A path tracking control method and device for an unmanned vehicle

Abstract

The present invention provides a path tracking control method and device for an unmanned vehicle. After obtaining the target path of the vehicle, the steering wheel angles in different dimensions can be calculated based on the path information of the target path, the posture information of the vehicle, and the predicted information of the target path, and the steering wheel angle of the vehicle can be controlled based on the information to complete the lateral control of the vehicle. Based on the present invention, the full working conditions and multiple scenarios of unmanned driving tasks can be handled, and the stability and accuracy of path tracking can be improved during the driving process of the unmanned vehicle, thereby ensuring the safety performance of the unmanned vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of whole vehicle control of unmanned vehicles, and more specifically, to a path tracking control method and device for an unmanned vehicle. Background Art

[0002] As a hot topic in the development of automobile technology, driverless technology has a profound impact on the development of the automobile industry and even the national economy and people's livelihood. In the future, driverless technology may bring revolutionary changes to human travel methods and industrial production methods, but the current driverless technology is still in a period of rapid development and there are still many technical problems to be solved.

[0003] The current unmanned driving technology routes are similar. The unmanned driving system is basically composed of a perception fusion layer composed of various sensors, a planning and decision-making layer, a vehicle control layer, and a horizontal and vertical related actuator layer. The vehicle control layer connects the upper-level instructions and actuators, and plays an important role in the performance of unmanned vehicles. In the vehicle control layer, the path tracking control technology directly affects the performance of the vehicle in tracking the target path when unmanned. It tracks the target path through a certain control method and is a key technology to achieve stable vehicle driving.

[0004] At present, due to certain stability issues in environmental perception, planning and decision-making technologies, the path information received by the vehicle control layer has certain stability issues, and there is also interaction delay in the interaction with the actuator layer. Therefore, developing a stable path tracking control method to ensure that the unmanned vehicle can stably track the target path in a complex road traffic environment is crucial to the driving performance and safety of the unmanned vehicle. Summary of the invention

[0005] In view of this, in order to solve the above problems, the present invention provides a path tracking control method and device for an unmanned vehicle, and the technical solution is as follows:

[0006] A path tracking control method for an unmanned vehicle, the method comprising:

[0007] Get the target path of the vehicle;

[0008] Calculating a first steering wheel angle of the vehicle based on the path information of the target path; and calculating a second steering wheel angle of the vehicle based on the posture information of the vehicle; and calculating a third steering wheel angle of the vehicle based on the predicted information of the target path;

[0009] The steering wheel of the vehicle is controlled according to the first steering wheel angle, the second steering wheel angle, and the third steering wheel angle to perform lateral control on the vehicle.

[0010] Preferably, the calculating the first steering wheel angle of the vehicle based on the path information of the target path includes:

[0011] Selecting a first target point on the target path using the speed of the vehicle, and acquiring a first curve curvature of the first target point;

[0012] Converting the curvature of the first curve into a vehicle wheel end turning angle by trigonometric function change;

[0013] According to a preset mapping relationship, the steering wheel angle mapped to the vehicle wheel end angle is used as the first steering wheel angle.

[0014] Preferably, the method further comprises:

[0015] The directional characteristic of the curvature of the first curve is corrected.

[0016] Preferably, the calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle comprises:

[0017] Taking a point on the target path that is closest to the origin of the vehicle coordinate system as a second target point;

[0018] determining a lateral offset and a first lateral angle of the vehicle at the second target point;

[0019] Acquire a second curve curvature of the second target point, and calculate a first lateral acceleration of the vehicle using the second curve curvature and the vehicle speed;

[0020] Determining a first proportional control coefficient corresponding to the first lateral acceleration in a lateral offset dimension and a second proportional control coefficient corresponding to the first lateral acceleration in a lateral angle dimension;

[0021] Calculating the steering wheel angle in the lateral offset dimension according to the first proportional control coefficient and the lateral offset; and calculating the steering wheel angle in the lateral angle dimension according to the second proportional control coefficient and the first lateral angle;

[0022] The sum of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension is taken as the second steering wheel angle.

[0023] Preferably, the method further comprises:

[0024] When the running state of the vehicle meets the preset dynamic integral compensation condition, determining the integral step length of the compensation according to the first lateral acceleration;

[0025] Compensating the steering wheel angle in the lateral offset dimension according to the integration step size;

[0026] Correspondingly, taking the superposition of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle includes:

[0027] The sum of the compensated steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension is taken as the second steering wheel angle.

[0028] Preferably, the calculating the third steering wheel angle of the vehicle based on the prediction information of the target path includes:

[0029] A point on the target path that is closest to the origin of the vehicle coordinate system is used as a third target point, and a prediction point is selected on the target path;

[0030] Calculating the time interval of the vehicle from the third target point to the predicted point according to the speed of the vehicle;

[0031] respectively determining a second lateral angle of the vehicle at the third target point and a third lateral angle of the prediction point, and calculating a predicted yaw rate of the vehicle according to the second lateral angle, the third lateral angle and the time interval;

[0032] acquiring a third curve curvature of the third target point, and calculating a second lateral acceleration of the vehicle using the third curve curvature and the vehicle speed;

[0033] determining a third proportional control coefficient corresponding to the second lateral acceleration in a yaw rate dimension;

[0034] An actual yaw rate of the vehicle is acquired, and the third steering wheel angle is calculated according to the actual yaw rate, the third proportional control coefficient, and the predicted yaw rate.

[0035] A path tracking control device for an unmanned vehicle, the device comprising:

[0036] A path acquisition module is used to obtain a target path of the vehicle;

[0037] a steering wheel angle calculation module, configured to calculate a first steering wheel angle of the vehicle based on the path information of the target path; and, to calculate a second steering wheel angle of the vehicle based on the posture information of the vehicle; and, to calculate a third steering wheel angle of the vehicle based on the predicted information of the target path;

[0038] A lateral control module is used to control the steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle and the third steering wheel angle to perform lateral control on the vehicle.

[0039] Preferably, the steering wheel angle calculation module for calculating the first steering wheel angle of the vehicle based on the path information of the target path is specifically used for:

[0040] A first target point is selected on the target path using the vehicle speed, and a first curve curvature of the first target point is obtained; the first curve curvature is converted into a vehicle wheel end angle through trigonometric function changes; and according to a preset mapping relationship, a steering wheel angle mapped by the vehicle wheel end angle is used as the first steering wheel angle.

[0041] Preferably, the steering wheel angle calculation module for calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle is specifically used for:

[0042] Take the point on the target path that is closest to the origin of the vehicle coordinate system as the second target point; determine the lateral offset and the first lateral angle of the vehicle at the second target point; obtain the second curve curvature of the second target point, and use the second curve curvature and the vehicle speed to calculate the first lateral acceleration of the vehicle; determine the first proportional control coefficient corresponding to the first lateral acceleration in the lateral offset dimension, and the second proportional control coefficient corresponding to the first lateral acceleration in the lateral angle dimension; calculate the steering wheel angle in the lateral offset dimension according to the first proportional control coefficient and the lateral offset; and calculate the steering wheel angle in the lateral angle dimension according to the second proportional control coefficient and the first lateral angle; and take the superposition of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle.

[0043] Preferably, the steering wheel angle calculation module for calculating the third steering wheel angle of the vehicle based on the prediction information of the target path is specifically used for:

[0044] A point on the target path that is closest to the origin of the vehicle coordinate system is taken as a third target point, and a prediction point is selected on the target path; a time interval of the vehicle from the third target point to the prediction point is calculated according to the vehicle speed; a second lateral angle of the vehicle at the third target point and a third lateral angle of the prediction point are determined respectively, and a predicted yaw velocity of the vehicle is calculated according to the second lateral angle, the third lateral angle and the time interval; a third curve curvature of the third target point is obtained, and a second lateral acceleration of the vehicle is calculated using the third curve curvature and the vehicle speed; a third proportional control coefficient corresponding to the second lateral acceleration in the yaw velocity dimension is determined; an actual yaw velocity of the vehicle is obtained, and a third steering wheel angle is calculated according to the actual yaw velocity, the third proportional control coefficient and the predicted yaw velocity.

[0045] The present invention provides a path tracking control method and device for an unmanned vehicle. After obtaining the target path of the vehicle, the steering wheel angles in different dimensions can be calculated based on the path information of the target path, the posture information of the vehicle, and the predicted information of the target path, and the steering wheel angle of the vehicle can be controlled based on the information to complete the lateral control of the vehicle. Based on the present invention, the full working conditions and multiple scenarios of unmanned driving tasks can be handled, and the stability and accuracy of path tracking can be improved during the driving process of the unmanned vehicle, thereby ensuring the safety performance of the unmanned vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0047] Figure 1 A method flow chart of a path tracking control method for an unmanned vehicle provided by an embodiment of the present invention;

[0048] Figure 2 An example of a target path provided for an embodiment of the present invention;

[0049] Figure 3 Another method flow chart of the path tracking control method of the unmanned vehicle provided by an embodiment of the present invention;

[0050] Figure 4 A schematic diagram of calculating the curvature of a curve to the turning angle of a vehicle wheel end provided in an embodiment of the present invention;

[0051] Figure 5A flowchart of another method of the path tracking control method of the unmanned vehicle provided by an embodiment of the present invention;

[0052] Figure 6 A flowchart of another method of the path tracking control method of the unmanned vehicle provided by an embodiment of the present invention;

[0053] Figure 7 A schematic structural diagram of a path tracking control device for an unmanned vehicle provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] The path tracking control method for an unmanned vehicle provided by the present invention can be applied to any vehicle with an unmanned driving function. Specifically, the method is applied to the vehicle control layer, which receives the target path sent by the planning and decision-making layer, calculates the steering wheel angle of the vehicle during real-time path tracking (i.e., the steering system control amount) through a certain control method, and sends it to the actuator layer for the steering system for lateral control. Therefore, the path tracking control method directly affects the performance of the unmanned vehicle when performing tasks such as patrolling, parking, and changing lanes.

[0057] See also Figure 1 The path tracking control method of an unmanned vehicle provided by an embodiment of the present invention comprises the following steps:

[0058] S10, obtaining a target path of the vehicle.

[0059] In the embodiment of the present invention, the planning decision layer integrates the fusion information of the perception fusion layer to generate the target path of the vehicle, and transmits the target path to the vehicle control layer in the form of a fitting curve. Specifically, the target path can be a global path or a local path, which is not limited in this embodiment.

[0060] Among them, the global path refers to the vehicle driving path generated by cameras or high-precision maps, which is processed by the perception fusion layer and sent to the downstream modules; the local path is a local path generated by the planning decision layer based on the global path when the vehicle approaches the global path or performs tasks such as changing lanes, detouring, and avoiding obstacles during autonomous driving.

[0061] In addition, the fitting curve refers to a two-dimensional curve in which the target path is in the vehicle coordinate system, with the center point of the rear axle of the vehicle as the coordinate origin, and the direction of the rear axle of the vehicle and the forward direction of the vehicle as the horizontal and vertical axes of the coordinates. Figure 2 is an example of a target path.

[0062] S20, calculating a first steering wheel angle of the vehicle based on the path information of the target path; and, calculating a second steering wheel angle of the vehicle based on the posture information of the vehicle; and, calculating a third steering wheel angle of the vehicle based on the predicted information of the target path.

[0063] In the embodiment of the present invention, in the control strategy based on path information, the vehicle control layer extracts the curvature characteristics of the curve of the target path in the vehicle coordinate system, and then finally maps it to the steering wheel angle of the unmanned vehicle.

[0064] In the specific implementation process, the "calculating the first steering wheel angle of the vehicle based on the path information of the target path" in step S20 can adopt the following steps, and the method flow chart is as follows: Figure 3 As shown:

[0065] S2011: Select a first target point on the target path using the vehicle speed, and obtain a first curve curvature of the first target point.

[0066] In an embodiment of the present invention, taking into account that the steering system has a certain response delay time to the turning angle command issued by the vehicle control layer, when selecting the first target point, the product of the response delay time and the current speed of the vehicle is used as the distance between the target point and the coordinate origin, and then the corresponding point is selected from the target path based on the distance as the first target point.

[0067] In addition, in the embodiment of the present invention, the curvature of the curve has a directional feature and a numerical feature, wherein the directional feature corresponds to the left turn and the right turn of the steering system. Therefore, in the embodiment of the present invention, the directional feature of the curvature of the first curve can also be corrected. Specifically, multiple points located in the front and rear directions of the first target point can be selected on the target path, such as ten points in front and behind, and the directional feature with the largest proportion is selected as the directional feature of the curvature of the first curve.

[0068] S2012: Convert the curvature of the first curve into a vehicle wheel end angle by changing a trigonometric function.

[0069] In an embodiment of the present invention, with reference to the theory of preview tracking and drawing an arc by an unmanned vehicle during path tracking, the curvature of the first curve is converted into a wheel-end turning angle of the vehicle through trigonometric function changes, thereby realizing the use of the wheel-end turning angle as a feedforward control quantity of the entire vehicle path tracking control method, thereby achieving effective separation and efficient utilization of path information.

[0070] See also Figure 4 The calculation diagram of the curve curvature to the vehicle wheel end angle is shown. Based on the arc drawing idea, when the vehicle wheel end angle is at a fixed angle, it will travel along a path with a fixed curvature. When the vehicle is tracking the path, assuming that the vehicle is traveling along a curve curvature, the vehicle wheel end angle under the curvature can be calculated, so that the relationship between the curve curvature and the vehicle wheel end angle can be approximated as shown in the trigonometric function relationship in the figure.

[0071] S2013: According to a preset mapping relationship, the steering wheel angle mapped to the vehicle wheel end angle is used as the first steering wheel angle.

[0072] In the embodiment of the present invention, the mapping relationship between the vehicle wheel end angle and the steering wheel angle may be set based on prior knowledge, which records the steering wheel angles corresponding to different vehicle wheel end angles.

[0073] In addition, in the embodiment of the present invention, the control strategy based on the posture information is to extract the posture information of the unmanned vehicle and make effective use of it. When the unmanned vehicle performs path tracking control, the target path sent by the upper layer of the unmanned driving system is first mapped to the vehicle coordinate system. The so-called vehicle coordinate system is a coordinate system with the center of the rear axle of the vehicle as the coordinate origin and the axle as the XY axis.

[0074] In the vehicle coordinate system, combined with the coordinate equation of the target path in this coordinate system, the vehicle's posture information at each moment can be calculated, including the distance between the center point of the vehicle's rear axle and the nearest point of the target path (i.e., lateral offset) and the angle between the vehicle's forward direction and the tangent direction of the target path (i.e., lateral angle).

[0075] The control strategy based on posture information consists of two parts: feedback control of lateral offset and lateral angle. First, we need to design a feature extraction function to extract the lateral offset and lateral angle of the vehicle relative to the target path in the vehicle coordinate system. Then we design a control application strategy:

[0076] As for lateral offset, it represents the relative distance relationship between the vehicle and the target path. However, since the transmission of signals has time delays whether from the planning and decision-making layer of the unmanned driving system to the vehicle control layer, or from the vehicle control layer to the actuator layer, corresponding considerations need to be made when designing a control method with lateral offset as feedback.

[0077] For the application strategy of lateral offset, it is mainly to design relevant parameters in combination with vehicle speed and curve curvature and apply them to the proportional control loop. At the same time, since the performance of the vehicle at high speed is more sensitive to steering adjustment, the limiting unit of the proportional loop output is designed from the perspective of system control safety to avoid oscillation of excessive adjustment caused by abnormal lateral offset of the steering system at various vehicle speeds due to other factors.

[0078] For the lateral angle, it characterizes the relative angle relationship between the vehicle and the target path, and its control strategy is relatively sensitive to the overall control result. The lateral angle is calculated based on the coordinate equation of the target path in the vehicle coordinate system. There is a certain degree of distortion from the curve fitting process to the angle calculation process, but the lateral angle is indispensable as an important control quantity. Therefore, when designing a control method with the lateral angle as feedback, it is used as an auxiliary adjustment control quantity for the lateral offset control result. The two work together to form a control method based on vehicle posture information, and assist in feedforward control based on path information, so that unmanned vehicles can complete stable and accurate tracking of the target path in most scenarios.

[0079] For the application strategy of the lateral angle, relevant parameters are designed in combination with the vehicle speed and curve curvature and applied to the proportional control loop. From the perspective of system control safety, a limiting unit for the proportional loop output is designed to avoid oscillation caused by excessive adjustment of the steering system due to abnormal deviation angle caused by other factors at various vehicle speeds.

[0080] By extracting and applying the two vehicle posture information of lateral offset and lateral angle, it is ensured that the unmanned vehicle can stably and accurately track the target path in most driving environments.

[0081] In the specific implementation process, the "calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle" in step S20 can adopt the following steps, and the method flow chart is as follows: Figure 5 As shown:

[0082] S2021: A point on the target path that is closest to the origin of the vehicle coordinate system is taken as a second target point.

[0083] In the embodiment of the present invention, a search function is designed to search for a point on the target path that is closest to the origin of the vehicle coordinate system, that is, the center point of the rear axle of the vehicle, as the second target point.

[0084] S2022: Determine the lateral offset and the first lateral angle of the vehicle at the second target point.

[0085] In the embodiment of the present invention, the distance between the second target point and the origin of the vehicle coordinate system is used as the lateral offset of the vehicle, and its direction is defined. A tangent line is drawn to the second target point, and the angle formed by the tangent line and the vehicle's forward direction is used as the lateral angle, and its direction is also defined. Figure 2 , Figure 2 The starting point of the middle target path can be used as the second target point, and its lateral offset and lateral angle are shown in the figure.

[0086] S2023: Obtain a second curve curvature of a second target point, and calculate a first lateral acceleration of the vehicle using the second curve curvature and the vehicle speed.

[0087] In the embodiment of the present invention, the first lateral acceleration is equal to the product of the square of the current vehicle speed and the curvature of the second curve.

[0088] S2024, determining a first proportional control coefficient corresponding to the first lateral acceleration in a lateral offset dimension and a second proportional control coefficient corresponding to the first lateral acceleration in a lateral angle dimension.

[0089] In the embodiment of the present invention, since the lateral acceleration represents the lateral stability of the vehicle during driving, when designing the first proportional control coefficient in the lateral offset dimension and the second proportional control coefficient in the lateral angle dimension, the basic design principle is that the larger the first lateral acceleration, the smaller the proportional control coefficient, so as to avoid the vehicle outputting a large angle control amount when the lateral stability is poor and aggravating the lateral instability state.

[0090] S2025, calculating the steering wheel angle in the lateral offset dimension according to the first proportional control coefficient and the lateral offset; and calculating the steering wheel angle in the lateral angle dimension according to the second proportional control coefficient and the first lateral angle.

[0091] In the embodiment of the present invention, the feedback control goal based on the lateral offset is to control it to be close to 0, so that the vehicle can accurately track the target path. Therefore, the output value of the proportional link - the steering wheel angle in the lateral offset dimension = the first proportional control coefficient * lateral offset.

[0092] Correspondingly, the feedback control target based on the lateral angle in the embodiment of the present invention is also to control it to tend to 0, so that the vehicle can accurately track the target path. Therefore, the output value of the proportional link - the steering wheel angle in the lateral angle dimension = the second proportional control coefficient * the first lateral angle.

[0093] In addition, since the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension are calculated based on the target path, and the target path has occasional instability, the output of the proportional link (the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension) can be restricted by upper and lower limits and the slope of change in the present invention to reduce the impact of occasional instability of the trajectory.

[0094] S2026: Taking the sum of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle.

[0095] On this basis, for the application strategy of lateral offset, the present invention takes into account the curve curvature of the target path and the relevant control parameters under the vehicle speed. At the same time, in order to more accurately adjust the vehicle position in real time, a real-time dynamic integral compensation method is designed, which also takes into account the influence of different path curvatures and vehicle speeds.

[0096] Specifically, in Figure 5 The path tracking control method of the unmanned vehicle shown in the figure also includes the following steps:

[0097] When the running state of the vehicle meets the preset dynamic integral compensation condition, the integral step length of the compensation is determined according to the first lateral acceleration; and the steering wheel angle in the lateral offset dimension is compensated according to the integral step length;

[0098] Correspondingly, step S2026 specifically includes: taking the sum of the compensated steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle.

[0099] In the embodiment of the present invention, there is a static deviation in the steering system response between vehicles. When designing dynamic integral compensation, it is necessary to eliminate the difference between vehicles. At the same time, when the vehicle is in a scene with strong side wind and other scenes, it is also necessary to eliminate the scene influence. Therefore, the present invention adjusts the output steering wheel angle in real time according to the change of lateral deviation during vehicle driving.

[0100] Among them, the dynamic integral compensation conditions include: the mark bit of the intelligent driving state is yes, the lateral offset is greater than the preset compensation threshold, the lateral offset continues to increase within several calculation cycles, and the mark bit of the lane change state is no.

[0101] In addition, when designing the integration step of the dynamic integral compensation, the basic design principle is that the greater the first lateral acceleration, the smaller the integration step, thereby avoiding unnecessary adjustments when the vehicle is in an unstable state.

[0102] It should also be noted that when the vehicle's operating state does not meet the preset dynamic integral compensation conditions, the dynamic integral compensation is exited and the integral step length before exit is maintained as a basis for subsequent compensation.

[0103] In addition, in the embodiment of the present invention, the control strategy based on the predicted information, taking into account the above two parts, whether it is based on the path information or based on the vehicle body posture information, is a control method designed based on the current real-time information. However, during the driving process of the unmanned vehicle, on the one hand, there is a delay in the collection, calculation and control links of real-time information, and on the other hand, due to the need to face some atypical driving scenes during driving, such as sudden sharp bends on straight roads, driving on irregular curved roads, etc., the control strategy based on real-time information is difficult to cover these control requirements well, so it is necessary to predict and extract the relevant information of the vehicle driving and make use of it.

[0104] In order to improve the driving stability of unmanned vehicles in road traffic environments such as sudden changes in curvature, it is necessary to extract and utilize the future road and vehicle information of the vehicle based on the idea of ​​prediction. The yaw angular velocity of the vehicle during driving represents the lateral motion stability of the vehicle. When the unmanned vehicle is driving on a path with sudden changes in curvature, it is necessary to predict the changes in future road information in advance and adopt corresponding control optimization strategies. The first two control strategies based on the current position path and posture information of the vehicle are difficult to fully cover the above path tracking requirements. Therefore, on the basis of the above two control strategies, designing a control strategy based on predictive information can help improve the driving stability of unmanned vehicles.

[0105] During the driving process of the unmanned vehicle, it is predicted that the vehicle will reach the predicted position after a period of time from the current position, and based on this, the yaw angle change of the vehicle is predicted, that is, the predicted yaw velocity is obtained. Combining the predicted yaw velocity and the actual yaw velocity of the vehicle's current position, a control method based on the predicted information is designed, that is, the difference between the predicted yaw velocity and the actual yaw velocity is used as the control amount to adjust the real-time position of the vehicle. This can further help the unmanned vehicle improve the tracking stability and accuracy when performing path tracking on roads with variable curvature.

[0106] In the specific implementation process, the "calculating the third steering wheel angle of the vehicle based on the predicted information of the target path" in step S20 can adopt the following steps, and the method flow chart is as follows: Figure 6 As shown:

[0107] S2031: A point on the target path that is closest to the origin of the vehicle coordinate system is taken as a third target point, and a prediction point is selected on the target path.

[0108] In the embodiment of the present invention, a search function is designed to search for a point on the target path that is closest to the origin of the vehicle's own vehicle coordinate system, that is, the center point of the vehicle's rear axle, as the third target point. The predicted point is a point on the target path that is a certain distance away from the third target point, and the size of the distance is preset and proportional to the current speed of the vehicle.

[0109] Continue to see Figure 2 , Figure 2 The starting point of the target path can be used as the third target point, and its lateral angle is shown in the figure. In addition, Figure 2 The middle prediction point is located between the target path start point and the target path end point, and its lateral angle is shown in the figure.

[0110] S2032, calculating the time interval from the third target point to the predicted point according to the vehicle speed.

[0111] In the embodiment of the present invention, the time interval from the third target point to the predicted point is equal to a value obtained by dividing the distance from the third target point to the predicted point in the target path by the current speed of the vehicle.

[0112] S2033, respectively determining a second lateral angle of the vehicle at the third target point and a third lateral angle at the prediction point, and calculating a predicted yaw rate of the vehicle according to the second lateral angle, the third lateral angle and the time interval.

[0113] It should be noted that the predicted yaw rate is a conceptual lateral swing speed of the vehicle, not the yaw rate at the prediction point.

[0114] In the embodiment of the present invention, the predicted yaw angular velocity=(third lateral angle−second lateral angle) / time interval.

[0115] S2034: Obtain a third curve curvature of a third target point, and calculate a second lateral acceleration of the vehicle using the third curve curvature and the vehicle speed.

[0116] In the embodiment of the present invention, the second lateral acceleration is equal to the product of the square of the current vehicle speed and the curvature of the third curve.

[0117] S2035: Determine a third proportional control coefficient corresponding to the second lateral acceleration in the yaw angular velocity dimension.

[0118] In the embodiment of the present invention, since the lateral acceleration represents the lateral stability of the vehicle during driving, when designing the third proportional control coefficient in the yaw angular velocity dimension, the basic design principle is that the greater the second lateral acceleration, the smaller the proportional control coefficient, so as to avoid the vehicle outputting a large angle control amount when the lateral stability is poor and aggravating the lateral instability state.

[0119] S2036: Acquire the actual yaw rate of the vehicle, and calculate the third steering wheel angle according to the actual yaw rate, the third proportional control coefficient and the predicted yaw rate.

[0120] In the embodiment of the present invention, the third steering wheel angle=(predicted yaw rate−actual yaw rate)*third proportional control coefficient.

[0121] Through the joint effect of the above three control strategies, it is ensured that the unmanned vehicle can stably and accurately track the target path of the unmanned driving system when performing tasks such as patrolling, parking and changing lanes, which plays an important role in improving the driving safety of unmanned vehicles.

[0122] S30: Control the steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle, and the third steering wheel angle to perform lateral control on the vehicle.

[0123] In an embodiment of the present invention, the superposition of the first steering wheel angle, the second steering wheel angle and the third steering wheel angle can be used as the actual steering wheel angle for controlling the vehicle steering wheel, and the actual steering wheel angle is sent to the steering system of the actuator layer, thereby performing laterally control of the vehicle.

[0124] The path tracking control method for an unmanned vehicle provided by an embodiment of the present invention can calculate the steering wheel angles in different dimensions based on the path information of the target path, the posture information of the vehicle, and the predicted information of the target path after acquiring the target path of the vehicle, and control the steering wheel angle of the vehicle based on the information to complete the lateral control of the vehicle. Based on the present invention, it is possible to cope with all working conditions and multiple scenarios of unmanned driving tasks, improve the stability and accuracy of path tracking during the driving process of unmanned vehicles, and thus ensure the safety performance of unmanned vehicles.

[0125] Based on the path tracking control method for the unmanned vehicle provided in the above embodiment, an embodiment of the present invention provides a device for executing the path tracking control method for the unmanned vehicle. The structural diagram of the device is shown in FIG. Figure 7 As shown, including:

[0126] The path acquisition module 10 is used to acquire the target path of the vehicle.

[0127] The steering wheel angle calculation module 20 is used to calculate a first steering wheel angle of the vehicle based on the path information of the target path; and, to calculate a second steering wheel angle of the vehicle based on the posture information of the vehicle; and, to calculate a third steering wheel angle of the vehicle based on the predicted information of the target path.

[0128] The lateral control module 30 is used to control the steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle and the third steering wheel angle to perform lateral control on the vehicle.

[0129] Optionally, the steering wheel angle calculation module 20 for calculating the first steering wheel angle of the vehicle based on the path information of the target path is specifically used to:

[0130] A first target point is selected on a target path using the vehicle speed, and a first curve curvature of the first target point is obtained; the first curve curvature is converted into a vehicle wheel end angle through trigonometric function changes; and according to a preset mapping relationship, a steering wheel angle mapped to the vehicle wheel end angle is used as a first steering wheel angle.

[0131] Optionally, the steering wheel angle calculation module 20 is further used for:

[0132] The directional characteristic of the curvature of the first curve is corrected.

[0133] Optionally, the steering wheel angle calculation module 20 for calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle is specifically used for:

[0134] A point on the target path that is closest to the origin of the vehicle coordinate system is taken as a second target point; a lateral offset and a first lateral angle of the vehicle at the second target point are determined; a second curve curvature of the second target point is obtained, and a first lateral acceleration of the vehicle is calculated using the second curve curvature and the vehicle speed; a first proportional control coefficient corresponding to the first lateral acceleration in the lateral offset dimension and a second proportional control coefficient corresponding to the first lateral acceleration in the lateral angle dimension are determined; a steering wheel angle in the lateral offset dimension is calculated based on the first proportional control coefficient and the lateral offset; and a steering wheel angle in the lateral angle dimension is calculated based on the second proportional control coefficient and the first lateral angle; and a second steering wheel angle is taken as the superposition of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension.

[0135] Optionally, the steering wheel angle calculation module 20 is further used for:

[0136] When the running state of the vehicle meets the preset dynamic integral compensation condition, the integral step length of the compensation is determined according to the first lateral acceleration; and the steering wheel angle in the lateral offset dimension is compensated according to the integral step length;

[0137] Correspondingly, the steering wheel angle calculation module 20 for taking the superposition of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle is specifically configured to:

[0138] The sum of the compensated steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension is taken as the second steering wheel angle.

[0139] Optionally, the steering wheel angle calculation module 20 for calculating a third steering wheel angle of the vehicle based on the prediction information of the target path is specifically used for:

[0140] A point on the target path that is closest to the origin of the vehicle coordinate system is taken as a third target point, and a prediction point is selected on the target path; a time interval from the third target point to the prediction point is calculated according to the vehicle speed; a second lateral angle of the vehicle at the third target point and a third lateral angle of the prediction point are determined respectively, and a predicted yaw velocity of the vehicle is calculated according to the second lateral angle, the third lateral angle and the time interval; a third curve curvature of the third target point is obtained, and a second lateral acceleration of the vehicle is calculated using the third curve curvature and the vehicle speed; a third proportional control coefficient corresponding to the second lateral acceleration in the yaw velocity dimension is determined; an actual yaw velocity of the vehicle is obtained, and a third steering wheel angle is calculated according to the actual yaw velocity, the third proportional control coefficient and the predicted yaw velocity.

[0141] The path tracking control device for an unmanned vehicle provided by an embodiment of the present invention can calculate the steering wheel angles in different dimensions based on the path information of the target path, the posture information of the vehicle, and the predicted information of the target path after acquiring the target path of the vehicle, and control the steering wheel angle of the vehicle based on the path information, thereby completing the lateral control of the vehicle. Based on the present invention, it is possible to cope with all working conditions and multiple scenarios of unmanned driving tasks, improve the stability and accuracy of path tracking during the driving process of unmanned vehicles, and thus ensure the safety performance of unmanned vehicles.

[0142] The path tracking control method and device for an unmanned vehicle provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

[0143] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0144] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device that includes a series of elements is inherent to the elements, or also includes elements inherent to these processes, methods, articles or devices. In the absence of further restrictions, the elements defined by the sentence "including a..." do not exclude the presence of other identical elements in the process, method, article or device that includes the elements.

[0145] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A path tracking control method for an unmanned vehicle, characterized in that: The method comprises: Get the target path of the vehicle; Calculating a first steering wheel angle of the vehicle based on the path information of the target path; and calculating a second steering wheel angle of the vehicle based on the posture information of the vehicle; and calculating a third steering wheel angle of the vehicle based on the predicted information of the target path; Controlling the steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle and the third steering wheel angle to perform lateral control on the vehicle; taking the sum of the first steering wheel angle, the second steering wheel angle and the third steering wheel angle as the actual steering wheel angle for controlling the steering wheel of the vehicle, and sending the actual steering wheel angle to the steering system of the actuator layer to perform lateral control on the vehicle; Wherein, calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle includes: Taking a point on the target path that is closest to the origin of the vehicle coordinate system as a second target point; determining a lateral offset and a first lateral angle of the vehicle at the second target point; Acquire a second curve curvature of the second target point, and calculate a first lateral acceleration of the vehicle using the second curve curvature and the vehicle speed; Determining a first proportional control coefficient corresponding to the first lateral acceleration in a lateral offset dimension and a second proportional control coefficient corresponding to the first lateral acceleration in a lateral angle dimension; Calculating the steering wheel angle in the lateral offset dimension according to the first proportional control coefficient and the lateral offset; and calculating the steering wheel angle in the lateral angle dimension according to the second proportional control coefficient and the first lateral angle; The sum of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension is taken as the second steering wheel angle.

2. The method according to claim 1, characterized in that The calculating a first steering wheel angle of the vehicle based on the path information of the target path includes: Selecting a first target point on the target path using the speed of the vehicle, and acquiring a first curve curvature of the first target point; Converting the curvature of the first curve into a vehicle wheel end turning angle by trigonometric function change; According to a preset mapping relationship, the steering wheel angle mapped to the vehicle wheel end angle is used as the first steering wheel angle.

3. The method according to claim 2, characterized in that The method further comprises: The directional characteristic of the curvature of the first curve is corrected.

4. The method according to claim 1, characterized in that: The method further comprises: When the running state of the vehicle meets the preset dynamic integral compensation condition, determining the integral step length of the compensation according to the first lateral acceleration; Compensating the steering wheel angle in the lateral offset dimension according to the integration step size; Correspondingly, taking the superposition of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle includes: The sum of the compensated steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension is taken as the second steering wheel angle.

5. The method according to claim 1, characterized in that The calculating a third steering wheel angle of the vehicle based on the prediction information of the target path includes: A point on the target path that is closest to the origin of the vehicle coordinate system is used as a third target point, and a prediction point is selected on the target path; Calculating the time interval of the vehicle from the third target point to the predicted point according to the speed of the vehicle; respectively determining a second lateral angle of the vehicle at the third target point and a third lateral angle of the prediction point, and calculating a predicted yaw rate of the vehicle according to the second lateral angle, the third lateral angle and the time interval; acquiring a third curve curvature of the third target point, and calculating a second lateral acceleration of the vehicle using the third curve curvature and the vehicle speed; determining a third proportional control coefficient corresponding to the second lateral acceleration in a yaw rate dimension; An actual yaw rate of the vehicle is acquired, and the third steering wheel angle is calculated according to the actual yaw rate, the third proportional control coefficient, and the predicted yaw rate.

6. A path tracking control device for an unmanned vehicle, characterized in that: The device comprises: A path acquisition module is used to obtain a target path of the vehicle; a steering wheel angle calculation module, configured to calculate a first steering wheel angle of the vehicle based on the path information of the target path; and, to calculate a second steering wheel angle of the vehicle based on the posture information of the vehicle; and, to calculate a third steering wheel angle of the vehicle based on the predicted information of the target path; a lateral control module, configured to control the steering wheel of the vehicle according to the first steering wheel angle, the second steering wheel angle and the third steering wheel angle, so as to perform lateral control on the vehicle; use the sum of the first steering wheel angle, the second steering wheel angle and the third steering wheel angle as the actual steering wheel angle for controlling the steering wheel of the vehicle, and send the actual steering wheel angle to the steering system of the actuator layer, so as to perform lateral control on the vehicle; Wherein, the steering wheel angle calculation module for calculating the second steering wheel angle of the vehicle based on the posture information of the vehicle is specifically used for: Take the point on the target path that is closest to the origin of the vehicle coordinate system as the second target point; determine the lateral offset and the first lateral angle of the vehicle at the second target point; obtain the second curve curvature of the second target point, and use the second curve curvature and the vehicle speed to calculate the first lateral acceleration of the vehicle; determine the first proportional control coefficient corresponding to the first lateral acceleration in the lateral offset dimension, and the second proportional control coefficient corresponding to the first lateral acceleration in the lateral angle dimension; calculate the steering wheel angle in the lateral offset dimension according to the first proportional control coefficient and the lateral offset; and calculate the steering wheel angle in the lateral angle dimension according to the second proportional control coefficient and the first lateral angle; and take the superposition of the steering wheel angle in the lateral offset dimension and the steering wheel angle in the lateral angle dimension as the second steering wheel angle.

7. The device according to claim 6, characterized in that The steering wheel angle calculation module for calculating the first steering wheel angle of the vehicle based on the path information of the target path is specifically used to: A first target point is selected on the target path using the vehicle speed, and a first curve curvature of the first target point is obtained; the first curve curvature is converted into a vehicle wheel end angle through trigonometric function changes; and according to a preset mapping relationship, a steering wheel angle mapped by the vehicle wheel end angle is used as the first steering wheel angle.

8. The device according to claim 6, characterized in that The steering wheel angle calculation module for calculating a third steering wheel angle of the vehicle based on the prediction information of the target path is specifically used for: A point on the target path that is closest to the origin of the vehicle coordinate system is taken as a third target point, and a prediction point is selected on the target path; a time interval of the vehicle from the third target point to the prediction point is calculated according to the vehicle speed; a second lateral angle of the vehicle at the third target point and a third lateral angle of the prediction point are determined respectively, and a predicted yaw velocity of the vehicle is calculated according to the second lateral angle, the third lateral angle and the time interval; a third curve curvature of the third target point is obtained, and a second lateral acceleration of the vehicle is calculated using the third curve curvature and the vehicle speed; a third proportional control coefficient corresponding to the second lateral acceleration in the yaw velocity dimension is determined; an actual yaw velocity of the vehicle is obtained, and a third steering wheel angle is calculated according to the actual yaw velocity, the third proportional control coefficient and the predicted yaw velocity.

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