An anthropomorphic anti-slip control method and system for unmanned mining trucks

Abstract

The present invention discloses a human-simulated anti-skid control method and system for unmanned mining trucks, which obtains the path request information sent by the mining truck and the predetermined human-simulated anti-skid rules of the machine group; determines whether the corresponding target road section has a historical skid event according to the path request information; if not, sends the task path to the mining truck normally, and controls the mining truck to travel normally according to the task path; if so, obtains the current weather and road conditions, and determines whether there are human-simulated anti-skid rules corresponding to the current weather and road conditions; if not, sends the task path to the mining truck normally, and controls the mining truck to travel normally according to the task path; if so, controls the mining truck to pass the skid section unmanned according to the corresponding human-simulated anti-skid rules. Advantages: Establish targeted anti-skid rules for different road conditions and weather conditions, continuously learn from the experience of manual driving, effectively solve various skid situations, and avoid the skid risk caused by a single control method.

Description

Technical Field

[0001] The present invention relates to a humanoid anti-slip control method and system for driverless mining trucks, belonging to the technical field of mining machinery. Background Art

[0002] With the continuous development of driverless technology, more and more ore transport vehicles using driverless technology have emerged in the field of mining machinery, which can effectively reduce labor costs and improve the production efficiency of mining area operations. An autonomous mining dump truck, also known as a driverless mining truck, is mainly an intelligent mining dump truck that can achieve autonomous driving technology. The mining working conditions are relatively complex. Under the combination of different harsh meteorological information (rain, snow, temperature), road condition information (wet and slippery conditions - manually reported, flatness, curvature), and vehicle condition information (load), general driverless control methods are difficult to adapt and may cause skidding. Moreover, the need to reproduce and test the same working conditions requires high time and economic costs. Currently, the relevant research at home and abroad mainly focuses on skid recognition methods, and measures such as applying braking measures and changing speed limits are taken to avoid skidding.

[0003] In the prior art, when the loss of traction is detected, the vehicle control system selects an appropriate braking level or braking strategy, or reduces the maximum driving speed. This control method is relatively simple and not applicable to the complex weather and road conditions in the mining area.

[0004] In the prior art, position sensors installed on the vehicle are configured to identify the vehicle direction (heading) and the vehicle driving direction (trajectory). When the difference between these two measured values exceeds a safety threshold, it may indicate that a skidding event has occurred. In order to track the geographical location of the skidding event, a database of historical skidding events is created to determine location-based risk factors and prevent future events. It mainly focuses on the detection of skidding and stores based on location, and does not involve how to solve the skidding problem. The method of storing based on location applies the same coping strategy under different weather and road conditions, which has limitations and affects the transportation efficiency.

[0005] In the prior art, sensors are used to identify the vehicle direction (heading) and the vehicle driving direction (trajectory). When the difference between the two exceeds the safety threshold, it may indicate that a skidding event has occurred. The skidding problem is solved by restricting the maximum speed. A database of historical skidding events is created based on the geographical location to determine location-based risk factors and prevent future events. It focuses on the detection of skidding and solves it by simply controlling the maximum speed. The control method is single and has limitations. Storing based on location applies the same coping strategy under different weather and road conditions, which has limitations and affects the transportation efficiency.

[0006] The general control algorithms of current driverless mining trucks are relatively simple. They can neither effectively solve the skidding problem nor balance anti-skid performance and efficiency, failing to meet the actual application requirements of driverless mining trucks. Therefore, a reliable anti-skid control system for driverless mining trucks needs to be designed. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide an anthropomorphic anti-skid control method and system for driverless mining trucks.

[0008] To solve the above technical problem, the present invention provides an anthropomorphic anti-skid control method for driverless mining trucks, including:

[0009] Obtain the path request information sent by the mining truck and the pre-determined anthropomorphic anti-skid rules of the fleet;

[0010] Judge whether there is a historical skidding event in the corresponding target section according to the path request information;

[0011] If not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path;

[0012] If so, obtain the current weather and road conditions, and judge whether there are anthropomorphic anti-skid rules corresponding to the current weather and road conditions according to the current weather and road conditions and the pre-determined anthropomorphic anti-skid rules of the fleet;

[0013] If not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path;

[0014] If so, control the mining truck to drive through the skidding section without a driver according to the corresponding anthropomorphic anti-skid rules.

[0015] Furthermore, the pre-determined anthropomorphic anti-skid rules include:

[0016] When the mining truck identifies a skidding situation, stop and report the fault to the fleet center, and request manual intervention to handle the fault;

[0017] Switch the mining truck to the remote operation mode. Manually drive remotely through the skidding section repeatedly at the remote operation terminal until there is no skidding situation. Record the control information of manual remote driving without skidding, and establish anthropomorphic anti-skid rules according to the control information;

[0018] Switch the mining truck to the driverless mode, and drive through the skidding section according to the established anthropomorphic anti-skid rules. If skidding still occurs, continue to switch to the remote operation mode and repeat the above actions until there is no skidding in the driverless mode;

[0019] Upload the anthropomorphic anti-skid rules corresponding to no skidding in the driverless mode to the fleet center;

[0020] Based on the currently collected road condition information and meteorological information, combined with the humanoid anti-slip rules corresponding to no skidding in the unmanned mode, establish the humanoid anti-slip rules for the vehicle fleet.

[0021] Further, the control information includes throttle, braking, steering, speed, driving trajectory, and load information.

[0022] Further, the humanoid anti-slip rules for the vehicle fleet are issued to all mining trucks.

[0023] Further, establishing the humanoid anti-slip rules according to the control information includes:

[0024] Preprocess the throttle, braking, steering, speed, driving trajectory, and load information to remove noise data;

[0025] Establish humanoid anti-slip rules based on the throttle, braking, steering, speed, driving trajectory, and load information after removing noise data.

[0026] Further, each humanoid anti-slip rule includes a unique rule identification bit, throttle rule, braking rule, steering rule, speed rule, path rule, and load rule.

[0027] A humanoid anti-slip control system for unmanned mining trucks includes:

[0028] An acquisition module for acquiring the path request information sent by the mining truck and the pre-determined humanoid anti-slip rules for the vehicle fleet;

[0029] A skidding warning module for judging whether there is a historical skidding event in the corresponding target section according to the path request information; if not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path; if so, acquire the current weather and road conditions, and judge whether there is a humanoid anti-slip rule corresponding to the current weather and road conditions according to the current weather and road conditions and the pre-determined humanoid anti-slip rules for the vehicle fleet; if not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path; if so, control the mining truck to drive through the skidding section without a driver according to the corresponding humanoid anti-slip rule.

[0030] Further, the acquisition module includes a skidding rule establishment module,

[0031] The skidding rule establishment module includes a remote operation module, a skidding monitoring module, a manual driving information collection module, a humanoid rule establishment module, a humanoid anti-slip control module, a skidding rule transceiver module, a road condition information collection module, a meteorological information collection module, and a vehicle fleet anti-slip rule establishment module;

[0032] After the slip monitoring module detects a slip situation, it remotely controls the mining truck through the teleoperation module until there is no slip situation. The manual driving information collection module synchronously collects manual driving information and sends it to the humanoid rule establishment module;

[0033] The humanoid rule establishment module establishes humanoid anti-slip rules based on the manual driving information, remotely switches the mining truck to the unmanned mode using the teleoperation module. After the humanoid anti-slip control module controls the mining truck to pass through the slip section according to the formed humanoid anti-slip rules, the anti-slip rule transceiver module receives the rules of the humanoid anti-slip control module and sends them to the fleet anti-slip rule establishment module. The road condition information collection module identifies each road condition information in the mining area and sends it to the fleet anti-slip rule establishment module. The meteorological information collection module collects the meteorological information in the mining area and sends it to the fleet anti-slip rule establishment module. The fleet anti-slip rule establishment module is used to establish fleet humanoid anti-slip rules and send the anti-slip rules to other mining trucks through the anti-slip rule transceiver module.

[0034] A computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform any of the methods described above.

[0035] A computing device, comprising,

[0036] One or more processors, a memory, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for performing any of the methods described above.

[0037] The beneficial effects achieved by the present invention:

[0038] The present invention can establish targeted anti-slip rules for different road sections, road conditions, and weather conditions, continuously learn the experience of manual driving, effectively solve various slip situations, and avoid the slip risks brought by a single control method.

[0039] The present invention can effectively warn of slip risk points in advance, warn the unmanned mining truck in advance that there is a slip risk in the front, and improve the safety of the unmanned mining truck.

[0040] The present invention is only enabled when the slip judgment is met and does not start when the slip situation does not conform, which can effectively solve the problem of efficiency reduction brought by a single control method such as speed reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is the system composition diagram provided by the embodiment of the present invention;

[0042] Figure 2 is the system working flow chart provided by the embodiment of the present invention;

[0043] Figure 3 It is a schematic diagram of the working process of the humanoid rule establishment module provided by the implementation of the present invention;

[0044] Figure 4 It is a working flow chart of the skid warning module provided by the implementation of the present invention;

[0045] Figure 5 It is a schematic diagram of the skid warning module provided by the implementation of the present invention. Detailed implementation manners

[0046] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and cannot be used to limit the protection scope of the present invention.

[0047] As Figure 4 shown, a humanoid anti-skid control method for unmanned mining trucks includes:

[0048] Obtain the path request information sent by the mining truck and the pre-determined humanoid anti-skid rules of the fleet;

[0049] Judge whether there is a historical skid event in the corresponding target section according to the path request information;

[0050] If not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path;

[0051] If so, obtain the current weather and road conditions, and judge whether there is a humanoid anti-skid rule corresponding to the current weather and road conditions according to the current weather and road conditions and the pre-determined humanoid anti-skid rules of the fleet;

[0052] If not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path;

[0053] If so, control the mining truck to drive through the skid section without a driver according to the corresponding humanoid anti-skid rule.

[0054] The pre-determined humanoid anti-skid rules include:

[0055] When the mining truck identifies a skid situation, stop and report the fault to the fleet center, and request manual intervention to handle the fault;

[0056] Switch the mining truck to the remote operation mode, and manually drive remotely through the skid section repeatedly at the remote operation end until there is no skid situation. Record the control information of the manual remote driving without skid, and establish a humanoid anti-skid rule according to the control information;

[0057] Switch the mining truck to the unmanned mode and pass through the skidding section according to the established humanoid anti-skid rules. If skidding still occurs, continue to switch to the remote operation mode and repeat the above actions until there is no skidding in the unmanned mode.

[0058] Upload the humanoid anti-skid rules corresponding to no skidding in the unmanned mode to the fleet center.

[0059] Based on the collected current road condition information and meteorological information, combined with the humanoid anti-skid rules corresponding to no skidding in the unmanned mode, establish the fleet humanoid anti-skid rules.

[0060] Through the pre-determined humanoid anti-skid rules, targeted anti-skid rules can be established for different road sections, road conditions, and weather conditions, continuously learning the experience of manual driving, establishing a humanoid anti-skid control algorithm, effectively solving various skidding situations, and avoiding the skidding risks brought by a single control method.

[0061] The control information includes throttle, braking, steering, speed, driving trajectory, and load information.

[0062] The fleet humanoid anti-skid rules are issued to all mining trucks.

[0063] The establishment of the humanoid anti-skid rules according to the control information includes:

[0064] Preprocess the throttle, braking, steering, speed, driving trajectory, and load information to remove noise data.

[0065] Establish humanoid anti-skid rules based on the throttle, braking, steering, speed, driving trajectory, and load information after removing noise data.

[0066] Each humanoid anti-skid rule contains a unique rule identification bit, throttle rule, braking rule, steering rule, speed rule, path rule, and load rule.

[0067] The present invention proposes a humanoid anti-skid control system for unmanned mining trucks, as Figure 1 shown, including: a remote operation module, an unmanned mining truck at least equipped with a skidding monitoring module, a manual driving information collection module, a humanoid rule establishment module, a humanoid anti-skid control module, and an anti-skid rule transceiver module, a fleet system at least equipped with a fleet anti-skid rule establishment module and an anti-skid rule transceiver module, a road condition information collection module, and a meteorological information collection module.

[0068] The remote operation module is used for the module that can manually drive the mining truck remotely when the mining truck fails or in other emergency situations. The remote operation module can directly send control signals to the mining truck. The driving mode of the remote operation module is the same as that in the mining truck cab. When remote operation is required, the mining truck can be remotely driven without personnel moving to the mining truck site.

[0069] The skid monitoring module is used to monitor whether the mining truck skids during driving.

[0070] The manual driving information collection module is used to collect various parameters during manual driving, including but not limited to information such as throttle, braking, steering, speed, driving trajectory, load, etc., and send the information to the humanoid rule establishment module.

[0071] The humanoid rule establishment module converts and processes the various information parameters of manual driving, and outputs rules including but not limited to humanoid throttle, braking, steering, speed, path, etc., and sends the humanoid rules to the humanoid anti-skid control module. The unmanned mining truck can control the mining truck to drive in a humanoid manner through this rule.

[0072] The mining truck humanoid anti-skid control module needs to be manually imported after manually confirming that the humanoid rule is indeed effective. In addition to importing the humanoid rule, it has an anti-skid rule identification bit to uniquely identify the current anti-skid rule. The humanoid anti-skid control module communicates with the mining truck anti-skid rule transceiver module and can send data to each other.

[0073] The mining truck anti-skid rule transceiver module is used to upload the humanoid rule to the fleet center to establish the humanoid rule at the fleet end. It can also receive the anti-skid rules established by other mining trucks from the fleet.

[0074] The fleet anti-skid rule transceiver module is used to receive the anti-skid rules sent from the unmanned mining truck and send the anti-skid rules already established in the fleet to the unmanned mining truck.

[0075] The fleet anti-skid rule establishment module combines the meteorological information, road condition information and the humanoid rules uploaded by the mining truck to establish the fleet-end anti-skid rules, including path information, speed, etc., and has an anti-skid rule identification bit to uniquely identify the anti-skid rule. The fleet anti-skid rule establishment module communicates with the fleet anti-skid rule transceiver module and can send data to each other.

[0076] The road condition information collection module identifies each road condition information in the mining area through a road test perception system or other means and sends it to the fleet control center, including road surface flatness, wetness, etc.

[0077] The meteorological information collection module collects the information provided by the mining area meteorological station or other systems and sends it to the fleet center.

[0078] The steps for the fleet anti-skid rule establishment module to establish the fleet humanoid anti-skid rule are as follows, as Figure 2 shown:

[0079] Step 1, the mining truck skid monitoring module identifies a skid situation, stops the vehicle and reports the fault to the fleet center, and requests manual intervention to handle the fault;

[0080] Step 2: Manually switch the mining truck to the remote operation mode. Manually drive remotely through the slippery section at the remote operation end repeatedly until there is no slippage. At the same time, the manual driving information collection module records the control information of manual driving in real time, and the humanoid rule establishment module establishes humanoid rules.

[0081] Step 3: Switch the mining truck to the unmanned mode and pass through the slippery section according to the formed humanoid anti-slip rules. If slippage still occurs, continue to switch to the remote operation mode and repeat the above actions until there is no slippage.

[0082] Step 4: If there is no slippage, manually confirm and import the humanoid rules into the humanoid anti-slip control module of the mining truck.

[0083] Step 5: The mining truck uploads the humanoid anti-slip control rules for the corresponding section to the fleet center.

[0084] Step 7: The fleet anti-slip rule establishment module establishes the fleet-end anti-slip rules according to the current road conditions (flatness, wetness, etc.), meteorological information (rain, snow, temperature), and combines the humanoid anti-slip rules uploaded by the mining truck.

[0085] The specific working steps of the humanoid rule establishment module are as follows, as Figure 3 shown:

[0086] Step 1: Perform data preprocessing on the throttle data, braking data, steering data, speed data, path data, load data, etc. recorded by the manual driving information collection module to remove noise data.

[0087] Step 2: Process and calculate the preprocessed data, and output the throttle, braking, steering, speed, path, etc. rules with humanoid strategies that can be directly used by the mining truck.

[0088] Step 3: According to the output rules, establish corresponding humanoid rules. Each rule contains a unique rule identification bit, throttle rule, braking rule, steering rule, speed rule, and path rule.

[0089] The present invention proposes a humanoid anti-slip warning system for unmanned mining trucks, as Figure 4 shown. The working process steps of the system are as follows:

[0090] Step 1: When the mining truck is about to enter the next section, it requests the task path from the fleet center.

[0091] Step 2: The fleet center judges whether there is a historical slippage event in the target section requested by the mining truck through the fleet anti-slip rule establishment module.

[0092] Step 3: If there is no historical skidding event, normally send the task path to the mining truck, and the mining truck travels according to the task path sent by the fleet;

[0093] Step 4: If there is a historical skidding event, then determine whether there is a corresponding anti-skid rule for the current weather and road conditions;

[0094] Step 5: If not, normally send the task path to the mining truck, and the mining truck travels according to the task path sent by the fleet;

[0095] Step 6: If it meets the requirements, then trigger the warning system according to the anti-skid rules on the fleet side. The fleet center will obtain the anti-skid rules from the system for establishing anti-skid rules on the fleet side, send a skidding warning and a skidding rule flag bit to the mining truck, inform the mining truck that there is an easily skiddable road surface, and notify the mining truck to pass according to the corresponding humanoid rules;

[0096] Step 7: The mining truck travels according to the task path and anti-skid rules sent by the fleet, and uses the corresponding humanoid control rules to pass through the easily skiddable section.

[0097] As Figure 5 shown, when an unmanned mining truck (S1) skids on a section of the road, the fleet center will store the historical skidding position based on the location, and establish the anti-skid rules on the fleet side in combination with the meteorological and road conditions at that time, and send the anti-skid rules to other mining trucks (S2). When any subsequent mining truck requests a corresponding section of the road, it will determine whether there is a corresponding anti-skid rule. The anti-skid rule is enabled only when the fleet has the corresponding rule. If it does not meet the corresponding rule, the anti-skid rule does not need to be enabled, and the mining truck passes through the corresponding section at the normal speed.

[0098] Correspondingly, the present invention further provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, and when the instructions are executed by a computing device, the computing device is caused to execute any one of the methods described above.

[0099] A computing device includes,

[0100] One or more processors, a memory, and one or more programs, where the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing any one of the methods described above.

[0101] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0102] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of blocks.

[0103] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing devices to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of blocks.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, such that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable devices provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of blocks.

[0105] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. An anti-slip control method for unmanned mining trucks imitating human behavior, characterized in that, Including: Obtain the path request information sent by the mining truck and the pre-determined humanoid anti-skid rules for the fleet; Judge whether there is a historical skidding event in the corresponding target section according to the path request information; If not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path; If so, obtain the current weather and road conditions, and judge whether there is a humanoid anti-skid rule corresponding to the current weather and road conditions according to the current weather and road conditions and the pre-determined humanoid anti-skid rules for the fleet; If not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path; If it exists, control the mining truck to drive through the skidding section without a driver according to the corresponding humanoid anti-skid rule; The pre-determined humanoid anti-skid rules include: When the mining truck identifies a skidding situation, stop and report the fault to the fleet center, and request manual intervention to handle the fault; Switch the mining truck to the remote operation mode, and manually remotely drive through the skidding section repeatedly at the remote operation end until there is no skidding situation. Record the control information of the manual remote driving without skidding, and establish a humanoid anti-skid rule according to the control information; Switch the mining truck to the unmanned mode, drive through the skidding section according to the established humanoid anti-skid rule. If skidding still occurs, continue to switch to the remote operation mode and repeat the above actions until there is no skidding in the unmanned mode; Upload the humanoid anti-skid rule corresponding to no skidding in the unmanned mode to the fleet center; According to the collected current road condition information and meteorological information, combined with the humanoid anti-skid rule corresponding to no skidding in the unmanned mode, establish the humanoid anti-skid rules for the fleet.

2. The humanoid anti-slip control method for driverless mining trucks according to claim 1, characterized in that, The control information includes throttle, brake, steering, speed, driving trajectory, and load information.

3. The humanoid anti-slip control method for driverless mining trucks according to claim 1, characterized in that, The humanoid anti-skid rules for the fleet are distributed to all mining trucks.

4. The humanoid anti-slip control method for driverless mining trucks according to claim 2, wherein The establishing the humanoid anti-skid rule according to the control information includes: Preprocess the throttle, brake, steering, speed, driving trajectory, and load information, and remove the noise data; Establish a humanoid anti-skid rule according to the throttle, brake, steering, speed, driving trajectory, and load information after removing the noise data.

5. The humanoid anti-slip control method for driverless mining trucks according to claim 4, characterized in that Each humanoid anti-skid rule contains a unique rule identification bit, throttle rule, brake rule, steering rule, speed rule, path rule, and load rule.

6. An anti-slip control system for an unmanned mining truck imitating human behavior, characterized in that, Including: An obtaining module for obtaining the path request information sent by the mining truck and the pre-determined humanoid anti-skid rules for the fleet; A skidding warning module for judging whether there is a historical skidding event in the corresponding target section according to the path request information; if not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path; if so, obtain the current weather and road conditions, and judge whether there is a humanoid anti-skid rule corresponding to the current weather and road conditions according to the current weather and road conditions and the pre-determined humanoid anti-skid rules for the fleet; if not, normally send the task path to the mining truck and control the mining truck to drive normally according to the task path; if it exists, control the mining truck to drive through the skidding section without a driver according to the corresponding humanoid anti-skid rule; The obtaining module includes a skidding rule establishment module, The skidding rule establishment module includes a teleoperation module, a skidding monitoring module, a manual driving information collection module, a humanoid rule establishment module, a humanoid anti-skid control module, a skid rule transceiver module, a road condition information collection module, a meteorological information collection module, and a fleet skid rule establishment module; After the skidding monitoring module detects a skidding situation, it remotely controls the mining truck through the teleoperation module until there is no skidding situation. The manual driving information collection module synchronously collects the manual driving information and sends it to the humanoid rule establishment module; The humanoid rule establishment module establishes humanoid anti-skid rules based on the manual driving information, remotely switches the mining truck to the unmanned mode through the teleoperation module. After the humanoid anti-skid control module controls the mining truck to pass through the skidding section according to the formed humanoid anti-skid rules, the skid rule transceiver module receives the rules of the humanoid anti-skid control module and sends them to the fleet skid rule establishment module. The road condition information collection module identifies each road condition information in the mining area and sends it to the fleet skid rule establishment module. The meteorological information collection module collects the meteorological information in the mining area and sends it to the fleet skid rule establishment module. The fleet skid rule establishment module is used to establish fleet humanoid anti-skid rules and send the skid rules to other mining trucks through the skid rule transceiver module.

7. A computer-readable storage medium storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods according to claims 1 to 5.

8. A computing device, characterized in that, Comprising, One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors. The one or more programs include instructions for performing any of the methods according to claims 1 to 5.

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