Vehicle driving control method, device, electronic equipment and storage medium

Abstract

The embodiment of the present invention discloses a vehicle driving control method, device, electronic device and storage medium. The method comprises: obtaining the current acceleration of the target vehicle in the current driving state, and determining the current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship, wherein the first corresponding relationship is the corresponding relationship between the driving acceleration and cornering stiffness of the target vehicle; determining the target control parameters corresponding to the target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle; and controlling the target vehicle to travel according to the expected trajectory information based on the target control parameters. The technical solution of the embodiment of the present invention can improve the accuracy of the target control parameters, and can effectively and stably control the driving of the target vehicle.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of vehicle control technology, and in particular to a vehicle driving control method, device, electronic device and storage medium. Background Art

[0002] With the rapid development of artificial intelligence technology, intelligent driving cars have been widely used. In the prior art, a three-degree-of-freedom dynamic model is usually established for the structure of an intelligent vehicle using a fixed lateral stiffness, and the front wheel angle sequence is analyzed to obtain the front wheel angle sequence, and the intelligent driving car is controlled to travel along a preset route based on the front wheel angle sequence. However, assuming the lateral stiffness as a fixed value reduces the accuracy of the established three-degree-of-freedom dynamic model, and the obtained front wheel angle sequence has poor accuracy, making it impossible to effectively and stably track the path of the intelligent driving car. Summary of the invention

[0003] The embodiments of the present invention provide a vehicle driving control method, device, electronic device and storage medium to improve the accuracy of target control parameters and effectively and stably control the driving of the target vehicle.

[0004] In a first aspect, an embodiment of the present invention provides a vehicle driving control method, comprising:

[0005] Acquire a current acceleration of the target vehicle in a current driving state, and determine a current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship, wherein the first corresponding relationship is a corresponding relationship between the driving acceleration and the cornering stiffness of the target vehicle;

[0006] Determining a target control parameter corresponding to the target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle;

[0007] The target vehicle is controlled to travel according to the expected trajectory information based on the target control parameter.

[0008] In a second aspect, an embodiment of the present invention further provides a vehicle driving control device, the device comprising:

[0009] a current cornering stiffness determination module, used to obtain a current acceleration of the target vehicle in a current driving state, and determine a current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship, wherein the first corresponding relationship is a corresponding relationship between the driving acceleration of the target vehicle and the cornering stiffness;

[0010] A target control parameter determination module, used to determine a target control parameter corresponding to the target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle;

[0011] The target vehicle driving control module is used to control the target vehicle to drive according to the expected trajectory information based on the target control parameters.

[0012] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0013] one or more processors;

[0014] a storage device for storing one or more programs,

[0015] When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle driving control method provided by any embodiment of the present invention.

[0016] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle driving control method provided by any embodiment of the present invention.

[0017] A vehicle driving control method provided by an embodiment of the present invention obtains the current acceleration of a target vehicle in a current driving state, determines the corresponding current side stiffness through a first correspondence relationship between the driving acceleration and side stiffness of the target vehicle established in advance, takes into account the influence of acceleration on side stiffness, more accurately determines the current side stiffness that meets the current driving state of the target vehicle, and determines the target control parameters corresponding to the target vehicle based on the current side stiffness and the expected trajectory information of the target vehicle, and controls the target vehicle to travel according to the expected trajectory information based on the target control parameters. The problem of inaccurate target control parameters caused by setting the side stiffness to a fixed value is solved, and the accuracy of the target control parameters is improved, so that the driving control effect of the target vehicle can be effectively and stably performed.

[0018] In addition, a vehicle driving control device, an electronic device and a storage medium provided by the present invention correspond to the above method and have the same beneficial effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A flow chart of a vehicle driving control method provided by an embodiment of the present invention;

[0021] Figure 2A structural diagram of a vehicle driving control device provided by an embodiment of the present invention;

[0022] Figure 3 A structural diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0024] It should be mentioned before discussing the exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0025] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0026] Embodiment 1

[0027] Figure 1 A flow chart of a vehicle driving control method provided in an embodiment of the present invention. The method can be executed by a vehicle driving control device, which can be implemented by software and / or hardware and can be configured in a terminal and / or server to implement the vehicle driving control method in an embodiment of the present invention.

[0028] like Figure 1 As shown, the method of this embodiment may specifically include:

[0029] S101. Obtain a current acceleration of a target vehicle in a current driving state, and determine a current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship.

[0030] The first corresponding relationship is the corresponding relationship between the driving acceleration and the cornering stiffness of the target vehicle. The current cornering stiffness includes the current front axle cornering stiffness and the current rear axle cornering stiffness.

[0031] In this embodiment, the target vehicle may be an unmanned intelligent vehicle, and sensors are provided at the bottom, wheels and other parts of the target vehicle. The sensors include speed sensors, positioning sensors and the like. By acquiring the collected data of each sensor, the current acceleration of the target vehicle in the current driving state can be determined. Furthermore, a first corresponding relationship can be established in advance. Exemplarily, the first corresponding relationship can be directly read through the operation and maintenance terminal, and the corresponding relationship between the driving acceleration and the lateral stiffness can also be determined through the corresponding relationship between other vehicle parameters and the driving acceleration. Other vehicle parameters may be the lateral velocity and yaw rate of the vehicle.

[0032] In this embodiment, the corresponding relationship can be expressed in the form of a relationship curve. For example, when the first corresponding relationship is displayed in the form of a relationship curve, the driving acceleration can be used as the horizontal axis of the curve, and the cornering stiffness can be used as the vertical axis of the curve.

[0033] In a specific implementation, before determining the current cornering stiffness corresponding to the current acceleration, it also includes: determining the actual motion parameters corresponding to each preset driving acceleration based on a second corresponding relationship between the preset driving acceleration and the actual motion parameters; determining the cornering stiffness corresponding to each driving acceleration based on a double-layer Kalman filter algorithm and the actual motion parameters to establish a first corresponding relationship.

[0034] The actual operating parameters include the actual lateral velocity and the actual yaw angular velocity, and the second corresponding relationship is the corresponding relationship between the driving acceleration, the actual lateral velocity and the actual yaw angular velocity.

[0035] It should be noted that the second corresponding relationship can be obtained by conducting a test in advance. The specific test process is as follows: 1. Detect the signal state of the combined navigation of the target vehicle and the state of the driving ground to avoid the measurement errors of the yaw rate and lateral velocity caused by the loss of the combined navigation signal and the bumps and slips of the road surface. 2. In the test, the target vehicle is controlled to accelerate on a straight road first. After accelerating to a preset speed and stabilizing, the steering wheel of a preset angle can be turned to generate a preset acceleration; the preset speed can be 30km / h. 3. After the preset acceleration is stable, the preset time is continued to determine the lateral velocity and yaw rate corresponding to the current preset acceleration at each preset time in the preset time. By adjusting the lateral acceleration, the lateral velocity and yaw rate corresponding to different preset accelerations can be obtained. In order to ensure the accuracy of the test, the corresponding lateral velocity and yaw rate can be determined when the acceleration is stable. Based on the preset accelerations in the test and the corresponding lateral velocities and yaw rates obtained in the test, the corresponding relationship between acceleration-lateral velocity-yaw rate can be generated. The corresponding relationship can be represented in the form of a curve and stored in the form of a mapping table.

[0036] In a specific implementation, based on a double-layer Kalman filter algorithm and actual motion parameters, the cornering stiffness corresponding to each driving acceleration is determined, which may include four steps: cornering stiffness parameter prediction, vehicle motion state prediction, vehicle motion state correction, and cornering stiffness parameter correction.

[0037] Specifically, when determining the cornering stiffness based on the double-layer Kalman filter algorithm, the above four steps can be repeated for different driving accelerations through multiple iterations until the cornering stiffness that meets the preset conditions is obtained; for example, the preset condition may be that the cornering stiffness obtained each time converges or the number of iterations reaches a preset number.

[0038] For different driving accelerations, in each iteration process, the cornering stiffness estimation matrix can be input, and the cornering stiffness estimation matrix can be corrected to obtain a corrected cornering stiffness matrix, and the corrected cornering stiffness matrix can be determined as the cornering stiffness corresponding to the driving acceleration. It should be noted that when determining the cornering stiffness estimation matrix, the corrected cornering stiffness matrix determined last time can be used as the cornering stiffness estimation matrix input this time to determine the cornering stiffness matrix this time.

[0039] For example, in order to more clearly illustrate the specific method of determining the cornering stiffness by the double-layer Kalman filter algorithm, the cornering stiffness is determined by taking a driving acceleration as an example, and the four steps of cornering stiffness parameter prediction, vehicle motion state prediction, vehicle motion state correction and cornering stiffness parameter correction are described respectively. The lateral velocity and yaw rate corresponding to each preset moment of acceleration in the test can be used as known data for each iteration, and the cornering stiffness is determined iteratively. The specific implementation process is as follows:

[0040] 1. Prediction of cornering stiffness parameters: In this embodiment, the time interval between iterations can be determined according to the time interval corresponding to each preset moment in the test. For example, the preset moment can be an evenly spaced moment with an interval of 0.02 seconds, and the time interval between iterations is also 0.02 seconds. The data of each iteration corresponds to the data collected at each preset interval in the test.

[0041] Each iteration requires input of the cornering stiffness estimation matrix. During the first iteration, those skilled in the art may set the cornering stiffness estimation matrix according to the actual application situation. In the subsequent iterations, the corrected cornering stiffness matrix determined last time may be used as the cornering stiffness estimation matrix input this time. In this embodiment, the cornering stiffness may include the front axle cornering angle stiffness C αf and rear axle slip angle stiffness C αr Therefore, the cornering stiffness estimation matrix can be a matrix containing the front axle cornering stiffness and the rear axle cornering stiffness. Furthermore, the cornering stiffness covariance matrix can also be set as The calculation formula is as follows:

[0042]

[0043] Where k represents the kth iteration, represents the cornering stiffness covariance matrix of the kth iteration, represents the cornering stiffness covariance matrix corresponding to the k-1th iteration, is the excitation noise covariance corresponding to the k-1th iteration.

[0044] 2. Vehicle motion state prediction:

[0045]

[0046]

[0047] in, is the state matrix obtained at the kth iteration, is the state matrix obtained at the k-1th iteration. The state quantities in the state matrix include the lateral velocity V y and yaw rate Based on the above and Can be determined

[0048] A k-1 is the state transfer matrix of the k-1th iteration, A k-1 The transpose of B k-1 is the control quantity transfer matrix of the k-1th iteration, is the state quantity covariance matrix of the kth iteration, is the state quantity covariance matrix of the k-1th iteration, R v is the process excitation noise covariance; u represents the input control quantity, which can be specifically set to the front wheel steering angle δ f , which can be collected through the collection equipment on the vehicle.

[0049] It should be noted that the state quantity transfer matrix, state quantity covariance matrix, etc. can be determined based on the state quantity; the control quantity transfer matrix, control quantity covariance matrix, etc. can be obtained through the control quantity. The state matrix and state quantity transfer matrix obtained in the previous iteration can be used to predict the state matrix and state quantity transfer matrix of this iteration. The specific calculation method of the transfer matrix and covariance matrix is ​​as follows:

[0050]

[0051]

[0052] Among them, A represents the transfer matrix, B represents the covariance matrix, l fis the distance from the center of mass of the vehicle to the front axle, l r is the distance from the center of mass of the vehicle to the rear axle, m is the mass of the vehicle, V x is the longitudinal velocity corresponding to the kth iteration, I z is the moment of inertia of the vehicle around the z-axis, and T is the time interval between iterations, which can be set to 0.02 seconds in this embodiment.

[0053] 3. Vehicle motion state correction:

[0054]

[0055]

[0056]

[0057] in: is the motion state filter gain matrix, which can be set by technicians in this field according to the actual application. C is the position transfer matrix from the center of mass of the vehicle to the rear axle, R n It is the noise covariance in the vehicle motion state correction process, which is used to reflect the degree of deviation between the lateral velocity and yaw rate before correction and the actual value. Those skilled in the art can set it according to the actual application. k is the actual state matrix corresponding to this iteration measured in the experiment, y k Including the lateral velocity at the rear axle of the vehicle actually obtained in the test and the yaw rate

[0058] It should be noted that The left side of the equal sign represents the matrix of the state quantity obtained after the kth iteration correction, and the right side of the equal sign represents the matrix of the state quantity before correction. The value obtained after the operation on the right side of the equal sign on the state matrix before correction is determined as the state matrix after correction. The corrected state matrix includes the corrected lateral velocity V y ′ and yaw rate

[0059] Similarly, In , the left side of the equal sign represents the state quantity covariance matrix obtained after the k-th iteration correction, and the right side of the equal sign represents the state quantity covariance matrix before the k-th iteration correction.

[0060] 4. Cornering stiffness parameter correction

[0061]

[0062]

[0063]

[0064] in:

[0065]

[0066] in. is the lateral stiffness filter gain matrix, V y ′ is the lateral velocity in the corrected state matrix, is the yaw rate in the corrected state matrix. e The correction covariance in the process of cornering stiffness parameter correction can be set by those skilled in the art according to the actual application situation. f is the distance from the center of mass of the vehicle to the front axle, l r is the distance from the center of mass of the vehicle to the rear axle, m is the mass of the vehicle, V x is the longitudinal velocity of the vehicle corresponding to the kth iteration process, I z is the moment of inertia of the vehicle around the z-axis, T is the time interval between iterations, which can be set to 0.02 seconds in this embodiment. I represents the unit matrix.

[0067] represents the corrected cornering stiffness matrix obtained at the kth iteration, represents the cornering stiffness matrix obtained at the k-1th iteration, including the front axle cornering stiffness C αf and rear axle slip angle stiffness C αr , so the cornering stiffness matrix can be a matrix containing the front axle cornering angle stiffness and the rear axle cornering angle stiffness.

[0068] It should be noted that the left side of the equal sign in the formula for the cornering stiffness parameter correction step is represents the cornering stiffness covariance matrix obtained after the k-th iterative correction, and the right side of the equal sign represents the cornering stiffness covariance matrix before the k-th iterative correction.

[0069] In this embodiment, when the cornering stiffness matrix that meets the preset conditions is obtained, the correspondence between the corrected cornering stiffness matrix and the driving acceleration can be obtained. The same operation as above is performed for each driving acceleration to obtain the first correspondence between each driving acceleration and the cornering stiffness.

[0070] S102: Determine target control parameters corresponding to the target vehicle based on the current cornering stiffness and expected trajectory information of the target vehicle.

[0071] In a specific implementation, a system state equation of the target vehicle in motion may be established based on the current cornering stiffness, and the target control parameters required when the target vehicle moves according to the expected trajectory information may be reflected based on the system state equation.

[0072] In this embodiment, a specific implementation method for determining a target control parameter corresponding to a target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle may include: obtaining the expected trajectory information and the current trajectory information of the target vehicle, and determining a state quantity of the target vehicle based on the current trajectory information and the expected trajectory information; wherein the state quantity includes at least one of a lateral position deviation, a lateral position deviation change rate, a heading angle deviation, and a heading angle deviation change rate; constructing a system state equation corresponding to the target vehicle based on the state quantity and the current cornering stiffness; wherein the control quantity of the system state equation is set to the target control parameter; and determining the control quantity corresponding to the system state equation through a model predictive control algorithm to obtain the target control parameter.

[0073] The current trajectory information includes the current driving position and current heading angle of the target vehicle, and the expected trajectory information includes the expected driving position and expected heading angle of the vehicle.

[0074] Optionally, the target control parameters may include a target front wheel steering angle value and a target braking yaw moment value. The system state equation is as follows:

[0075]

[0076] Among them, e lat is the lateral position deviation, is the lateral position deviation change rate, is the heading angle deviation, ω is the rate of change of the heading angle deviation, 1 / R is the curvature of the desired trajectory at the closest point to the target vehicle, and the target front wheel turning angle is δ f , the target braking yaw moment is M b . C r Indicates the current rear axle slip angle stiffness in the current slip stiffness, C f represents the current front axle slip angle stiffness in the current slip stiffness, m represents the mass of the target vehicle, V x represents the current longitudinal speed of the target vehicle. b represents the distance from the center of mass of the target vehicle to the rear axle. z Represents the moment of inertia of the target vehicle around the z-axis.

[0077] In specific implementation, different weight coefficients Q can be set for the front wheel steering angle and the braking yaw moment to adjust the ratio of the target front wheel steering angle and the target braking yaw moment; when the path curvature is too large and the front wheel steering angle cannot meet the path tracking requirements, the braking yaw moment and the front wheel steering angle can be used to jointly control the vehicle. The weight coefficient Q can be:

[0078]

[0079] in, is the target front wheel steering angle weight, is the target braking yaw moment weight. By calculating the system state equation according to the model predictive control algorithm, the target control parameter can be determined, that is, the target front wheel turning angle is δ f , the target braking yaw moment is M b .

[0080] S103: Control the target vehicle to travel according to the expected trajectory information based on the target control parameters.

[0081] In a specific implementation, the target control parameters may be sent to the vehicle braking system so that the vehicle braking system controls the vehicle driving according to the target control parameters, thereby making the actual driving route meet the requirements of the expected trajectory information.

[0082] In this embodiment, the target control parameter includes a target front wheel steering angle value and a target braking yaw moment value; it may also include other control parameters other than the target front wheel steering angle value and the target braking yaw moment value, such as a vehicle running speed value, etc., which are not limited in this embodiment of the present invention. Specifically, controlling the target vehicle to travel according to the expected trajectory information based on the target control parameter includes: sending the target front wheel steering angle value and the target braking yaw moment value to the vehicle braking system, so that the vehicle braking system controls the target vehicle to travel according to the expected trajectory information according to the target front wheel steering angle value and the target braking yaw moment value.

[0083] In a specific implementation, the target front wheel steering angle value and the target braking yaw moment value can be sent to the vehicle braking system respectively, so that the front wheel steering angle of the target vehicle can be controlled according to the target front wheel steering angle value, and the braking yaw moment can be controlled at the same time, so that the target vehicle can finally travel according to the trajectory information.

[0084] In this embodiment, it also includes: when it is determined that the vehicle steering system fails, determining the execution front wheel steering angle value and the execution braking yaw moment value of the vehicle braking system at the moment of the failure; converting the execution front wheel steering angle value into a first redundant braking yaw moment, superimposing the first redundant braking yaw moment and the execution braking yaw moment value to generate a first superimposed torque; sending the first superimposed torque to the braking system to control the target vehicle to travel according to the first superimposed torque.

[0085] In a specific implementation, when the chassis domain controller detects that the vehicle steering system sends a fault message, it is determined that the vehicle steering system has a fault, and the brake redundant steering function can be activated. The execution front wheel angle value and the execution braking yaw torque value executed by the vehicle braking system at the time of the fault can be determined. Due to the failure of the vehicle steering system, it is impossible to continue steering according to the original execution front wheel angle value, then the execution front wheel angle value can be converted into a first redundant braking yaw torque, and the braking yaw torque can be adjusted to achieve the same effect as steering according to the execution front wheel angle value. Specifically, the execution front wheel angle value can be converted into a first redundant braking yaw torque, and the first redundant braking yaw torque and the execution braking yaw torque value are superimposed to generate a first superimposed torque. The steering effect produced by controlling the vehicle according to the first superimposed torque is equivalent to the steering effect achieved by controlling the vehicle according to the execution front wheel angle value and the execution braking yaw torque value.

[0086] This embodiment avoids the problem of being unable to drive along the desired route when the vehicle steering system fails by adjusting the braking yaw torque, and can ensure that the target vehicle drives along the desired route, thereby improving the stability and effectiveness of the driving process.

[0087] Optionally, the target vehicle is controlled to travel according to the expected trajectory information based on the target control parameters, including: when it is determined that the maximum steering angle value of the vehicle steering system is less than the target front wheel steering angle value, determining the steering angle difference between the maximum steering angle value and the target front wheel steering angle value; converting the steering angle difference into a second redundant braking yaw moment, superimposing the second redundant braking yaw moment and the target braking yaw moment value to generate a second superimposed torque; and sending the second superimposed torque to the braking system to control the target vehicle to travel according to the expected trajectory information according to the second superimposed torque.

[0088] In this embodiment, when the steering function of the vehicle steering system cannot meet the target front wheel angle value for driving according to the expected trajectory information, it is necessary to ensure that the target vehicle drives according to the expected trajectory information by adjusting the braking yaw torque. Specifically, it can be determined whether the vehicle steering system can achieve the target front wheel angle value by judging the magnitude relationship between the maximum angle value that the vehicle steering system can achieve and the target front wheel angle value. When the maximum angle value is less than the target front wheel angle value, it means that the vehicle steering system cannot achieve the target front wheel angle value, and the angle difference between the maximum angle value and the target front wheel angle value can be used; the angle difference is converted into a second redundant braking yaw torque, and the second redundant braking yaw torque and the target braking yaw torque value are superimposed to obtain a second superimposed torque. The target vehicle is controlled according to the second superimposed torque, so that the target vehicle can be ensured to drive according to the expected trajectory information, thereby improving the stability and effectiveness of the driving process.

[0089] In this embodiment, it also includes: obtaining the current center of mass sideslip angle of the target vehicle detected by the chassis domain controller, and determining the future center of mass sideslip angle at a preset future moment based on the current center of mass sideslip angle, the current yaw angular velocity and the current front wheel turning angle; when the future center of mass sideslip angle is greater than a preset threshold, determining a pre-controlled yaw torque that meets a preset stability condition, and sending the pre-controlled yaw torque to the braking system.

[0090] In order to ensure the driving stability of the target vehicle and avoid the target vehicle from deviation, the current center of mass sideslip angle of the target vehicle can be obtained, and the future center of mass sideslip angle at a preset future moment can be determined based on the current center of mass sideslip angle, the current yaw angular velocity and the current front wheel turning angle. When the future center of mass sideslip angle is greater than a preset threshold, it means that the vehicle may deviate to the side at a future moment, and it is necessary to control the target vehicle to maintain stability by pre-controlling the yaw moment to avoid deviation; when the future center of mass sideslip angle is less than or equal to the preset threshold, it means that the vehicle will not deviate to the side at a future moment, and no pre-control is required.

[0091] For example, different preset thresholds may be set according to road conditions in different environments. For example, the preset threshold of the sideslip angle of the center of mass on a good road surface may be set to 12 degrees, and the preset threshold corresponding to a slippery road surface may be set to 2 degrees.

[0092] Furthermore, when the future sideslip angle of the center of mass is greater than a preset threshold, the difference between the future sideslip angle of the center of mass and the preset threshold can be calculated, and the difference can be converted into a supplementary yaw moment. The target braking yaw moment that is originally required to be executed in the future is superimposed with the supplementary yaw moment to obtain a pre-controlled yaw moment, and the pre-controlled yaw moment will be sent to the braking system at the future to control the target vehicle from slipping sideways.

[0093] A vehicle driving control method provided by an embodiment of the present invention obtains the current acceleration of a target vehicle in a current driving state, determines the corresponding current side stiffness through a first correspondence relationship between the driving acceleration and side stiffness of the target vehicle established in advance, takes into account the influence of acceleration on side stiffness, more accurately determines the current side stiffness that meets the current driving state of the target vehicle, and determines the target control parameters corresponding to the target vehicle based on the current side stiffness and the expected trajectory information of the target vehicle, and controls the target vehicle to travel according to the expected trajectory information based on the target control parameters. The problem of inaccurate target control parameters caused by setting the side stiffness to a fixed value is solved, and the accuracy of the target control parameters is improved, so that the driving control effect of the target vehicle can be effectively and stably performed.

[0094] Embodiment 2

[0095] Figure 2This is a structural diagram of a vehicle driving control device provided in an embodiment of the present invention, and the device is used to execute the vehicle driving control method provided in any of the above embodiments. The device and the vehicle driving control method of the above embodiments belong to the same inventive concept, and the details not described in detail in the embodiment of the vehicle driving control device can refer to the embodiment of the above vehicle driving control method. The device may specifically include:

[0096] A current cornering stiffness determination module 10 is used to obtain a current acceleration of the target vehicle in a current driving state, and determine a current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship, wherein the first corresponding relationship is a corresponding relationship between the driving acceleration and the cornering stiffness of the target vehicle;

[0097] A target control parameter determination module 11 is used to determine a target control parameter corresponding to the target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle;

[0098] The target vehicle driving control module 12 is used to control the target vehicle to drive according to the expected trajectory information based on the target control parameters.

[0099] Based on any optional technical solution in the embodiments of the present invention, optionally, the device further includes:

[0100] an actual motion parameter determination module, configured to determine the actual motion parameter corresponding to each preset driving acceleration based on a preset second correspondence relationship between the driving acceleration and the actual motion parameter before determining the current cornering stiffness corresponding to the current acceleration;

[0101] The first corresponding relationship establishing module is used to determine the cornering stiffness corresponding to each of the driving accelerations based on a double-layer Kalman filter algorithm and the actual motion parameters to establish the first corresponding relationship.

[0102] Based on any optional technical solution in the embodiment of the present invention, optionally, the target control parameter determination module 11 includes:

[0103] a current trajectory information acquisition unit, configured to acquire the desired trajectory information and the current trajectory information of the target vehicle, and determine the state quantity of the target vehicle based on the current trajectory information and the desired trajectory information; wherein the state quantity includes at least one of the lateral position deviation, the lateral position deviation change rate, the heading angle deviation and the heading angle deviation change rate;

[0104] A system state equation construction unit, used to construct a system state equation corresponding to the target vehicle based on the state quantity and the current cornering stiffness; wherein the control quantity of the system state equation is set to the target control parameter;

[0105] The target control parameter determination unit is used to determine the control quantity corresponding to the system state equation through a model predictive control algorithm to obtain the target control parameter.

[0106] Based on any optional technical solution in the embodiment of the present invention, optionally, the target control parameter includes a target front wheel steering angle value and a target braking yaw moment value; the target vehicle driving control module 12 includes:

[0107] A parameter sending unit is used to send the target front wheel steering angle value and the target braking yaw moment value to a vehicle braking system, so that the vehicle braking system controls the target vehicle to travel according to the expected trajectory information according to the target front wheel steering angle value and the target braking yaw moment value.

[0108] Based on any optional technical solution in the embodiments of the present invention, optionally, the following further includes:

[0109] The first superposition torque generating module is used to determine the execution front wheel steering angle value and the execution braking yaw moment value of the vehicle braking system at the moment of failure when it is determined that the vehicle steering system fails; convert the execution front wheel steering angle value into a first redundant braking yaw moment, superimpose the first redundant braking yaw moment and the execution braking yaw moment value to generate a first superposition torque; and send the first superposition torque to the braking system to control the target vehicle to travel according to the first superposition torque.

[0110] Based on any optional technical solution in the embodiment of the present invention, optionally, the target vehicle driving control module 12 includes:

[0111] The second superposition torque generating unit is used to determine the angle difference between the maximum angle value and the target front wheel angle value when it is determined that the maximum angle value of the vehicle steering system is less than the target front wheel angle value; convert the angle difference into a second redundant braking yaw moment, superimpose the second redundant braking yaw moment and the target braking yaw moment value to generate a second superposition torque; and send the second superposition torque to the braking system to control the target vehicle to travel according to the expected trajectory information according to the second superposition torque.

[0112] Based on any optional technical solution in the embodiments of the present invention, optionally, the following further includes:

[0113] A future center of mass sideslip angle determination module is used to obtain the current center of mass sideslip angle of the target vehicle detected by the chassis domain controller, and determine the future center of mass sideslip angle at a preset future moment based on the current center of mass sideslip angle, the current yaw angular velocity and the current front wheel turning angle;

[0114] The pre-controlled yaw moment determination module is used to determine the pre-controlled yaw moment that meets the preset stability condition when the future center of mass sideslip angle is greater than a preset threshold, and send the pre-controlled yaw moment to the braking system.

[0115] The vehicle driving control device provided in the embodiment of the present invention can execute the vehicle driving control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0116] It is worth noting that in the embodiment of the above-mentioned vehicle driving control device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0117] Embodiment 3

[0118] Figure 3 A structural diagram of an electronic device provided in an embodiment of the present invention. Figure 3 A block diagram of an exemplary electronic device 20 suitable for implementing an embodiment of the present invention is shown. The electronic device 20 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0119] like Figure 3 As shown, the electronic device 20 is in the form of a general computing device. The components of the electronic device 20 may include but are not limited to: one or more processors or processing units 201, a system memory 202, and a bus 203 connecting different system components (including the system memory 202 and the processing unit 201).

[0120] Bus 203 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus structures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0121] The electronic device 20 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 20, including volatile and non-volatile media, removable and non-removable media.

[0122] The system memory 202 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 204 and / or cache memory 205. The electronic device 20 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 206 may be used to read and write non-removable, non-volatile magnetic media. A disk drive for reading and writing removable non-volatile disks (such as "floppy disks"), and an optical disk drive for reading and writing removable non-volatile optical disks (such as CD-ROM, DVD-ROM or other optical media) may be provided. In these cases, each drive may be connected to the bus 203 via one or more data medium interfaces. The memory 202 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of various embodiments of the present invention.

[0123] A program / utility 208 having a set (at least one) of program modules 207 may be stored, for example, in the memory 202, such program modules 207 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 207 generally perform the functions and / or methods of the embodiments described herein.

[0124] The electronic device 20 may also communicate with one or more external devices 209 (e.g., keyboards, pointing devices, displays 210, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 20, and / or may communicate with any device that enables the electronic device 20 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 211. Furthermore, the electronic device 20 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 212. As shown, the network adapter 212 communicates with other modules of the electronic device 20 via a bus 203. It should be understood that other hardware and / or software modules may be used in conjunction with the electronic device 20, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0125] The processing unit 201 executes various functional applications and data processing by running programs stored in the system memory 202 .

[0126] An electronic device provided by the present invention can implement the following method: obtaining the current acceleration of the target vehicle in the current driving state, determining the current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship, wherein the first corresponding relationship is the corresponding relationship between the driving acceleration and cornering stiffness of the target vehicle; determining the target control parameter corresponding to the target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle; and controlling the target vehicle to travel according to the expected trajectory information based on the target control parameter. The problem of inaccurate target control parameters caused by setting the cornering stiffness to a fixed value is solved, and the accuracy of the target control parameters is improved, so that the driving control effect of the target vehicle can be effectively and stably performed.

[0127] Embodiment 4

[0128] An embodiment of the present invention provides a storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute a vehicle driving control method when executed by a computer processor, the method comprising:

[0129] The current acceleration of the target vehicle in the current driving state is obtained, and the current cornering stiffness corresponding to the current acceleration is determined based on a pre-established first corresponding relationship, wherein the first corresponding relationship is the corresponding relationship between the driving acceleration and cornering stiffness of the target vehicle; based on the current cornering stiffness and the expected trajectory information of the target vehicle, the target control parameter corresponding to the target vehicle is determined; based on the target control parameter, the target vehicle is controlled to travel according to the expected trajectory information. The problem of inaccurate target control parameters caused by setting the cornering stiffness to a fixed value is solved, and the accuracy of the target control parameters is improved, so that the driving control effect of the target vehicle can be effectively and stably performed.

[0130] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present invention is not limited to the method operations described above, and can also execute related operations in the vehicle driving control method provided in any embodiment of the present invention.

[0131] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, a device or a device or used in combination with it.

[0132] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0133] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0134] Computer program code for performing the operation of embodiments of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0135] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A vehicle driving control method, characterized in that: include: Acquire a current acceleration of the target vehicle in a current driving state, and determine a current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship, wherein the first corresponding relationship is a corresponding relationship between the driving acceleration and the cornering stiffness of the target vehicle; Determining a target control parameter corresponding to the target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle; Controlling the target vehicle to travel according to the desired trajectory information based on the target control parameter; Before determining the current cornering stiffness corresponding to the current acceleration, the method further includes: Based on a second correspondence relationship between a preset driving acceleration and an actual motion parameter, determining the actual motion parameter corresponding to each preset driving acceleration; wherein the actual motion parameter includes an actual lateral velocity and an actual yaw angular velocity, and the second correspondence relationship is a correspondence relationship between the driving acceleration, the actual lateral velocity, and the actual yaw angular velocity; Based on the double-layer Kalman filter algorithm and the actual motion parameters, the cornering stiffness corresponding to each of the driving accelerations is determined, including cornering stiffness parameter prediction, vehicle motion state prediction, vehicle motion state correction and cornering stiffness parameter correction, so as to establish the first corresponding relationship.

2. The method according to claim 1, characterized in that The determining, based on the current cornering stiffness and the expected trajectory information of the target vehicle, a target control parameter corresponding to the target vehicle comprises: Acquire the expected trajectory information and current trajectory information of the target vehicle, and determine the state quantity of the target vehicle based on the current trajectory information and the expected trajectory information; wherein the state quantity includes at least one of a lateral position deviation, a lateral position deviation change rate, a heading angle deviation, and a heading angle deviation change rate; Based on the state quantity and the current cornering stiffness, a system state equation corresponding to the target vehicle is constructed; wherein the control quantity of the system state equation is set as the target control parameter; The control quantity corresponding to the system state equation is determined by a model predictive control algorithm to obtain the target control parameter.

3. The method according to claim 1, characterized in that The target control parameters include a target front wheel steering angle value and a target braking yaw moment value; The step of controlling the target vehicle to travel according to the expected trajectory information based on the target control parameter includes: The target front wheel steering angle value and the target braking yaw moment value are sent to a vehicle braking system, so that the vehicle braking system controls the target vehicle to travel according to the expected trajectory information according to the target front wheel steering angle value and the target braking yaw moment value.

4. The method according to claim 3, characterized in that Also includes: When it is determined that the vehicle steering system fails, determining the execution front wheel steering angle value and the execution braking yaw moment value of the vehicle braking system at the time of the failure; converting the execution front wheel steering angle value into a first redundant braking yaw moment, and superimposing the first redundant braking yaw moment and the execution braking yaw moment value to generate a first superimposed moment; The first superimposed torque is sent to the braking system to control the target vehicle to travel according to the first superimposed torque.

5. The method according to claim 3, characterized in that: The step of controlling the target vehicle to travel according to the expected trajectory information based on the target control parameter includes: When it is determined that the maximum steering angle value of the vehicle steering system is less than the target front wheel steering angle value, determining a steering angle difference between the maximum steering angle value and the target front wheel steering angle value; converting the rotation angle difference into a second redundant braking yaw moment, and superimposing the second redundant braking yaw moment and the target braking yaw moment value to generate a second superimposed moment; The second superimposed torque is sent to the braking system to control the target vehicle to travel according to the expected trajectory information according to the second superimposed torque.

6. The method according to claim 1, characterized in that Also includes: Obtaining a current center of mass sideslip angle of the target vehicle detected by the chassis domain controller, and determining a future center of mass sideslip angle at a preset future moment based on the current center of mass sideslip angle, the current yaw angular velocity, and the current front wheel turning angle; When the future sideslip angle of the center of mass is greater than a preset threshold, a pre-controlled yaw moment satisfying a preset stability condition is determined, and the pre-controlled yaw moment is sent to a braking system.

7. A vehicle driving control device, characterized in that: include: a current cornering stiffness determination module, used to obtain a current acceleration of the target vehicle in a current driving state, and determine a current cornering stiffness corresponding to the current acceleration based on a pre-established first corresponding relationship, wherein the first corresponding relationship is a corresponding relationship between the driving acceleration of the target vehicle and the cornering stiffness; A target control parameter determination module, used to determine a target control parameter corresponding to the target vehicle based on the current cornering stiffness and the expected trajectory information of the target vehicle; A target vehicle driving control module, used for controlling the target vehicle to drive according to the expected trajectory information based on the target control parameter; an actual motion parameter determination module, configured to determine the actual motion parameter corresponding to each preset driving acceleration based on a second corresponding relationship between the preset driving acceleration and the actual motion parameter; wherein the actual motion parameter includes an actual lateral velocity and an actual yaw rate, and the second corresponding relationship is a corresponding relationship between the driving acceleration, the actual lateral velocity, and the actual yaw rate; The first correspondence establishing module is used to determine the cornering stiffness corresponding to each driving acceleration based on a double-layer Kalman filter algorithm and the actual motion parameters, including cornering stiffness parameter prediction, vehicle motion state prediction, vehicle motion state correction and cornering stiffness parameter correction, so as to establish the first correspondence.

8. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle driving control method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle driving control method as described in any one of claims 1 to 6 is implemented.

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