Ramp stability control method and controller for mine roadway unmanned trolley

Abstract

The invention discloses a ramp stability control method for a mine roadway unmanned trolley and a controller. Entering a ramp stable mode when the vehicle enters a preset slope section, collecting vehicle data and filtering in the mode, and performing centroid offset estimation and centroid change trend quantity construction based on the obtained filtered state data at the current control moment to obtain a transverse offset quantity and a centroid change rate; when it is determined that a load slip event occurs based on the change rate and the vehicle acceleration, the gear of the vehicle is switched to reduce the upper speed limit, the steering change rate and the wheel end differential amplitude of the vehicle; generating a risk score based on the transverse offset, the load slip event indication quantity, the slope angle of the preset slope section and the partial state data, and obtaining a stable control boundary set according to the score; and performing limit compensation by using the set, and determining the braking amount of wheels on the left and right sides of the vehicle based on a compensation result so as to perform vehicle control. The driving stability and safety of the trolley under the ramp working condition can be improved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control and autonomous driving technology, specifically relating to a slope stability control method and controller for an unmanned vehicle used in mining roadways. Background Technology

[0002] Currently, unmanned vehicles for mining roadways are being gradually applied in underground transportation and inspection scenarios. However, roadways often include slopes, and the road surface is prone to slipperiness and significant vibration and impact. At the same time, uneven loading of the vehicle and slippage of materials in the truck bed can cause the vehicle's center of gravity to shift continuously or change abruptly in a short period of time. Under the coupled effect of slope and turning, this can easily induce the risk of side tilting / overturning.

[0003] In existing technologies, some solutions focus on downhill braking safety, while others focus on predicting and warning of rollover trends. Still others improve stability through center of gravity compensation. However, during incline driving, existing solutions often struggle to simultaneously achieve timely risk identification and classification, adaptive adjustment of control boundaries, and continuous and stable execution of compensation actions, given the rapid changes in the center of gravity caused by load slippage. Therefore, there is still room for improvement in adaptability and traffic efficiency on complex slopes. In other words, existing technologies cannot solve the problem of unmanned mining tunnel vehicles experiencing continuous or short-term center of gravity shifts due to uneven loading and material slippage on slopes, and the significantly increased risk of rollover under the combined effects of slope and curves. Summary of the Invention

[0004] In order to solve the above-mentioned problems in the prior art, the present invention provides a slope stability control method and controller for unmanned vehicles in mine roadways.

[0005] The technical problem to be solved by this invention is achieved through the following technical solution: This invention provides a slope stability control method for an unmanned vehicle in a mine roadway, comprising: Determine if the vehicle is currently on a preset slope; if so, enter slope stabilization mode. In the slope stabilization mode, the vehicle status data of the current cycle is collected and filtered to obtain the filtered status data of the current control moment, with an interval of one cycle between two adjacent control moments; Based on the filtered state data at the current control moment, the centroid offset is estimated and the centroid change trend is constructed to obtain the lateral offset and centroid change rate at the current control moment. The lateral direction refers to the direction perpendicular to the vehicle's driving direction in the plane where the vehicle is located, and the longitudinal direction refers to the vehicle's driving direction. Based on the centroid change rate and the vehicle acceleration at the current control moment, the load slip event indication at the current control moment is determined to determine whether a load slip event has occurred. When the load slip event occurs, the vehicle gear is switched to reduce the vehicle speed limit, vehicle steering change rate, and vehicle wheel-end differential amplitude. Based on the lateral offset, the load slip event indication, the slope angle of the preset slope segment, and the filtered partial state data at the current control moment, a risk score for the current control moment is generated, and the set of stable control boundaries for the current control moment is determined according to the risk score. Using the set of stable control boundaries for clearance compensation, and based on the reference control parameters obtained from the clearance compensation, the braking amount of the wheels on both sides of the vehicle's longitudinal direction is determined for vehicle control.

[0006] The present invention also provides a slope stability controller for an unmanned vehicle in a mining roadway, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory is used to store computer programs; When the processor executes the program stored in the memory, it implements the steps of the above-mentioned slope stability control method for unmanned mining roadway vehicles.

[0007] Compared with the prior art, the beneficial effects of the present invention are as follows: 1) After entering the slope area, the present invention switches to the slope stability mode and comprehensively collects vehicle status data to complete the online estimation of the vehicle's center of gravity shift trend under slope conditions; further, a load slip event recognition mechanism is introduced. When a load slip event is detected, a more conservative control gear is triggered, thereby changing from "post-event over-limit restriction" to "early risk suppression", reducing the risk of rollover under curved slopes and continuous slopes.

[0008] 2) This invention classifies risks based on slope, degree of turning and signs of adhesion change, and adaptively tightens control boundaries such as vehicle speed limit, vehicle lateral acceleration limit, vehicle yaw rate limit and vehicle front wheel angle limit according to the risk level, so that the compensation control action is stably executed within the safety constraints, avoiding excessive operation that may induce slippage or secondary risks.

[0009] 3) The present invention sets up a periodic review and gradual degradation mechanism. When the compensation effect is insufficient, it gradually slows down until it stops safely and issues an alarm. This improves the robustness and deployability of the present invention on complex slopes, thereby ensuring the safety of roadway operation while taking into account traffic efficiency and reducing the frequency of manual intervention.

[0010] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Attached Figure Description

[0011] Figure 1 This is a flowchart illustrating a slope stability control method for an unmanned vehicle in a mine roadway provided by an embodiment of the present invention. Figure 2 This is a top-view diagram of a vehicle provided in an embodiment of the present invention, and a vehicle coordinate system established in the top-view diagram of the vehicle. A schematic diagram; Figure 3 This invention provides a side view of a vehicle on a ramp and a ground coordinate system established within that side view. A schematic diagram. Detailed Implementation

[0012] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0013] This invention provides a slope stability control method for an unmanned vehicle in a mining roadway, which is executed by the controller of the unmanned vehicle. Figure 1 This is a flowchart illustrating a slope stability control method for an unmanned trolley in a mine roadway, as provided in an embodiment of the present invention. Figure 1 As shown, the method includes: S101. Determine if the vehicle is currently on a preset slope. If so, enter the slope stabilization mode.

[0014] In some embodiments, the controller calculates the slope angle at a preset frequency using the vehicle's inertial measurement unit during driving. By judging the calculated slope angle Is it greater than the preset entry threshold? To determine whether it is currently on a preset slope, it combines a pre-constructed regional map with its own location at a preset frequency to match its position with the preset slope. If the calculated slope angle... Greater than the preset entry threshold If the vehicle's position matches a preset slope (e.g., a steep slope), it indicates that the vehicle has entered the preset slope; otherwise, it indicates that the vehicle has not entered the preset slope. Preset entry threshold. The settings can be configured according to actual needs; this invention does not impose any limitations on this. It should be noted that the slope angle is calculated using the vehicle's inertial measurement unit. Since this is existing technology, the specific calculation principle will not be elaborated in this invention.

[0015] S102. In slope stabilization mode, the vehicle status data of the current cycle is collected and filtered to obtain the filtered status data of the current control moment. The interval between two adjacent control moments is one cycle.

[0016] For example, the filtered state data at the current control moment includes: the vehicle speed, vehicle yaw rate, and normal load of each wheel of the vehicle at the current control moment.

[0017] In this invention, a preset sampling period is used. The vehicle's speed, yaw rate, and normal load on each wheel are continuously collected to obtain data for each preset sampling period. The vehicle's original speed, original yaw rate, and original normal load on each wheel are sampled over a preset period. The collected raw vehicle speed, raw yaw rate, and raw normal load of each wheel are used as vehicle state data at a control moment. Thus, the vehicle state data at the first control moment constitutes the first preset sampling period. The vehicle's original speed, original yaw rate, and original normal load on each wheel are collected internally. The vehicle state data at the second control moment constitutes the second preset sampling period. The vehicle's original speed, original yaw rate, and original normal load on each wheel are collected internally, and so on.

[0018] Due to significant vibration and impact in underground tunnels and uneven road surfaces, raw sensor data often contains high-frequency jitter. Directly using the raw signals to judge the trend of centroid changes or sudden load slippage can easily lead to misjudgments, causing the controller to frequently enter a conservative mode (i.e., a mode with low vehicle speed limits, low vehicle steering rate of change, and low wheel-end differential amplitude), thus affecting driving efficiency. Therefore, after obtaining the vehicle's raw speed, raw yaw rate, and raw normal load on each wheel at the current control moment, these data need to be filtered, and the smoothed amount obtained after filtering is used as the basis for subsequent calculations. Through this processing, the subsequent method mainly responds to the real changes caused by load migration and slippage, rather than being overly sensitive to vibration and noise. For example, a first-order low-pass filter or moving average can be chosen to filter the raw data, then the... The expressions for the filtered state data at each control time point are as follows: ; ; ; in, Indicates the first Vehicle speed at a given moment in time. Indicates the first The vehicle's original speed at each control moment. Indicates the first Vehicle yaw rate at each control moment No. The vehicle's original yaw rate at each control moment. Indicates the vehicle's number The normal load on each wheel, for example , Indicates the vehicle's number The original normal load of each wheel. This represents the filtering operator; in engineering practice, a first-order low-pass filter or a moving average filter can be used. To demonstrate feasibility, The following recursive low-pass form can be used: , No. The control time and the first A preset sampling period is between each control moment. , For preset coefficients, express / / , express / / , express / / .

[0019] To further explain some of the parameters mentioned above, a vehicle coordinate system is established in the top-view diagram of the vehicle. , The direction in which a vehicle moves forward is called the lateral direction. It is the direction perpendicular to the vehicle's forward direction; it can be called longitudinal or the left-hand direction of the vehicle. Specifically, as shown... Figure 2 As shown. Simultaneously, a ground coordinate system is established in the vehicle's ramp side view. , It is perpendicular to The direction of the plane, specifically as follows: Figure 3 As shown. It is a three-dimensional coordinate system with the vehicle's center of mass as the origin. Specifically, such as... Figure 2 As shown, the vehicle's wheelbase is Wheelbase is And satisfy ,in , The centroids Distances to the front and rear axles. Vehicle speed at the center of gravity. Yaw rate The front wheel steering angle is The vehicle's first The longitudinal and lateral forces in the tire coordinate system of each wheel are respectively , The vehicle's first Normal load of each wheel Perpendicular to the paper ( Figure 2 (Not shown in the diagram), used for subsequent centroid offset trend estimation. To avoid ambiguity in wheel position numbering, such as... Figure 2 As shown, this invention adopts the following wheel numbering convention: the left front wheel is wheel number 1, the right front wheel is wheel number 2, the left rear wheel is wheel number 3, and the right rear wheel is wheel number 4. Figure 3 As shown, the slope angle of the slope section is... The height of the center of mass is The vehicle's weight is . , These represent the resultant forces of the original normal loads on the front and rear axles of the vehicle, respectively. They can be understood as the sum of the original normal loads on the left and right wheels of the corresponding axles. It is the sum of the original normal loads on the two front wheels (wheel 1 and wheel 2) of the vehicle. This is the sum of the original normal loads on the two rear wheels (wheels 3 and 4) of the vehicle. To ensure comparability of criteria under different slopes, this invention uses an approximate relationship between the total normal load and the slope as a normalization reference, that is, under slope conditions, the total normal load varies with... change: This relationship is not used for precise dynamic solutions, but rather for subsequent scale consistency processing of risk quantities to avoid threshold mismatch caused by slope changes.

[0020] S103. Based on the filtered state data at the current control moment, perform centroid offset estimation and centroid change trend construction to obtain the lateral offset and centroid change rate at the current control moment. The lateral direction refers to the direction perpendicular to the vehicle's driving direction in the plane where the vehicle is located, and the longitudinal direction refers to the vehicle's driving direction.

[0021] After data acquisition and preprocessing, the present invention proceeds to the centroid offset estimation step. Compared with using only attitude thresholds, centroid offset can reflect the risk trend of uneven loading and material migration earlier, especially in curved and continuous slope sections, where centroid offset often precedes obvious attitude overshoot. In some embodiments, the above S103 is implemented through steps S1031~S1035: S1031, Based on the normal load of each wheel of the vehicle at the current control moment and the wheelbase between the front and rear axles of the vehicle. Determine the distance from the center of mass to the front axle of the vehicle at the current control moment. .

[0022] The distance from the center of gravity to the front axle of the vehicle reflects the impact of material migration on axle load redistribution, thus enabling the determination of whether the center of gravity is shifted forward or backward, and the trend of this shift over time. For example, the distance from the center of gravity to the front axle of the vehicle at any given control moment... The calculation formula is: ,in, That is, the sum of the normal loads on the two rear wheels of the vehicle at any given control moment. That is, the sum of the normal loads on the two front wheels of the vehicle at any given control moment. .

[0023] S10312. Based on the normal load of each wheel of the vehicle at the current control moment, determine the sum of the normal loads of the front wheels of the vehicle and the sum of the normal loads of the rear wheels of the vehicle.

[0024] For example, the sum of the normal loads on the front wheels of the vehicle at any given control moment The sum of the normal loads of the rear wheels of the vehicle The calculation formula is:

[0025] in, , These are the normal loads of wheels 1, 2, 3, and 4 of the vehicle at any given control time.

[0026] S1033. Based on the vehicle's lateral track width, the sum of the normal loads on the front wheels of the vehicle, and the sum of the normal loads on the rear wheels of the vehicle, determine the lateral offset at the current control moment.

[0027] For example, the lateral offset at any control moment The calculation formula is: This introduces... The purpose is to convert the load ratio difference between the front and rear wheels of a vehicle into an offset that is consistent with the vehicle's geometry, so that it can be directly used in stability margin calculations.

[0028] S1034. Based on the distance from the centroid to the front axle of the vehicle at the current control moment, and the lateral offset at the current control moment, construct the centroid state vector at the current control moment.

[0029] To determine whether the offset is a slow migration or a slip transition, the controller will estimate the longitudinal position. Compared with the horizontal estimation The states are merged into a centroid state vector, and the discrete increments and rates of change of the centroid states are calculated separately. For example, the first... Centroid state vector at each control moment = , Indicates the first The distance from the center of mass to the front axle of the vehicle at each control moment , It is the first Lateral offset at each control moment .

[0030] S1035. Determine the centroid change rate at the current control moment based on the difference between the centroid state vector at the current control moment and the centroid state vector at the previous control moment, as well as the time interval between two adjacent control moments.

[0031] For example, the first rate of change of the center of mass at each control moment , , Indicates the first The centroid state vector at each control moment. Describes the L1 norm of a vector. No. The change in the center of mass at each control moment. The larger the value, the more drastic the change in the center of mass, and the more likely it is to indicate overall material slippage or abrupt changes in loading.

[0032] S104. Based on the rate of change of the center of gravity and the vehicle acceleration at the current control moment, determine the load slip event indication at the current control moment to determine whether a load slip event has occurred. When a load slip event occurs, control the switching of the vehicle's gear to reduce the vehicle speed limit, the vehicle steering change rate, and the vehicle wheel end differential amplitude.

[0033] The most dangerous moments on underground ramps often occur after a sudden shift in the center of gravity caused by a short-term overall slippage of material. If the vehicle continues to travel using a normal ramp strategy at this point, the combined effects of steering or differential movement can amplify the risk of rollover. Therefore, this invention specifically identifies load slippage events in this step and immediately switches to a more conservative control level upon detection, allowing the vehicle to mitigate the risk before continuing with subsequent control. In some embodiments, the above S104 is implemented through steps S1041~S1043: S1041. Based on the vehicle's lateral and longitudinal acceleration at the current control moment, generate the impact intensity at the current control moment. The vehicle acceleration includes the vehicle's lateral and longitudinal acceleration, with longitudinal acceleration referring to the vehicle's direction of travel.

[0034] For example, the first Impact intensity at each control moment , , They represent the first The lateral and longitudinal accelerations at each control moment.

[0035] S1042. Determine whether the rate of change of the centroid at the current control moment is greater than the preset centroid jump threshold. And whether the impact intensity at the current control moment is greater than the preset impact threshold.

[0036] For example, for the first In terms of a control moment, judgment Is it greater than ,as well as Is it greater than .

[0037] S1043. If the rate of change of the center of mass at the current control moment is greater than the preset center of mass jump threshold, and the impact intensity at the current control moment is greater than the preset impact threshold, then the load slip event indicator at the current control moment is 1, which is used to indicate that a load slip event has occurred; otherwise, the load slip event indicator at the current control moment is 0, which is used to indicate that no load slip event has occurred.

[0038] For example, for the first In terms of a control moment ,in, Indicates the first The load slip event indication at each control moment.

[0039] It should be noted that the significance of using a combined determination of the rate of change of the center of mass and the impact strength is that relying solely on the rate of change may be affected by noise, and relying solely on the impact strength may misjudge road bumps as slippage. When both conditions are met simultaneously, it better reflects that a sudden slippage has indeed occurred in the material. When this happens, the controller immediately switches to a conservative mode, thereby suppressing the risk of secondary amplification after slippage by reducing the upper speed limit, reducing the rate of change of steering, and reducing the differential amplitude at the wheel ends.

[0040] S105. Based on the lateral offset and load slip event indication, the slope angle of the preset slope segment, and the filtered partial state data at the current control time, generate a risk score for the current control time, and determine the set of stable control boundaries for the current control time based on the risk score.

[0041] Here, based on the lateral offset at the current control moment and the slope angle of the preset slope segment... and the vehicle's center of gravity height and lateral wheelbase The maximum lateral acceleration at the current control moment is determined; based on the vehicle speed and yaw rate at the current control moment, the lateral excitation intensity at the current control moment is determined; based on the slope angle and preset slope threshold of the preset slope segment... The risk score for the current control moment is generated by taking into account the maximum lateral acceleration, lateral excitation intensity, and load slip event indication at the current control moment. For example, the risk score for any given control moment... The expression is as follows: ; ; ; in, , and There are three weighting coefficients, and , and The sum is 1. , and The value can be set according to actual needs. Let be the transverse excitation intensity at any given control moment. Let be the maximum lateral acceleration at any given control moment. The expression reflects an intuitive principle: the higher the center of gravity and the greater the lateral offset, the more likely the vehicle is to roll. When the slope is steeper, the normal load decreases, and the stability margin also decreases. This is the load slip event indication value at any given control moment. This is a stability margin parameter, which is a preset value. and These are the vehicle speed and yaw rate at any given control moment, respectively. This indicates taking the absolute value. Risk score. These respectively reflect the degree of lateral excitation approaching the boundary, the slope amplification effect, and the additional risk of slip events.

[0042] In this invention, the controller is based on a risk score. Mapping continuous risk indicators to discrete risk levels For example, risk levels can be classified using the following piecewise function form:

[0043] in, and As the risk classification threshold, satisfying , These correspond to low, medium, and high risk levels, respectively. Risk classification thresholds can be determined through simulation analysis or real-vehicle calibration and adjusted based on vehicle structural parameters and load characteristics. Each risk level corresponds to a set of stability control boundaries. The set of stable control boundaries can be expressed as:

[0044] in, Indicates vehicle speed. This indicates the vehicle's yaw rate. Indicates that the front wheels of the vehicle are turning. This indicates the lateral acceleration of the vehicle. Indicates risk level The corresponding vehicle speed limit, Indicates risk level The corresponding upper limit of vehicle yaw rate, Indicates risk level The corresponding upper limit of the front wheel steering angle of the vehicle, Indicates risk level The corresponding upper limit of vehicle lateral acceleration. , , , It is an upper limit function that varies with the risk level, reflecting the constraint relationship that "the higher the risk, the tighter the boundary". , , , These are all control boundary parameters that vary with the risk level, used to constrain the executable control range of the vehicle under different risk states. The aforementioned upper control parameters can be determined through theoretical analysis based on the vehicle dynamics model, or obtained through stability simulation analysis, or determined through real vehicle testing and calibration. They can also be determined using any combination of the above methods, and can be modified and optimized according to actual application scenarios. This invention does not limit these methods. can be By working backward, a correspondence is established between "limiting yaw" and "limiting lateral excitation": ,in To avoid extremely small positive numbers that can be divided by zero at low speeds, and to ensure computational stability.

[0045] Here, by comparing multiple risk score intervals corresponding to multiple preset risk levels with the risk score at the current control time, the risk score interval in which the risk score at the current control time falls is determined; the risk level corresponding to the risk score interval in which the risk score at the current control time falls is taken as the risk level at the current control time; and a set of stable control boundaries corresponding to the risk level at the current control time is taken as the set of stable control boundaries at the current control time. For example, if the risk score at the current control time... Then the set of stable control boundaries at the current control moment is a set of stable control boundaries corresponding to the low-risk level. The same logic applies to other cases.

[0046] S106. Use the set of stable control boundaries for clearance compensation. Based on the reference control parameters obtained from the clearance compensation, determine the braking amount of the wheels on both sides of the vehicle in order to control the vehicle.

[0047] It should be noted that autonomous driving systems are typically divided into a perception layer, a planning layer, and a control layer, and the controller described in this invention is the control layer. After obtaining the control boundary set, this invention enters the limit compensation control and closed-loop verification stage. The controller first limits the speed and steering commands (i.e., some expected parameters) output by the planning layer, ensuring that the vehicle's target is always within the allowable range of the current risk level, reducing unnecessary excitation from the source. Subsequently, the controller combines center of gravity offset and yaw motion to suppress and distribute wheel-end differential, making the vehicle more restrained on the offset side and smoother on the non-offset side, thereby suppressing further deterioration of lateral load transfer. In some embodiments, the above S106 is implemented through steps S1061~S1064: S1061. Using the saturation operator, generate the reference vehicle speed, reference vehicle yaw rate, and reference vehicle front wheel angle based on the desired vehicle speed, desired front wheel steering angle, and desired yaw rate at the current control time, as well as the upper limits of vehicle speed, vehicle yaw rate, and vehicle front wheel steering angle in the stable control boundary set at the current control time.

[0048] Here, at each control moment, the vehicle planning layer provides the controller with a desired vehicle speed. A desired front wheel steering angle for a vehicle and the expected vehicle yaw rate The controller then generates the reference vehicle speed for that control moment based on the three desired parameters at that control moment and the upper limits of vehicle speed, vehicle yaw rate, and vehicle front wheel steering angle in the stable control boundary set at that control moment. Baseline vehicle yaw rate and the front wheel steering angle of the benchmark vehicle : ,in, This is a saturation operator. This treatment ensures that the vehicle will not perform excessive speed or steering maneuvers during high-risk phases, reducing roll amplification factors at the source.

[0049] S1062, Based on the reference vehicle speed Baseline vehicle yaw rate and the front wheel steering angle of the benchmark vehicle Generate reference drive control quantity .

[0050] For example, for any given control moment, with that given control moment's... , and Using this as input, the reference drive control quantity for any given control moment can be generated by executing the speed closed-loop control method. Since speed closed-loop control methods already exist, the specific implementation principle of this method will not be elaborated upon in this invention.

[0051] S1063. Based on the lateral offset and vehicle yaw rate at the current control moment, generate the differential suppression amount at the current control moment.

[0052] To further suppress bias-side excitation, the controller needs to construct a differential suppression quantity. For example, the differential suppression quantity at any given control moment... ,in This is a preset adjustment coefficient, which can be set according to actual needs. and These represent the lateral offset and vehicle yaw rate at any given control moment, respectively. It should be noted that... This can be understood as the adjustment amount of the drive / braking difference between the left and right wheels of the vehicle at any given control moment.

[0053] S1064. Based on the saturation operator, the upper limit of the differential amplitude corresponding to the risk level at the current control moment, the differential suppression amount at the current control moment, and the reference drive control amount, the braking amount of the wheels on both sides of the vehicle in the longitudinal direction is generated respectively, and the braking amount is used to control the driving state of the vehicle.

[0054] For example, the expression for the braking amount of the left and right wheels of the vehicle at any given control moment is as follows: ; in, This represents the braking amount of the vehicle's left wheels (i.e., wheels 1 and 3) at any given control moment. This represents the braking amount of the right-side wheels (i.e., wheels 2 and 4) of the vehicle at any given control moment. This represents the upper limit of the drive / braking differential adjustment corresponding to the risk level at any given control moment. It should be noted that... and , , , These are all control boundary parameters that vary with risk level, used to constrain the executable control range of the vehicle under different risk states. The aforementioned upper control limit parameters can be determined through theoretical analysis based on the vehicle dynamics model, or obtained through stability simulation analysis, or determined through real vehicle testing and calibration, or any combination of the above methods, and can be modified and optimized according to the actual application scenario. It should be noted that the set of stable control boundaries corresponding to high risk levels... , , , All are smaller than the set of stability control boundaries corresponding to the medium-risk level. , , , The set of stability control boundaries corresponding to the medium-risk level includes... , , , All are smaller than the set of stability control boundaries corresponding to the low-risk level. , , , Thus, when the risk level reaches a high level, the control actions naturally shift to a conservative strategy focused on deceleration and small differential movements, avoiding a secondary amplification of risk caused by sudden turns or strong differential movements following a change in the center of gravity.

[0055] In some embodiments, after S106, the method further includes: S107. Based on the risk score and centroid change rate at the current control moment, calculate the verification index at the current control moment, and determine whether the verification index at the current control moment is greater than or equal to the verification index at multiple consecutive historical control moments.

[0056] For example, the first Verification metrics at each control moment ,in, and The preset coefficients, and and The sum is 1, and the specific value can be set according to actual needs. After calculating... Then, make a judgment Are they all greater than or equal to? , , … ,in It is a positive integer greater than 1, and the specific value can be set according to actual needs. Indicates the first The verification metrics for each control moment are the same, and so on for the others.

[0057] S108. If so, gradually reduce the vehicle speed until it stops, and issue a warning signal and request manual handling.

[0058] For example, if All are greater than or equal to , , … If the speed is too low, it indicates that the controller's braking effect is insufficient and the risk has not been effectively suppressed. Therefore, the safety exit procedure is initiated, and the reference speed is gradually reduced until the vehicle stops safely. At the same time, an alarm and a request for manual handling are issued through sound and light or communication.

[0059] In some embodiments, if All less than , , … If the calculated slope angle is within a certain range, it indicates that the controller's braking effect is effective, meaning the risk is effectively suppressed. The vehicle continues in slope stabilization mode until it is determined that the vehicle has exited the preset slope segment through slope angle analysis and map position matching. At this point, slope stabilization mode exits, and the risk score and baseline control parameters (i.e., baseline vehicle speed, baseline vehicle yaw rate, and baseline vehicle front wheel steering angle) are recorded at each control moment in slope stabilization mode for pre-compensation reference when entering the same slope segment subsequently. It should be noted that when the analyzed slope angle... ,and If the preset time period is reached, it is determined that the vehicle has left the preset slope section. Alternatively, if the vehicle's position does not match the position of the preset slope section and this mismatch lasts for the preset time period, it is determined that the vehicle has left the preset slope section. This makes the exit of the slope stabilization mode more stable and reliable.

[0060] This invention has the following advantages: This invention employs an online estimation method for center of gravity offset based on wheel-end normal load distribution. It estimates the longitudinal center of gravity position using the front and rear axle load distribution relationship and constructs the lateral center of gravity offset and its rate of change index using the load difference between the left and right wheels. This characterizes the continuous offset and short-term jumps caused by uneven loading and material migration, providing direct state basis for stability margin assessment and control decisions under slope conditions.

[0061] This invention designs a load slip event identification mechanism that combines abrupt changes in center of gravity and impact characteristics. It monitors rapid changes in the amplitude or direction of center of gravity offset within a short time window and makes a joint judgment based on vibration and impact characteristics obtained from inertial measurements. After a slip event is identified, the controller immediately switches to a more conservative control level and prioritizes the suppression of high-risk excitations, thereby reducing the risk of lateral tilt amplification in curved and continuous slope sections.

[0062] This invention proposes a risk classification and adaptive tightening boundary compensation control strategy for slope stability. It integrates the slope magnitude, yaw excitation intensity, and slip event information to form a risk level, and dynamically tightens the control boundaries such as the upper limit of vehicle speed, upper limit of acceleration, steering amplitude and rate of change, and differential amplitude according to the risk level. Within the boundary constraints, torque limiting or light braking is implemented on the high-risk side, combined with global speed reduction and small steering strategies. At the same time, control verification and safe exit are achieved through periodic review and gradual safety handling to ensure continuous stable driving on complex slopes.

[0063] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0064] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0065] In this specification, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple instances. While different embodiments may describe certain measures, this does not mean that these measures cannot be combined to produce a good effect.

[0066] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for slope stability control of an unmanned trolley in a mine roadway, characterized in that, include: Determine if the vehicle is currently on a preset slope; if so, enter slope stabilization mode. In the slope stabilization mode, the vehicle status data of the current cycle is collected and filtered to obtain the filtered status data of the current control moment, with an interval of one cycle between two adjacent control moments; Based on the filtered state data at the current control moment, the centroid offset is estimated and the centroid change trend is constructed to obtain the lateral offset and centroid change rate at the current control moment. The lateral direction refers to the direction perpendicular to the vehicle's driving direction in the plane where the vehicle is located, and the longitudinal direction refers to the vehicle's driving direction. Based on the centroid change rate and the vehicle acceleration at the current control moment, the load slip event indication at the current control moment is determined to determine whether a load slip event has occurred. When the load slip event occurs, the vehicle gear is switched to reduce the vehicle speed limit, vehicle steering change rate, and vehicle wheel-end differential amplitude. Based on the lateral offset, the load slip event indication, the slope angle of the preset slope segment, and the filtered partial state data at the current control moment, a risk score for the current control moment is generated, and the set of stable control boundaries for the current control moment is determined according to the risk score. Using the set of stable control boundaries for clearance compensation, and based on the reference control parameters obtained from the clearance compensation, the braking amount of the wheels on both sides of the vehicle's longitudinal direction is determined for vehicle control.

2. The slope stability control method for unmanned mining roadways according to claim 1, characterized in that, After performing vehicle control using the compensated set of stable control boundaries and the determined differential of the wheels, the method further includes: Based on the risk score and centroid change rate at the current control moment, calculate the verification index at the current control moment, and determine whether the verification index at the current control moment is greater than or equal to the verification index at multiple consecutive historical control moments. If so, gradually reduce the vehicle speed until it stops, and issue a warning signal and request manual intervention.

3. The slope stability control method for unmanned mining roadways according to claim 1, characterized in that, The method further includes: After the vehicle exits the preset slope, it exits the slope stabilization mode and records the risk score and the baseline control parameters at each control moment in the slope stabilization mode.

4. The slope stability control method for unmanned mining roadways according to claim 1, characterized in that, The filtered state data at the current control moment includes: the vehicle speed, vehicle yaw rate, and normal load of each wheel of the vehicle at the current control moment.

5. The slope stability control method for unmanned mining roadways according to claim 4, characterized in that, The process of estimating the centroid offset and constructing the centroid change trend based on the filtered state data at the current control moment, to obtain the lateral offset and centroid change rate at the current control moment, includes: Based on the normal load of each wheel of the vehicle at the current control moment and the wheelbase between the front and rear axles of the vehicle, determine the distance from the center of mass to the front axle of the vehicle at the current control moment. Based on the normal load of each wheel of the vehicle at the current control moment, determine the sum of the normal loads of the front wheels of the vehicle and the sum of the normal loads of the rear wheels of the vehicle. The lateral offset at the current control moment is determined based on the vehicle's lateral track, the sum of the normal loads on the front wheels of the vehicle, and the sum of the normal loads on the rear wheels of the vehicle. Based on the distance from the centroid to the front axle of the vehicle at the current control moment, and the lateral offset at the current control moment, construct the centroid state vector at the current control moment; The centroid change rate at the current control moment is determined based on the difference between the centroid state vector at the current control moment and the centroid state vector at the previous control moment, as well as the time interval between two adjacent control moments.

6. The slope stability control method for unmanned mining roadways according to claim 1, characterized in that, The step of determining the load slip event indication at the current control moment based on the centroid change rate and the vehicle acceleration at the current control moment to determine whether a load slip event has occurred includes: The impact intensity at the current control moment is generated based on the vehicle's lateral and longitudinal accelerations at the current control moment. The vehicle accelerations include the vehicle's lateral and longitudinal accelerations, with the longitudinal direction referring to the vehicle's travel direction. Determine whether the rate of change of the center of mass at the current control moment is greater than a preset center of mass jump threshold, and whether the impact intensity at the current control moment is greater than a preset impact threshold. If the rate of change of the center of mass at the current control moment is greater than the preset center of mass jump threshold, and the impact intensity at the current control moment is greater than the preset impact threshold, then the load slip event indicator at the current control moment is 1, which indicates that a load slip event has occurred; otherwise, the load slip event indicator at the current control moment is 0, which indicates that no load slip event has occurred.

7. The slope stability control method for unmanned mining roadways according to claim 4, characterized in that, The process of generating a risk score for the current control time based on the lateral offset, the load slip event indication, the slope angle of the preset slope segment, and the filtered partial state data at the current control time includes: Based on the lateral offset, the slope angle of the preset slope, the center of gravity height and lateral wheel track of the vehicle at the current control moment, the maximum lateral acceleration at the current control moment is determined. Based on the vehicle speed and yaw rate at the current control moment, determine the lateral excitation intensity at the current control moment; Based on the slope angle and preset slope threshold of the preset slope segment, as well as the maximum lateral acceleration, lateral excitation intensity, and load slip event indication at the current control moment, a risk score is generated for the current control moment.

8. The slope stability control method for unmanned mining roadways according to claim 4, characterized in that, The step of determining the set of stable control boundaries at the current control moment based on the risk score includes: By comparing the multiple risk score intervals corresponding to the preset multiple risk levels with the risk score at the current control time, the risk score interval in which the risk score at the current control time is located is determined. The risk level corresponding to the risk score interval in which the risk score is located at the current control time is taken as the risk level at the current control time. The set of stable control boundaries corresponding to the risk level at the current control moment is taken as the set of stable control boundaries at the current control moment. Each set of stable control boundaries includes: vehicle speed limit, vehicle yaw rate limit, vehicle front wheel steering angle limit, and vehicle lateral acceleration limit.

9. The slope stability control method for unmanned mining roadways according to claim 8, characterized in that, The step of performing boundary compensation on the stable control boundary set, and determining the braking amount of the wheels on both sides of the vehicle's longitudinal direction based on the reference control parameters obtained from the boundary compensation for vehicle control, includes: Using the saturation operator, the reference vehicle speed, reference vehicle yaw rate, and reference vehicle front wheel angle are generated based on the desired vehicle speed, desired front wheel steering angle, and desired yaw rate at the current control time, as well as the upper limits of vehicle speed, vehicle yaw rate, and vehicle front wheel steering angle in the stable control boundary set at the current control time. A reference drive control quantity is generated based on the reference vehicle speed, the reference vehicle yaw rate, and the reference vehicle front wheel steering angle. Based on the lateral offset and vehicle yaw rate at the current control moment, the differential suppression amount at the current control moment is generated; Based on the saturation operator, the upper limit of differential amplitude corresponding to the risk level at the current control moment, the differential suppression amount at the current control moment, and the reference drive control amount, the braking amounts of the wheels on both sides of the vehicle's longitudinal direction are generated respectively, and the vehicle's driving state is controlled using the braking amounts.

10. A slope stabilization controller for an unmanned mining tunnel vehicle, comprising a processor, a communication interface, a memory, and a communication bus, characterized in that, The processor, the communication interface, and the memory communicate with each other via the communication bus; The memory is used to store computer programs; When the processor executes a program stored in the memory, it implements the steps of the method described in any one of claims 1-9.

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