A collision detection and early warning method and system for underground trackless equipment

Abstract

The application relates to the technical field of anti-collision detection, in particular to an anti-collision detection and early warning method and system for underground trackless equipment, which comprises the following steps: acquiring the hinged angle of the underground trackless equipment and the linear speeds of the left and right front wheels in real time; calculating the steering driving pressure difference, combining the hinged angle at each sampling time, and the difference between the theoretical linear speed difference and the actual linear speed difference of the left and right front wheels to construct the wheel speed slip deviation; calculating the echo radial speed of each scanning point; screening all obstacle candidate points based on the correlation degree of the steering driving pressure difference and the echo radial speed, and then obtaining the obstacle distance at the current sampling time; reducing the deceleration by using the wheel speed slip deviation, then calculating the minimum safe braking distance at the current sampling time, and comparing the minimum safe braking distance with the obstacle distance to determine whether to perform obstacle early warning. The above method improves the early warning accuracy of obstacles in narrow spaces and the braking safety on wet and slippery roads.

Description

Technical Field

[0001] This application relates to the field of collision avoidance detection technology, specifically to a collision avoidance detection and early warning method and system for underground trackless equipment. Background Technology

[0002] Transport tunnels in underground metal mines and coal mines are generally characterized by narrow spaces (often less than 1 meter of clearance on one side) and rugged, slippery surfaces (often with accumulated water and mud). Trackless transport equipment such as loaders adopt a centrally articulated structure, using hydraulic cylinders to drive the front and rear frames to generate a relative angle for steering.

[0003] Current collision avoidance technologies primarily rely on vehicle-mounted lidar to measure environmental distances. However, in narrow alleyways, when a vehicle steers or skids due to slippery road surfaces, the radar coordinate system rigidly deflects along with the front frame. This deflection causes the originally stationary rough rock wall to exhibit severe relative motion (i.e., background sway) within the radar's field of view. Because the alleyway wall is extremely close to the vehicle, this relative motion caused by the vehicle's own movement is often misinterpreted by existing detection systems based on Doppler velocity or simple distance thresholds as sudden near-wall obstacles, leading to frequent false alarms.

[0004] Furthermore, existing collision avoidance systems typically predict collision risk based on fixed rigid body dynamics models, assuming a constant road surface adhesion coefficient. However, in actual underground operations, the slipperiness of the road surface varies drastically. When a vehicle skids on a muddy surface, its effective braking capacity is significantly lower than the nominal value. If the system still estimates the braking distance based on a dry road surface model, it will lead to delayed intervention and a collision; conversely, blindly increasing the safety margin may result in frequent unnecessary braking under normal operating conditions, affecting operational efficiency.

[0005] Therefore, the key issue in improving the safety of trackless equipment operation in underground mines is how to effectively distinguish between the moving static background and the independent obstacles, and dynamically adjust the safety boundary according to the real-time road conditions, under conditions where the vehicle's motion state is uncertain (with steering and sideslip) and the tunnel space is limited. Summary of the Invention

[0006] To address the aforementioned technical problems, the purpose of this application is to provide a collision avoidance detection and early warning method and system for underground trackless equipment. The specific technical solution adopted is as follows:

[0007] In a first aspect, embodiments of this application provide a collision avoidance detection and early warning method for underground trackless equipment, the method comprising the following steps:

[0008] The system acquires real-time data on the left and right steering cylinder pressures, hinge angles, left and right front wheel linear velocities, and laser point cloud data of the underground trackless equipment. The laser point cloud data includes the polar coordinates of each scanning point at each sampling time.

[0009] Based on the difference in left and right steering cylinder pressure at each sampling time, a steering drive pressure difference is constructed. Combined with the hinge angle at each sampling time, and the difference between the linear velocity difference between the left and right front wheels under theoretical conditions and the linear velocity difference under actual conditions, a wheel speed slip deviation is constructed to characterize the road surface slippage at each sampling time.

[0010] Based on the polar coordinate angle matching of each scan point at the current sampling time and the previous sampling time, the echo radial velocity of each scan point is calculated; based on the hinge angle and the linear velocities of the left and right front wheels at the current sampling time, it is determined whether the vehicle is stuck at the current sampling time; if stuck, no obstacle warning is issued.

[0011] If there is no jamming, based on the correlation between the steering drive pressure difference and the echo radial velocity of each scan point in the nearest time period of the current sampling time, all obstacle candidate points are screened from all scan points at the current sampling time, and then the obstacle distance at the current sampling time is obtained.

[0012] The nominal maximum deceleration is reduced by the wheel speed slip deviation at the current sampling time, and then the minimum safe braking distance at the current sampling time is calculated. This distance is then compared with the obstacle distance at the current sampling time to determine whether an obstacle warning should be issued and the warning level.

[0013] Preferably, the method for constructing the wheel speed slip deviation is as follows:

[0014] When the absolute value of the steering drive pressure difference at any sampling moment is greater than the preset minimum effective pressure threshold, and the absolute value of the hinge angle is greater than the preset minimum effective angle threshold, the wheel speed slip deviation at that sampling moment is calculated: In the formula, The wheel speed slip deviation at the k-th sampling time; , Let represent the linear velocities of the left front wheel and the right front wheel at the k-th sampling time, respectively; This represents the theoretical difference in left and right wheel speeds at the k-th sampling moment under the no-slip assumption. This represents the steering drive pressure difference at the k-th sampling time. For preset small constants;

[0015] Conversely, the wheel speed slip deviation at that sampling moment is set to 0.

[0016] Preferably, the method for calculating the echo radial velocity at each scanning point is as follows:

[0017] Map the polar coordinates of all scan points at the previous sampling time to the coordinate system at the current sampling time, and obtain the polar coordinates of each scan point at the previous sampling time after rotation compensation.

[0018] Among the scan points after coordinate rotation compensation at the previous sampling time, search for the scan point with the smallest angular deviation from each scan point at the current sampling time, and record it as the matching point of each scan point at the current sampling time.

[0019] If the absolute difference between the angle between any scan point and its matching point at the current sampling time is less than the preset angle matching threshold, the matching is considered successful; otherwise, the scan point at the current sampling time is considered to have no historical corresponding point and is marked as invalid.

[0020] Among the successfully matched scan points, the difference between the distance measurement value of each scan point and its matching point at the current sampling time is calculated, and the ratio of the difference to the sampling period is recorded as the echo radial velocity of each scan point at the current sampling time.

[0021] Preferably, the specific process for determining whether the vehicle is stuck at the current sampling time is as follows:

[0022] Each sampling time and the preset time period preceding it are recorded as the detection window for each sampling time;

[0023] Calculate the average rate of change of the hinge angle and the average linear velocity of the left and right front wheels within the detection window at the current sampling time;

[0024] If the average hinge angle change rate is less than the preset minimum hinge angle change rate, and the average value is less than the preset minimum wheel speed, then the vehicle at the current sampling time is determined to be in a stuck state.

[0025] Conversely, if the vehicle is not stuck at the current sampling time, it is determined that the vehicle is not stuck.

[0026] Preferably, the specific process of selecting all candidate obstacle points from all scan points at the current sampling time is as follows:

[0027] The absolute values ​​of the Pearson correlation coefficients between all steering drive pressure differences within the detection window at the current sampling time and the echo radial velocities at each scan point within the detection window under all hysteresis steps are calculated.

[0028] If the maximum value among all absolute values ​​of any scan point is less than a preset irrelevant threshold, then the scan point is recorded as an obstacle candidate point.

[0029] Preferably, the method for obtaining the obstacle distance at the current sampling time is as follows:

[0030] Cluster the polar coordinates of all obstacle candidate points at the current sampling time, and calculate the lateral width of each cluster.

[0031] If the lateral width of any cluster is within the preset target size range, then the cluster is recorded as an obstacle cluster;

[0032] Calculate the nearest Euclidean distance between all obstacle clusters and the vehicle's outer contour at the current sampling time, and record the minimum value among all the nearest Euclidean distances as the obstacle distance at the current sampling time;

[0033] If there is no obstacle cluster at the current sampling time, then the distance of the obstacle at the current sampling time is set to infinity.

[0034] Preferably, the formula for reducing the nominal maximum deceleration is: In the formula, This represents the attachment-constrained deceleration at the current sampling time. This is the nominal maximum deceleration of the vehicle on a dry concrete road surface; This is the preset maximum reduction factor; This represents the wheel speed slip deviation at the current sampling moment; The normalization function has the following expression: ;in, is the preset saturation slip deviation; min() is the minimum value function.

[0035] Preferably, the formula for calculating the minimum safe braking distance at the current sampling time is: In the formula, This represents the minimum safe braking distance at the current sampling time. This refers to the vehicle's speed at the current sampling moment, obtained in real time. This refers to the inherent response time of the hydraulic braking system. This represents the attachment-constrained deceleration at the current sampling time. Preset a safety redundancy distance.

[0036] Preferably, the specific process for determining whether to issue an obstacle warning and the warning level is as follows:

[0037] Set the preset buffer distance ;

[0038] The minimum safe braking distance and obstacle distance at the current sampling time are denoted as follows: and ;

[0039] when or When the obstacle is not in a certain condition, no obstacle warning will be issued; otherwise, an obstacle warning will be issued.

[0040] When issuing obstacle warnings: If the current time is determined to be a Level 1 warning, then the current time is determined to be a Level 1 warning. If the current time is determined to be a Level II warning, then the current time is determined to be a Level II warning.

[0041] Secondly, embodiments of this application also provide a collision avoidance detection and early warning system for underground trackless equipment, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described collision avoidance detection and early warning methods for underground trackless equipment.

[0042] This application has at least the following beneficial effects:

[0043] This application introduces steering drive pressure and echo radial velocity as reference signals, enabling the differentiation of walls and obstacles from a dynamic causal perspective under conditions where the radar field of view sways significantly due to severe vehicle steering or sideslip. This method no longer relies on simple geometric background modeling, thus exhibiting strong robustness to irregular rock walls and non-rigid vehicle vibrations. It solves the problem of frequent false alarms in narrow curves caused by traditional methods, significantly reducing the false alarm rate in confined spaces.

[0044] By sensing slip characteristics in real time and constructing wheel speed slip deviation, the nominal maximum deceleration can be dynamically corrected, solving the problem of braking distance deviation in fixed models on low-friction surfaces. This not only ensures that the system can intervene in advance to avoid collisions under extreme wet and slippery conditions, but also prevents excessive braking torque on low-friction surfaces from causing wheel lock-up and loss of control, achieving a balance between safety and efficiency and improving braking safety on wet and slippery surfaces. Attached Figure Description

[0045] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 A flowchart illustrating the steps of a collision avoidance detection and early warning method for underground trackless equipment, as provided in one embodiment of this application;

[0047] Figure 2 A flowchart illustrating the acquisition of obstacle distance at the current sampling time, provided as an embodiment of this application. Detailed Implementation

[0048] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a collision avoidance detection and early warning method and system for underground trackless equipment proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0050] The following description, in conjunction with the accompanying drawings, details the specific scheme of the anti-collision detection and early warning method and system for underground trackless equipment provided in this application.

[0051] Please see Figure 1 The diagram illustrates a flowchart of a collision avoidance detection and early warning method for underground trackless equipment according to an embodiment of this application. The method includes the following steps:

[0052] Step 1: Real-time acquisition of the left and right steering cylinder pressures, hinge angles, left and right front wheel linear velocities, and laser point cloud data of the underground trackless equipment; among which, the laser point cloud data includes the polar coordinates of each scanning point at each sampling time.

[0053] When collecting vehicle data and environmental perception data from underground trackless equipment, direct data fusion can lead to timing misalignment because the vehicle control system (such as CAN bus) and the environmental perception system (such as LiDAR) usually operate at different sampling frequencies (in this embodiment, the sampling frequency of CAN bus data is 50Hz and the sampling frequency of LiDAR data is 10Hz).

[0054] To ensure the accuracy of subsequent causal analysis, the following synchronous data acquisition strategy was implemented: First, the sampling time of the LiDAR data was used as the clock reference. Then, various CAN bus data were read in real time through the vehicle's CAN bus interface; the various CAN bus data refer to the left steering cylinder pressure. Right steering cylinder pressure The relative hinge angle between the front frame and the rear frame Left front wheel linear velocity and the linear velocity of the right front wheel Simultaneously, laser point cloud data of the surrounding environment of the underground trackless equipment is acquired in real time using lidar. It should be noted that the laser point cloud data at a single sampling moment includes the point cloud coordinates of several scanning points. The point cloud coordinates are in polar coordinate format and include the distance and angle of each scanning point.

[0055] Next, data downsampling and alignment are performed: for the sampling period corresponding to each sampling time of the lidar. (In this embodiment, it is 100ms) Multiple frames of CAN bus data arriving within a time interval are extracted using the timestamp nearest neighbor matching method, and the CAN bus data at each sampling time is obtained.

[0056] Through the above steps, time-aligned multimodal data was constructed, eliminating the influence of frequency differences between different sensors.

[0057] Step 2: Based on the difference in left and right steering cylinder pressure at each sampling time, a steering drive pressure difference is constructed. Combined with the hinge angle at each sampling time, and the difference between the linear velocity difference between the left and right front wheels under theoretical conditions and the linear velocity difference under actual conditions, a wheel speed slip deviation is constructed to characterize the road surface slippage at each sampling time.

[0058] Furthermore, the pressure differential of the hydraulic steering system is the direct source of the torque driving the vehicle frame to rotate. In order to accurately distinguish the different environmental responses caused by left turns and right turns in subsequent steps, it is necessary to extract the pressure characteristics with directional symbols.

[0059] Specifically, taking the k-th sampling time as an example, the following analysis is performed to calculate the steering drive pressure difference at the k-th sampling time: In the formula, This represents the steering drive pressure difference at the k-th sampling time. This represents the pressure of the left steering cylinder at the k-th sampling time; This represents the right steering cylinder pressure at the k-th sampling time.

[0060] Under this definition, if This represents the driving torque that the vehicle experiences to the left; if This represents the driving torque applied to the vehicle when it rotates to the right. This signed steering drive pressure difference will serve as the active excitation signal in subsequent correlation analysis.

[0061] It should be noted that existing technologies often use the absolute value of the pressure difference to characterize the strength of the steering, but this loses directional information, making it impossible to distinguish the correlation between same-direction and opposite-direction movements. This embodiment intentionally retains the symbol information to match the vector variation characteristics of radar echoes.

[0062] Furthermore, in order to quantify the degree of road slipperiness, this embodiment introduces a pre-gating logic to address the calculation divergence problem that may be caused by the extremely small pressure difference when the vehicle is driving straight or making minor adjustments.

[0063] Specifically, based on the vehicle's Ackerman steering geometry model, the hinge angle at the k-th sampling time is used. Vehicle wheelbase and wheelbase Calculate the theoretical difference in left and right wheel speeds at the k-th sampling time under the no-slip assumption. : In the formula, This represents the theoretical difference in left and right wheel speeds at the k-th sampling moment under the no-slip assumption. The wheelbase of the vehicle; This refers to the vehicle's wheelbase. Let k be the vehicle's center speed at the current time. is the hinge angle at the k-th sampling time; tan() is the tangent function.

[0064] Set the preset minimum effective pressure threshold (In this embodiment, it is set to 2.0 MPa) and a preset minimum effective angle threshold. (In this embodiment, it is set to 2.0 degrees).

[0065] like and If the vehicle is in a significant steering condition at the k-th sampling time, and meets the physical conditions for calculating slip characteristics, then the wheel speed slip deviation at that sampling time is calculated: In the formula, The wheel speed slip deviation at the k-th sampling time; , Let represent the linear velocities of the left front wheel and the right front wheel at the k-th sampling time, respectively; This represents the theoretical difference in left and right wheel speeds at the k-th sampling moment under the no-slip assumption. This represents the steering drive pressure difference at the k-th sampling time. To prevent the denominator from being zero, a preset small constant is used; in this embodiment, it is set to 0.1 MPa. The obtained wheel speed slip deviation reflects the non-geometric motion deviation generated under unit driving torque; the larger the value, the wetter the road surface at the corresponding sampling time.

[0066] Conversely, if the above conditions are not met (such as straight-line driving or fine-tuning), then the working condition at the k-th sampling time is determined to be unsuitable for calculating slip, and the wheel speed slip deviation at the k-th sampling time is directly calculated. Set to 0 to prevent numerical noise interference.

[0067] To support subsequent correlation analysis, each sampling time and the preset time period preceding it are recorded as the detection window for each sampling time. The preset time period must be set to meet the sample size required for correlation calculation; in this embodiment, the preset time period is 2.0 seconds.

[0068] It should be noted that during the initial system startup, if the time interval before each sampling moment is less than 2.0 seconds, the system status is marked as "initializing". During this period, the system only makes a conservative early warning based on the closest distance at the current radar sampling moment, and does not enable subsequent early warning analysis functions to avoid algorithm errors caused by insufficient data length.

[0069] Step 3: Based on the polar coordinate angle matching of each scan point at the current sampling time and the previous sampling time, calculate the echo radial velocity of each scan point; based on the hinge angle and the linear velocities of the left and right front wheels at the current sampling time, determine whether the vehicle is stuck at the current sampling time; if stuck, do not issue an obstacle warning.

[0070] Because the lidar is fixed to the front frame, when the hydraulic system drives the front frame to rotate relative to the rear frame (or relative to the ground coordinate system), the radar coordinate system will deflect accordingly. This rigid rotation causes a drastic change in the distance reading of the originally stationary tunnel wall in the radar polar coordinate system. In order to extract the true radial motion information implied in the echo, it is necessary to first use the vehicle's kinematic parameters to eliminate this apparent displacement introduced by the mechanical structure rotation.

[0071] Specifically, the point cloud data from the previous sampling time is converted from polar coordinates to Cartesian coordinates; then, the hinge angle increment from the previous sampling time to the current sampling time is calculated: ;in, , Let be the hinge angles at the k-th and (k-1)-th sampling times, respectively. Construct a two-dimensional rotation matrix. This allows the Cartesian coordinates of all scan points from the previous sampling time to be mapped to the coordinate system of the current sampling time. ;in, The coordinates of the j-th scan point at the (k-1)-th sampling time are the Cartesian coordinates after rotation compensation. The rectangular coordinates of the j-th scan point at the (k-1)-th sampling time; It is a two-dimensional rotation matrix.

[0072] Furthermore, the rotation-compensated rectangular coordinates of the previous sampling time are converted into polar coordinates to obtain the rotation-compensated polar coordinates of each scan point at the previous sampling time.

[0073] Furthermore, the radial velocity of the environmental point cloud needs to be calculated. However, since the radar scans in a rotating manner, and the polar coordinate angle of the i-th scan point at the previous sampling time may not completely coincide with the polar coordinate angle of the i-th scan point at the current sampling time (i.e., spatial discrepancy exists), directly subtracting scan points with the same index would introduce significant discretization noise. Therefore, this embodiment employs a nearest neighbor matching strategy to obtain matching points for each scan point at the current sampling time from all scan points at the previous sampling time.

[0074] Specifically, for the angle of the i-th scan point at the current sampling time and the corresponding distance measurement value Perform the following operations: Among the scan points after coordinate rotation compensation at the previous sampling time, search for the scan point with the smallest angular deviation from the i-th scan point at the current sampling time, and denot it as the matching point of the i-th scan point at the current sampling time. ; Calculate the absolute difference between the angle between the i-th scan point and its matching point at the current sampling time; if the obtained absolute difference is less than the preset angle matching threshold (set to in this embodiment), then... If the i-th scan point at the current sampling time has no historical corresponding point (it may be a newly entered area of ​​view), then the scan point is considered to be invalid.

[0075] Calculate the echo radial velocity of the i-th scan point at the current sampling time among the successfully matched scan points: In the formula, Let be the echo radial velocity of the i-th scan point at the k-th sampling time; The distance measurement value of the i-th scan point at the k-th sampling time; The distance measurement value of the matching point of the i-th scan point at the k-th sampling time is the distance measurement value of the matching point at the (k-1)-th sampling time. The sampling period.

[0076] income It characterizes the radial approach or departure motion of an object relative to the vehicle frame, as well as the residual motion caused by non-rigid vibrations of the vehicle (such as roll and pitch).

[0077] Furthermore, during underground operations, it is common for vehicle wheels to become stuck in mud or obstructed. In such situations, the driver may drastically operate the steering lever, resulting in a differential steering drive pressure. Violent fluctuations, but the vehicle body did not actually move (i.e., the hinge angle). (The position remains unchanged, and the wheel speed is zero). If subsequent correlation analysis is forcibly performed at this point, the system will detect an excitation (large steering drive pressure difference) but no response, thus incorrectly identifying the static wall as an obstacle and triggering an alarm, causing the vehicle to be completely unable to get out of trouble.

[0078] To avoid this adverse effect, the system introduces motion validity gating before proceeding with correlation analysis:

[0079] Calculate the average hinge angle change rate within the detection window at the current sampling time. and average wheel speed Among them, average wheel speed This refers to the average linear velocity of the left and right front wheels within the detection window at the current sampling moment. A preset minimum hinge angle change rate is set. (In this embodiment) Set as ) and preset minimum wheel speed (In this embodiment) Set as ).

[0080] like and If the vehicle is stuck at the current sampling time, it is determined that the vehicle is in a stuck state. At this time, even if The system is very large, and it also forcibly skips the subsequent correlation calculation steps, directly determining that the environment at the current sampling time is a static background. At this time, the state is a safe state, and no obstacle warning is given.

[0081] Conversely, if the vehicle is not stuck at the current sampling time and there is actual physical movement, then the subsequent analysis continues.

[0082] Through this gating logic, the system ensures that collision avoidance detection only takes effect when the vehicle has actual movement capability, significantly improving robustness in complex trapped conditions.

[0083] Step 4: If there is no jamming, based on the correlation between the steering drive pressure difference and the echo radial velocity of each scan point in the nearest time period of the current sampling time, all obstacle candidate points are selected from all scan points at the current sampling time, and then the obstacle distance at the current sampling time is obtained.

[0084] Due to the impact of the hydraulic system, tire deformation, and uneven road surfaces, the vehicle body will experience complex non-rigid vibrations (such as roll and pitch). These vibrations are physically generated by the hydraulic drive torque (i.e., the steering drive pressure difference). Therefore, the radial velocity of the radar echo from a normal tunnel wall should exhibit a strong time correlation with the steering drive pressure difference. Conversely, the movement of an independent obstacle is not controlled by the vehicle's hydraulic system and therefore does not exhibit this correlation.

[0085] Based on the above characteristics, the steering drive pressure difference at all sampling times within the detection window at the current sampling time is arranged in chronological order to obtain the steering drive pressure difference sequence at the current sampling time. A preset lag interval is set. ,in, In this embodiment The value is 20, and the implementer can choose this value based on the time lag range between the echo radial velocity and the steering drive pressure difference; the lag step number at the current sampling time is... The echo radial velocity of the i-th scan point within the detection window at all sampling times is arranged in chronological order, denoted as where is the radial velocity of the i-th scan point at the current sampling time with a hysteresis step of . The echo radial velocity sequence at time n. It should be noted that if the detection window at the current sampling time spans from the nth to the (n+h)th sampling time, then the lag step number at the current sampling time is... The detection window time interval is the nth-th up to the n+h-th Each sampling time.

[0086] Next, iterating through all possible lag steps, the absolute value of the Pearson correlation coefficient between the steering drive pressure difference sequence and the echo radial velocity sequence at the i-th scan point at each lag step is calculated, and the maximum value among all absolute values ​​is recorded as the following coefficient of the i-th scan point at the current sampling time. In calculating the Pearson correlation coefficient, if the denominator is 0, then the denominator is set to a preset minimum constant. In this embodiment, the preset minimum constant is 0.001.

[0087] It should be noted that the steering drive pressure difference and the echo radial velocity are directly used for matching here because in the non-rigid vibration model, the excitation torque and response speed are usually expressed as signals of the same frequency.

[0088] Furthermore, based on the calculated following coefficients, attribute discrimination is performed on each scan point:

[0089] Set a preset irrelevant threshold (In this embodiment, it is set to 0.4). If This indicates that the radial motion of the i-th scan point at the current sampling time is highly correlated with the vehicle's hydraulic steering action, and the scan point is determined to be a normal background motion (such as a tunnel wall, air duct, etc.). If the movement of the scanning point is independent of the vehicle's hydraulic system, then the scanning point is determined to be a candidate obstacle point.

[0090] Similarly, obtain all candidate obstacle points at the current sampling time.

[0091] Furthermore, in order to eliminate single-point false alarms caused by radar random noise and obtain the true physical location of obstacles, it is necessary to perform spatial clustering on the retained independent target candidate points.

[0092] Collect the coordinate set of all obstacle candidate points at the current sampling time, and use the coordinate set as input to a density-based clustering algorithm (such as DBSCAN). Set the clustering neighborhood radius (0.5m in this embodiment) and the minimum number of points. (In this embodiment, we take 3), and output several clusters. Calculate the horizontal width of each cluster. If the horizontal width of any cluster is within the preset target size range (its specific value needs to cover the typical width of obstacles such as personnel and mining equipment, which is set to 0.2m-2.5m in this embodiment), then the cluster is recorded as an obstacle cluster, indicating that the cluster is an obstacle.

[0093] Furthermore, the nearest Euclidean distances from all obstacle clusters to the vehicle's outer contour at the current sampling time are calculated, and the minimum value among all nearest Euclidean distances is recorded as the obstacle distance at the current sampling time. This information is then passed to the subsequent control module. If there are no obstacle clusters at the current sampling time, then it is marked. In this embodiment, the flowchart for obtaining the obstacle distance at the current sampling time is as follows: Figure 2 As shown.

[0094] Step 5: Use the wheel speed slip deviation at the current sampling time to reduce the nominal maximum deceleration, then calculate the minimum safe braking distance at the current sampling time, and compare it with the obstacle distance at the current sampling time to determine whether to issue an obstacle warning and the warning level.

[0095] On wet roads, the coefficient of friction between the vehicle's tires and the road surface decreases, resulting in a significantly lower maximum usable braking deceleration than the nominal value on dry roads. To prevent collisions caused by insufficient braking distance estimation, the system needs to correct for the nominal deceleration.

[0096] Since a larger wheel speed slip deviation indicates a more slippery road surface, the reduction in deceleration will be greater. Therefore, as a preferred implementation, the nominal maximum deceleration is reduced using the wheel speed slip deviation at the current sampling time.

[0097] In this embodiment, the attachment-limited deceleration at the current sampling time is denoted as... Its specific expression is: In the formula, This represents the attachment-constrained deceleration at the current sampling time. The nominal maximum deceleration of the vehicle on a dry concrete road surface is taken as 3.5 m / s² in this embodiment; The maximum reduction factor is set to 0.6 in this embodiment, which means that the braking capacity will be reduced by up to 60% under extremely slippery road conditions. This represents the wheel speed slip deviation at the current sampling moment; The normalization function has the following expression: ;in, To preset the saturation slip deviation, it is set to 5 in this embodiment. When the measured wheel speed slip deviation When this value is reached, it indicates that the road surface has reached the worst adhesion state; min() is the function to take the minimum value.

[0098] income This represents the maximum deceleration of the vehicle at the current sampling time due to the influence of slippery road surface.

[0099] Furthermore, the vehicle braking process includes a control system response phase and a physical deceleration phase. For underground trackless equipment employing fully hydraulic braking, the hydraulic pressure build-up delay is not negligible.

[0100] Therefore, based on kinematic principles, the minimum safe braking distance at the current sampling moment is calculated: In the formula, This represents the minimum safe braking distance at the current sampling time. This refers to the vehicle's speed at the current sampling moment, obtained in real time. The inherent response time of the hydraulic braking system is 0.4s, which covers the total time for the solenoid valve to actuate, the pipeline to fill with oil, and the brake to close. This represents the attachment-constrained deceleration at the current sampling time. To pre-set a safety redundancy distance, 0.5m is used in this embodiment to compensate for sensor measurement errors and the discreteness of the actuator.

[0101] income It represents the physical limit distance that a vehicle can avoid a collision under the current vehicle speed and road conditions at the current sampling time.

[0102] Finally, the distance to the obstacle at the current moment. Minimum safe braking distance at the current moment The comparison is performed, and then a tiered early warning system is implemented.

[0103] Specifically, set the preset buffer distance. In this embodiment, it is set to 1.5 times the vehicle width to provide the driver with a window for manual reaction.

[0104] when or If the system determines that the current moment is safe, it will remain in silent monitoring mode, without issuing obstacle warnings or interfering with the driver's normal operation; otherwise, it will issue obstacle warnings.

[0105] When issuing obstacle warnings: If the current time is determined to be a Level 1 warning, the audible and visual alarm in the driver's cab will be triggered (e.g., intermittent buzzer sound and flashing yellow warning light) to alert the driver to obstacles ahead and to release the accelerator; when If the system detects a collision, it determines that the current moment is a Level 2 warning, which indicates an irreversible risk of collision. In this case, the system should immediately execute the following instructions through the vehicle control unit (VCU): forcibly cut off the pilot oil circuit of the travel system to return the transmission to neutral; trigger the working brake circuit to apply emergency braking pressure; and maintain the braking state until the vehicle comes to a complete stop.

[0106] Through the above method, the system achieves a closed loop of perception and control. In particular, it utilizes dynamic correction based on slip characteristics. This mechanism ensures the minimum safe braking distance. It can automatically expand and contract according to the slipperiness of the road surface: the slipperier the road surface, the more it expands and contracts. The smaller, The larger the valve, the earlier intervention can be implemented, thus effectively avoiding safety accidents caused by the inability to brake in time.

[0107] Based on the same inventive concept as the above method, this application embodiment also provides a collision avoidance detection and early warning system for underground trackless equipment, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the above-mentioned collision avoidance detection and early warning method for underground trackless equipment.

[0108] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0109] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0110] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A collision detection and early warning method for underground trackless equipment, characterized in that, The method includes the following steps: The system acquires real-time data on the left and right steering cylinder pressures, hinge angles, left and right front wheel linear velocities, and laser point cloud data of the underground trackless equipment. The laser point cloud data includes the polar coordinates of each scanning point at each sampling time. Based on the difference in left and right steering cylinder pressure at each sampling time, a steering drive pressure difference is constructed. Combined with the hinge angle at each sampling time, and the difference between the linear velocity difference between the left and right front wheels under theoretical conditions and the linear velocity difference under actual conditions, a wheel speed slip deviation is constructed to characterize the road surface slippage at each sampling time. Based on the polar coordinate angle matching of each scan point at the current sampling time and the previous sampling time, the echo radial velocity of each scan point is calculated; based on the hinge angle and the linear velocities of the left and right front wheels at the current sampling time, it is determined whether the vehicle is stuck at the current sampling time; if stuck, no obstacle warning is issued. If there is no jamming, based on the correlation between the steering drive pressure difference and the echo radial velocity of each scan point in the nearest time period of the current sampling time, all obstacle candidate points are screened from all scan points at the current sampling time, and then the obstacle distance at the current sampling time is obtained. The nominal maximum deceleration is reduced by the wheel speed slip deviation at the current sampling time, and then the minimum safe braking distance at the current sampling time is calculated. This distance is then compared with the obstacle distance at the current sampling time to determine whether an obstacle warning should be issued and the warning level.

2. The anti-collision detection and warning method for underground trackless equipment according to claim 1, characterized in that, The method for constructing the wheel speed slip deviation is as follows: When the absolute value of the steering drive pressure difference at any sampling moment is greater than the preset minimum effective pressure threshold, and the absolute value of the hinge angle is greater than the preset minimum effective angle threshold, the wheel speed slip deviation at that sampling moment is calculated: In the formula, The wheel speed slip deviation at the k-th sampling time; , Let represent the linear velocities of the left front wheel and the right front wheel at the k-th sampling time, respectively; This represents the theoretical difference in left and right wheel speeds at the k-th sampling moment under the no-slip assumption. This represents the steering drive pressure difference at the k-th sampling time. For preset small constants; Conversely, the wheel speed slip deviation at that sampling moment is set to 0.

3. The anti-collision detection and warning method for underground trackless equipment according to claim 1, wherein, The method for calculating the radial velocity of the echo at each scanning point is as follows: Map the polar coordinates of all scan points at the previous sampling time to the coordinate system at the current sampling time, and obtain the polar coordinates of each scan point at the previous sampling time after rotation compensation. Among the scan points after coordinate rotation compensation at the previous sampling time, search for the scan point with the smallest angular deviation from each scan point at the current sampling time, and record it as the matching point of each scan point at the current sampling time. If the absolute difference between the angle between any scan point and its matching point at the current sampling time is less than the preset angle matching threshold, the matching is considered successful; otherwise, the scan point at the current sampling time is considered to have no historical corresponding point and is marked as invalid. Among the successfully matched scan points, the difference between the distance measurement value of each scan point and its matching point at the current sampling time is calculated, and the ratio of the difference to the sampling period is recorded as the echo radial velocity of each scan point at the current sampling time.

4. The collision avoidance detection and early warning method for underground trackless equipment as described in claim 1, characterized in that, The specific process for determining whether a vehicle is stuck at the current sampling time is as follows: Each sampling time and the preset time period preceding it are recorded as the detection window for each sampling time; Calculate the average rate of change of the hinge angle and the average linear velocity of the left and right front wheels within the detection window at the current sampling time; If the average hinge angle change rate is less than the preset minimum hinge angle change rate, and the average value is less than the preset minimum wheel speed, then the vehicle at the current sampling time is determined to be in a stuck state. Conversely, if the vehicle is not stuck at the current sampling time, it is determined that the vehicle is not stuck.

5. The anti-collision detection and warning method of underground trackless equipment according to claim 4, characterized in that, The specific process of filtering out all candidate obstacle points from all scan points at the current sampling time is as follows: The absolute values ​​of the Pearson correlation coefficients between all steering drive pressure differences within the detection window at the current sampling time and the echo radial velocities at each scan point within the detection window under all hysteresis steps are calculated. If the maximum value among all absolute values ​​of any scan point is less than a preset irrelevant threshold, then the scan point is recorded as an obstacle candidate point.

6. The anti-collision detection and warning method for underground trackless equipment according to claim 1, wherein, The method for obtaining the obstacle distance at the current sampling time is as follows: Cluster the polar coordinates of all obstacle candidate points at the current sampling time, and calculate the lateral width of each cluster. If the lateral width of any cluster is within the preset target size range, then the cluster is recorded as an obstacle cluster; Calculate the nearest Euclidean distance between all obstacle clusters and the vehicle's outer contour at the current sampling time, and record the minimum value among all the nearest Euclidean distances as the obstacle distance at the current sampling time; If there is no obstacle cluster at the current sampling time, then the distance of the obstacle at the current sampling time is set to infinity.

7. The anti-collision detection and warning method for underground trackless equipment according to claim 1, wherein, The formula for reducing the nominal maximum deceleration is as follows: In the formula, This represents the attachment-constrained deceleration at the current sampling time. This is the nominal maximum deceleration of the vehicle on a dry concrete road surface; The preset maximum reduction factor; This represents the wheel speed slip deviation at the current sampling moment; The normalization function has the following expression: ;in, is the preset saturation slip deviation; min() is the minimum value function.

8. The anti-collision detection and warning method of underground trackless equipment according to claim 7, characterized in that, The formula for calculating the minimum safe braking distance at the current sampling time is: In the formula, This represents the minimum safe braking distance at the current sampling time. This refers to the vehicle's speed at the current sampling moment, obtained in real time. This refers to the inherent response time of the hydraulic braking system. This represents the attachment-constrained deceleration at the current sampling time. Preset a safety redundancy distance.

9. The anti-collision detection and early warning method for underground trackless equipment as described in claim 1, characterized in that, The specific process for determining whether to issue an obstacle warning and the warning level is as follows: Setting a preset buffer distance ; Let the minimum safe braking distance and the obstacle distance at the current sampling time be denoted as and respectively. When or no obstacle warning is performed; on the contrary; Provide obstacle warnings; When the obstacle early warning is performed: when , it is determined that the current time is a first level early warning; when , it is determined that the current time is a second level early warning.

10. A collision avoidance detection and early warning system for underground trackless equipment, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the anti-collision detection and early warning method for underground trackless equipment as described in any one of claims 1-9.

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