Vehicle control method and device, vehicle and storage medium

Abstract

The invention discloses a vehicle control method and device, a vehicle and a readable storage medium, and the method comprises the steps: determining a target path point and a related path point corresponding to the target path point from a planned path of a vehicle according to the pose information of the vehicle; determining a course angle proportionality coefficient according to the curvature of the related path points in the planned path and the speed of the vehicle; according to the path point information of the target path point, the course angle proportionality coefficient, a preset course angle integral coefficient and a preset course angle differential coefficient, the course angle deviation feedback control quantity of the vehicle is determined; and controlling the vehicle according to the course angle deviation feedback control quantity. According to the method, real-time adjustment of the course angle proportionality coefficient according to the curvature of the related path point and the vehicle speed of the vehicle is achieved, the accuracy of the course angle proportionality coefficient is high, the accuracy of the determined course angle deviation feedback control quantity is high, and then the accuracy of vehicle control is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and more specifically, to a vehicle control method, device, vehicle, and computer-readable storage medium. Background Art

[0002] Vehicle intelligent driving control is one of the research hotspots in the vehicle field today. The performance of vehicle intelligent driving control directly affects the user experience. Vehicle intelligent driving control usually adopts a control scheme that decouples lateral control and longitudinal control. Lateral control outputs steering wheel angle and longitudinal control outputs driving torque, thereby achieving vehicle control based on steering wheel angle and driving torque.

[0003] However, using existing control methods, the vehicle control accuracy is low, resulting in a poor user experience of the vehicle's intelligent driving control function. Summary of the invention

[0004] The present application proposes a vehicle control method, device, vehicle and computer-readable storage medium to improve the vehicle control accuracy and thereby improve the experience of the vehicle's intelligent driving control function.

[0005] In a first aspect, an embodiment of the present application provides a vehicle control method, the method comprising:

[0006] According to the position information of the ego vehicle, the target path point and the related path points corresponding to the target path point are determined from the planned path of the ego vehicle;

[0007] Determine the heading angle proportional coefficient according to the curvature at the relevant path points in the planned path and the speed of the vehicle;

[0008] The heading angle deviation feedback control amount of the ego vehicle is determined according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient and the preset heading angle differential coefficient; the heading angle deviation feedback control amount is used to indicate the angle corrected for the steering wheel of the ego vehicle when correcting the deviation of the heading angle of the ego vehicle;

[0009] The vehicle is controlled according to the heading angle deviation feedback control quantity.

[0010] In a second aspect, an embodiment of the present application further provides a vehicle control device, the device comprising:

[0011] A first determination module is used to determine a target path point and related path points corresponding to the target path point from a planned path of the vehicle according to the position information of the vehicle;

[0012] A coefficient determination module is used to determine the heading angle proportional coefficient according to the curvature at the relevant path points in the planned path and the speed of the vehicle;

[0013] The second determination module is used to determine the heading angle deviation feedback control amount of the ego vehicle according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient and the preset heading angle differential coefficient; the heading angle deviation feedback control amount is used to indicate the angle corrected for the steering wheel of the ego vehicle when correcting the deviation of the heading angle of the ego vehicle;

[0014] The control module is used to control the vehicle according to the heading angle deviation feedback control amount.

[0015] In a third aspect, an embodiment of the present application further provides a vehicle, characterized in that the vehicle comprises: one or more processors; a memory; one or more applications, wherein one or more applications are stored in the memory and configured to be executed by one or more processors, and one or more programs are configured to execute the above method.

[0016] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores a program code executable by a processor, and when the program code is executed by the processor, the processor executes the above method.

[0017] The present application provides a vehicle control method, device, vehicle and computer-readable storage medium. In the present application, a target path point and related path points corresponding to the target path point are determined from a planned path of the self-vehicle, and then a heading angle proportional coefficient is determined according to the curvature at the related path points in the planned path and the speed of the self-vehicle, thereby achieving real-time adjustment of the heading angle proportional coefficient according to the curvature at the related path points and the speed of the self-vehicle, so that the heading angle proportional coefficient is related to the real-time driving process of the self-vehicle, and the accuracy of the heading angle proportional coefficient is relatively high, so that the heading angle deviation feedback control amount determined according to the heading angle proportional coefficient has a high accuracy, thereby improving the accuracy of the self-vehicle control based on the heading angle deviation feedback control amount, greatly reducing the tracking deviation when the accuracy of the heading angle deviation feedback control amount determined by using a fixed heading angle proportional coefficient is low, and the occurrence of the self-vehicle head-shaking caused by the low accuracy of the self-vehicle control, thereby effectively improving the user experience of the vehicle's intelligent driving control function.

[0018] Other features and advantages of the embodiments of the present application will be described in the subsequent description, and partly become apparent from the description, or can be understood by practicing the embodiments of the present application. The purposes and other advantages of the embodiments of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A schematic diagram of a vehicle hardware environment suitable for an embodiment of the present application is shown.

[0021] Figure 2 A flow chart of a vehicle control method proposed according to an embodiment of the present application is shown.

[0022] Figure 3 Show Figure 2 The corresponding step S140 of the embodiment is a flowchart in an embodiment.

[0023] Figure 4 A schematic diagram showing a vehicle control process in an embodiment of the present application.

[0024] Figure 5 A structural block diagram of a vehicle control device proposed in one embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] In order to make those skilled in the art better understand the present application scheme, the technical scheme in the present application embodiment will be clearly and completely described below in conjunction with the drawings in the present application embodiment. Obviously, the described embodiment is only a part of the present application embodiment, rather than all the embodiments. The components of the present application embodiment usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but merely represents the selected embodiment of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0026] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0027] Reference Figure 1 , Figure 1A schematic diagram of a vehicle hardware environment suitable for an embodiment of the present application is shown, wherein the vehicle 100 includes a driving system 110, which may have multiple built-in autonomous driving functions. The driving system 110 may store an electronic map, and the driving system 110 may plan a driving route based on the electronic map stored in the driving system, and may also control the vehicle's autonomous driving based on the planned driving route.

[0028] The driving system 110 may include a data acquisition device 111 , one or more (only one is shown in the figure) processors 112 , and a memory 113 .

[0029] The data acquisition device 111 is used to detect the vehicle's posture information and the environmental information around the vehicle. The data acquisition device 111 may include an in-vehicle camera, an in-vehicle infrared sensor, an in-vehicle monitoring radar, an outside-vehicle camera, an outside-vehicle monitoring radar, a door monitoring radar, a vehicle speed sensor, and a steering wheel angle sensor.

[0030] The processor 112 may be a microcontroller unit (MCU) having a built-in memory 113 . The memory 113 stores a program that can execute the contents of the following embodiments, and the processor 112 may execute the program stored in the memory 113 .

[0031] The processor 112 may include one or more processors. The processor 112 uses various interfaces and lines to connect various parts of the entire vehicle 100, and executes various functions of the vehicle 100 and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 113, and calling data stored in the memory 113.

[0032] The memory 113 may include a random access memory (RAM) or a read-only memory (ROM). The memory 15 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 15 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the following various method embodiments, etc.

[0033] See also Figure 2 , Figure 2 A flow chart of a vehicle control method proposed according to an embodiment of the present application is shown, which is used for a vehicle, and the method includes:

[0034] S110: Determine a target path point and related path points corresponding to the target path point from the planned path of the vehicle according to the position information of the vehicle.

[0035] The vehicle in this embodiment can be an electric vehicle or a fuel vehicle, or a sedan, an SUV, a bus, a truck, etc.; the self-vehicle refers to the vehicle itself.

[0036] The position information of the vehicle refers to information indicating the position and posture of the vehicle. The position information of the vehicle may include coordinates (x a ,y a ), the coordinates may refer to the coordinates of the ego vehicle in the xoy coordinate plane of the world coordinate system, the coordinates may refer to the coordinates of key points on the ego vehicle, and the key points on the ego vehicle may be the center of mass of the ego vehicle, the center point of the rear axle of the ego vehicle, etc.; the posture information of the ego vehicle may also include the actual heading angle φ used to indicate the posture of the ego vehicle a and vehicle speed v a (the actual speed of the vehicle), etc.

[0037] In this embodiment, the position and posture information of the vehicle can be collected by various sensors in the vehicle, and the sensors may include, for example, a vehicle speed sensor and a steering wheel angle sensor, etc. In this embodiment, the position and posture information of the vehicle may refer to the real-time position and posture information of the vehicle when executing the vehicle control method of the present application.

[0038] The planned path of the self-vehicle refers to the path planned by the self-vehicle's track calculation module based on the driving state of the self-vehicle. Among them, the track calculation module can calculate the track of the self-vehicle according to the speed, acceleration, surrounding obstacles, speed of obstacles, acceleration of obstacles and road information of the self-vehicle to obtain the planned path of the self-vehicle. The planned path of the self-vehicle may include multiple path points, each path point corresponds to a planning time. If the self-vehicle drives according to the planned path points, the planning time corresponding to each path point is reached, and the self-vehicle is located at the path point; multiple path points are connected in sequence to form a planned path, wherein the order of the path points refers to the order of the planning time corresponding to the path points, that is, the path point with the earlier planning time is located in front of the path point with the later planning time. Among them, the planning time can be set based on demand, for example, the interval between any two adjacent planning times is 0.1s.

[0039] Each path point in the planned path corresponds to its own path point information, and the path point information of the path point may include the coordinates (x r ,y r ) and attitude, wherein the coordinates in the path point information of the waypoint may refer to the coordinates of the waypoint in the xoy coordinate plane of the world coordinate system, and the attitude in the path point information of the waypoint may include the desired heading angle φ of the vehicle at the waypoint r And the curvature k at the path point in the planned path r And other information.

[0040] After obtaining the position information and the planned path of the vehicle, a target path point and related path points corresponding to the target path point are determined from multiple path points included in the planned path of the vehicle based on the position information and the planned path of the vehicle.

[0041] In this embodiment, the relevant path point corresponding to the target path point may refer to the path point in the planned path of the vehicle that is closest to the target path point, or may refer to the path point in the planned path of the vehicle that has the most similar path point information to the target path point, wherein the most similar path point information means that the relative distance is within a preset threshold range and the posture is most similar; the preset threshold range can be set based on demand, for example, the preset threshold range is 0.5m. The most similar posture may mean that the difference in the expected heading angle is the smallest or the difference in curvature is the smallest.

[0042] In some embodiments, the planned path includes a plurality of ordered path points (wherein the order of the plurality of path points refers to the above description and is not repeated here); the related path points include a first related path point and a second related path point; S110 may include: according to the posture information of the vehicle, determining from the plurality of path points a path point with the smallest distance difference to the vehicle as a target path point; determining from the plurality of path points a first path point located after the target path point as a first related path point; determining from the plurality of path points a second path point located after the target path point as a second related path point.

[0043] After determining the target path point closest to the vehicle, the first path point after the target path point in the planned path is obtained as the first related path point, and the second path point after the target path point in the planned path is obtained as the second related path point.

[0044] S120: Determine a heading angle proportional coefficient according to the curvature at relevant path points in the planned path and the speed of the vehicle.

[0045] The speed of the vehicle refers to the actual speed in the position information of the vehicle. After the relevant path points are determined, the curvature at the relevant path points can be obtained from the path point information of the relevant path points, and then the heading angle proportional coefficient can be determined by combining the curvature at the relevant path points and the speed of the vehicle.

[0046] In some embodiments, the relevant path points include a first relevant path point and a second relevant path point. Accordingly, S120 may include: determining an adjustment coefficient based on the vehicle speed and a calibration constant; the adjustment coefficient is positively correlated with the vehicle speed; determining an adjustment amplitude based on a curvature difference between a curvature at a first relevant path point and a curvature at a second relevant path point in the planned path; the adjustment amplitude is positively correlated with the curvature difference; determining a heading angle proportional coefficient based on the sine value of the adjustment amplitude and the adjustment coefficient.

[0047] In this embodiment, the calibration constant can be set based on demand and is not limited. For example, the calibration constant can include a first calibration constant d and a second calibration constant e, so that according to the first calibration constant d, the second calibration constant e and the vehicle speed v a , determine the adjustment coefficient, wherein the process of determining the adjustment coefficient a refers to formula 1, which is as follows:

[0048] a=d*v a +e

[0049] It is understandable that Formula 1 is only an example, and other methods of calculating the adjustment coefficient may be determined as long as the adjustment coefficient is positively correlated with the vehicle speed.

[0050] After the adjustment coefficient a is obtained, the adjustment amplitude can be determined based on the curvature difference between the curvature at the first relevant path point and the curvature at the second relevant path point in the planned path, and other calibration constants. Exemplarily, the other calibration constants may include a third calibration constant b and a fourth calibration constant c. Accordingly, the process of determining the adjustment amplitude f may refer to Formula 2, which is as follows:

[0051] f=b*(k n+1 ―k n+2 )+c

[0052] Among them, k n+1 is the curvature at the first relevant path point in the planned path, k n+2 is the curvature at the second relevant path point in the planned path, (k n+1 ―k n+2 ) is the curvature difference between the curvature at the first relevant path point and the curvature at the second relevant path point.

[0053] It is understandable that Formula 2 is only an example, and other methods for calculating the adjustment range may be determined as long as the adjustment range is positively correlated with the curvature difference.

[0054] After the adjustment amplitude f is obtained, the heading angle proportional coefficient can be determined by combining the sine value of the adjustment amplitude and the adjustment coefficient. For example, the product of the sine value of the adjustment amplitude f and the adjustment coefficient a can be calculated as the heading angle proportional coefficient. When the adjustment coefficient a is determined according to Formula 1 and the adjustment amplitude f is determined according to Formula 2, the determination process of the heading angle proportional coefficient refers to Formula 3, which is as follows:

[0055] K p―psi =a*sinf=a*sin[b*(k n+1 ―k n+2 )+c]

[0056] Among them, Kp―psi is the heading angle scale factor.

[0057] In this embodiment, for the convenience of description, k n represents the curvature at the target path point in the planned path, k n+1 represents the curvature at the first relevant path point in the planned path, k n+2 It represents the curvature at the second relevant path point in the planned path. The curvature of the path point at the future planning moment during the driving process of the ego vehicle is used to obtain the changes in the planned path in advance to deal with the poor curve tracking accuracy caused by the action delay of the ego vehicle and the vehicle shaking problem caused by control overshoot after exiting the curve.

[0058] However, when k n ≠k n+1 ≠k n+2 When k is , the curvature of three consecutive path points is discontinuous, which means that the vehicle is in the variable curvature path tracking stage. At this time, the response of the heading angle deviation feedback controller is expected to be larger, and the deviation caused by the delayed response of the fast convergence action is delayed. n ≠k n+1 =k n+2 , which means that the variable curvature path stage is over. At this time, it is expected that the output of the heading angle deviation feedback controller should be as stable as possible to reduce the control out of range. Therefore, based on the above analysis, it is determined that the heading angle deviation feedback controller maintains a fixed heading angle integral coefficient and heading angle differential coefficient, and uses an adjustable heading angle proportional coefficient. The acquisition process of the adjustable heading angle proportional coefficient is as above and will not be repeated.

[0059] S130, determining a heading angle deviation feedback control amount of the vehicle according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient, and the preset heading angle differential coefficient.

[0060] Among them, the heading angle deviation feedback control amount is used to indicate the angle corrected for the steering wheel of the own vehicle when correcting the deviation of the heading angle of the own vehicle; in other words, after the own vehicle controls the steering wheel to turn according to the heading angle deviation feedback control amount of the own vehicle, the deviation of the heading angle of the own vehicle is eliminated.

[0061] After obtaining the heading angle proportional coefficient, the preset heading angle integral coefficient and the heading angle differential coefficient are obtained, so that the heading angle deviation feedback controller can determine the heading angle deviation feedback control amount of the vehicle according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient and the preset heading angle differential coefficient; wherein, the preset heading angle integral coefficient and the heading angle differential coefficient are values ​​that can be set based on demand, and this application does not impose any constraints, wherein, under different driving conditions, the preset heading angle integral coefficient and the heading angle differential coefficient are fixed.

[0062] In this embodiment, the heading angle deviation feedback controller can be a PID (Proportion Integration Differentiation, proportional-integral-differential) controller, that is, the heading angle

[0063] The deviation feedback controller performs proportional-integral-differential operations based on the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient, and the preset heading angle differential coefficient, and the operation result obtained is the heading angle deviation feedback control amount of the vehicle.

[0064] In some embodiments, S130 may include: determining the heading angle deviation based on the difference between the expected heading angle in the waypoint information of the target waypoint and the actual heading angle in the posture information of the vehicle; determining the heading angle deviation feedback control amount based on the heading angle deviation, the heading angle proportional coefficient, the heading angle integral coefficient and the heading angle differential coefficient.

[0065] The heading angle of the vehicle can be obtained from the vehicle's posture information as the actual heading angle φ of the vehicle a , and obtain the desired heading angle φ at the target path point from the path point information of the target path point rn , then, φ can be calculated rn With φ a The difference between the heading angle and the heading angle is taken as the heading angle deviation. psi =φ rn ―φ a .

[0066] Afterwards, the heading angle deviation feedback controller is based on e psi A proportional-integral-differential operation is performed to obtain a heading angle deviation feedback control amount, wherein the proportional-integral-differential operation refers to Formula 4, which is as follows:

[0067]

[0068] Among them, u psi (t) is the heading angle deviation feedback control quantity, K I―psi is the preset heading angle integral coefficient, K d―psi is the preset heading angle differential coefficient, t is the planning time of the target path point; ∫e psi (t)dt is the integral of the heading angle deviations at each planning moment before the planning moment t within the planning period (the planning period can be a fixed period set based on demand, for example, every 5 seconds is a planning period) where the planning moment t is located (that is, the accumulated heading angle deviation). It is the rate of change of heading angle deviation corresponding to the planning time t (generally, it is the difference between the heading angle deviation at the planning time t and the heading angle deviation at the planning time t-1).

[0069] As shown in the above formula 4, the heading angle deviation feedback controller actually performs a weighted summation of the heading angle deviation, the cumulative heading angle deviation and the heading angle deviation change rate, wherein the weight of the heading angle deviation is the heading angle proportional coefficient, the weight of the cumulative heading angle deviation is the heading angle integral coefficient, and the weight of the heading angle deviation change rate is the heading angle differential coefficient.

[0070] S140: Control the vehicle according to the heading angle deviation feedback control amount.

[0071] After the heading angle deviation feedback control amount is obtained, the vehicle is controlled according to the heading angle deviation feedback control amount.

[0072] Among them, the heading angle deviation feedback control amount is the control parameter of the ego vehicle in the lateral control direction. Therefore, the steering wheel angle of the ego vehicle's steering wheel can be determined based on the heading angle deviation feedback control amount, and then the steering wheel rotation of the ego vehicle can be controlled by the steering wheel angle to achieve lateral control of the ego vehicle.

[0073] The driving torque of the vehicle in the longitudinal control direction can be determined based on existing control means, so as to control the vehicle laterally and longitudinally in combination with the driving torque and the steering wheel angle determined according to the method of the present application.

[0074] It is worth mentioning that the vehicle control method of the present application can be used in the driving process and parking process of the vehicle, etc., and is not limited to one of the driving process or the parking process of the vehicle.

[0075] In this embodiment, the target path point and the related path points corresponding to the target path point are determined from the planned path of the self-vehicle, and then the heading angle proportional coefficient is determined according to the curvature at the related path points in the planned path and the speed of the self-vehicle, so that the heading angle proportional coefficient is adjusted in real time according to the curvature at the related path points and the speed of the self-vehicle, so that the heading angle proportional coefficient is related to the real-time driving process of the self-vehicle, and the accuracy of the heading angle proportional coefficient is relatively high, so that the heading angle deviation feedback control amount determined according to the heading angle proportional coefficient has a high accuracy, and the accuracy of the self-vehicle control based on the heading angle deviation feedback control amount is improved, and the tracking deviation when the accuracy of the heading angle deviation feedback control amount determined by using a fixed heading angle proportional coefficient is low, and the occurrence of the self-vehicle head-shaking caused by the low accuracy of the self-vehicle control is greatly reduced, thereby effectively improving the user experience of the vehicle intelligent driving control function.

[0076] At the same time, in this embodiment, a specific means for determining the heading angle proportional coefficient is also proposed, so that the accuracy of the determined heading angle proportional coefficient is further improved, thereby further improving the accuracy of the self-vehicle control.

[0077] In one embodiment, if Figure 3As shown, S140 may include:

[0078] S210: Determine a lateral distance deviation according to the position information of the vehicle and the path point information of the target path point.

[0079] Based on the posture information of the vehicle and the waypoint information of the target waypoint, the distance deviation in the lateral direction may be determined as the lateral distance deviation.

[0080] Specifically, the position difference between the ego vehicle and the target path point can be determined based on the position information in the ego vehicle's posture information and the position information in the path point information of the target path point; according to the expected heading angle in the path point information of the target path point, the position difference is projected in the lateral direction of the ego vehicle to obtain the lateral distance deviation.

[0081] For example, the position information of the vehicle can be (x a ,y a ), the location information of the target path point is (x rn ,y rn ), at this time, the position difference between the vehicle and the target path point can include the difference in the x direction (x rn -x a ) and the difference in the y direction (y rn -y a ), then, based on Formula 5, the position difference between the ego vehicle and the target path point is projected in the lateral direction of the ego vehicle to obtain the lateral distance deviation e dist , Formula 5 is as follows:

[0082]

[0083] S220: Determine a lateral distance deviation feedback control amount of the vehicle based on the lateral distance deviation, a preset lateral distance proportional coefficient, a preset lateral distance integral coefficient, and a preset lateral distance differential coefficient.

[0084] Among them, the lateral distance deviation feedback control amount is used to indicate the angle of correction for the steering wheel of the own vehicle when correcting the deviation of the lateral distance of the own vehicle; in other words, after the own vehicle controls the steering wheel to turn according to the lateral distance deviation feedback control amount of the own vehicle, the deviation of the lateral distance of the own vehicle is eliminated.

[0085] In this embodiment, the lateral distance deviation feedback control amount of the vehicle can be determined by the lateral distance deviation feedback controller according to the lateral distance deviation, the preset lateral distance proportional coefficient, the preset lateral distance integral coefficient and the preset lateral distance differential coefficient; wherein, the preset lateral distance proportional coefficient, the lateral distance integral coefficient and the lateral distance differential coefficient are values ​​that can be set based on demand, and this application does not impose any constraints, wherein, under different driving conditions, the preset lateral distance proportional coefficient, the lateral distance integral coefficient and the lateral distance differential coefficient are fixed.

[0086] Among them, the lateral distance deviation feedback controller and the heading angle deviation feedback controller are both objective manifestations of the lateral control performance of the vehicle, and the two are strongly coupled. Therefore, the lateral control needs to be designed by taking both into account. However, in actual driving, especially in parking, the heading angle deviation is more obvious than the lateral distance deviation. Therefore, the lateral distance deviation feedback controller is set to use a fixed coefficient (that is, a fixed lateral distance proportional coefficient, a fixed lateral distance integral coefficient and a fixed lateral distance differential coefficient), and the heading angle deviation feedback controller uses a fixed heading angle integral coefficient, a fixed heading angle differential coefficient and a real-time adjusted heading angle proportional coefficient.

[0087] In this embodiment, the lateral distance deviation feedback controller can be a PID (Proportion Integration Differentiation) controller, that is, the lateral distance deviation feedback controller performs proportional-integral-differential operations according to the lateral distance deviation, a preset lateral distance proportional coefficient, a preset lateral distance integral coefficient, and a preset lateral distance differential coefficient, and the operation result obtained is the lateral distance deviation feedback control amount of the vehicle.

[0088] The lateral distance deviation feedback controller is based on the lateral distance deviation e dist The proportional-integral-differential operation process refers to Formula 6, which is as follows:

[0089]

[0090] Among them, u dist (t) is the lateral distance deviation feedback control quantity, K p―dist is the preset horizontal distance scale factor, K I―dist is the preset lateral distance integral coefficient, K d―dist is the preset lateral distance differential coefficient, t is the planning time of the target path point; ∫e dist (t)dt is the integral of the lateral distance deviations of each planning time before planning time t in the planning cycle where planning time t is located (that is, the cumulative lateral distance deviation), is the change rate of the lateral distance deviation corresponding to the planning time t (generally the difference between the lateral distance deviation at the planning time t and the lateral distance deviation at the planning time t-1).

[0091] As shown in the aforementioned formula six, the lateral distance deviation feedback controller actually performs a weighted summation of the lateral distance deviation, the cumulative lateral distance deviation and the lateral distance deviation change rate, wherein the weight of the lateral distance deviation is the lateral distance proportional coefficient, the weight of the cumulative lateral distance deviation is the lateral distance integral coefficient, and the weight of the lateral distance deviation change rate is the lateral distance differential coefficient.

[0092] S230: Determine a feedforward calibration amount according to the curvature at the target path point in the planned path.

[0093] Among them, the feedforward calibration quantity is used to indicate the ideal steering wheel angle corresponding to the ego vehicle when the ego vehicle drives to the target path point according to the planned path; generally speaking, under ideal conditions, the ego vehicle drives according to the planned path. If the ego vehicle drives to the target path point according to the planned path, the steering wheel angle of the ego vehicle when the ego vehicle is at the target path point is obtained as the ideal steering wheel angle corresponding to the ego vehicle.

[0094] In some embodiments, a target correspondence for the vehicle can be obtained; the target correspondence is used to indicate the correspondence between a calibrated steering wheel angle and a calibrated curvature of the steering wheel; based on the target correspondence, a calibrated steering wheel angle corresponding to the curvature at the target path point in the planned path is determined as a feedforward calibration quantity.

[0095] Among them, different vehicles have different structures, so the target correspondence relationship can be different. The same vehicle model has the same structure, so the target correspondence relationship of vehicles of the same vehicle model can be the same. The target correspondence relationship can be expressed in the form of a curve or a table. The target correspondence relationship involves two quantities, the steering wheel angle and the curvature. Based on the needs, multiple calibrated steering wheel angles can be set for the steering wheel of the vehicle. For each steering wheel angle, the respective curvature is determined as the calibrated curvature corresponding to each calibrated steering wheel angle. According to each calibrated steering wheel angle and the calibrated curvature corresponding to each calibrated steering wheel angle, a curve or a table is drawn to obtain the target correspondence relationship.

[0096] After the target correspondence is obtained, a calibrated steering wheel angle corresponding to the curvature at the target path point in the planned path can be determined from the target correspondence as a feedforward calibration quantity.

[0097] S240: Determine a steering wheel angle of the steering wheel of the vehicle based on the heading angle deviation feedback control amount, the lateral distance deviation feedback control amount, and the feedforward calibration amount.

[0098] For example, the heading angle deviation feedback control amount, the lateral distance deviation feedback control amount and the feedforward calibration amount can be superimposed, and the superimposed result is used as the steering wheel angle. The means for achieving superposition include but are not limited to summation, weighted summation, etc.

[0099] S250: Control the vehicle according to the steering wheel angle.

[0100] After obtaining the steering wheel angle, the steering wheel angle can be transmitted to the actuator EPS (Electronic Power Steering) in the vehicle, and the actuator EPS of the vehicle controls the vehicle based on the steering wheel angle to achieve lateral control of the vehicle.

[0101] The vehicle control process of this embodiment is as follows Figure 4 As shown, first, the target path point is determined from the planned path of the ego vehicle, and then the relevant path points are selected based on the target path point. At the same time, the lateral distance deviation and the heading angle deviation are determined according to the path point information of the target path point and the posture information of the ego vehicle. After that, the heading angle proportional coefficient is determined according to the speed of the ego vehicle and the curvature of the relevant path points; and the heading angle deviation feedback control amount and the lateral distance deviation feedback control amount are determined. Finally, in the vehicle control stage, the feedforward calibration amount is obtained, and based on the feedforward calibration amount, the heading angle deviation feedback control amount and the lateral distance deviation feedback control amount, the steering wheel angle is output to the actuator (that is, the aforementioned EPS), and the actuator realizes vehicle control.

[0102] In this embodiment, the heading angle ratio parameter is adjusted in real time in the lateral control direction of the vehicle, so that the heading angle ratio parameter is related to the driving condition of the vehicle, and the heading angle ratio parameter is accurate, so that the heading angle deviation feedback control amount determined according to the heading angle ratio parameter is more accurate, thereby improving the accuracy of the determined steering wheel angle, thereby effectively reducing the occurrence of the vehicle's head shaking problem caused by large tracking deviation and heading angle exceeding the adjustment range, thereby improving the user experience of the vehicle's intelligent driving function.

[0103] See attached Figure 5 , Figure 5 The structure block diagram of a vehicle control device proposed in one embodiment of the present application is shown. For use in a vehicle, the device 800 includes:

[0104] A first determination module 810 is used to determine a target path point and related path points corresponding to the target path point from a planned path of the vehicle according to the position information of the vehicle;

[0105] A coefficient determination module 820 is used to determine a heading angle proportional coefficient according to the curvature at the relevant path points in the planned path and the speed of the vehicle;

[0106] The second determination module 830 is used to determine the heading angle deviation feedback control amount of the ego vehicle according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient and the preset heading angle differential coefficient; the heading angle deviation feedback control amount is used to indicate the angle corrected for the steering wheel of the ego vehicle when correcting the deviation of the heading angle of the ego vehicle;

[0107] The control module 840 is used to control the vehicle according to the heading angle deviation feedback control amount.

[0108] Optionally, the relevant path points include a first relevant path point and a second relevant path point; the coefficient determination module 820 is also used to determine the adjustment coefficient based on the vehicle speed and the calibration constant; the adjustment coefficient is positively correlated with the vehicle speed; based on the curvature difference between the curvature at the first relevant path point and the curvature at the second relevant path point in the planned path, the adjustment amplitude is determined; the adjustment amplitude is positively correlated with the curvature difference; based on the sine value of the adjustment amplitude and the adjustment coefficient, the heading angle proportional coefficient is determined.

[0109] Optionally, the second determination module 830 is also used to determine the heading angle deviation based on the difference between the expected heading angle in the waypoint information of the target waypoint and the actual heading angle in the posture information of the vehicle; and determine the heading angle deviation feedback control amount based on the heading angle deviation, the heading angle proportional coefficient, the heading angle integral coefficient and the heading angle differential coefficient.

[0110] Optionally, the planned path includes multiple ordered path points; the related path points include a first related path point and a second related path point; the first determination module 810 is also used to determine, based on the posture information of the vehicle, from the multiple path points the path point with the smallest distance difference from the vehicle as the target path point; determine from the multiple path points the first path point located after the target path point as the first related path point; determine from the multiple path points the second path point located after the target path point as the second related path point.

[0111] Optionally, the control module 840 is also used to determine the lateral distance deviation based on the posture information of the self-vehicle and the path point information of the target path point; determine the lateral distance deviation feedback control amount of the self-vehicle based on the lateral distance deviation, the preset lateral distance proportional coefficient, the preset lateral distance integral coefficient and the preset lateral distance differential coefficient; the lateral distance deviation feedback control amount is used to indicate the angle corrected for the steering wheel of the self-vehicle when correcting the deviation of the lateral distance of the self-vehicle; determine the feedforward calibration amount based on the curvature at the target path point in the planned path; the feedforward calibration amount is used to indicate the ideal steering wheel angle corresponding to the self-vehicle when the self-vehicle travels to the target path point according to the planned path; determine the steering wheel angle of the steering wheel of the self-vehicle based on the heading angle deviation feedback control amount, the lateral distance deviation feedback control amount and the feedforward calibration amount; and control the self-vehicle according to the steering wheel angle.

[0112] Optionally, the control module 840 is also used to determine the position difference between the ego vehicle and the target path point based on the position information in the ego vehicle's posture information and the position information in the path point information of the target path point; and project the position difference in the lateral direction of the ego vehicle according to the expected heading angle in the path point information of the target path point to obtain a lateral distance deviation.

[0113] Optionally, the control module 840 is also used to obtain a target correspondence for the vehicle; the target correspondence is used to indicate the correspondence between the calibrated steering wheel angle and the calibrated curvature of the steering wheel; based on the target correspondence, the calibrated steering wheel angle corresponding to the curvature at the target path point in the planned path is determined as a feedforward calibration quantity.

[0114] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0115] In addition, each function in each embodiment of the present application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of software function module.

[0116] In addition, each function in each embodiment of the present application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of software function module.

[0117] In addition, each function in each embodiment of the present application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of software function module.

[0118] On the other hand, the present application also provides a computer-readable storage medium, in which program code is stored. The program code can be called by a processor to execute the method described in the above method embodiment.

[0119] The computer readable storage medium may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk, or a cluster of ROMs. Optionally, the computer readable storage medium comprises a non-transitory computer-readable storage medium. The computer readable storage medium has storage space for program codes that execute any of the method steps in the above method. These program codes can be read from or written to one or more computer program products. The program code can be compressed, for example, in an appropriate form.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A vehicle control method, characterized in that: The method comprises: Determining a target path point and related path points corresponding to the target path point from a planned path of the vehicle according to the position information of the vehicle; Determining a heading angle proportional coefficient according to the curvature at the relevant path points in the planned path and the speed of the vehicle; Determine the heading angle deviation feedback control amount of the ego vehicle according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient and the preset heading angle differential coefficient; the heading angle deviation feedback control amount is used to indicate the angle corrected for the steering wheel of the ego vehicle when correcting the deviation of the heading angle of the ego vehicle; The vehicle is controlled according to the heading angle deviation feedback control amount.

2. The method according to claim 1, characterized in that The relevant path points include a first relevant path point and a second relevant path point; The determining of the heading angle proportional coefficient according to the curvature at the relevant path points in the planned path and the speed of the vehicle comprises: Determining an adjustment coefficient according to the vehicle speed and a calibration constant; the adjustment coefficient is positively correlated with the vehicle speed; determining an adjustment amplitude based on a curvature difference between a curvature at the first relevant path point and a curvature at the second relevant path point in the planned path; the adjustment amplitude being positively correlated with the curvature difference; The heading angle proportional coefficient is determined based on the sine value of the adjustment amplitude and the adjustment coefficient.

3. The method according to claim 1, characterized in that The method of determining the heading angle deviation feedback control amount of the vehicle according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient and the preset heading angle differential coefficient includes: Determining a heading angle deviation according to a difference between an expected heading angle in the waypoint information of the target waypoint and an actual heading angle in the posture information of the ego vehicle; A heading angle deviation feedback control amount is determined based on the heading angle deviation, the heading angle proportional coefficient, the heading angle integral coefficient, and the heading angle differential coefficient.

4. The method according to claim 1, characterized in that: The planned path includes a plurality of ordered path points; the related path points include a first related path point and a second related path point; The step of determining a target path point and related path points corresponding to the target path point from a planned path of the vehicle according to the position information of the vehicle includes: According to the position information of the vehicle, determine, from the plurality of path points, a path point with the smallest distance difference from the vehicle as a target path point; Determine a first path point located after the target path point from the plurality of path points as the first relevant path point; A second path point located after the target path point is determined from the multiple path points as the second related path point.

5. The method according to claim 1, characterized in that The controlling the vehicle according to the heading angle deviation feedback control amount includes: Determining a lateral distance deviation according to the posture information of the vehicle and the path point information of the target path point; Determining a lateral distance deviation feedback control amount of the vehicle based on the lateral distance deviation, a preset lateral distance proportional coefficient, a preset lateral distance integral coefficient, and a preset lateral distance differential coefficient; the lateral distance deviation feedback control amount is used to indicate an angle corrected for the steering wheel of the vehicle when correcting the deviation of the lateral distance of the vehicle; Determining a feedforward calibration amount according to the curvature at the target path point in the planned path; the feedforward calibration amount is used to indicate an ideal steering wheel angle corresponding to the vehicle when the vehicle travels to the target path point according to the planned path; Determining a steering wheel angle of the steering wheel of the vehicle based on the heading angle deviation feedback control amount, the lateral distance deviation feedback control amount and the feedforward calibration amount; The vehicle is controlled according to the steering wheel angle.

6. The method according to claim 5, characterized in that The determining of the lateral distance deviation according to the posture information of the vehicle and the path point information of the target path point includes: Determining a position difference between the ego vehicle and the target path point based on the position information in the ego vehicle's posture information and the position information in the path point information of the target path point; According to the expected heading angle in the waypoint information of the target waypoint, the position difference is projected in the lateral direction of the vehicle to obtain a lateral distance deviation.

7. The method according to claim 5, characterized in that The step of determining a feedforward calibration amount according to the curvature at the target path point in the planned path includes: Acquire a target correspondence relationship for the vehicle; the target correspondence relationship is used to indicate a correspondence relationship between a calibrated steering wheel angle and a calibrated curvature of the steering wheel; Based on the target correspondence, a calibrated steering wheel angle corresponding to the curvature at the target path point in the planned path is determined as the feedforward calibration amount.

8. A vehicle control device, characterized in that: The device comprises: A first determination module is used to determine a target path point and related path points corresponding to the target path point from a planned path of the ego vehicle according to the position information of the ego vehicle; A coefficient determination module, used to determine a heading angle proportional coefficient according to the curvature at the relevant path points in the planned path and the speed of the vehicle; A second determination module is used to determine the heading angle deviation feedback control amount of the ego vehicle according to the path point information of the target path point, the heading angle proportional coefficient, the preset heading angle integral coefficient and the preset heading angle differential coefficient; the heading angle deviation feedback control amount is used to indicate the angle corrected for the steering wheel of the ego vehicle when correcting the deviation of the heading angle of the ego vehicle; A control module is used to control the vehicle according to the heading angle deviation feedback control amount.

9. A vehicle, characterized in that: include: one or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program code executable by a processor, and when the program code is executed by the processor, the processor executes the method according to any one of claims 1 to 7.

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