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

Abstract

The present invention discloses a vehicle driving control method, device, electronic device and storage medium. The method comprises: obtaining the current road trajectory information and the current yaw angle information of the target vehicle; determining the current preview information of the current vehicle according to the current road trajectory information and the preview module in the pre-constructed target driver model; obtaining the target steering wheel angle according to the current yaw angle information, the current preview information and the following module in the target driver model, so as to control the target vehicle to drive according to the target steering wheel angle at the next moment. By running the technical solution provided by the embodiment of the present invention, the problem that the traditional preview module simplifies the vehicle into a particle, the vehicle posture control is not considered in the calculation process, and the vehicle sways left and right during the trajectory tracking process, which affects the riding comfort, can be solved, and the beneficial effect of improving the stability of vehicle control and reducing the difficulty of vehicle control can be achieved.

Description

Technical Field

[0001] The present invention relates to vehicle driving control technology, and in particular to a vehicle driving control method, device, electronic equipment and storage medium. Background Art

[0002] The core of the human-vehicle closed-loop control system model is the driver model, which is a mathematical expression of the real driver's control ability. The driver model plays a vital role in areas such as vehicle handling stability and autonomous driving trajectory tracking control technology.

[0003] The driver model may include a preview module. During the vehicle's autonomous driving process, the path planning module outputs a reference trajectory, and the positioning module obtains the vehicle's real-time position, posture and other status information. The driver model calculates the vehicle's acceleration and deceleration requests and control signals such as the steering wheel angle based on the reference trajectory, real-time position, vehicle speed and other information, and outputs them to the vehicle's actuator to control the vehicle to travel along the expected reference trajectory.

[0004] The traditional preview module simplifies the vehicle into a point mass and eliminates the longitudinal and lateral distance deviations between the current point and the preview point by controlling the longitudinal and lateral accelerations. This method can obtain good trajectory position tracking accuracy, but because the vehicle posture control is not considered in the calculation process, the vehicle will sway left and right during the trajectory tracking process, affecting ride comfort. Summary of the invention

[0005] The present invention provides a vehicle driving control method, device, electronic equipment and storage medium to improve the stability of vehicle control and reduce the difficulty of vehicle control.

[0006] According to one aspect of the present invention, a vehicle driving control method is provided, the method comprising:

[0007] Acquiring current road trajectory information of a target vehicle and current yaw angle information of the target vehicle;

[0008] Determining current preview information of the current vehicle according to the current road trajectory information and a preview module in a pre-built target driver model;

[0009] According to the current yaw angle information, the current preview information and the following module in the target driver model, a target steering wheel angle is obtained, so as to control the target vehicle to travel according to the target steering wheel angle at the next moment.

[0010] According to another aspect of the present invention, there is provided a vehicle driving control device, the device comprising:

[0011] An information acquisition module, used to acquire current road trajectory information of a target vehicle and current yaw angle information of the target vehicle;

[0012] An information determination module, configured to determine current preview information of the current vehicle according to the current road trajectory information and a preview module in a pre-built target driver model;

[0013] The target steering wheel angle acquisition module is used to obtain the target steering wheel angle according to the current yaw angle information, the current preview information and the following module in the target driver model, so as to control the target vehicle to travel according to the target steering wheel angle at the next moment.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle driving control method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle driving control method described in any embodiment of the present invention when executed.

[0019] The technical solution of the embodiment of the present invention is to obtain the current road trajectory information of the target vehicle and the current yaw angle information of the target vehicle; determine the current preview information of the current vehicle according to the current road trajectory information and the preview module in the pre-built target driver model; obtain the target steering wheel angle according to the current yaw angle information, the current preview information and the following module in the target driver model, so as to control the target vehicle to travel according to the target steering wheel angle at the next moment. The problem that the traditional preview module simplifies the vehicle into a mass point, does not consider the vehicle posture control in the calculation process, and the vehicle yaws left and right during the trajectory tracking process, which affects the ride comfort, is solved, and the beneficial effect of improving the stability of vehicle control and reducing the difficulty of vehicle control is achieved.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A flow chart of a vehicle driving control method provided in Embodiment 1 of the present invention;

[0022] Figure 2 A flowchart of a method for constructing a target driver model provided in Embodiment 2 of the present invention;

[0023] Figure 3 A schematic diagram of a vehicle model provided in Embodiment 2 of the present invention;

[0024] Figure 4 A basic block diagram of an existing driver model provided in Embodiment 2 of the present invention;

[0025] Figure 5 A basic block diagram of a target driver model provided by Embodiment 2 of the present invention;

[0026] Figure 6 A basic block diagram of a first process driver model provided by Embodiment 2 of the present invention;

[0027] Figure 7 A basic block diagram of a second process driver model provided by Embodiment 2 of the present invention;

[0028] Figure 8 A schematic diagram of the structure of a vehicle driving control device provided in Embodiment 3 of the present invention;

[0029] Fig. 9 It is a schematic diagram of the structure of an electronic device used to implement an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", "target", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] Embodiment 1

[0033] Figure 1 This is a flow chart of a vehicle driving control method provided in Embodiment 1 of the present invention. This embodiment can be applied to controlling the driving of an autonomous driving vehicle. The method can be executed by a vehicle driving control device provided in an embodiment of the present invention. The device can be implemented in software and / or hardware. Figure 1 The vehicle driving control method provided in this embodiment includes:

[0034] Step 110: Acquire current road trajectory information of the target vehicle and current yaw angle information of the target vehicle.

[0035] The target vehicle is the vehicle currently controlling the driving mode. The current road trajectory data is the trajectory data available when the current vehicle is driving on the road, such as the path data of the planned target vehicle to be driven, etc., which can be obtained through the corresponding path planning module.

[0036] The current yaw angle information of the target vehicle is information related to the current yaw angle of the target vehicle, and may include a current yaw angular velocity and a current yaw angle. The current yaw angle information may be obtained through a vehicle sensor or calculated through a target driver model.

[0037] Step 120: Determine current preview information of the current vehicle according to the current road trajectory information and a preview module in a pre-built target driver model.

[0038] The target driver model includes a preview module and a tracking module. The target driver model corresponds to the driver-vehicle closed-loop system. The driver-vehicle closed-loop system is a system that performs follow-up control based on the input information of the road ahead. If the system is simplified, it can be represented as a system consisting of a "predictor" and a "follower" in series. The predictor represents the driver's preview link, which depends on factors such as the driver's preview method, and corresponds to the preview module in the target driver model. The tracker represents the driver's steering and the vehicle's response, and corresponds to the tracking module in the target driver model.

[0039] The current preview information of the current vehicle is determined according to the current road trajectory information and the preview module in the pre-built target driver model, that is, the current road trajectory information is input into the preview module in the target driver model to obtain the current preview information of the current vehicle, wherein the current preview information may include the preview point corresponding to the current vehicle position, and the angle between the track tangent at the preview point and the horizontal axis of the geodetic coordinate system can be determined through the preview point. Among them, the preview point is a hypothetical point where the driver's eyes are focused on a point in front during driving, and this assumption is usually consistent with actual experience.

[0040] Step 130: Obtain a target steering wheel angle according to the current yaw angle information, the current preview information and a following module in the target driver model, so as to control the target vehicle to travel according to the target steering wheel angle at the next moment.

[0041] In order to minimize the difference between the vehicle yaw angle and the angle between the trajectory tangent at the preview point and the horizontal axis of the geodetic coordinate system, the target preview module parameters are determined, and the target preview module is obtained according to the target preview module parameters. The current road trajectory information is input into the target preview module to obtain target preview information. The target preview information and the current yaw angle information are input into the following module in the target driver model to obtain the target steering wheel angle.

[0042] In the process of the target vehicle driving towards the target preview point, the steering wheel of the target vehicle is turned according to the target steering wheel angle at the end of the current moment and the beginning of the next moment to generate a target yaw angle. At this time, the target yaw angle satisfies the minimum difference between the angle between the trajectory tangent at the target preview point and the horizontal axis of the geodetic coordinate system, so that the amplitude of the vehicle swing is reduced while ensuring the driving accuracy.

[0043] The technical solution provided in this embodiment no longer simplifies the vehicle into a single mass point, but takes the change in the vehicle yaw angle during the tracking process from the current point of the target vehicle to the preview point as the control target, and calculates the target steering wheel angle that ensures the posture of the vehicle preview point, that is, the vehicle yaw angle when the target vehicle reaches the target preview point in the spatial distance is consistent with the tangent direction of the trajectory where the target preview point is located, avoiding the phenomenon that the vehicle frequently yaws left and right during the trajectory tracking process, improving the stability of vehicle control, and thus improving the comfort of the user's vehicle riding. In addition, since the end time of this calculation is the start time of the next stage, if the vehicle yaw angle at the start time of the next stage is very different from the trajectory tangent direction at the corresponding preview point position, it will increase the difficulty of steering control in the next stage. The target steering wheel angle obtained by this solution controls the vehicle driving, so that the yaw angle of the vehicle when driving is less different from the trajectory tangent direction at the preview point position, reducing the difficulty of steering control of the vehicle in the next stage.

[0044] Embodiment 2

[0045] Figure 2 The flowchart of a method for constructing a target driver model provided in the second embodiment of the present invention is provided. This technical solution is to supplement the construction process of the target driver model. Compared with the above solution, this solution is specifically optimized as follows: the construction process of the target driver model includes:

[0046] Constructing a target vehicle model in the following module according to the vehicle yaw angle information; wherein the vehicle yaw angle information includes the vehicle yaw angular velocity;

[0047] The target driver model is constructed according to the target vehicle model, and the process driver model is determined according to the target driver model, so as to determine the parameter information of the target driver model according to the process driver model. Figure 2 As shown:

[0048] Step 210: construct a target vehicle model in the following module according to the vehicle yaw angle information; wherein the vehicle yaw angle information includes the vehicle yaw angular velocity.

[0049] The target vehicle model in the following module is constructed according to the vehicle yaw angle information, wherein the vehicle yaw angle information may be the vehicle yaw angular velocity, etc. The target vehicle model is used to determine the relationship between the steering wheel angle and the vehicle yaw angular velocity, and the target vehicle model is constructed according to the vehicle yaw angular velocity and a preset formula.

[0050] In this embodiment, optionally, constructing a target vehicle model in the following module according to the vehicle yaw angle information includes:

[0051] Determining a first transfer function between the vehicle yaw rate and the vehicle steering wheel angle;

[0052] Obtaining the angle relationship between the vehicle steering wheel angle and the vehicle steering wheel angle;

[0053] According to the relationship between the first transfer function and the steering angle, a second transfer function between the vehicle yaw rate and the vehicle steering wheel angle is determined, and the second transfer function is determined as the target vehicle model.

[0054] The roll steering angle, lateral force angle and tire slip angle of the vehicle suspension and steering are considered together as the comprehensive slip angle of the front and rear wheels. In this way, the vehicle can be approximately regarded as a two-degree-of-freedom system to analyze the vehicle's response when the vehicle's steering wheel angle or vehicle steering wheel angle is input.

[0055] Figure 3 A schematic diagram of a vehicle model provided in the second embodiment of the present invention. Figure 3 As shown, the vehicle model is a two-degree-of-freedom vehicle model.

[0056] The physical meanings of the parameters in the figure are as follows:

[0057] ψVehicle yaw angle, where the vehicle yaw angle is the angle between the vehicle axis and the X-axis of the geodetic coordinate system; is the vehicle yaw angular velocity;

[0058] Vehicle heading angle, where the vehicle heading angle is the angle between the vehicle's absolute speed direction and the X-axis of the geodetic coordinate system;

[0059] β Vehicle center of mass sideslip angle, where the vehicle center of mass sideslip angle is the angle between the vehicle's absolute speed direction and the X-axis of the vehicle coordinate system;

[0060] v: absolute speed of the vehicle, determined by the lateral and longitudinal speeds of the vehicle;

[0061] V: The projection of the vehicle's absolute velocity in the vehicle coordinate system;

[0062] P y1 , P y2 : The lateral force on the front and rear wheels of the vehicle;

[0063] δ1, δ2: comprehensive side slip angles of the front and rear wheels;

[0064] δ: steering wheel angle; a: distance from center of mass to front axle; b: distance from center of mass to rear axle;

[0065] l: Wheelbase.

[0066] in:

[0067]

[0068] From the geometric relationship:

[0069]

[0070]

[0071] When the dynamics of the vehicle is ignored, the balance of the y-direction force and the moment balance around the center of mass is:

[0072]

[0073]

[0074] Where m is the mass of the vehicle, and I is the moment of inertia of the vehicle around the Z axis.

[0075] From the mechanical properties of tires, we can get:

[0076]

[0077]

[0078] Where K1 and K2 are the effective cornering stiffness of the front and rear wheels of the vehicle respectively;

[0079] Then, substitute formula (6) (7) into (4) (5), perform Latten transformation, and set the initial condition to zero, r→r(S), β→β(S), and solve for the first transfer function of the vehicle yaw rate r to the vehicle steering wheel angle δ input:

[0080]

[0081] Where S is the Laplace variable.

[0082] Rewrite equation (8) in the form of a standard transfer function:

[0083]

[0084] Among them, G r ' is the steady-state gain.

[0085]

[0086] and

[0087]

[0088]

[0089]

[0090] ρ is the inertia radius of the whole body around the Z axis;

[0091] And define K as the stability factor:

[0092]

[0093] Among them, C1 and C2 are the cornering coefficients of the front and rear wheels (the ratio of cornering stiffness to axle load mass).

[0094]

[0095]

[0096] If the dynamic characteristics of the vehicle steering system are ignored, the vehicle steering wheel angle δ SW The relationship between the steering angle and the vehicle steering wheel angle δ is:

[0097]

[0098] Where i is the steering system transmission ratio.

[0099] Then the vehicle yaw rate r is proportional to the steering wheel angle δ SW The second transfer function is:

[0100]

[0101] in is the steady-state gain of the yaw rate to the steering wheel angle. The second transfer function is determined as the target vehicle model.

[0102] A target vehicle model is constructed to determine the relationship between the steering wheel angle and the vehicle's yaw rate, which facilitates the subsequent construction of the driver model.

[0103] Step 220: construct the target driver model according to the target vehicle model, and determine the process driver model according to the target driver model, so as to determine parameter information of the target driver model according to the process driver model.

[0104] A target driver model is constructed according to the target vehicle model as a part of the target driver model, and a process driver model is determined according to the target driver model, so as to determine parameter information of the target driver model according to the process driver model, so that the target steering wheel angle is determined according to the target driver model, the current road trajectory information and the current yaw angle information obtained through the target driver model.

[0105] Figure 4 This is a basic block diagram of an existing driver model provided by Embodiment 2 of the present invention. Figure 4 As shown, w1, w2, w3, w4 are the driver model weights, y, are the lateral acceleration, lateral velocity and lateral displacement output by the vehicle. Due to the limitations of physiological factors and the moment of inertia of the vehicle steering wheel, the driver does not make a steering action immediately after receiving the road ahead information and vehicle status feedback information during the actual driving process. The vehicle starts to respond after a certain period of time after the driver's control signal is input. Therefore, a delay module is added to the preview optimization artificial neural network driver model:

[0106] in, is the reaction delay of the driver's nervous system, t d It is the delay time of nerve response; Indicates the response delay of the driver's arm and the vehicle steering wheel's rotational inertia, T h is the time constant of the inertia delay link. According to the work of several researchers, the driver's neural response delay time is generally around 0.2 to 0.3 seconds, and the time constant of the inertia delay link is generally 0.1 seconds.

[0107] The driver-vehicle closed-loop system corresponding to the existing driver model is expressed by the transfer function:

[0108]

[0109] Among them, P(S) is the predictor transfer function, which represents the driver's preview link in the driver-vehicle closed-loop system. This link depends on factors such as the driver's preview method; F(S) is the follower transfer function, which represents the driver's steering and vehicle response in the driver-vehicle closed-loop system.

[0110] f: road trajectory information input;

[0111] f e : The effective road trajectory information input obtained after the preview link processing;

[0112] y: Driver-vehicle closed-loop system output.

[0113] The error between the road trajectory input and the closed-loop system output is defined as:

[0114] e(S)=f(S)-y(S) (21)

[0115] Then the transfer function of the error to the road trajectory input is:

[0116]

[0117] Assuming that the driver's eyes are focused on one point in front of him during driving is called the single-point preview assumption, which is usually quite consistent with actual experience. Corresponding to the single-point preview assumption, in the driver-car closed-loop system, the transfer function of the predictor is:

[0118]

[0119] Where T p It is the preview time for the driver.

[0120] Expand it using Taylor series to get:

[0121]

[0122] At the same time, the inverse of the follower transfer function F(S) -1 Also expanded using Taylor series:

[0123] F(S) -1 =F0+F1·S+F2·S 2 +F3·S 3 +··· (25)

[0124] Substituting equations (24) and (25) into equation (22), we can obtain:

[0125]

[0126] It can be seen from the above formula that when the driver-car closed-loop system satisfies:

[0127] p(S)·F(S)≈1 (27)

[0128] That is, the inverse of the follower transfer function should be as close as possible to the predictor transfer function, so that the error of the entire system can be as small as possible and the best possible following effect can be achieved.

[0129] When the follower F(S) satisfies formula (28), F(S) is called an n-order follower. At this time, if the n+1 and higher-order frequency parts are ignored, the error is 0 and the system has a better following effect.

[0130] F i -P i =0(i=0,1,···n) (28)

[0131] The target driver model is a simplified model based on the existing driver model. Figure 5 This is a basic block diagram of a target driver model provided by Embodiment 2 of the present invention. Figure 5 As shown in the figure, w1, w2, w3 are the driver model weights, f(t) is the current road trajectory information of the target vehicle, and f e(t) is the current preview information obtained after f(t) is processed by the preview module. is the target steering wheel angle, δ SW is the actual vehicle steering wheel angle determined according to the target steering wheel angle, r is the actual vehicle yaw velocity determined according to the target steering wheel angle, and Ψ is the actual vehicle yaw angle determined according to the target steering wheel angle.

[0132] In this embodiment, optionally, determining a process driver model according to a target driver model, so as to determine parameter information of the target driver model according to the process driver model, includes:

[0133] Obtaining a first process driver model according to a division operation between the target driver model and a first weight in the target driver model;

[0134] Decomposing the first weight in the first process driver model into a first steady-state gain of the vehicle yaw rate to the steering wheel angle and an undetermined parameter;

[0135] Equivalently converting the delay module in the first process driver model and the target vehicle model into a third transfer function between the target steering wheel angle and the vehicle yaw rate;

[0136] A second process driver model is constructed according to the first process driver model, the first steady-state gain, the undetermined parameter and the third transfer function, so as to determine parameter information of the target driver model according to the second process driver model.

[0137] The first weight w1 of the target driver model is used as a divisor to remove each weight value to obtain a first process driver model. Figure 6 This is a basic block diagram of a first process driver model provided by the second embodiment of the present invention. The factors characterizing the commonality of each weight are reflected in w1, and the ratio of each weight to w1 reflects the relationship between various parameters of the driver model.

[0138] Figure 7 This is a basic block diagram of a second process driver model provided by the second embodiment of the present invention. Figure 7 As shown, the first weight in the first process driver model is decomposed into the first steady-state gain of the vehicle yaw rate to the steering wheel angle and the undetermined parameters; that is, w1 is decomposed into 1 / K0 and 1 / G r Two parts, K0 is an undetermined parameter, G r is the first steady-state gain of the vehicle's yaw rate to the steering wheel angle. Let w1 / w1 be w 11 , let w2 / w1 be w 22 , let w3 / w1 be w 33 .

[0139] The delay module and the target vehicle model in the first process are equivalent to a third transfer function between the target steering wheel angle and the actual vehicle yaw rate;

[0140] Among them, the third transfer function is

[0141] The second process driver model is constructed according to the first process driver model, the first steady-state gain, the undetermined parameter and the third transfer function. By constructing the first process driver model and the second process driver model, the parameters in the target driver model are determined, so as to obtain the target steering wheel angle according to the target driver model, the current road trajectory information and the current yaw angle information obtained by the target driver model, thereby improving the accuracy of obtaining the target steering wheel angle.

[0142] In this embodiment, optionally, determining the current preview information of the current vehicle according to the current road trajectory information and a preview module in a pre-built target driver model includes:

[0143] Determining a target preview time according to the second process driver model, and determining module parameters of the preview module according to the target preview time;

[0144] The current preview information is determined according to the current road trajectory information and the preview module.

[0145] Among them, the target preview time is the optimal preview time, so that the vehicle determines the optimal preview point according to the optimal preview time, so that when the vehicle travels to the optimal preview point, it can avoid being too far away from the preview point to cause a decrease in accuracy, and at the same time avoid being too short away from the preview point to cause the vehicle to swing more frequently.

[0146] In the second process driver model, the equation between each parameter in the driver model and the vehicle state quantity (vehicle yaw rate, vehicle yaw angle) is:

[0147]

[0148] According to the condition of no static error:

[0149] w 11 =-w 22 =1 (30)

[0150] Substitute (29) into (28) and perform Laplace transform on both sides of (28) to obtain:

[0151]

[0152] The equations (24), (28) and (31) are as follows:

[0153]

[0154] Thus, the parameter information of the target driver model is obtained:

[0155]

[0156] Where T p is the preview time of the driver. At the same time, the target preview time can be determined by the second-order and third-order error equations of formula (32):

[0157]

[0158] Determine T q1 and T q2 :

[0159] As mentioned above, the transfer function is the equivalent expression of the delay module of the driver model and the target vehicle model, then:

[0160]

[0161] By calculating and ignoring the high-order terms of the Laplace variable S, we get:

[0162]

[0163] Where, T h ,t d is the time constant of the lag link of the driver model;

[0164] T1, T2, τ1 are the parameters of the two-degree-of-freedom vehicle model, see Equations (11), (12) and (13) for details.

[0165] In summary, the parameters of the target driver model have been analyzed and derived.

[0166] Based on the principle of minimum error, the target preview time is determined according to the second process driver model, and the module parameters of the preview module are determined according to the target preview time, so that the current preview information obtained by the preview module through the current road trajectory information is the optimal preview information, which is convenient for the subsequent acquisition of the optimal steering wheel angle according to the optimal preview information, thereby improving the accuracy of determining the target steering wheel angle.

[0167] The embodiment of the present invention constructs a target vehicle model in a following module according to vehicle yaw angle information; constructs a target driver model according to the target vehicle model, and determines a process driver model according to the target driver model, so as to determine parameter information of the target driver model according to the process driver model, thereby obtaining an optimal steering wheel angle according to the target driver model with determined parameter information, so that the vehicle yaw angle generated when the target vehicle is controlled to drive according to the optimal steering wheel angle at the next moment is the optimal yaw angle, and the difference between the optimal yaw angle at this time and the angle between the tangent of the trajectory at the preview point and the horizontal axis of the geodetic coordinate system is minimized, so that the vehicle yaw angle when the target vehicle reaches the target preview point in the spatial distance is consistent with the tangent direction of the trajectory where the target preview point is located, avoiding the phenomenon that the vehicle frequently yaws left and right during the trajectory tracking process, improving the stability of vehicle control, and thus improving the riding comfort of the user.

[0168] Embodiment 3

[0169] Figure 8 This is a schematic diagram of the structure of a vehicle driving control device provided in the third embodiment of the present invention. The device can be implemented by hardware and / or software, can execute a 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. Figure 8 As shown, the device comprises:

[0170] An information acquisition module 810 is used to acquire current road trajectory information of a target vehicle and current yaw angle information of the target vehicle;

[0171] An information determination module 820, configured to determine current preview information of the current vehicle according to the current road trajectory information and a preview module in a pre-built target driver model;

[0172] The target steering wheel angle acquisition module 830 is used to obtain the target steering wheel angle according to the current yaw angle information, the current preview information and the following module in the target driver model, so as to control the target vehicle to travel according to the target steering wheel angle at the next moment.

[0173] On the basis of the above technical solutions, optionally, the device further includes: a target driver model construction module, the target driver model construction module includes:

[0174] A target vehicle model building unit, used to build a target vehicle model in the following module according to the vehicle yaw angle information; wherein the vehicle yaw angle information includes the vehicle yaw angular velocity;

[0175] The target driver model construction unit is used to construct the target driver model according to the target vehicle model, and determine the process driver model according to the target driver model, so as to determine parameter information of the target driver model according to the process driver model.

[0176] On the basis of the above technical solutions, optionally, the target vehicle model building unit includes:

[0177] A first transfer function determination subunit, used to determine a first transfer function between the vehicle yaw rate and the vehicle steering wheel angle;

[0178] A turning angle relationship acquisition subunit, used for acquiring the turning angle relationship between the vehicle steering wheel angle and the vehicle steering wheel angle;

[0179] The second transfer function determination subunit is used to determine a second transfer function between the vehicle yaw rate and the vehicle steering wheel angle according to the relationship between the first transfer function and the steering angle, and determine the second transfer function as the target vehicle model.

[0180] On the basis of the above technical solutions, optionally, the target driver model building unit includes:

[0181] Determining a process driver model according to a target driver model, so as to determine parameter information of the target driver model according to the process driver model, comprises:

[0182] A first process driver model obtaining subunit, configured to obtain a first process driver model according to a division operation between the target driver model and a first weight in the target driver model;

[0183] A weight decomposition unit, used for decomposing the first weight in the first process driver model into a first steady-state gain of the vehicle yaw rate to the steering wheel angle and a parameter to be determined;

[0184] A third transfer function determination subunit, configured to equate the delay module in the first process driver model and the target vehicle model to a third transfer function between the target steering wheel angle and the vehicle yaw rate;

[0185] The second process driver model construction subunit is used to construct the second process driver model according to the first process driver model, the first steady-state gain, the undetermined parameter and the third transfer function, so as to determine the parameter information of the target driver model according to the second process driver model.

[0186] On the basis of the above technical solutions, optionally, the information determination module includes:

[0187] a module parameter determination unit, configured to determine a target preview time according to the second process driver model, and determine a module parameter of the preview module according to the target preview time;

[0188] A current preview information determination unit is used to determine the current preview information according to the current road trajectory information and the preview module.

[0189] Embodiment 4

[0190] Fig. 9 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0191] like Fig. 9 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0192] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0193] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a vehicle driving control method.

[0194] In some embodiments, the vehicle travel control method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the vehicle travel control method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the vehicle travel control method in any other appropriate manner (e.g., by means of firmware).

[0195] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0196] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0197] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0198] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0199] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0200] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0201] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0202] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle driving control method, characterized in that: include: Acquiring current road trajectory information of a target vehicle and current yaw angle information of the target vehicle; Inputting the current road trajectory information into a preview module in a pre-built target driver model to obtain current preview information of the target vehicle; According to the current yaw angle information, the current preview information and the following module in the target driver model, a target steering wheel angle is obtained, so as to control the target vehicle to travel according to the target steering wheel angle at the next moment; The target driver model construction process includes: Constructing a target vehicle model in the following module according to the vehicle yaw angle information; wherein the vehicle yaw angle information includes the vehicle yaw angular velocity; Constructing the target driver model according to the target vehicle model; Obtaining a first process driver model according to a division operation between the target driver model and a first weight in the target driver model; Decomposing the first weight in the first process driver model into a first steady-state gain of the vehicle yaw rate to the steering wheel angle and an undetermined parameter; Equivalently converting the delay module in the first process driver model and the target vehicle model into a third transfer function between the target steering wheel angle and the vehicle yaw rate; A second process driver model is constructed according to the first process driver model, the first steady-state gain, the undetermined parameter and the third transfer function, so as to determine parameter information of the target driver model according to the second process driver model.

2. The method according to claim 1, characterized in that Constructing a target vehicle model in the following module according to the vehicle yaw angle information includes: Determining a first transfer function between the vehicle yaw rate and the vehicle steering wheel angle; Obtaining the angle relationship between the vehicle steering wheel angle and the vehicle steering wheel angle; According to the relationship between the first transfer function and the steering angle, a second transfer function between the vehicle yaw rate and the vehicle steering wheel angle is determined, and the second transfer function is determined as the target vehicle model.

3. The method according to claim 1, characterized in that Inputting the current road trajectory information into a preview module in a pre-built target driver model to obtain current preview information of the target vehicle includes: Determining a target preview time according to the second process driver model, and determining module parameters of the preview module according to the target preview time; The current preview information is determined according to the current road trajectory information and the preview module.

4. A vehicle driving control device, characterized in that: include: An information acquisition module, used to acquire current road trajectory information of a target vehicle and current yaw angle information of the target vehicle; An information determination module, used for inputting the current road trajectory information into a preview module in a pre-built target driver model to obtain current preview information of the target vehicle; a target steering wheel angle acquisition module, configured to obtain a target steering wheel angle according to the current yaw angle information, the current preview information and a following module in the target driver model, so as to control the target vehicle to travel according to the target steering wheel angle at the next moment; The vehicle driving control device further includes: a target driver model building module; The target driver model building module comprises: A target vehicle model building unit, used to build a target vehicle model in the following module according to the vehicle yaw angle information; wherein the vehicle yaw angle information includes the vehicle yaw angular velocity; a target driver model building unit, configured to build the target driver model according to the target vehicle model, and determine a process driver model according to the target driver model, so as to determine parameter information of the target driver model according to the process driver model; Wherein, the target driver model building unit includes: Determining a process driver model according to a target driver model, so as to determine parameter information of the target driver model according to the process driver model, comprises: A first process driver model obtaining subunit, configured to obtain a first process driver model according to a division operation between the target driver model and a first weight in the target driver model; A weight decomposition unit, used for decomposing the first weight in the first process driver model into a first steady-state gain of the vehicle yaw rate to the steering wheel angle and a parameter to be determined; A third transfer function determination subunit, configured to equate the delay module in the first process driver model and the target vehicle model to a third transfer function between the target steering wheel angle and the vehicle yaw rate; The second process driver model construction subunit is used to construct the second process driver model according to the first process driver model, the first steady-state gain, the undetermined parameter and the third transfer function, so as to determine the parameter information of the target driver model according to the second process driver model.

5. The device according to claim 4, characterized in that The target vehicle model building unit comprises: A first transfer function determination subunit, used to determine a first transfer function between the vehicle yaw rate and the vehicle steering wheel angle; A turning angle relationship acquisition subunit, used for acquiring the turning angle relationship between the vehicle steering wheel angle and the vehicle steering wheel angle; The second transfer function determination subunit is used to determine a second transfer function between the vehicle yaw rate and the vehicle steering wheel angle according to the relationship between the first transfer function and the steering angle, and determine the second transfer function as the target vehicle model.

6. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle driving control method according to any one of claims 1 to 3.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle driving control method according to any one of claims 1 to 3 when executed.

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