State switching method, device and equipment of unmanned mine car and storage medium

Abstract

The invention provides a state switching method, device and equipment for an unmanned mine car and a storage medium, and the method comprises the steps: firstly, obtaining the driving data of the unmanned mine car, the driving data comprising a current actual vehicle speed, a target vehicle speed, an actual acceleration and a target acceleration; determining a hysteresis band threshold value based on the current actual vehicle speed and the target vehicle speed, wherein the hysteresis band threshold value is used for representing the deviation value between the actual acceleration and the target acceleration when the unmanned mine car is subjected to state switching; and determining the motion state of the unmanned mine car based on the actual acceleration, the target acceleration and the hysteresis band threshold, wherein the motion state comprises an acceleration state or a deceleration state. Therefore, according to the embodiment of the invention, the frequent acceleration or deceleration of the vehicle caused by the fluctuation of the target acceleration near the critical threshold can be reduced, so that the stability of the unmanned mine car in the driving process is improved.

Description

Technical Field

[0001] This disclosure relates to the field of unmanned driving, and in particular to a method, apparatus, equipment and storage medium for switching the state of an unmanned mining truck. Background Technology

[0002] With the continuous development of the field of autonomous driving, autonomous vehicles are increasingly being used in harsh working conditions in high-altitude and extremely cold mining areas. Due to the steep slopes, poor road conditions, heavy loads, and numerous curves in mines, speed control of autonomous mining trucks becomes complex. During the operation of autonomous mining trucks, acceleration and deceleration are unavoidable due to various factors such as road conditions, work tasks, and driving environment.

[0003] Currently, the acceleration and deceleration of unmanned mining trucks are mainly affected by the target acceleration. That is, when the acceleration is greater than the critical threshold, the truck will accelerate immediately, and when the acceleration is less than the critical threshold, the truck will decelerate immediately. If the target acceleration fluctuates frequently around the critical threshold, it will cause frequent switching of the throttle and brake, resulting in the ore and other materials on the unmanned mining truck being spilled or the equipment being damaged due to violent shaking.

[0004] Therefore, improving the stability of unmanned mining trucks during operation is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] To address the aforementioned technical problems, this disclosure provides a method, apparatus, device, and storage medium for switching the state of an unmanned mining truck. By introducing a hysteresis band threshold that is dynamically adjusted based on the actual vehicle speed, the driving state of the unmanned mining truck can be determined using the hysteresis band threshold, the actual acceleration, and the target acceleration. This reduces the frequent acceleration or deceleration of the vehicle caused by fluctuations in the target acceleration near the critical threshold, thereby improving the stability of the unmanned mining truck during operation.

[0006] In a first aspect, embodiments of this disclosure provide a method for switching the state of an unmanned mining truck, the method comprising:

[0007] Acquire driving data of the unmanned mining truck; wherein, the driving data includes the current actual speed, target speed, actual acceleration, and target acceleration;

[0008] The hysteresis band threshold is determined based on the current actual vehicle speed and the target vehicle speed; wherein, the hysteresis band threshold is used to characterize the command holding interval of the unmanned mining truck in the acceleration control stage;

[0009] The motion state of the unmanned mining vehicle is determined based on the actual acceleration, the target acceleration, and the hysteresis band threshold; wherein the motion state includes an acceleration state or a deceleration state.

[0010] In one optional implementation, the current actual vehicle speed is obtained by filtering the acquired GPS vehicle speed and the drive-by-wire chassis feedback vehicle speed using a preset Kalman filter.

[0011] In one optional implementation, before determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold, the following steps are included:

[0012] The actual acceleration is filtered using a preset low-pass filter to obtain the filtered acceleration; wherein the filter coefficients of the preset low-pass filter are calculated based on the sampling frequency and the preset cutoff frequency, and the filter coefficients are used to filter the actual acceleration by substituting them into the difference equation of the preset low-pass filter.

[0013] Accordingly, determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold includes:

[0014] The motion state of the unmanned mining vehicle is determined based on the filtered acceleration, the target acceleration, and the hysteresis threshold.

[0015] In an optional implementation, before determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold, the method further includes:

[0016] The time difference between the system timestamp of the vehicle control unit and the state transition timestamp corresponding to the current state of the unmanned mining truck is determined as the retention time of the current state;

[0017] Accordingly, determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold includes:

[0018] If it is determined that the duration of the current state is greater than a preset time threshold, then the motion state of the unmanned mining vehicle is determined based on the actual acceleration, the target acceleration, and the hysteresis band threshold.

[0019] In one optional implementation, determining the hysteresis band threshold based on the current actual speed of the target vehicle and the target speed includes:

[0020] Determine the ratio between the current actual speed of the unmanned mining truck and the target speed, and sum the ratio with a preset value to obtain the value to be processed;

[0021] The product of the value to be processed and the preset dynamic threshold factor is performed to obtain the hysteresis threshold; wherein, the preset dynamic threshold factor is determined by the actual performance of the unmanned mining vehicle.

[0022] In one optional implementation, determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold includes:

[0023] If the target acceleration is determined to be positive and the actual acceleration is less than the difference between the target acceleration and the hysteresis band threshold, then the motion state of the unmanned mining truck is determined to be the first acceleration state.

[0024] If the target acceleration is determined to be positive and the actual acceleration is greater than the sum of the target acceleration and the hysteresis threshold, then the motion state of the unmanned mining truck is determined to be the first deceleration state.

[0025] If the target acceleration is determined to be negative, and the actual acceleration is less than the difference between the target acceleration and the hysteresis band threshold, then the motion state of the unmanned mining truck is determined to be the second acceleration state.

[0026] If the target acceleration is determined to be negative, and the actual acceleration is greater than the sum of the target acceleration and the hysteresis threshold, then the motion state of the unmanned mining vehicle is determined to be the second deceleration state.

[0027] Secondly, this disclosure provides a state switching device for an unmanned mining truck, the device comprising:

[0028] The acquisition module is used to acquire the driving data of the unmanned mining truck; wherein, the driving data includes the current actual vehicle speed, the target vehicle speed, the actual acceleration, and the target acceleration;

[0029] The first determining module is used to determine a hysteresis band threshold based on the current actual vehicle speed and the target vehicle speed; wherein, the hysteresis band threshold is used to characterize the command holding interval of the unmanned mining truck in the acceleration control stage;

[0030] The second determining module is used to determine the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold; wherein the motion state includes an acceleration state or a deceleration state.

[0031] Thirdly, this disclosure provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to implement the above-described method.

[0032] Fourthly, this disclosure provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method described above.

[0033] Fifthly, this disclosure provides a computer program product comprising a computer program / instruction that, when executed by a processor, implements the method described above.

[0034] The technical solution provided in this disclosure has at least the following advantages compared with the prior art:

[0035] This disclosure provides a method, apparatus, device, and storage medium for switching the state of an unmanned mining truck. Specifically, the method first acquires the driving data of the unmanned mining truck, which includes the current actual speed, target speed, actual acceleration, and target acceleration. Then, a hysteresis threshold is determined based on the current actual speed and target speed. The hysteresis threshold is used to characterize the deviation between the actual acceleration and the target acceleration when the unmanned mining truck switches states. Next, the motion state of the unmanned mining truck is determined based on the actual acceleration, target acceleration, and hysteresis threshold. The motion state includes an acceleration state or a deceleration state.

[0036] As can be seen, by introducing a hysteresis band threshold that is dynamically adjusted based on the actual vehicle speed, the unmanned mining truck can determine its next driving state by using the hysteresis band threshold, the actual acceleration, and the target acceleration. This reduces the frequent acceleration or deceleration of the vehicle caused by the target acceleration fluctuating around the critical threshold, thereby improving the stability of the unmanned mining truck during driving. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0038] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart illustrating a state switching method for an unmanned mining truck provided in an embodiment of this disclosure;

[0040] Figure 2 Another method for switching the state of an unmanned mining truck provided in this embodiment of the present disclosure;

[0041] Figure 3 This is a schematic diagram of the structure of a state switching device for an unmanned mining truck provided in an embodiment of the present disclosure;

[0042] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0043] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0044] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0045] Currently, the acceleration and deceleration of unmanned mining trucks are mainly affected by the target acceleration. That is, when the acceleration is greater than the critical threshold, the truck will accelerate immediately, and when the acceleration is less than the critical threshold, the truck will decelerate immediately. If the target acceleration fluctuates frequently around the critical threshold, it will cause frequent switching of the throttle and brake, resulting in the ore and other materials on the unmanned mining truck being spilled or the equipment being damaged due to violent shaking.

[0046] Secondly, frequent rapid acceleration or braking can lead to energy waste, especially in hybrid or pure electric mining trucks, where frequent switching can cause recycling interruptions or inefficiencies. Furthermore, frequent switching between drive and braking can cause mechanical stress and impact on the power transmission system (engine, gearbox, drive axle) and braking system (brake discs / drums, brake pads, brake hydraulic system), accelerating wear and severely reducing the service life of the unmanned mining truck.

[0047] To this end, this disclosure provides a method for switching the state of an unmanned mining truck. Specifically, firstly, the driving data of the unmanned mining truck is acquired, including the current actual speed, target speed, actual acceleration, and target acceleration. Then, a hysteresis threshold is determined based on the current actual speed and target speed. The hysteresis threshold is used to characterize the deviation between the actual acceleration and the target acceleration when the unmanned mining truck switches states. Next, the motion state of the unmanned mining truck is determined based on the actual acceleration, target acceleration, and hysteresis threshold. The motion state includes an acceleration state or a deceleration state.

[0048] As can be seen, by introducing a hysteresis band threshold that is dynamically adjusted based on the actual vehicle speed, the unmanned mining truck can determine its next driving state by using the hysteresis band threshold, the actual acceleration, and the target acceleration. This can reduce the frequent acceleration or deceleration of the vehicle caused by the target acceleration fluctuating near the critical threshold, thereby improving the stability of the unmanned mining truck during driving.

[0049] Based on the above method embodiments, this disclosure provides a state switching method for unmanned mining trucks, such as... Figure 1 The diagram shown is a flowchart illustrating a state switching method for an unmanned mining truck provided in an embodiment of this disclosure.

[0050] S101: Obtain driving data of the unmanned mining truck.

[0051] The driving data includes the current actual speed, target speed, actual acceleration, and target acceleration.

[0052] The state switching method for unmanned mining trucks provided in this disclosure can be applied to the decision-making layer of unmanned mining trucks. The decision-making layer is mainly responsible for analyzing and making decisions based on the information provided by the perception layer in order to realize the autonomous driving behavior of unmanned mining trucks. For example, during the driving process of the mining truck, various behavioral decisions are made based on the starting point and the destination, as well as the surrounding environment, such as acceleration, deceleration, and steering.

[0053] The current actual speed of the driverless mining truck can be determined based on the GPS (Global Positioning System) speed and the speed feedback from the drive-by-wire chassis. The GPS speed refers to the vehicle's speed measured using dynamic GPS positioning during operation, over a period of time between two points in time. The drive-by-wire chassis feedback speed refers to the vehicle's actual speed information collected by the drive-by-wire chassis through speed sensors.

[0054] In practical applications, GPS vehicle speed signals may be affected by external environmental obstructions or interference, leading to unstable data. Furthermore, the vehicle speed feedback from the drive-by-wire chassis may also contain errors during low-speed and gear-shifting conditions. Therefore, to obtain a more accurate, stable, and reliable actual vehicle speed, embodiments of this disclosure can also design a Kalman filter to fuse these noisy data, thereby reducing the impact of errors from a single sensor and improving the accuracy and robustness of the current speed calculation.

[0055] Specifically, a preset Kalman filter is used to filter the GPS vehicle speed and the vehicle speed fed back from the drive-by-wire chassis to obtain the current actual speed of the unmanned mining truck. The specific filtering process will be described in subsequent embodiments and will not be repeated here.

[0056] The driving data of the driverless mining truck also includes target speed and target acceleration. Target speed refers to the real-time target speed for path planning. Specifically, the target speed can be dynamically calculated based on real-time information such as current road conditions, obstacles, speed limit signs, and the speed of the vehicle ahead, representing the driverless mining truck's real-time speed at the next moment. Target acceleration refers to the acceleration value that the driverless mining truck needs to achieve under specific conditions.

[0057] The driving data of the unmanned mining truck also includes actual acceleration. The calculation process of actual acceleration can be as follows: First, calculate the speed difference between the current actual speed of the unmanned mining truck and the speed of the previous frame as the change in speed. Then, calculate the time difference between the two frames as the change in time. Finally, calculate the ratio between the change in speed and the change in time as the actual acceleration.

[0058] S102: Determine the hysteresis threshold based on the current actual vehicle speed and the target vehicle speed.

[0059] The hysteresis threshold is used to characterize the deviation between the actual acceleration and the target acceleration when the unmanned mining vehicle switches states.

[0060] In this embodiment of the disclosure, after acquiring the driving data of the unmanned mining truck, a hysteresis threshold is determined based on the current actual speed and target speed in the driving data, so as to control the acceleration or deceleration state of the unmanned mining truck using the hysteresis threshold.

[0061] The hysteresis threshold consists of an upper threshold and a lower threshold. The upper threshold refers to the minimum actual acceleration that triggers the unmanned mining truck to switch to acceleration mode during the actual acceleration change process. In other words, when the actual acceleration is greater than the upper threshold, the engine is controlled to perform a driving operation. The lower threshold refers to the maximum actual acceleration that triggers the engine to switch to braking mode during the actual acceleration change process. In other words, when the actual acceleration is less than the lower threshold, the engine is controlled to perform a braking operation.

[0062] Since the hysteresis band threshold defines a range that allows the actual acceleration to fluctuate near the target acceleration, it can reduce the frequent switching of drive or braking states due to small fluctuations in the actual acceleration when it approaches the target acceleration, thus improving the smoothness of drive and braking switching and driving stability.

[0063] Specifically, firstly, the ratio between the current actual speed of the unmanned mining truck and the path-limited speed is calculated, and then the ratio is summed with a preset value to obtain the value to be processed, where the preset value is 1; then the value to be processed is multiplied with a preset dynamic threshold factor to obtain the hysteresis threshold.

[0064] The path-limited speed refers to the maximum speed at which an unmanned mining truck can safely travel on a specific path during autonomous driving, determined based on path planning and environmental conditions. The preset dynamic threshold factor can be determined based on the performance of the unmanned mining truck or through experience-based adjustments. This preset dynamic threshold factor reflects the speed maintenance range of the unmanned mining truck, i.e., the acceleration range in which speed is maintained. Since different mining trucks correspond to different preset dynamic threshold factors, the hysteresis threshold needs to be adjusted according to the preset dynamic threshold factor. The range of the preset dynamic threshold factor is 0.05-0.2.

[0065] In practical applications, the hysteresis band threshold can be calculated using the following formula:

[0066]

[0067] Among them, y t The hysteresis threshold is represented by α, the preset dynamic threshold factor is represented by v, and the current actual vehicle speed is represented by v. b This indicates the speed limit for the route. Both the current actual speed and the speed limit for the route are measured in km / h.

[0068] As can be seen from the above formula, the higher the current actual vehicle speed, the larger the corresponding hysteresis threshold, thereby increasing the tolerance at high speeds; the lower the current actual vehicle speed, the smaller the corresponding hysteresis threshold, thereby improving the accuracy of low-speed control.

[0069] S103. Determine the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis threshold.

[0070] The motion state of the unmanned mining truck includes acceleration state or acceleration state.

[0071] Specifically, if the target acceleration is positive, and the actual acceleration is determined to be less than the difference between the target acceleration and the hysteresis threshold, it indicates that the actual vehicle speed is lower than the target speed. In this case, acceleration is required, and the corresponding motion state of the unmanned mining truck is the first acceleration state. Additionally, if braking control inputs still exist at this time, they must be reset to zero before acceleration; otherwise, acceleration proceeds directly.

[0072] If the target acceleration is positive, and the actual acceleration is determined to be greater than the sum of the target acceleration and the hysteresis threshold, it means that the actual vehicle speed has reached or exceeded the target vehicle speed. At this time, it is necessary to decelerate to prevent the vehicle speed from continuing to increase and exceeding the speed limit. The corresponding motion state of the unmanned mining truck is the first deceleration state.

[0073] If the target acceleration is negative, and the actual acceleration is determined to be less than the difference between the target acceleration and the hysteresis band threshold, it indicates that the deceleration (absolute value) reached by the actual vehicle speed is too large, causing the actual vehicle speed to be lower than the target speed. In this case, the braking control quantity needs to be reduced to prevent the vehicle speed from continuing to decrease. The corresponding motion state of the unmanned mining truck is the second acceleration state (also known as the deceleration over-compensation state). In addition, if there is still a throttle control quantity at this time, and the target acceleration continues to increase (gradually approaching zero from a negative value), then the throttle needs to be increased slowly to prevent the vehicle speed from continuing to decrease.

[0074] If the target acceleration is negative, and the actual acceleration is determined to be greater than the sum of the target acceleration and the hysteresis threshold, it indicates that the actual vehicle speed is much greater than the target speed. In this case, the braking control quantity needs to be increased according to the loading status of the unmanned mining truck, and the corresponding motion state of the unmanned mining truck is the second deceleration state (also known as the rapid deceleration state). Additionally, if a throttle control quantity still exists at this time, and the actual vehicle speed is greater than the maximum permissible safety threshold of the target speed, then the throttle control quantity is cleared and the braking control quantity is increased. Otherwise, the actual vehicle speed is close to the target speed and remains within the permissible error range of the target speed.

[0075] In the state switching method for the unmanned mining truck provided in this embodiment, the driving data of the unmanned mining truck is first acquired, including the current actual speed, target speed, actual acceleration, and target acceleration. Then, a hysteresis band threshold is determined based on the current actual speed and target speed. The hysteresis band threshold is used to characterize the deviation between the actual acceleration and the target acceleration when the unmanned mining truck switches states. Next, the motion state of the unmanned mining truck is determined based on the actual acceleration, target acceleration, and hysteresis band threshold. The motion state includes an acceleration state or a deceleration state.

[0076] As can be seen, by introducing a hysteresis band threshold that is dynamically adjusted based on the current actual vehicle speed, the unmanned mining truck can determine its next driving state by using the hysteresis band threshold, actual acceleration, and target acceleration. This can reduce the frequent acceleration or deceleration of the vehicle caused by the target acceleration fluctuating near the critical threshold, thereby improving the stability of the unmanned mining truck during driving.

[0077] In practical applications, first-order low-pass filters cannot effectively balance sensitivity and stability during filtering, and their low order results in poor amplitude-frequency characteristics, leading to low fidelity for low-frequency detection signals and difficulty in achieving steep filtering characteristics. Therefore, to achieve better filtering performance and lower computational complexity, a second-order Butterworth low-pass filter can be designed as a preset low-pass filter to filter the actual acceleration.

[0078] Specifically, the transfer function of the second-order Butterworth low-pass filter is:

[0079]

[0080] Where ω0 represents the cutoff angular velocity, and Q represents the quality factor, which takes the value of . S represents the analog filter, and H(s) represents the transfer function of the analog filter.

[0081] First, the analog filter is converted into a digital filter using a bilinear transformation. The formula for calculating the bilinear transformation can be expressed as: Among them, T s Indicates the sampling interval (i.e., the sampling frequency f). s (the reciprocal of the first digit), S represents an analog filter, and Z represents a digital filter.

[0082] Then, the digital filter Z obtained by the bilinear transformation is substituted into the above transfer function for discretization to obtain the transfer function of the digital filter:

[0083]

[0084] Where H(z) represents the transfer function of the digital filter, b0, b1, b2, a1, a2 are the coefficients of the digital filter, X(z) represents the Z-variance of the input signal, and Y(z) represents the Z-variance of the output signal.

[0085] The difference equation for the digital filter implemented in the program is as follows:

[0086] y(n)=b0x(n)+b1x(n-1)+b2x(n-2)-a1y(n-1)-a2y(n-2)(4);

[0087] Where x(n) represents the current sampled value, x(n-1) represents the previous sampled value, x(n-2) represents the sampled value two years before last, y(n) represents the current filtered output value, y(n-1) represents the previous filtered output value, and y(n-2) represents the filtered output value two years before last.

[0088] Next, the coefficients of the digital filter can be obtained through algebraic operations. Specifically, the coefficients... Where f c f is the preset cutoff frequency of the digital filter. s Sampling frequency, b1 = 2b0, b2 = b0,

[0089] In practical applications, the range of the preset cutoff frequency can be 0. <f c <f c / 2.

[0090] Furthermore, by substituting the coefficients k of the digital filter into b0, b1, b2, a1, and a2, all the coefficients of the difference equation can be obtained, which can then be used to filter the actual acceleration.

[0091] As can be seen, in the process of filtering the actual acceleration using a preset low-pass filter, the filter coefficients of the preset low-pass filter can be calculated based on the sampling frequency and the preset cutoff frequency. By substituting the filter coefficients into the difference equation of the preset low-pass filter, high-frequency filtering of the actual acceleration is achieved, making the acceleration change after filtering smoother. While ensuring efficient filtering of high-frequency noise, the fidelity of the low-frequency signal is well maintained.

[0092] In this embodiment of the disclosure, after filtering the actual acceleration using a preset low-pass filter to obtain the filtered acceleration, the motion state of the unmanned mining vehicle is determined based on the filtered acceleration, the target acceleration, and the hysteresis threshold.

[0093] Since the preset low-pass filter can handle the problem of jumps and instabilities in the calculated actual acceleration caused by the instability of GPS signal, the effect of high-frequency noise can be suppressed after filtering the actual acceleration by the preset low-pass filter. Compared with the frequent switching of drive and braking caused by directly using the actual acceleration calculated based on GPS vehicle speed, the embodiments of this disclosure can further improve the stability of the unmanned mining truck during the driving process by using the filtered acceleration.

[0094] In one alternative implementation, to further smooth the state transition, a state holding time can be introduced before determining the motion state of the unmanned mining vehicle based on the actual acceleration, target acceleration, and hysteresis threshold. That is, once the state transitions, the state must be maintained for at least a period of time before transitioning to another state. This can be achieved by recording the timestamp of the state transition and locking the state for a period of time after the transition.

[0095] Specifically, the time difference between the system timestamp of the on-board control unit and the state transition timestamp corresponding to the current state of the unmanned mining truck is determined as the retention time of the current state.

[0096] The current state refers to the specific state that the unmanned mining truck is in at a certain moment. Common states include: stopped state, accelerating state, decelerating state, and cruising state.

[0097] It is understandable that the system timestamp of the vehicle control unit is the current time of the unmanned mining truck, the current state is the state of the unmanned mining truck when it last switched states, and the state switching timestamp is the timestamp recorded when the last state switch occurred.

[0098] If the current state duration is determined to be greater than a preset time threshold, it indicates that the unmanned mining vehicle has reached its state transition time. At this point, the motion state of the unmanned mining vehicle is determined based on the actual acceleration, target acceleration, and hysteresis threshold, serving as the target decision state after the transition. If the current state duration is determined to be less than the preset time threshold, it indicates that the unmanned mining vehicle has not reached its state transition time, and the current state remains unchanged. Furthermore, when calculating the state duration, the timestamp of the previous state transition must be initialized after each program restart.

[0099] As can be seen, the embodiments of this disclosure introduce a preset time threshold to control the state switching of the unmanned mining truck, thereby solving the instability of the unmanned mining truck during operation caused by frequent switching of acceleration and deceleration states.

[0100] In practical applications, an emergency threshold can also be set so that when the actual acceleration suddenly changes significantly, a state switch can be performed even if the state switch time has not yet been reached.

[0101] Specifically, when the difference between the actual acceleration and the target acceleration is greater than the emergency threshold, the motion state of the unmanned mining truck is determined based on the actual acceleration, the target acceleration, and the hysteresis band threshold to address the problem of unstable vehicle speed caused by untimely state switching. The emergency threshold is greater than the hysteresis band threshold.

[0102] In one optional implementation, after determining the motion state of the unmanned mining vehicle based on the actual acceleration, target acceleration, and hysteresis threshold as the target decision state after switching, it can also be determined whether the target decision state is consistent with the current state. If it is determined that the target decision state is inconsistent with the current state, the current state is updated to the target decision state, and the system timestamp of the currently collected vehicle control unit is determined as the state switching timestamp corresponding to the target decision state, while the updated current state is output.

[0103] As can be seen, the embodiments of this disclosure can update the decision state by combining the current state and the target decision state, which enhances the robustness of decision state switching and further improves the smoothness of state switching of unmanned mining trucks.

[0104] In practical applications, the process of filtering GPS vehicle speed and drive-by-wire chassis feedback vehicle speed using a preset Kalman filter can include a prediction stage and a correction stage. The prediction stage includes state estimate prediction and covariance prediction, while the correction stage includes Kalman gain calculation, optimal state estimate correction, and covariance correction.

[0105] Specifically, the formula for predicting the state estimate can be:

[0106]

[0107] in, Let A represent the estimated state value at the current moment (e.g., vehicle speed), and let A represent the state transition matrix. This represents the state estimate at the previous moment.

[0108] The formula for predicting covariance can be:

[0109] P - k = A × P - k-1 ×A T +Q (6);

[0110] Among them, P - k P represents the covariance between the measured and estimated values. - k-1 Let A represent the posterior estimated covariance matrix of the previous time step, i.e., the state uncertainty of the previous time step after measurement correction. T Let represent the transpose of the state transition matrix, and Q represent the process noise covariance matrix.

[0111] The Kalman gain calculation formula can be:

[0112]

[0113] Among them, K k H represents the Kalman gain, used to characterize the weights of prediction and measurement errors in the state-optimal estimation process. H represents the measurement matrix. T R represents the transpose of the measurement matrix, and R represents the measurement noise matrix.

[0114]

[0115] in, The optimal estimate of the state, z k This indicates the measured value.

[0116] P k = (IK k ×H)×P - k (9);

[0117] Among them, P k Let I denote the posterior estimated covariance matrix at the current time, and let P denote the identity matrix. - k This represents the prior estimate of the covariance matrix (uncertainty in the prediction stage).

[0118] In this embodiment of the disclosure, the vehicle speed is estimated using the GPS speed and observed using the vehicle speed fed back by the drive-by-wire chassis. By designing appropriate process noise covariance matrices and measurement noise covariance matrices, a Kalman filter is used to fuse the observed and estimated values, thereby reducing the influence of errors from a single sensor and improving the accuracy and robustness of the actual speed estimation.

[0119] Figure 2 This is a flowchart illustrating another state switching method for an unmanned mining truck provided in an embodiment of this disclosure. This method can be executed by a state switching device of the unmanned mining truck, which can be implemented in software and / or hardware, and is generally integrated into an electronic device, such as... Figure 2 As shown, the method includes:

[0120] S201: Obtain the GPS speed, target speed, target acceleration, and drive-by-wire chassis feedback speed of the unmanned mining truck.

[0121] S202: The current actual speed of the unmanned mining truck is obtained by filtering the vehicle speed from the GPS system and the feedback speed from the drive-by-wire chassis using a preset Kalman filter.

[0122] S203: Determine the actual acceleration of the unmanned mining truck based on the current actual vehicle speed, and use a preset low-pass filter to filter the actual acceleration to obtain the filtered acceleration.

[0123] S204: Determine the duration of the current state based on the system timestamp of the on-board control unit and the state transition timestamp corresponding to the current state of the unmanned mining truck.

[0124] S205: If it is determined that the holding time of the current state is greater than the preset time threshold, the motion state of the unmanned mining truck is determined based on the filtered acceleration, the target acceleration, and the hysteresis threshold, and is used as the target decision state.

[0125] The hysteresis threshold is determined based on the current actual speed and target speed of the unmanned mining truck.

[0126] S206: If it is determined that the target decision state is inconsistent with the current state, the current state is updated using the target decision state, and the system timestamp of the currently collected vehicle control unit is determined as the state switching timestamp corresponding to the target decision state.

[0127] As can be seen, the state switching method for the unmanned mining truck provided in this embodiment firstly fuses data from multiple sensors (such as GPS and drive-by-wire chassis) to calculate the actual speed and actual acceleration, reducing errors from single-sensor measurements and improving the accuracy of actual speed and actual acceleration estimation. Secondly, a state-holding mechanism is introduced to reduce the instability of driving and braking caused by frequent acceleration and deceleration switching. Furthermore, by introducing a hysteresis band threshold dynamically adjusted based on the current actual vehicle speed, the next driving state of the unmanned mining truck is determined using the hysteresis band threshold, actual acceleration, and target acceleration. This reduces frequent acceleration or deceleration caused by fluctuations in target acceleration near the critical threshold, thereby improving the stability of the unmanned mining truck during operation.

[0128] Based on the above method embodiments, this disclosure also provides a state switching device for an unmanned mining truck, referencing... Figure 3 This is a schematic diagram of the structure of a state switching device for an unmanned mining truck provided in an embodiment of this disclosure. The device includes:

[0129] The acquisition module 301 is used to acquire the driving data of the unmanned mining truck; wherein, the driving data includes the current actual vehicle speed, the target vehicle speed, the actual acceleration, and the target acceleration;

[0130] The first determining module 302 is used to determine a hysteresis band threshold based on the current actual vehicle speed and the target vehicle speed; wherein, the hysteresis band threshold is used to characterize the command holding interval of the unmanned mining truck in the acceleration control stage;

[0131] The second determining module 303 is used to determine the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration and the hysteresis band threshold; wherein the motion state includes an acceleration state or a deceleration state.

[0132] In one optional implementation, the current actual vehicle speed is obtained by filtering the acquired GPS vehicle speed and the drive-by-wire chassis feedback vehicle speed using a preset Kalman filter.

[0133] In one optional embodiment, the apparatus further includes:

[0134] A filtering module is used to filter the actual acceleration using a preset low-pass filter to obtain the filtered acceleration; wherein the filter coefficients of the preset low-pass filter are calculated based on the sampling frequency and a preset cutoff frequency, and the filter coefficients are used to be substituted into the difference equation of the preset low-pass filter to filter the actual acceleration.

[0135] Accordingly, the second determining module includes:

[0136] The first determining submodule is used to determine the motion state of the unmanned mining vehicle based on the filtered acceleration, the target acceleration, and the hysteresis threshold.

[0137] In one optional embodiment, the apparatus further includes:

[0138] The third determining module is used to determine the time difference between the system timestamp of the vehicle control unit and the state switching timestamp corresponding to the current state of the unmanned mining truck, as the holding time of the current state;

[0139] Accordingly, the second determining module includes:

[0140] The second determining submodule is used to determine the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold if the holding time of the current state is determined to be greater than a preset time threshold.

[0141] In one optional implementation, the second determining module includes:

[0142] The third determining submodule is used to determine the ratio between the current actual speed of the unmanned mining truck and the target speed, and to sum the ratio with a preset value to obtain the value to be processed.

[0143] The product operation submodule is used to perform a product operation on the value to be processed and a preset dynamic threshold factor to obtain the hysteresis threshold; wherein, the preset dynamic threshold factor is determined by the actual performance of the unmanned mining vehicle.

[0144] In one optional implementation, the second determining module includes:

[0145] The first state determination submodule is used to determine the motion state of the unmanned mining truck as the first acceleration state if the target acceleration is determined to be positive and the actual acceleration is less than the difference between the target acceleration and the hysteresis band threshold.

[0146] The second state determination submodule is used to determine the motion state of the unmanned mining truck as the first deceleration state if the target acceleration is determined to be positive and the actual acceleration is greater than the sum of the target acceleration and the hysteresis threshold.

[0147] The third state determination submodule is used to determine the motion state of the unmanned mining truck as the second acceleration state if the target acceleration is determined to be negative and the actual acceleration is less than the difference between the target acceleration and the hysteresis band threshold.

[0148] The fourth state determination submodule is used to determine the motion state of the unmanned mining vehicle as the second deceleration state if the target acceleration is determined to be negative and the actual acceleration is greater than the sum of the target acceleration and the hysteresis threshold.

[0149] In the state switching device for the unmanned mining truck provided in this embodiment, the driving data of the unmanned mining truck is first acquired, including the current actual speed, target speed, actual acceleration, and target acceleration. Then, a hysteresis band threshold is determined based on the current actual speed and target speed. The hysteresis band threshold is used to characterize the deviation between the actual acceleration and the target acceleration when the unmanned mining truck switches states. Next, the motion state of the unmanned mining truck is determined based on the actual acceleration, target acceleration, and hysteresis band threshold. The motion state includes an acceleration state or a deceleration state.

[0150] As can be seen, by introducing a hysteresis band threshold that is dynamically adjusted based on the actual vehicle speed, the unmanned mining truck can determine its next driving state by using the hysteresis band threshold, the actual acceleration, and the target acceleration. This can reduce the frequent acceleration or deceleration of the vehicle caused by the target acceleration fluctuating near the critical threshold, thereby improving the stability of the unmanned mining truck during driving.

[0151] In addition to the methods and apparatus described above, this disclosure also provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to implement the state switching method for the unmanned mining truck described in this disclosure.

[0152] This disclosure also provides a computer program product, which includes a computer program / instruction. When the computer program / instruction is executed by a processor, it implements the state switching method for the unmanned mining truck described in this disclosure.

[0153] In addition, this disclosure also provides an electronic device, see [link to relevant documentation]. Figure 4 As shown, it may include:

[0154] The electronic device includes a processor 401, a memory 402, an input device 403, and an output device 404. The number of processors 401 in the electronic device can be one or more. Figure 4 Taking a processor as an example. In some embodiments of this disclosure, the processor 401, memory 402, input device 403, and output device 404 can be connected via a bus or other means, wherein, Figure 4 Taking the example of a connection between China and Israel via a bus.

[0155] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications of the electronic device and the state switching of the unmanned mining truck by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function, etc. In addition, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. The input device 403 can be used to receive input digital or character information, and generate signal inputs related to user settings and function control of the electronic device.

[0156] Specifically in this embodiment, the processor 401 loads the executable files corresponding to the processes of one or more applications into the memory 402 according to the following instructions, and the processor 401 runs the applications stored in the memory 402 to realize the various functions of the above-mentioned electronic device.

[0157] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0158] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for switching the state of an unmanned mining truck, characterized in that, The method includes: Acquire driving data of the unmanned mining truck; wherein, the driving data includes the current actual speed, target speed, actual acceleration, and target acceleration; The hysteresis band threshold is determined based on the current actual vehicle speed and the target vehicle speed; wherein, the hysteresis band threshold is used to characterize the command holding interval of the unmanned mining truck in the acceleration control stage; The motion state of the unmanned mining vehicle is determined based on the actual acceleration, the target acceleration, and the hysteresis band threshold; wherein the motion state includes an acceleration state or a deceleration state.

2. The method according to claim 1, characterized in that, The current actual vehicle speed is obtained by filtering the acquired GPS vehicle speed and the vehicle speed fed back by the drive-by-wire chassis using a preset Kalman filter.

3. The method according to claim 1, characterized in that, Before determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold, the method further includes: The actual acceleration is filtered using a preset low-pass filter to obtain the filtered acceleration; wherein the filter coefficients of the preset low-pass filter are calculated based on the sampling frequency and the preset cutoff frequency, and the filter coefficients are used to filter the actual acceleration by substituting them into the difference equation of the preset low-pass filter. Accordingly, determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold includes: The motion state of the unmanned mining vehicle is determined based on the filtered acceleration, the target acceleration, and the hysteresis threshold.

4. The method according to claim 1, characterized in that, Before determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold, the method further includes: The time difference between the system timestamp of the vehicle control unit and the state transition timestamp corresponding to the current state of the unmanned mining truck is determined as the retention time of the current state; Accordingly, determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold includes: If it is determined that the duration of the current state is greater than a preset time threshold, then the motion state of the unmanned mining vehicle is determined based on the actual acceleration, the target acceleration, and the hysteresis band threshold.

5. The method according to claim 1, characterized in that, The step of determining the hysteresis band threshold based on the current actual vehicle speed and the target vehicle speed includes: Determine the ratio between the current actual speed of the unmanned mining truck and the target speed, and sum the ratio with a preset value to obtain the value to be processed; The product of the value to be processed and the preset dynamic threshold factor is performed to obtain the hysteresis threshold; wherein, the preset dynamic threshold factor is determined by the actual performance of the unmanned mining vehicle.

6. The method according to claim 1, characterized in that, Determining the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold includes: If the target acceleration is determined to be positive and the actual acceleration is less than the difference between the target acceleration and the hysteresis band threshold, then the motion state of the unmanned mining truck is determined to be the first acceleration state. If the target acceleration is determined to be positive and the actual acceleration is greater than the sum of the target acceleration and the hysteresis threshold, then the motion state of the unmanned mining truck is determined to be the first deceleration state. If the target acceleration is determined to be negative, and the actual acceleration is less than the difference between the target acceleration and the hysteresis band threshold, then the motion state of the unmanned mining truck is determined to be the second acceleration state. If the target acceleration is determined to be negative, and the actual acceleration is greater than the sum of the target acceleration and the hysteresis threshold, then the motion state of the unmanned mining vehicle is determined to be the second deceleration state.

7. A state switching device for an unmanned mining truck, characterized in that, The device includes: The acquisition module is used to acquire the driving data of the unmanned mining truck; wherein, the driving data includes the current actual vehicle speed, the target vehicle speed, the actual acceleration, and the target acceleration; The first determining module is used to determine a hysteresis band threshold based on the current actual vehicle speed and the target vehicle speed; wherein, the hysteresis band threshold is used to characterize the command holding interval of the unmanned mining truck in the acceleration control stage; The second determining module is used to determine the motion state of the unmanned mining vehicle based on the actual acceleration, the target acceleration, and the hysteresis band threshold; wherein the motion state includes an acceleration state or a deceleration state.

8. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program / instruction that, when executed by a processor, implements the method as described in any one of claims 1-6.

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