Collision detection methods, devices, media and equipment for multi-axle all-wheel steering vehicles

Abstract

This application provides a collision detection method, apparatus, medium, and device for a multi-axle all-wheel steering vehicle. The method includes: acquiring the current steering mode of the target vehicle and the path points to be traveled in the vehicle's body coordinate system; calculating predicted trajectory points for the front axle center, vehicle center, and rear axle center of the target vehicle based on the steering mode and the path points to be traveled; calculating curvature based on the predicted trajectory point of the vehicle center and calculating cumulative distance based on the coordinate differences between the path points to be traveled; and generating a driving trajectory based on the curvature, cumulative distance, and the predicted trajectory points of the front axle center, vehicle center, and rear axle center for collision detection. The technical solution of this application embodiment can ensure a high degree of matching between the predicted driving trajectory and the actual driving trajectory of the vehicle, improving the accuracy of the vehicle's collision detection results.

Description

Technical Field

[0001] This application relates to a collision detection method, apparatus, medium, and equipment for a multi-axle all-wheel steering vehicle. Background Technology

[0002] With the upgrading of port automation, Intelligent Guided Vehicles (IGVs) are widely used due to their multi-mode steering capabilities (such as front-wheel steering, all-wheel steering, and diagonal steering). However, current IGV collision detection algorithms are mainly based on the vehicle's centerline or front axle path. When faced with complex steering patterns, they may miss detections or trigger false alarms. Summary of the Invention

[0003] The embodiments of this application provide a collision detection method, apparatus, medium, and equipment for multi-axle all-wheel steering vehicles, which can at least to a certain extent ensure the accuracy of collision detection results and reduce the occurrence of missed detections and false triggering events.

[0004] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0005] According to one aspect of the embodiments of this application, a collision detection method for a multi-axle all-wheel steering vehicle is provided, the multi-axle all-wheel steering vehicle having a front axle, a middle axle and a rear axle, wherein the center point of the vehicle's middle axle is the vehicle center;

[0006] The method includes:

[0007] Obtain the current steering mode of the target vehicle and the path points to be traveled in the vehicle's body coordinate system;

[0008] Based on the steering mode and the path to be driven, the predicted trajectory points of the front axle center, vehicle center, and rear axle center of the target vehicle are calculated respectively.

[0009] The curvature is calculated based on the predicted trajectory point at the center of the vehicle, and the cumulative distance is calculated based on the coordinate difference between the points on the path to be traveled.

[0010] A driving trajectory is generated based on the curvature, the cumulative distance, and the predicted trajectory points of the front axle center, the vehicle center, and the rear axle center for collision detection.

[0011] According to one aspect of the embodiments of this application, a collision detection device for a multi-axle all-wheel steering vehicle is provided. The multi-axle all-wheel steering vehicle has a front axle, a middle axle, and a rear axle, and the center point of the vehicle's middle axle is the vehicle center.

[0012] The device includes:

[0013] The acquisition module is used to acquire the current steering mode of the target vehicle and the driving path points in the vehicle's body coordinate system.

[0014] The first calculation module is used to calculate the predicted trajectory points of the front axle center, vehicle center, and rear axle center of the target vehicle according to the steering mode and the path point to be driven.

[0015] The second calculation module is used to calculate the curvature based on the predicted trajectory point at the center of the vehicle, and to calculate the cumulative distance based on the coordinate difference between the points on the path to be traveled.

[0016] The processing module is used to generate a driving trajectory based on the curvature, the cumulative distance, and the predicted trajectory points of the front axle center, the vehicle center, and the rear axle center for collision detection.

[0017] According to one aspect of the embodiments of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the collision detection method for a multi-axle all-wheel steering vehicle as described in the above embodiments.

[0018] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the collision detection method for a multi-axle all-wheel steering vehicle as described in the above embodiments.

[0019] According to one aspect of the embodiments of this application, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the collision detection method for a multi-axle all-wheel steering vehicle provided in the above embodiments.

[0020] In some embodiments of this application, the technical solutions involve obtaining the current steering mode of the target vehicle and the path points to be traveled in the vehicle's body coordinate system. Then, based on the steering mode and the path points, predicted trajectory points for the front axle center, vehicle center, and rear axle center of the target vehicle are calculated. Next, the curvature is calculated based on the predicted trajectory point of the vehicle center, and the cumulative distance is calculated based on the coordinate differences between the path points. Finally, a driving trajectory is generated based on the curvature, cumulative distance, and the predicted trajectory points for the front axle center, vehicle center, and rear axle center for collision detection. This ensures a high degree of match between the predicted driving trajectory and the vehicle's actual driving trajectory, improving the accuracy of the vehicle's collision detection results.

[0021] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0022] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0023] Figure 1 A schematic diagram of a multi-axle all-wheel steering vehicle to which embodiments of this application can be applied is shown.

[0024] Figure 2 It shows Figure 1 The diagram shows the steering modes of a multi-axle all-wheel steering vehicle.

[0025] Figure 3 A schematic flowchart of a collision detection method for a multi-axle all-wheel steering vehicle according to an embodiment of this application is shown.

[0026] Figure 4 A block diagram of a collision detection device for a multi-axle all-wheel steering vehicle according to an embodiment of this application is shown.

[0027] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0028] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0029] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0030] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0031] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0032] Figure 1 A schematic diagram of a multi-axle all-wheel steering vehicle to which embodiments of this application can be applied is shown. Figure 1 As shown, the vehicle may have three axles, located at the front, middle, and rear of the vehicle, respectively, namely the front axle, middle axle, and rear axle. It should be understood that the center point of the vehicle's middle axle is the vehicle's center.

[0033] Under different application scenarios and operating conditions, the vehicle can select an appropriate steering mode to improve steering effect and efficiency. It should be noted that in other embodiments, the multi-axle all-wheel steering vehicle may have other numbers of axles, and this application does not impose any special limitations on this. In one example, the multi-axle all-wheel steering vehicle may be an Intelligent Guided Vehicle (IGV), which may also be other mobile handling robots or autonomous vehicles, and there are no special limitations on this.

[0034] Specifically, such as Figure 2 As shown, Figure 1 The multi-axle all-wheel steering vehicle shown can have the following steering modes:

[0035] Front-wheel steering mode: In this mode, the front and center axles of the vehicle steer in coordination, while the rear axle remains fixed.

[0036] Rear-wheel steering mode: In this mode, the vehicle's center and rear axles steer in coordination, while the front axle remains fixed.

[0037] Diagonal driving mode: This means that the three axles of the vehicle turn in the same direction and angle.

[0038] Full eight mode: The front and rear axles of the vehicle steer in opposite directions, while the center axle remains fixed.

[0039] It should be understood that flexibly selecting the appropriate steering mode for the current working conditions while driving can enable the vehicle to follow the route better, ensuring the efficiency and safety of cargo transportation.

[0040] Figure 3 A schematic flowchart of a collision detection method for a multi-axle all-wheel steering vehicle according to an embodiment of this application is shown. Figure 3 As shown, the method includes at least steps S310 to S340, which are described in detail below.

[0041] In step S310, the current steering mode of the target vehicle and the driving path points in the vehicle body coordinate system of the target vehicle are obtained.

[0042] Steering mode refers to the steering method used by a vehicle during driving. Different steering modes result in different wheel steering angles and directions, thus affecting the vehicle's trajectory. Common steering modes include front-wheel steering, rear-wheel steering, all-wheel steering, and diagonal steering.

[0043] The vehicle coordinate system can be a coordinate system established with the center point of the vehicle's central axis (i.e., the vehicle center) as the origin, the vehicle's direction of travel as the positive x-axis, and the direction perpendicular to the vehicle's direction of travel and to the left as the positive y-axis. It is used to describe the positional relationship of various points on the vehicle and points on the path to be traveled relative to the vehicle center.

[0044] The path points to be traveled can refer to a series of points that the vehicle needs to pass through sequentially according to the planned route during its journey. These points contain information such as the vehicle's position (x, y coordinates) and the angle of travel direction (theta) during its journey.

[0045] In this embodiment, the steering status of the target vehicle can be monitored in real time through the vehicle's control system or sensors to determine the current steering mode. For example, the current steering operation command can be obtained through the vehicle's steering control module to determine the current steering mode. Alternatively, the steering angle of the wheels can be directly measured using steering angle sensors mounted on the wheels to determine whether the vehicle is in front-wheel steering, rear-wheel steering, all-wheel steering, or diagonal steering mode.

[0046] The path points to be traveled are usually provided by the vehicle's path planning system. These path points are planned based on factors such as the vehicle's starting position, target position, and driving environment. These path points can be transformed from the world coordinate system to the target vehicle's body coordinate system, that is, with the vehicle's center as the origin, the coordinates of the path points are transformed accordingly based on the vehicle's current driving direction and position.

[0047] In step S320, based on the steering mode and the path to be driven, the predicted trajectory points of the front axle center, vehicle center, and rear axle center of the target vehicle are calculated respectively.

[0048] The predicted trajectory points are calculated using specific algorithms and models based on the vehicle's steering pattern and the path to be traveled, representing the possible coordinate positions that the vehicle's axle center points (front axle center, vehicle center, and rear axle center) may reach during future driving. They reflect the vehicle's dynamic path information during travel and are a crucial basis for collision detection.

[0049] In one embodiment of this application, step S320 includes:

[0050] Traverse the points of the path to be driven from front to back, and for each point of the path to be driven, determine the first horizontal coordinate increment and the first vertical coordinate increment of the current point of the path to be driven relative to the previous point of the path to be driven.

[0051] When the steering mode is full eight mode, the second horizontal coordinate increment and the second vertical coordinate increment of the vehicle center relative to its previous predicted trajectory point are determined based on the first horizontal coordinate increment and the first vertical coordinate increment.

[0052] Based on the second horizontal coordinate increment, the second vertical coordinate increment, and the coordinate information of the previous predicted trajectory point of the vehicle center, determine the coordinate information of the current predicted trajectory point of the vehicle center;

[0053] Based on the coordinate information of the current predicted trajectory point of the vehicle center, determine the coordinate information of the current predicted trajectory points of the front axle center and the rear axle center of the target vehicle;

[0054] When the steering mode is any mode other than the full eight mode, the third horizontal coordinate increment and the third vertical coordinate increment of the rear axle center relative to its previous predicted trajectory point are determined based on the first horizontal coordinate increment and the first vertical coordinate increment.

[0055] Based on the third horizontal coordinate increment, the third vertical coordinate increment, and the coordinate information of the previous predicted trajectory point at the rear axle center, determine the coordinate information of the current predicted trajectory point at the rear axle center;

[0056] Based on the coordinate information of the current predicted trajectory point of the rear axle center, the coordinate information of the current predicted trajectory points of the vehicle center and front axle center of the target vehicle are determined.

[0057] The horizontal coordinate increment refers to the difference in coordinates between two adjacent path points along the x-axis in the vehicle coordinate system. In other words, it's the difference between the x-coordinate of the current path point and the x-coordinate of the previous path point, reflecting the change in the vehicle's movement along the x-axis.

[0058] The y-coordinate increment refers to the difference in coordinates between two adjacent path points along the y-axis in the vehicle coordinate system. In other words, it's the difference between the y-coordinate of the current path point and the y-coordinate of the previous path point, reflecting the change in the vehicle's movement along the y-axis.

[0059] In this embodiment, each path point is processed sequentially, starting from the first path point to be driven. For each current path point to be driven, the first horizontal coordinate increment and the first vertical coordinate increment between it and the previous path point to be driven are calculated.

[0060] When the vehicle's steering mode is full eight mode, the calculated first horizontal coordinate increment and first vertical coordinate increment are used, combined with the set offset (used to calculate the increment of the vehicle center trajectory point coordinates), to calculate the second horizontal coordinate increment and second vertical coordinate increment of the vehicle center relative to its previous predicted trajectory point.

[0061] Then, based on the second horizontal coordinate increment, the second vertical coordinate increment, and the coordinate information of the previous predicted trajectory point of the vehicle center, the coordinate information of the current predicted trajectory point of the vehicle center is determined. Next, based on the coordinate information of the current predicted trajectory point of the vehicle center, the coordinate information of the current predicted trajectory points of the front axle center and the rear axle center of the target vehicle is determined.

[0062] In one embodiment, determining the coordinate information of the current predicted trajectory points of the front axle center and rear axle center of the target vehicle based on the coordinate information of the current predicted trajectory point of the vehicle center includes:

[0063] Based on the coordinate information of the current predicted trajectory point of the vehicle center and the coordinate information of the path point to be traveled, the orientation information of the current predicted trajectory point of the vehicle center is determined;

[0064] Based on the coordinates and orientation of the current predicted trajectory point of the vehicle center, the coordinates of the current predicted trajectory points of the front axle center and rear axle center of the target vehicle are determined.

[0065] In this embodiment, based on the coordinate information of the current predicted trajectory point of the vehicle center and the coordinate information of the path point to be traveled, the orientation information of the vehicle center, that is, the driving direction of the vehicle center at the current predicted trajectory point, can be calculated using trigonometric functions.

[0066] Given the coordinates and orientation of the current predicted trajectory point at the vehicle's center, as well as the pre-set distance from the front axle center to the vehicle's center, the coordinates of the current predicted trajectory point at the front axle center of the target vehicle can be determined based on geometric relationships. Similarly, the coordinates of the current predicted trajectory point at the rear axle center of the target vehicle can be determined.

[0067] Next, when the vehicle's current steering mode is any mode other than the full eight-axis mode, the third horizontal coordinate increment and the third vertical coordinate increment of the rear axle center relative to its previous predicted trajectory point are calculated based on the first horizontal coordinate increment and the first vertical coordinate increment, combined with the preset offset.

[0068] Then, combining the third horizontal coordinate increment, the third vertical coordinate increment, and the coordinate information of the previous predicted trajectory point at the rear axle center, the coordinate information of the current predicted trajectory point at the rear axle center is determined. As mentioned before, based on the coordinate information of the current predicted trajectory point at the rear axle center, the coordinate information of the current predicted trajectory points at the vehicle center and the front axle center is determined.

[0069] In one embodiment, determining the coordinate information of the vehicle center and the front axle center of the target vehicle based on the coordinate information of the current predicted trajectory point of the rear axle center includes:

[0070] Based on the coordinate information of the current predicted trajectory point of the rear axle center and the coordinate information of the point on the path to be traveled, the orientation information of the current predicted trajectory point of the rear axle center is determined;

[0071] Based on the coordinates and orientation of the current predicted trajectory point of the rear axle center, the coordinates of the current predicted trajectory points of the vehicle center and front axle center of the target vehicle are determined.

[0072] In this embodiment, the orientation information of the rear axle center is calculated using trigonometric functions based on the coordinates of the currently predicted trajectory point of the rear axle center and the coordinates of the point on the path to be traveled. That is, the angle between the vehicle's travel direction at the currently predicted trajectory point of the rear axle center and the positive x-axis direction of the vehicle coordinate system.

[0073] Next, given the coordinates and orientation of the currently predicted trajectory point at the rear axle center, as well as the pre-set distance from the vehicle center to the rear axle center, the coordinates of the currently predicted trajectory point at the vehicle center are determined based on geometric relationships. Similarly, the coordinates of the currently predicted trajectory point at the front axle center can be determined.

[0074] Please continue to refer to this. Figure 3 In step S330, the curvature is calculated based on the predicted trajectory point of the vehicle center, and the cumulative distance is calculated based on the coordinate difference between the points on the path to be traveled.

[0075] Curvature can be a physical quantity that measures the degree of curvature of a vehicle's trajectory. It should be understood that the greater the curvature, the greater the curvature of the trajectory and the greater the degree of steering of the vehicle.

[0076] The cumulative distance can be the distance traveled from the first traversed path point to the current path point being predicted.

[0077] In one embodiment, calculating the curvature based on the predicted trajectory point at the center of the vehicle includes:

[0078] When the sequence number of the current trajectory point to be driven is less than 2, the current curvature value is determined to be 0;

[0079] When the sequence number of the current trajectory point to be driven is greater than or equal to 2, the current curvature value is calculated based on the coordinate information of the current predicted trajectory point of the vehicle center and the coordinate information of the two previous predicted trajectory points.

[0080] In this embodiment, when calculating the curvature of the vehicle's trajectory, if the index of the current trajectory point to be driven is less than 2 (i.e., the index is 0 or 1), the curvature value cannot be accurately calculated due to the insufficient number of usable trajectory points. In this case, the current curvature value is directly determined as 0.

[0081] When the sequence number of the current trajectory point to be driven is greater than or equal to 2, it indicates that there is enough trajectory point information (the current point and the two preceding points) for curvature calculation. Specifically, the coordinate information of the current predicted trajectory point at the vehicle center and the coordinate information of the two preceding predicted trajectory points are obtained. The coordinate difference between adjacent trajectory points is calculated. Based on the coordinate difference, the change in the tangent slope of the middle predicted trajectory point (i.e., the predicted trajectory point preceding the current predicted trajectory point) among the three adjacent predicted trajectory points is calculated. Then, the curvature value corresponding to the current predicted trajectory point is calculated based on the curvature formula.

[0082] In one embodiment, calculating the cumulative distance based on the coordinate differences between the points on the path to be traveled includes:

[0083] The single-step distance is determined based on the coordinates of the current path point to be traveled and the previous path point to be traveled.

[0084] The single-step distance is added to the cumulative distance corresponding to the previous path point to be traveled to determine the cumulative distance corresponding to the current path point to be traveled.

[0085] The single-step distance can refer to the straight-line distance between a vehicle and the next path point, which is used to measure the displacement length of the vehicle between adjacent path points.

[0086] Cumulative distance refers to the total distance traveled by the vehicle along the driving path, starting from the initial point on the path and passing through each subsequent point. It is obtained by summing up the distances of each individual step.

[0087] In this embodiment, the straight-line distance between two points can be determined based on the coordinates of the current point to be traveled and the coordinates of the previous point to be traveled. Then, the calculated single-step distance is added to the cumulative distance corresponding to the previous point to be traveled to obtain the cumulative distance corresponding to the current point to be traveled.

[0088] Please continue to refer to this. Figure 3 In step S340, a driving trajectory is generated based on the curvature, the cumulative distance, and the predicted trajectory points of the front axle center, the vehicle center, and the rear axle center for collision detection.

[0089] In this embodiment, the coordinates, curvature, and cumulative distance of predicted trajectory points at the front axle center, vehicle center, and rear axle center can be collected. The predicted trajectory points provide the future positions of key vehicle components, the curvature describes the degree of curvature of the driving trajectory, and the cumulative distance records the total mileage traveled along the path. Then, using the collected data, the vehicle's driving trajectory is generated according to a specific algorithm and rules. This driving trajectory can be a continuous curve that accurately describes the vehicle's driving path. When generating the trajectory, it is necessary to ensure the smoothness and continuity of the curve to conform to the actual driving characteristics of the vehicle.

[0090] The generated driving trajectory is used for collision detection. This involves comparing and analyzing the trajectory with obstacle information in the surrounding environment to determine the likelihood of a collision. If a collision risk is predicted, appropriate avoidance measures are taken promptly, such as adjusting speed or changing direction, to ensure vehicle safety.

[0091] Thus, by integrating the predicted trajectory points of the front axle center, vehicle center, and rear axle center, along with curvature and cumulative distance information, a complete and detailed vehicle trajectory can be generated. This allows the vehicle's control system to fully understand the vehicle's position and attitude changes during future driving, providing more accurate data support for subsequent collision detection and path planning.

[0092] In one embodiment, step S340 includes:

[0093] When the traversal of the path points to be driven is completed or the cumulative distance reaches a predetermined threshold, the coordinate information of the predicted trajectory point of the front axle center of the target vehicle, the coordinate information of the predicted trajectory point of the vehicle center, the orientation, the curvature value, and the coordinate information of the predicted trajectory point of the rear axle center are sorted according to the order of the path points to be driven to generate a complete driving trajectory.

[0094] In this embodiment, when the traversal of the path points to be driven is completed or the cumulative distance reaches a predetermined threshold, the coordinate information of the predicted trajectory point of the vehicle's front axle center, the coordinate information of the predicted trajectory point of the vehicle's center, the orientation, the curvature value, and the coordinate information of the predicted trajectory point of the rear axle center are collected for each path point to be driven. The collected data are arranged sequentially according to the order of the path points to be driven, ensuring that all information corresponding to each path point is complete and in the same order.

[0095] The sorted data is integrated, and the predicted trajectory points are connected in sequence to form a complete driving trajectory of the vehicle's front axle center, center, and rear axle center. At the same time, combined with curvature change and cumulative distance information, a detailed and continuous vehicle driving trajectory is constructed.

[0096] In this way, by sorting and integrating the data according to the path points, a complete and orderly vehicle trajectory can be generated. This allows the vehicle's control system to fully understand the vehicle's position changes and attitude during future driving, providing accurate data support for subsequent collision detection, path planning, and vehicle control.

[0097] Based on the technical solutions of the above embodiments, the following describes a specific application scenario of an embodiment of this application:

[0098] According to another embodiment of this application, a collision detection method for a multi-axle all-wheel steering vehicle is provided.

[0099] This method generates a vehicle's trajectory for collision detection based on relative path points and the vehicle's steering pattern. The trajectory information includes: the trajectory points (i.e., predicted trajectory points) of the vehicle's front axle center (x_f, y_f), vehicle center (x_c, y_c), and rear axle center (x_r, y_r), the orientation of the vehicle center (theta_c), the curvature (k), and the cumulative distance s of the route (starting from 0).

[0100] The steps include the following:

[0101] (1) Let the distance from the center of the front axle to the center of the vehicle be axle_to_center (the distance from the center of the rear axle to the center of the vehicle is equal to it).

[0102] (2) Perform coordinate transformation on the path point to be driven in the world coordinate system to obtain the path point to be driven relative to the vehicle (where the vehicle coordinate system takes the vehicle center as the origin, the vehicle driving direction as the x-axis, and the direction perpendicular to the vehicle driving direction and to the left as the y-axis), and traverse the path point to be driven (x(i), y(i), theta(i), s(i)).

[0103] (3) When i=0, set x_c(i)=-axle_to_center, y_c(i)=0.0, theta_c(i)=theta_0; x_r(i)=-2*axle_to_center, y_r(i)=0.0;

[0104] (4) When i>0, let dx=x(i)-x(i-1) and dy=y(i)-y(i-1), and determine whether the current turning mode is the full eight mode. If so, execute step (5); otherwise, execute step (6). (5)

[0106] a. Set L_offs=2.0 (i.e., the aforementioned offset, which can be calibrated and used to calculate the increment of the vehicle center trajectory point coordinates), dx_c (the increment of the vehicle center trajectory in the x-axis direction) = (x_c(i-1)-x(i))*(dx*(x_c(i-1)-x(i))+dy*(y_c(i-1)-y(i))) / (L_offs*L_offs), dy_c (calculate the increment of the vehicle center trajectory in the y-axis direction) = (y_c(i-1)-y(i))*(dx*(x_c(i-1)-x(i))+dy*(y_c(i-1)-y(i))) / (L_offs*L_offs).

[0107] b. Calculate the predicted trajectory point and orientation of the vehicle center: x_c(i)=x_c(i-1)+dx_c, y_c(i)=y_c(i-1)+dy_c, theta_c(i)=atan2(y(i)-y_c(i),x(i)-x_c(i));

[0108] c. Calculate the predicted trajectory point of the rear axis center: x_r(i) = x_c(i) - axle_to_center * cos(theta_c(i)), y_r(i) = y_c(i) - axle_to_center * sin(theta_c(i));

[0109] d. Calculate the predicted trajectory point of the front axle center: x_f(i)=x_c(i)+axle_to_center*cos(theta_c(i)), y_f(i)=y_c(i)+axle_to_center*sin(theta_c(i));

[0110] e. Calculate curvature k: If i<2, set k(i)=0, otherwise let dx_0=x_c(i-1)-x_c(i-2), dy_0=y_c(i-1)-y_c(i-2), dx_1=x_c(i)-x_c(i-1), dy_1=y_c(i)-y_c(i-1) , dfdx=(dy_1 / dx_1+dy_0 / dx_0) / 2, d2fdx2=(dy_1 / dx_1-dy_0 / dx_0) / ((dx_1+x(i)-x(i-1)) / 2), k(i)=abs(d2fdx2) / (1+dfdx*dfdx)1.5 .

[0111] Understandably, dfdx is an approximation of the first derivative, which is obtained by averaging the slope of the current segment (i.e., dy_1 / dx_1) and the slope of the previous segment (i.e., dy_0 / dx_0).

[0112] df2dx2 is an approximation of the second derivative. (dy_1 / dx_1-dy_0 / dx_0) represents the change in slope, and ((dx_1+x(i)-x(i-1)) / 2) represents the average change in the X-axis. Dividing the two gives df2dx2. (6)

[0114] a. Set L_offs=5.0 (can be calibrated), dx_r=(x_r(i-1)-x(i))*(dx*(x_r(i-1)-x(i))+dy*(y_r(i-1)-y(i))) / (L_off s*L_offs), dy_r=(y_r(i-1)-y(i))*(dx*(x_r(i-1)-x(i))+dy*(y_r(i-1)-y(i))) / (L_offs*L_offs).

[0115] b. Calculate the predicted trajectory point and orientation of the rear axle center: x_r(i)=x_r(i-1)+dx_r, y_r(i)=y_r(i-1)+dy_r, theta_r(i)=atan2(y(i)-y_r(i),x(i)-x_r(i));

[0116] c. Calculate the trajectory point and orientation of the vehicle center: theta_c(i)=theta_r(i); x_c(i)=x_r(i)+axle_to_center*cos(theta_c(i)), y_c(i)=y_r(i)+axle_to_center*sin(theta_c(i));

[0117] e. Calculate the trajectory point of the front axle center: x_f(i)=x_c(i)+axle_to_center*cos(theta_c(i)), y_f(i)=y_c(i)+axle_to_center*sin(theta_c(i));

[0118] c. Calculate curvature k: If i<2, set k(i)=0, otherwise let dx_0=x_c(i-1)-x_c(i-2), dy_0=y_c(i-1)-y_c(i-2), dx_1=x_c(i)-x_c(i-1), dy_1=y_c(i)-y_c(i-1) , dfdx=(dy_1 / dx_1+dy_0 / dx_0) / 2, d2fdx2=(dy_1 / dx_1-dy_0 / dx_0) / ((dx_1+x(i)-x(i-1)) / 2), k(i)=abs(d2fdx2) / (1+dfdx*dfdx) 1.5 .

[0119] (7) Calculate the cumulative distance s: ds = (dx*dx + dy*dy) 0.5 , s(i) = s(i-1)+ds;

[0120] (8) Repeat steps (4)-(7) until the last point of the relative path is reached or s(i)>cur_spd_mps*10, where cur_spd_mps is the current vehicle speed and cur_spd_mps*10 determines the length of the predicted driving trajectory, that is, the predicted trajectory length is the distance traveled at the current vehicle speed for 10 seconds.

[0121] (9) Generate the corresponding driving trajectory based on the calculated driving trajectory points of the front axle center, vehicle center, and rear axle center, as well as the orientation of the vehicle center at each driving trajectory point.

[0122] The following describes an embodiment of the apparatus described in this application, which can be used to execute the collision detection method for a multi-axle all-wheel steering vehicle as described in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the collision detection method for a multi-axle all-wheel steering vehicle described in this application.

[0123] Figure 4 A block diagram of a collision detection device for a multi-axle all-wheel steering vehicle according to an embodiment of this application is shown.

[0124] Reference Figure 4 As shown, a collision detection device for a multi-axle all-wheel steering vehicle according to an embodiment of this application includes:

[0125] The acquisition module is used to acquire the current steering mode of the target vehicle and the driving path points in the vehicle's body coordinate system.

[0126] The first calculation module is used to calculate the predicted trajectory points of the front axle center, vehicle center, and rear axle center of the target vehicle according to the steering mode and the path point to be driven.

[0127] The second calculation module is used to calculate the curvature based on the predicted trajectory point at the center of the vehicle, and to calculate the cumulative distance based on the coordinate difference between the points on the path to be traveled.

[0128] The processing module is used to generate a driving trajectory based on the curvature, the cumulative distance, and the predicted trajectory points of the front axle center, the vehicle center, and the rear axle center for collision detection.

[0129] Figure 5 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0130] It should be noted that, Figure 5 The computer system of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0131] like Figure 5 As shown, the computer system includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 502 or programs loaded from storage portion 508 into Random Access Memory (RAM) 503, such as performing the methods described in the above embodiments. The RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0132] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0133] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs various functions defined in the system of this application.

[0134] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0135] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0136] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0137] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.

[0138] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0139] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the methods according to the embodiments of this application.

[0140] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0141] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A collision detection method for a multi-axle all-wheel-steering vehicle, characterized by, The multi-axle all-wheel steering vehicle has a front axle, a middle axle and a rear axle, and a center point of the middle axle of the vehicle is a vehicle center; The method comprises: acquiring a current steering mode of a target vehicle and path points to be traveled in a body coordinate system of the target vehicle; calculating predicted trajectory points of a front axle center, the vehicle center and a rear axle center of the target vehicle respectively according to the steering mode and the path points to be traveled; calculating a curvature according to the predicted trajectory point of the vehicle center and calculating a cumulative distance according to coordinate difference values between the path points to be traveled; generating a travel trajectory for collision detection according to the curvature, the cumulative distance and the predicted trajectory points of the front axle center, the vehicle center and the rear axle center; wherein the real-time calculation of the predicted trajectory points of the front axle center, the vehicle center and the rear axle center of the target vehicle according to the steering mode and the path points to be traveled comprises: traversing the path points to be traveled from front to back, and for each path point to be traveled, determining a first horizontal coordinate increment and a first vertical coordinate increment of the current path point to be traveled relative to a previous path point to be traveled; when the steering mode is a full eight mode, determining a second horizontal coordinate increment and a second vertical coordinate increment of the vehicle center relative to a previous predicted trajectory point of the vehicle center according to the first horizontal coordinate increment and the first vertical coordinate increment; determining coordinate information of a current predicted trajectory point of the vehicle center according to the second horizontal coordinate increment, the second vertical coordinate increment and coordinate information of the previous predicted trajectory point of the vehicle center; determining coordinate information of current predicted trajectory points of the front axle center and the rear axle center of the target vehicle according to the coordinate information of the current predicted trajectory point of the vehicle center; when the steering mode is other than the full eight mode, determining a third horizontal coordinate increment and a third vertical coordinate increment of the rear axle center relative to a previous predicted trajectory point of the rear axle center according to the first horizontal coordinate increment and the first vertical coordinate increment; determining coordinate information of a current predicted trajectory point of the rear axle center according to the third horizontal coordinate increment, the third vertical coordinate increment and coordinate information of the previous predicted trajectory point of the rear axle center; determining coordinate information of current predicted trajectory points of the vehicle center and the front axle center of the target vehicle according to the coordinate information of the current predicted trajectory point of the rear axle center.

2. The method of claim 1, wherein, determining the coordinate information of the current predicted trajectory points of the front axle center and the rear axle center of the target vehicle according to the coordinate information of the current predicted trajectory point of the vehicle center comprises: determining orientation information of the current predicted trajectory point of the vehicle center according to the coordinate information of the current predicted trajectory point of the vehicle center and coordinate information of the path points to be traveled; determining the coordinate information of the current predicted trajectory points of the front axle center and the rear axle center of the target vehicle according to the coordinate information and the orientation information of the current predicted trajectory point of the vehicle center.

3. The method of claim 1, wherein, determining the coordinate information of the current predicted trajectory points of the vehicle center and the front axle center of the target vehicle according to the coordinate information of the current predicted trajectory point of the rear axle center comprises: determine orientation information of the rear axle center current predicted trajectory point according to the coordinate information of the rear axle center current predicted trajectory point and the coordinate information of the to-be-traveled path point; determine coordinate information of a current predicted trajectory point of a front axle center and a vehicle center of the target vehicle according to the coordinate information and the orientation information of the rear axle center current predicted trajectory point.

4. The method of claim 1, wherein, calculate a curvature according to the predicted trajectory point of the vehicle center, including: when a serial number of a current to-be-traveled trajectory point is less than 2, determine a current curvature value as 0; when the serial number of the current to-be-traveled trajectory point is greater than or equal to 2, calculate the current curvature value according to the coordinate information of the vehicle center current predicted trajectory point and coordinate information of two preceding predicted trajectory points.

5. The method of claim 1, wherein, calculate an accumulated distance according to coordinate difference values between the to-be-traveled path points, including: determine a single-step distance according to coordinate information of a current to-be-traveled path point and a preceding to-be-traveled path point; add the single-step distance and an accumulated distance corresponding to the preceding to-be-traveled path point to determine an accumulated distance corresponding to the current to-be-traveled path point.

6. The method of any one of claims 1-5, wherein, generate a travel trajectory according to the curvature, the accumulated distance, and the predicted trajectory points of the front axle center, the vehicle center, and the rear axle center, including: when to-be-traveled path point traversal ends or the accumulated distance reaches a predetermined threshold, sort coordinate information of a front axle center predicted trajectory point, coordinate information of a vehicle center predicted trajectory point, orientation, a curvature value, and coordinate information of a rear axle center predicted trajectory point of the target vehicle according to a sequence of the to-be-traveled path points to generate a complete travel trajectory.

7. A collision detection device for a multi-axle all-wheel-steering vehicle, characterized by comprising: The multi-axle all-wheel steering vehicle has a front axle, a middle axle, and a rear axle, and a center point of the vehicle middle axle is a vehicle center; The device includes: an acquisition module configured to acquire a current steering mode of a target vehicle and to-be-traveled path points in a body coordinate system of the target vehicle; a first calculation module configured to calculate predicted trajectory points of a front axle center, a vehicle center, and a rear axle center of the target vehicle respectively according to the steering mode and the to-be-traveled path points; a second calculation module configured to calculate a curvature according to the predicted trajectory point of the vehicle center and to calculate an accumulated distance according to coordinate difference values between the to-be-traveled path points; a processing module configured to generate a travel trajectory according to the curvature, the accumulated distance, and the predicted trajectory points of the front axle center, the vehicle center, and the rear axle center for collision detection.

8. A computer readable medium having stored thereon a computer program, characterized in that, The computer program, when executed by a processor, implements the method of any one of claims 1 to 6.

9. An electronic device, comprising: includes: one or more processors; a storage device configured to store one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1 to 6.

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