units involved in the fault post-processing system for unmanned mining trucks provided in this application embodiment can be found in the following references. Figures 1 to 4 The corresponding descriptions in the method will not be repeated here.
[0055] Based on the above, Figures 1 to 4 Accordingly, this application also provides a storage medium storing a computer program, which, when executed by a processor, implements the above-described method. Figures 1 to 4 The method shown is for handling malfunctions in unmanned mining trucks.
[0056] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.
[0057] Based on the above, Figures 1 to 4 The method shown, and Figure 5 To achieve the above objectives, this application also provides a computer device, specifically a personal computer, server, network device, etc., comprising a storage medium and a processor; the storage medium for storing computer programs; and the processor for executing the computer programs to achieve the above objectives. Figures 1 to 4 The method shown is for handling malfunctions in unmanned mining trucks.
[0058] Optionally, the computer device may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Bluetooth interfaces, Wi-Fi interfaces), etc.
[0059] Those skilled in the art will understand that the computer device structure provided in this embodiment does not constitute a limitation on the computer device, and may include more or fewer components, or combine certain components, or have different component arrangements.
[0060] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages and stores the hardware and software resources of a computer device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software within the physical device.
[0061] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms, or it can be implemented by hardware. When the fault diagnosis system receives fault data reported by any functional system, it directly finds the corresponding target fault handling measures based on the fault data and sends the target fault handling measures to the unmanned driving system. The unmanned driving system then generates a list of measures to be executed based on the target fault handling measures and executes these measures according to their processing priority. This achieves the technical effect of automatically handling faults in unmanned mining trucks, ensuring both the timeliness and accuracy of fault handling after a fault occurs in the unmanned mining truck, thereby greatly improving the safety of the unmanned mining truck.
[0062] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing this application. Those skilled in the art will understand that the modules in the apparatus of the embodiment can be distributed within the apparatus of the embodiment as described, or can be modified to be located in one or more apparatuses different from this embodiment. The modules of the above-described embodiment can be combined into one module, or further divided into multiple sub-modules.
[0063] The serial numbers in this application are for descriptive purposes only and do not represent the superiority or inferiority of any particular implementation scenario. The above disclosures are merely a few specific implementation scenarios of this application; however, this application is not limited thereto, and any variations conceived by those skilled in the art should fall within the protection scope of this application.
Claims
1. A post-fault handling method for unmanned mining trucks, characterized in that, include: When the fault diagnosis system receives fault data reported by any functional system of the unmanned mining truck, it compares the received fault data with preset data. If the comparison result shows that the received fault data belongs to the preset data, it determines the corresponding target fault handling measure from the preset fault handling measures based on the fault data, and sends the target fault handling measure to the unmanned driving system. The preset data refers to the data of currently known faults that have preset fault handling measures. Otherwise, it performs error processing and sends the generated error information to the preset management terminal corresponding to the staff. The autonomous driving system receives multiple target fault handling measures, generates a list of measures to be executed based on the multiple target fault handling measures, and executes the measures to be executed sequentially based on the processing priority of the measures to be executed in the list of measures to be executed. The method further includes: When the measure to be executed is a self-repairing measure, the unmanned driving system identifies action control data and self-repairing code from the self-repairing measure, and performs self-repairing processing on the unmanned mining truck based on the action control data and the self-repairing code. The action control data is used to instruct the unmanned mining truck on how to act, and the self-repairing code is used to instruct the unmanned mining truck on how to perform self-repair. When the measure to be executed is a scheduling measure that cannot be self-repaired, the unmanned driving system sends the scheduling measure to the cloud platform so that the cloud platform can establish a scheduling task based on the scheduling measure. The scheduling task is to schedule the vehicle to perform maintenance or charging for the unmanned mining truck. The unmanned driving system includes a perception layer, a planning layer, a decision-making layer, and a control layer. The perception layer acquires real-time environmental data of the unmanned mining truck. The planning layer performs path planning based on the measures to be executed and the surrounding environmental data to obtain target planned path data. The decision-making layer acquires the current operating status of the unmanned mining truck and determines the latest operating status of the unmanned mining truck based on the current operating status. The control layer identifies action control data from the measures to be executed and performs post-fault handling for the unmanned mining truck based on the action control data, the latest operating status, and the target planned path data.
2. The method according to claim 1, characterized in that, After generating a list of measures to be executed based on multiple target fault handling measures, the method further includes: When the autonomous driving system receives a new target fault handling measure, it updates the list of measures to be executed based on the new target fault handling measure, determines the processing priority of the measures to be executed included in the updated list of measures to be executed, and executes the measures to be executed in the updated list of measures to be executed in sequence according to the processing priority.
3. The method according to claim 1, characterized in that, The preset fault handling measures include deceleration measures, stopping measures, self-repair measures, and scheduling measures. Each preset fault handling measure is marked with an urgency level label, and the handling priority is determined based on the urgency level label.
4. The method according to claim 3, characterized in that, When the list of measures to be executed includes multiple deceleration measures but does not include parking measures, the minimum throttle value, the minimum expected speed value, and the maximum braking speed value corresponding to the multiple deceleration measures are obtained, and the unmanned mining truck is controlled based on the minimum throttle value, the minimum expected speed value, and the maximum braking speed value. When the list of measures to be executed includes parking measures, the unmanned mining truck is controlled based on the parking measures, and the throttle of the unmanned mining truck is reset to zero.
5. The method according to claim 1, characterized in that, The method further includes: The unmanned driving system obtains the current operating status of the unmanned mining truck and determines the task category of the current task based on the current operating status. When the task category is a safety task, the latest operating status is updated to a suspended operating status, and the steps of the pending measures are executed sequentially based on the processing priority of the pending measures in the pending measures list.
6. A fault post-processing system for unmanned mining trucks, characterized in that, This includes fault diagnosis systems and autonomous driving systems; The fault diagnosis system is used to compare the received fault data with preset data when it receives fault data reported by any functional system of the unmanned mining truck. If the comparison result shows that the received fault data belongs to the preset data, the system determines the corresponding target fault handling measure from the preset fault handling measures based on the fault data and sends the target fault handling measure to the unmanned driving system. The preset data refers to the data of currently known faults that have preset fault handling measures. Otherwise, the system performs error processing and sends the generated error information to the preset management terminal corresponding to the staff. The autonomous driving system is configured to receive multiple target fault handling measures, generate a list of measures to be executed based on the multiple target fault handling measures, and execute the measures to be executed sequentially based on the processing priority of the measures to be executed in the list of measures to be executed. The autonomous driving system is also used for: When the measure to be executed is a self-repairing measure, the unmanned driving system identifies action control data and self-repairing code from the self-repairing measure, and performs self-repairing processing on the unmanned mining truck based on the action control data and the self-repairing code. The action control data is used to instruct the unmanned mining truck on how to act, and the self-repairing code is used to instruct the unmanned mining truck on how to perform self-repair. When the measure to be executed is a scheduling measure that cannot be self-repaired, the unmanned driving system sends the scheduling measure to the cloud platform so that the cloud platform can establish a scheduling task based on the scheduling measure. The scheduling task is to schedule the vehicle to perform maintenance or charging for the unmanned mining truck. The unmanned driving system includes a perception layer, a planning layer, a decision-making layer, and a control layer. The perception layer acquires real-time environmental data of the unmanned mining truck. The planning layer performs path planning based on the measures to be executed and the surrounding environmental data to obtain target planned path data. The decision-making layer acquires the current operating status of the unmanned mining truck and determines the latest operating status of the unmanned mining truck based on the current operating status. The control layer identifies action control data from the measures to be executed and performs post-fault handling for the unmanned mining truck based on the action control data, the latest operating status, and the target planned path data.
7. The system according to claim 6, characterized in that, The autonomous driving system is further configured to, when receiving a new target fault handling measure, update the list of measures to be executed based on the new target fault handling measure, determine the processing priority of the measures to be executed included in the updated list of measures to be executed, and execute the measures to be executed in the updated list of measures to be executed in sequence according to the processing priority.
8. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 5.
9. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 5.