CN117584993A

CN117584993A - Vehicle control method, vehicle machine, vehicle and storage medium

Info

Publication number: CN117584993A
Application number: CN202410020525.5A
Authority: CN
Inventors: 郝爽
Original assignee: Continental Software System Development Center Chongqing Co ltd
Current assignee: Continental Software System Development Center Chongqing Co ltd
Priority date: 2024-01-04
Filing date: 2024-01-04
Publication date: 2024-02-23

Abstract

The application relates to the technical field of vehicle control, and discloses a vehicle control method, a vehicle machine, a vehicle and a storage medium. The method is applied to the vehicle and comprises the following steps: determining first road surface information of a first road area based on an image of the first road area, where the vehicle is currently located, acquired by image acquisition equipment, wherein the road surface information comprises an adhesion coefficient and a confidence coefficient of the adhesion coefficient; determining a first numerical value corresponding to a reference index of the vehicle according to the state information of the vehicle, determining whether the vehicle is in an understeer state or not based on the first numerical value and the first reference numerical value, and determining the first reference numerical value based on the first road surface information; in the event that it is determined that the vehicle is in an understeer condition, braking logic corresponding to the understeer condition is executed. Compared with the condition that the first reference value is a fixed value, in the method, the first reference value can be obtained through dynamic adjustment based on the first road surface information, the judgment of the understeer state is more timely, and the execution of the braking logic is also more timely.

Description

Vehicle control method, vehicle machine, vehicle and storage medium

Technical Field

The present disclosure relates to the field of vehicle control technologies, and in particular, to a vehicle control method, a vehicle machine, a vehicle, and a storage medium.

Background

As the demands on safety and comfort of vehicles are increasing, the electronic brake systems (Electronic Brake Systems, EBS) of vehicles are developing more rapidly as an important component of vehicle safety systems. The EBS acquires self-state data of the vehicle such as the wheel speed of the vehicle, the steering angle of the steering wheel, the gravity and the like based on a speed sensor (such as a four-wheel speed sensor), a steering angle sensor (such as a steering wheel steering angle sensor), a gravity sensor and the like, determines a current value corresponding to a reference index corresponding to an abnormal state of the vehicle based on the self-state data, and executes braking logic corresponding to the abnormal state based on the current value and the reference value corresponding to the reference index so as to perform corresponding processing on the vehicle when the abnormal state occurs.

In the above manner, the reference value corresponding to the reference index is obtained based on experiments and is a fixed value. However, the degree of damage of the abnormal state of the vehicle varies in different road situations. The setting of the reference value corresponding to the reference index to be too large or too small can affect the execution of the braking logic corresponding to the abnormal state of the vehicle, thereby affecting the running safety of the user.

Disclosure of Invention

The embodiment of the application provides a vehicle control method, a vehicle machine, a vehicle and a storage medium.

In a first aspect, an embodiment of the present application provides a vehicle control method, applied to a vehicle, where the method includes: determining first road surface information of a first road area based on an image of the first road area, where the vehicle is currently located, acquired by image acquisition equipment, wherein the road surface information comprises an adhesion coefficient and a confidence coefficient of the adhesion coefficient; determining a first numerical value corresponding to a reference index of the vehicle according to the state information of the vehicle, and determining whether the vehicle is in an understeer state or not based on the first numerical value and the first reference numerical value, wherein the reference index is used for indicating the possibility that the vehicle is in the understeer state currently, and the first reference numerical value is determined based on the first road surface information; in the event that it is determined that the vehicle is in an understeer condition, braking logic corresponding to the understeer condition is executed, wherein the braking logic is operable to compensate for the understeer condition of the vehicle.

It can be understood that the vehicle-mounted device determines whether the vehicle is currently in an understeer state based on the first value and the first reference value, and the first reference value is dynamically adjusted based on the road surface information of the first road area where the vehicle is currently located. Compared with the condition that the first reference value is a fixed value, the method adjusts the first reference value based on different road surface information, and the determination of the understeer state is more timely, so that the execution of the brake logic is more timely.

In a possible implementation of the first aspect, the reference indicator includes a difference between a theoretical steering angle and an actual steering angle of the vehicle; and determining whether the vehicle is in an understeer condition based on the first value and the first reference value, comprising: and under the condition that the first values are larger than the first reference value in the first duration, determining that the vehicle is in an understeer state currently.

In a possible implementation of the first aspect, the first duration is determined according to the first road surface information.

The first duration may be obtained based on a second duration, which may be a duration corresponding to second road surface information, and the second road surface information may be road surface information corresponding to a second road area located behind the first road area in a driving direction of the vehicle. Under the condition, if the vehicle determines that the confidence coefficient in the first road surface information is larger than the confidence coefficient threshold value and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the second road surface information, the adhesion coefficient of the road is reduced, the possibility that the vehicle generates an understeer state is increased, and at the moment, the second time length can be reduced to the first time length, namely, the entering time for judging whether the vehicle is in the understeer state is shortened, so that the understeer state is judged more timely.

Similarly, when the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the second road surface information, which indicates that the possibility of the vehicle generating the understeer state is reduced, the second period of time may be increased to the first period of time.

In a possible implementation of the first aspect, the first reference value is determined based on the first road surface information, and includes: acquiring a second reference value corresponding to the stored reference index, wherein the second reference value is determined based on second pavement information; the second reference value is updated to the first reference value based on the first road surface information and the second road surface information.

It is understood that the second reference value is determined based on second road surface information, which may be road surface information corresponding to a second road area located behind the first road area in the traveling direction of the vehicle. That is, at this time, the second reference value is also dynamically determined based on the second road surface information. In addition, the second road surface information may be a road surface information determined by a test in advance before the vehicle leaves the factory. In this case, the second reference value is a fixed value obtained based on the second road surface information, so that it is determined whether the vehicle is in an understeer state based on the fixed second reference value during the running of the vehicle.

In a possible implementation of the first aspect, updating the second reference value to the first reference value based on the first road surface information and the second road surface information includes: reducing the second reference value to a first reference value under the condition that the confidence coefficient in the first road surface information is larger than the first confidence coefficient and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the second road surface information; and increasing the second reference value to the first reference value in the case that the confidence coefficient in the first road surface information is larger than the first confidence coefficient and the adhesion coefficient in the first road surface information is larger than the adhesion coefficient in the second road surface information.

Taking the first reference value as a first UCL entry threshold value corresponding to the first road area, taking the second reference value as a second UCL entry threshold value corresponding to the second road area as an example, if the road surface adhesion coefficient is reduced from the second road area to the first road area, the phenomenon that the vehicle is more likely to have understeer and skid at the moment is indicated. At this time, the size of the UCL entry threshold may be dynamically adjusted based on the first road surface information, for example, the second UCL entry threshold is reduced to the first UCL entry threshold, so that the UCL control logic is triggered more easily or earlier.

It will be appreciated that the above process is performed on the premise that the confidence of the adhesion coefficient in the first road surface information is higher, e.g., greater than the first confidence. Therefore, the accuracy of the adhesive force coefficient in the first road surface information can be ensured to be higher, and the accuracy of the adjustment process is further ensured to be higher.

The determining formula of the UCL entry threshold value is UCL entry threshold value= (brake intervention basic threshold value-UCL offset value) multiplied by a correction coefficient. The correction factor is obtained based on the product of the road condition judgment correction factor, the lateral acceleration correction factor and the turning radius correction factor, so that the road condition judgment correction factor and the UCL entry threshold value form a positive correlation as known from the formula.

Therefore, if the road surface adhesion coefficient is reduced from the second road area to the first road area, the value of the road condition judgment correction factor can be reduced, so that the UCL entry threshold value can be reduced, namely, the second UCL entry threshold value is reduced to the first UCL entry threshold value, so that the UCL control logic is triggered more easily or earlier.

Similarly, if the road surface adhesion coefficient increases from the second road area to the first road area, the UCL entry threshold value can be increased by increasing the road condition judgment correction factor.

In a possible implementation of the first aspect, the second road surface information is road surface information corresponding to a second road area behind the first road area; and, the second reference value is determined based on the third reference value corresponding to the stored reference index and the second road surface information.

In a possible implementation of the first aspect, the second reference value is determined based on a third reference value corresponding to a pre-stored reference index and the second road surface information, and includes: the second reference value is obtained by reducing the third reference value when the difference between the adhesion coefficient in the first road surface information and the adhesion coefficient in the second road surface information is greater than a threshold value and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the second road surface information; or the second reference value is obtained by adding the third reference value when the difference between the adhesion coefficient in the first road surface information and the adhesion coefficient in the second road surface information is greater than a threshold value and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the second road surface information; the difference between the third reference value and the second reference value is smaller than the difference between the second reference value and the first reference value.

It can be understood that the method provided by the application can also be used for performing pre-fine adjustment on the UCL entry threshold value when the adhesion coefficient of the road surface in front of the vehicle running is about to be suddenly changed by judging the road surface information. For example, when the vehicle is driving on the second road area, if it is determined that the difference between the adhesion coefficient of the first road area ahead and the adhesion coefficient of the current second road area is greater than the threshold value, and the adhesion coefficient of the first road area is smaller than the adhesion coefficient of the second road area (i.e., the adhesion coefficient is about to fall), the current third UCL entry threshold value (i.e., the third reference value) may be reduced to the second UCL entry threshold value (i.e., the second reference value), and preparation may be made for the abrupt change of the road surface information in advance. When the vehicle runs on the first road area, the UCL entry threshold value can be further reduced based on the second road surface information and the first road surface information, namely, the second reference value is reduced to the first reference value.

However, in order to avoid that the UCL entry threshold value is adjusted excessively in advance, which affects the current running state of the vehicle, the value of the UCL entry threshold value adjusted in advance needs to be smaller than the adjustment value of the UCL entry threshold value at the present time, that is, the difference between the second reference value and the third reference value needs to be smaller than the difference between the second reference value and the first reference value.

In one possible implementation of the first aspect, in a case where it is determined that the vehicle is in an understeer state, executing the braking logic corresponding to the understeer state includes: determining a second torque corresponding to the self-state information of the vehicle; reducing the torque output by the engine of the vehicle from the first torque to a second torque corresponding to the second torque being greater than a first torque threshold corresponding to the engine of the vehicle; and reducing the torque output by the engine of the vehicle from the first torque to a first torque threshold corresponding to the second torque being less than or equal to the first torque threshold corresponding to the engine.

In a possible implementation of the first aspect, the first torque threshold is determined based on: acquiring a second torque threshold corresponding to an engine of the stored vehicle, wherein the second torque threshold is obtained based on third road surface information; and updating the second torque threshold value to be the first torque threshold value based on the first road surface information and third road surface information, wherein the third road surface information is road surface information corresponding to the second torque threshold value.

It is understood that the third road surface information may be road surface information corresponding to a third road area located behind the first road area where the vehicle is currently located in the traveling direction of the vehicle. That is, at this time, the second torque threshold value is also dynamically determined based on the third-way plane information. In addition, the third road surface information may be road surface information determined by a test in advance before the vehicle leaves the factory. In this case, the second torque threshold value is a fixed value obtained based on the third road surface information so that a specific torque reducing operation is performed based on the fixed second torque threshold value during running of the vehicle.

In a possible implementation of the first aspect, updating the second torque threshold to the first torque threshold based on the first road surface information and the third road surface information includes: increasing the second torque threshold to the first torque threshold under the condition that the confidence coefficient in the first road surface information is larger than the second confidence coefficient and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the third road surface information; and reducing the second torque threshold to the first torque threshold under the condition that the confidence coefficient in the first road surface information is larger than the second confidence coefficient and the adhesion coefficient in the first road surface information is larger than the adhesion coefficient in the third road surface information.

Taking the first torque threshold value as a first torque minimum limit value corresponding to a first road region, the second torque threshold value as a second torque minimum limit value corresponding to a third road region as an example, if the road surface adhesion coefficient is reduced from the third road region to the first road region, the understeer state of the vehicle is more obvious at this time, and the torque of the engine needs to be further reduced. At this time, in order to avoid too small a torque decrease, the torque minimum limit value may be dynamically adjusted, such as increasing the second torque minimum limit value to the first torque minimum limit value.

It will be appreciated that the above process is performed on the premise that the confidence level of the adhesion coefficient in the first road surface information is higher, e.g., greater than the second confidence level. Therefore, the accuracy of the adhesive force coefficient in the first road surface information can be ensured to be higher, and the accuracy of the adjustment process is further ensured to be higher. The values of the first confidence and the second confidence may be the same or different.

The torque minimum limit value is determined by the formula MMin, friction=f (engine_min_tq_tab, engine_min_tq_mu_tab). Wherein MMin and Friction represent torque minimum limit values obtained based on Friction coefficients; f represents the friction coefficient of the engine; the Engine_min_tq_tab parameter represents the reference torque magnitude of the four wheels of the vehicle; the Engine_min_tq_mu_tab parameter represents the reference torque adjustment coefficients for the four wheels of the vehicle. From the above formula, the torque minimum limit value is in positive correlation with the engine_min_tq_tab or the engine_min_tq_mu_tab.

Therefore, if the road surface adhesion coefficient decreases from the third road region to the first road region, the engine_min_tq_tab or the engine_min_tq_mu_tab can be increased, so that the torque minimum limit value can be increased, and the torque of the Engine is prevented from being reduced too little.

Similarly, if the road surface adhesion coefficient increases from the third road region to the first road region, the torque minimum limit value can be further reduced by reducing the value of engine_min_tq_tab or engine_min_tq_mu_tab.

In a second aspect, the present application provides a vehicle machine comprising: one or more processors; one or more memories; the one or more memories store one or more programs that, when executed by the one or more processors, cause the vehicle to perform the first aspect and any one of the possible vehicle control methods of the first aspect.

In a third aspect, the present application provides a vehicle, and the vehicle includes the vehicle machine according to the foregoing second aspect.

In a fourth aspect, the present application provides a computer readable storage medium having instructions stored thereon, which when executed on a computer, cause the computer to perform the first aspect and any one of the possible vehicle control methods of the first aspect.

In a fifth aspect, the present application provides a computer program product comprising: and executing the instructions, wherein the executing instructions are stored in a readable storage medium, and at least one processor of the vehicle machine can read the executing instructions from the readable storage medium, and the executing instructions are executed by the at least one processor, so that the vehicle machine realizes the first aspect and any one of the possible vehicle control methods of the first aspect.

The technical scheme provided by the embodiment of the application at least brings the following beneficial effects:

in the embodiment of the application, the vehicle machine determines a first reference value corresponding to the reference index based on first road surface information (such as an adhesion coefficient and a confidence coefficient) of a road where the vehicle is currently located, determines a first value corresponding to the reference index based on self-state information (such as a steering angle of wheels) of the vehicle, determines whether the vehicle is currently in an understeer state based on the first value and the first reference value, and if so, executes braking logic corresponding to the understeer state to compensate the understeer state of the vehicle. Compared with the condition that the first reference value is a fixed value, in the method, the first reference value can be obtained through dynamic adjustment based on the first road surface information, the determination of the understeer state is more timely, and further the execution of the braking logic is more timely.

Drawings

FIG. 1 illustrates a data processing flow diagram of a conventional electric brake system, according to some embodiments of the present application;

FIG. 2 illustrates a flow diagram of a vehicle control method, according to some embodiments of the present application;

FIG. 3 illustrates a schematic view of a forward region in a direction of travel of a vehicle, according to some embodiments of the present application;

FIG. 4 illustrates a schematic diagram of calibration parameters contained by a brake function control module, according to some embodiments of the present application;

FIG. 5 illustrates a schematic diagram of parameters included in a correction factor, according to some embodiments of the present application;

FIG. 6 is a schematic diagram illustrating a manner of adjustment of a calibration parameter map according to some embodiments of the present application;

FIG. 7 illustrates a flow chart for adjusting a calibration parameter map in the event of a sudden road surface change, according to some embodiments of the present application;

FIG. 8 illustrates a data processing flow diagram of an electronic braking system corresponding to a vehicle control method, according to some embodiments of the present application;

FIG. 9 illustrates a data processing flow diagram of an electronic braking system corresponding to another vehicle control method, according to some embodiments of the present application;

fig. 10 illustrates a system schematic of a vehicle machine, according to some embodiments of the present application.

Detailed Description

Illustrative embodiments of the present application include, but are not limited to, vehicle control methods, vehicle machines, vehicles, and storage media.

The principle of the electric brake system in the vehicle interior will be briefly described first.

Fig. 1 shows a data processing flow chart of a conventional electronic brake system. It will be appreciated that taking a vehicle as an example, in fig. 1, four-wheel speed sensors are used to acquire wheel speed signals of each of four wheels of the vehicle; the steering wheel angle sensor is used for determining a rotation angle signal and a rotation direction signal of the steering wheel when the vehicle turns; the gravity sensor is used for determining a gravity center signal of the vehicle based on the gravity of the vehicle, and the like.

Therefore, after the four-wheel speed sensor acquires the wheel speed signal of each wheel, the steering wheel angle sensor acquires the rotation angle signal and the rotation direction signal of the steering wheel, and the gravity sensor acquires the signals such as the gravity center of the vehicle, the signals can be input into a motion model of the vehicle to obtain the result data such as the wheel speed, the gravity center position, the rotation angle and the rotation direction of the vehicle, and the result data such as the transverse and longitudinal acceleration and the yaw rate of the vehicle can be further obtained through calculation.

The lateral acceleration of the vehicle is acceleration due to centrifugal force generated when the vehicle turns; the longitudinal acceleration of the vehicle refers to acceleration in the traveling direction of the vehicle. Yaw rate refers to the angular velocity at which the vehicle rotates about a Z-axis perpendicular to the ground.

In addition, the pedal state data of the vehicle (for example, determined by displacement of the pedal) and the result data such as the hydraulic pressure data of each connection pump in the vehicle may be obtained based on the motion model of the vehicle from the pedal state signal and the hydraulic pressure signal acquired by the pedal sensor, the hydraulic pressure sensor, and the like in the vehicle.

And then, inputting the result data output by the motion model of the vehicle and a calibration parameter mapping table (hereinafter referred to as a mapping table) of the vehicle into an input signal preprocessing module to perform data preprocessing operation, so as to obtain preprocessed data. The preprocessing operation may be, for example, to adjust the format of data to a data type that can be called by a brake function module in the electronic brake system, remove noise data in the data, and so on.

The calibration parameter mapping table is used for representing one-to-one correspondence between each control logic and corresponding parameter in the input signal preprocessing module, the braking function control module and the arbitration algorithm module. The preprocessing module, the braking function control module and the arbitration algorithm module can help to realize respective algorithms and functions by searching the mapping table.

Taking the example of a brake function control module, the brake function control module includes a plurality of systems, such as an active yaw control (Active Yaw Control, AYC) system, an Anti-lock system (Anti-lock Brake System) system, etc., which can calculate respective function demands based on the data obtained after the preprocessing. For example, the AYC system can control the yaw rate and yaw rate of the vehicle by actively braking the wheels to generate additional yaw moment, thereby improving the stability and handling performance of the vehicle. The system is provided with judgment logic such as understeer control logic (Understeer Control Logic, UCL) and the like, and parameters corresponding to the understeer control logic further comprise UCL entry THRESHOLD value (UCL_threshold_IN), UCL exit THRESHOLD value (UCL_threshold_OUT), confirmation time for entering UCL, confirmation time for exiting UCL and the like. For example, the UCL entry threshold corresponds to a first value, the UCL exit threshold corresponds to a second value, the acknowledgement time period for entering the UCL corresponds to a first time period, the acknowledgement time period for exiting the UCL corresponds to a second time period, and so on. The UCL entering threshold value and the first numerical value can form a calibration parameter mapping table.

It is to be understood that the understeer condition refers to when the steering angle of the steering wheel of the vehicle is fixed, and if the running speed of the vehicle is changed, the actual steering radius of the vehicle is larger than the theoretical steering radius, and the vehicle cannot be steered according to the theoretical steering radius based on the steering angle of the steering wheel, that is, the vehicle is represented as sideslip outward while turning.

For example, if it is determined that the first related parameter is greater than the first value based on the own state data (steering angle, wheel steering angle, etc.) of the vehicle for the first period of time, it indicates that the current state of the vehicle is an understeer state, braking logic needs to be performed, for example, a target speed to which the vehicle needs to be decelerated is calculated to compensate for the understeer state of the vehicle by deceleration, or torque of an engine of the vehicle is reduced to secure driving safety of the vehicle. Similarly, if it is determined that the second related parameter is greater than the second value based on the vehicle's own state data and for the second period of time, it indicates that the current vehicle is in a non-understeer state, i.e., no braking logic is required to be executed.

When the vehicle is in an understeer state, the braking function control module calculates a target speed or target torque, then sends out a deceleration request or a torque reduction request (i.e. a function request), and transmits the deceleration request or the torque reduction request to the arbitration algorithm module for processing.

The arbitration algorithm module performs arbitration based on the functional requirements of each system and the preprocessed data output by the input signal preprocessing module, and an arbitration conclusion is obtained. For example, if the antilock system of the vehicle determines that the functional demand of the antilock system is, based on the current vehicle state, requesting a greater wheel end pressure, and the active yaw control module determines that the functional demand is, requesting a lesser wheel end pressure, then the arbitration algorithm module is required to arbitrate the different wheel end pressures requested by the antilock system and the active yaw control module to obtain the final wheel end pressure because only one wheel end pressure is output at the same time for the same wheel of the vehicle.

Based on the above, after the arbitration algorithm module obtains the arbitration conclusion, the arbitration conclusion is sent to the lower execution module to execute, for example, the arbitration conclusion is that the wheel end pressure of the left front wheel of the vehicle is set to be M newton, and then the lower execution module can apply the wheel end pressure of M newton to the left front wheel of the vehicle based on the arbitration conclusion. The data processing process of the electronic brake system ends.

Based on the above-described process, the reference value corresponding to the reference index corresponding to the abnormal state of the vehicle is fixed, but the degree of damage of the abnormal state of the vehicle is different in different road situations. Setting the reference value corresponding to the reference index too large or too small can affect the execution of the braking logic corresponding to the abnormal state of the vehicle, thereby affecting the running safety of the user. Taking the current value corresponding to the reference index as the first related parameter as an example, after the vehicle machine determines the first related parameter based on the self state data of the vehicle, if the first related parameter is determined to be greater than the first value (UCL entering threshold value), the vehicle can be determined to be in an understeer state, and then the understeer state is processed. However, if the first value is set too large, the vehicle is determined to be in an understeer state when the vehicle is in a serious understeer state, and then the understeer state is processed, and at this time, the running safety of the user cannot be ensured.

In order to solve the technical problems, an embodiment of the present application provides a vehicle control method. In the method, the vehicle-mounted device can determine the condition of the road surface (for example, the adhesion coefficient of the road surface, the confidence coefficient of the adhesion coefficient and the like) based on the image of the road surface where the vehicle is currently located, which is acquired by the image acquisition device. Then, the vehicle machine may determine a reference value (i.e., a first reference value) corresponding to a reference index of the abnormal state of the vehicle based on the road surface condition, and determine a current value (i.e., a first value) corresponding to the reference index based on the state data (e.g., steering angle, etc.) of the vehicle, so as to execute a braking logic corresponding to the abnormal state based on the current value and the reference value (e.g., when the current value is greater than the reference value, determine that the vehicle is in the abnormal state, and execute a corresponding braking logic, such as reducing torque of an engine of the vehicle, etc.), so as to intervene in the abnormal state of the vehicle, and ensure the running safety of the vehicle.

In some embodiments, the vehicle may input at least one image obtained based on the image capturing device and of the road surface on which the vehicle is currently located into the pre-trained adhesion determination model, to obtain the road surface condition of the road surface on which the vehicle is currently located, such as the adhesion coefficient, the confidence of the adhesion coefficient, and the like.

It should be appreciated that the adhesion determination model may be any neural network model that may process an image, such as a convolutional neural network model (CNN). Taking the adhesive force determination model as a convolutional neural network model as an example, after the vehicle machine inputs at least one image into the convolutional neural network, the convolutional neural network model determines the adhesive force coefficient of the road surface by extracting the road surface characteristics in the image, and outputs the related confidence coefficient. The confidence is used to represent the reliability of the adhesion coefficient, and can be expressed as a percentage.

It can be understood that a low road surface adhesion coefficient means that the road surface is smoother, such as an icy or snowy road surface; a high road surface adhesion coefficient means that the road surface is rough, such as a normal asphalt road surface or a gravel road surface.

In some embodiments, the vehicle may input the obtained vehicle state data into an algorithm of a current value corresponding to the specific reference index, so as to obtain the current value corresponding to the reference index. It should be appreciated that the algorithm for the current value to which the reference index corresponds may be any algorithm that can determine the current value.

In some embodiments, the vehicle-mounted device determines the reference value corresponding to the reference index of the abnormal state of the vehicle based on the road surface condition, by adjusting the reference value of the road surface behind the current road surface corresponding to the reference index in the vehicle in real time according to the road surface condition, so as to obtain the reference value of the current road surface corresponding to the reference index.

For example, taking an understeer state as an example, when it is determined that the adhesion coefficient of the road on which the vehicle is traveling is reduced, the possibility that the vehicle is in an understeer and thus slipping state increases, at this time, the UCL entry threshold value may be reduced, the understeer state of the vehicle may be determined earlier, and thus the abnormal state of the vehicle may be handled more timely.

In some embodiments, when it is determined based on the image capturing device that the adhesion is suddenly changed, for example, when the vehicle is moving ahead from a high-adhesion road surface to a low-adhesion road surface, the reference value corresponding to the reference index may be further fine-tuned in advance, for example, the UCL entry threshold value is reduced in advance. In addition, the confirmation time length for entering the UCL can be adjusted in advance, for example, the confirmation time length for entering the UCL is reduced, and the intervention of understeer logic is further accelerated. The method can be used for timely processing the abnormal state of the vehicle by adjusting the magnitude of the reference value corresponding to the reference index in advance, so that the severity of the abnormal state of the vehicle caused by the abrupt change of the road surface adhesive force is reduced.

It can be appreciated that the vehicle control method provided in the embodiment of the present application may be applied to a vehicle. It is understood that a vehicle is any device in a vehicle, etc., such as a processor of a vehicle, that can perform the methods provided herein.

For the purpose of making the technical solutions of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and thoroughly described below with reference to the accompanying drawings. Fig. 2 shows a flow diagram of a vehicle control method according to an embodiment of the present application. In addition, the execution main bodies of the following steps are all vehicle machines, and are not shown one by one for convenience of description. As shown in fig. 2, the process includes, but is not limited to, the following steps:

201: and determining first road surface information of the first road area based on the image of the first road area where the vehicle is currently located, which is acquired by the image acquisition equipment.

In the embodiment of the present application, the first road surface information includes, but is not limited to, an adhesion coefficient of the road surface (for indicating the adhesion magnitude of the road surface) and a confidence (or certainty) of the adhesion coefficient, and it is understood that the confidence is used to indicate the reliability of the adhesion coefficient.

In an exemplary embodiment, if the vehicle machine is to acquire the road surface information of the first road area where the vehicle is currently located, the vehicle machine may first acquire the road surface information of the front area in the driving direction of the vehicle (i.e., the front area of the first road area) based on the image acquisition device. Then, the vehicle can determine when the vehicle is in the front area based on the road surface information of the front area, the distance of the front area from the current position of the vehicle, the current speed of the vehicle, and the like, and store the information in a database inside the vehicle. Therefore, when the vehicle travels to the aforementioned front area, the road surface information of the road surface on which the vehicle is currently located can be acquired by querying the database.

The manner in which the vehicle machine obtains the road surface information of the front area in the vehicle running direction based on the image acquisition device includes, but is not limited to, that after the vehicle machine obtains at least one image of the road surface of the front area in the vehicle running direction based on the image acquisition device located on the vehicle, the at least one image may be input into a pre-trained adhesion determination model, and the adhesion determination model may output the adhesion coefficient of the road surface corresponding to the front area in the vehicle running direction and the confidence of the adhesion coefficient (may also be understood as the confidence of the adhesion determination model) based on the input at least one image.

The adhesion determination model may be any neural network model that can process an image, such as a convolutional neural network model (CNN), among others. Taking the adhesive force determination model as a convolutional neural network model as an example, after the vehicle machine inputs at least one image into the convolutional neural network, the convolutional neural network model determines the adhesive force coefficient of the road surface by extracting the road surface characteristics in the image, and outputs the related confidence coefficient.

It will be appreciated that the aforementioned front region may be a front direction in the vehicle driving direction, or may be an oblique front direction in the vehicle driving direction, and the range of the front region may be empirically set, or may be flexibly adjusted according to an actual application scenario.

Fig. 3 shows a schematic view of a front region in the vehicle traveling direction. As shown in fig. 3, the front region in the vehicle traveling direction is divided into a plurality of different sub-regions. The subareas A1, A2 and A3 can be regarded as different areas right in front of the right wheel in the running direction of the vehicle; similarly, the sub-areas B1, B2, and B3 can be regarded as different areas obliquely ahead of the right wheel in the vehicle traveling direction. The area right in front of the left wheel in the vehicle traveling direction is the same as the area obliquely in front, and will not be described in detail here.

Based on the content of fig. 3, after the vehicle machine acquires at least one image of the front area in the vehicle running direction based on the image acquisition device, the at least one image is input into the adhesion determination model, and the adhesion determination model can output the adhesion coefficient of the road surface corresponding to each sub-area in the vehicle running direction and the confidence of the adhesion coefficient. It will be appreciated that the adhesion determination model may also output a reference distance or the like of each sub-region from the current location of the vehicle based on the at least one image.

After the vehicle machine determines each time when the vehicle reaches each sub-area based on the information such as the reference distance, the current speed of the vehicle and the like, each time, the adhesion coefficient of the road surface corresponding to each sub-area and the confidence coefficient can be stored in the database. When the vehicle is determined to travel to the corresponding sub-region based on each time, the road surface information of the road surface on which the vehicle is currently located can be obtained by querying the database.

In an exemplary embodiment, the distance range of the sub-regions, the adhesion coefficient of the road surface, and the magnitude of the confidence (certainty) may be seen in table 1 below.

TABLE 1

As is clear from table 1, the range of distances between the sub-areas is divided into three sub-areas, each of which is defined by 5 meters, 15 meters, and 25 meters, in front of the right and left wheels of the vehicle and in front of the vehicle. For the road surface adhesion coefficient, if the road surface is a new dry road of concrete, the road surface corresponds to a reference adhesion coefficient; if the road surface is a dry old road of concrete, the road surface corresponds to another reference adhesion coefficient, and the other conditions are the same, and are not described in detail herein. For certainty, taking the example of certainty determined by an adhesion determination model, the adhesion determination model may output a visual reference weight ratio, i.e., certainty, based on the complexity of the information in the image input to the model. It can be understood that, in the embodiment of the present application, since the road surface information obtained based on the adhesion determination model only plays a role of assisting in determining the running state of the vehicle, the range of certainty factor may be 0% -50%.

It should be understood that the relevant data in table 1 is only exemplary, and does not limit the application, that is, the data such as certainty may be flexibly adjusted according to the actual application.

202: and determining a first numerical value corresponding to a reference index of the vehicle according to the state information of the vehicle, and determining whether the vehicle is in an understeer state or not based on the first numerical value and the first reference numerical value, wherein the reference index is used for indicating the possibility that the vehicle is in the understeer state currently, and the first reference numerical value is determined based on the first road surface information.

It will be appreciated that the reference index may refer to the calibration parameter mentioned above (e.g. the difference between the theoretical steering angle and the actual steering angle of the vehicle), and in this case, the reference index and the first reference value corresponding to the reference index may form the calibration parameter map. In this embodiment of the present application, the calibration parameter mapping table includes all calibration parameters in the vehicle and reference values corresponding to the calibration parameters. Taking an electronic brake system in a vehicle as an example, an input signal preprocessing module, a brake function control module and an arbitration algorithm module in the electronic brake system correspond to a plurality of calibration parameters, and the calibration parameters can assist each module to execute respective brake logic for realizing the brake function of the vehicle.

Taking the brake function control module as an example, fig. 4 shows a schematic diagram of calibration parameters included in the brake function control module. As shown in fig. 4, the brake function control module includes a plurality of control systems, such as an Anti-lock braking system (Anti-lock Brake System, ABS), an active yaw control (Active Yaw Control, AYC) system, a traction control system (Traction Control System, TCS), a diesel injection electronic control (Electric Diesel Control, EDC) system, a hill start assist (Hill Start Assist, HAS) system, an intelligent integrated brake (Integrated Power Brake, IPB) system, a steep hill descent control (Hill Descent Control) system, and the like.

Taking an active yaw control (Active Yaw Control, AYC) system of a plurality of control systems as an example, the system further comprises a plurality of control logics, such as yaw rate control logic (BetaP), yaw rate deviation control logic (dpsp), stationary operation angle deviation control logic (dstandle), lane change yaw rate deviation control logic (LCL), sensitive body stabilization logic (SESP), active rollover protection logic (ARP), understeer Control Logic (UCL), trailer stabilization assistance logic (TSA), dynamic torque conversion logic (DTV), and the like. Taking UCL control logic as an example, the UCL control logic is typically triggered when a significant understeer occurs IN the vehicle, and the logic further includes a plurality of calibration parameters, such as UCL entry THRESHOLD (ucl_threshold_in), UCL exit THRESHOLD (ucl_threshold_out), a confirmation period for entering UCL, and a confirmation period for exiting UCL.

It should be understood that, in the embodiment of the present application, the reference index may include a difference between a theoretical steering angle (such as a front wheel steering angle) and an actual steering angle (a front wheel steady steering angle) of the vehicle in the first road area, where the first reference value may be a value corresponding to the UCL entry threshold value mentioned above.

The measurement value of the front wheel steering angle is obtained by measuring the steering wheel angle and dividing the steering angle by the steering ratio of the steering system, and can be also understood as the steering angle of the vehicle steel ring; the steady-state steering angle of the front wheels is a system calculated value and can be understood as the angle of rotation of the tread of the wheel which is in contact with the road surface.

In the case where the reference index includes a difference between the theoretical steering angle and the actual steering angle of the vehicle, determining whether the vehicle is in an understeer state based on the first value and the first reference value includes: and under the condition that the first values are larger than the first reference value in the first duration, determining that the vehicle is in an understeer state currently.

The first duration may refer to an acknowledgement duration into the UCL. It is appreciated that if the first value is greater than the first reference value for a first duration, it may be determined that the vehicle is currently in an understeer condition.

In general, the reference value corresponding to the calibration parameter is a fixed value, but in the embodiment of the present application, the magnitude of the reference value corresponding to the calibration parameter may be dynamically adjusted based on the road surface information, so as to change the triggering or executing condition of each brake logic.

Thus, in one possible implementation, the first reference value may be determined by, but not limited to: acquiring a second reference value corresponding to the stored reference index, wherein the second reference value is determined based on second pavement information; the second reference value is updated to the first reference value based on the first road surface information and the second road surface information.

It may be appreciated that in the embodiment of the present application, the second reference value may be updated to the first reference value based on the first road surface information and the second road surface information, that is, the process of determining the first reference value corresponding to the reference index based on the first road surface information and the second road surface information is a dynamically adjusted process. Further, the method for updating the second reference value to the first reference value based on the first road surface information and the second road surface information comprises the following two methods:

mode one: and reducing the second reference value to the first reference value under the condition that the confidence coefficient in the first road surface information is larger than the first confidence coefficient and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the second road surface information.

Mode two: and increasing the second reference value to the first reference value in the case that the confidence coefficient in the first road surface information is larger than the first confidence coefficient and the adhesion coefficient in the first road surface information is larger than the adhesion coefficient in the second road surface information.

The second road surface information is road surface information corresponding to a second road area behind the first road area; and, the second reference value is determined based on the third reference value corresponding to the stored reference index and the second road surface information.

In the first mode, in the embodiment of the present application, taking the first reference value as the first UCL entry threshold value corresponding to the first road area, the second reference value is the second UCL entry threshold value corresponding to the second road area as an example, if the road surface adhesion coefficient decreases from the second road area to the first road area, it is indicated that the vehicle is more likely to have understeer and skid phenomena at this time. At this time, the size of the UCL entry threshold may be dynamically adjusted based on the first road surface information, for example, the second UCL entry threshold is reduced to the first UCL entry threshold, so that the UCL control logic is triggered more easily or earlier.

Furthermore, the above-described process is performed on the premise that the confidence of the adhesion coefficient in the first road surface information is high, for example, greater than the first confidence. Therefore, the accuracy of the adhesive force coefficient in the first road surface information can be ensured to be higher, and the accuracy of the adjustment process is further ensured to be higher.

In an exemplary embodiment, the UCL entry threshold is determined as follows:

UCL entry threshold= (brake intervention basic threshold-UCL offset value). Times.correction coefficient formula (1)

In the conventional manner of determining the UCL entry threshold, parameters such as the brake intervention basic threshold, the UCL offset value, and the correction coefficient in the above formula (1) are all fixed values, and each parameter may be obtained based on experiments. The braking intervention basic threshold value is determined based on the difference between the theoretical steering angle and the actual steering angle of the vehicle, and the correction coefficient comprises two aspects: a lateral acceleration correction factor and a turning radius correction factor. The correction factor may be, for example, a product of the lateral acceleration correction factor and the turning radius correction factor.

However, as shown in fig. 5, in the embodiment of the present application, the UCL entry threshold value is adjusted based on the first road surface information, so that the parameter of the road condition judgment correction factor can be newly added in the correction factor. That is, in the embodiment of the present application, the correction coefficient in the above formula (1) is obtained based on the product of the road condition determination correction factor, the lateral acceleration correction factor, and the turning radius correction factor. Therefore, the embodiment of the application can determine the road condition judgment correction factor (such as increasing or decreasing the road condition judgment correction factor) based on the first road surface information, multiply the determined road condition judgment correction factor with the lateral acceleration correction factor and the turning radius correction factor to obtain the correction factor, and obtain the first UCL entry threshold based on the formula (1). It can be understood that the road condition judgment correction factor and the UCL entry threshold value are in positive correlation under the condition that the brake intervention basic threshold value, the UCL offset value, the lateral acceleration correction factor and the turning radius correction factor are fixed. Therefore, in the mode, the road condition judgment correction factor can be dynamically adjusted based on the first road surface information, so that the aim of adjusting the UCL entry threshold value (namely determining the first UCL entry threshold value) is fulfilled.

For example, the correspondence between the road surface information (e.g., the first road surface information) and the road condition determination correction factor can be seen in table 2 below.

TABLE 2

Based on the above table, it can be understood that if the current road surface is low in adhesion coefficient and the adhesion coefficients of the roads where the two front tires of the vehicle are located are approximately the same, the situation that the vehicle is possibly under-turned is indicated, and the road condition judgment correction factor can be adjusted to 90% -100%, that is, the road condition judgment correction factor is reduced, so as to reduce the UCL entering threshold value. In addition, in this case, as long as the adhesion coefficient of the road surface is smaller, the value of the road condition judgment correction factor is smaller, so that when the adhesion of the road surface is reduced and the possibility of occurrence of an understeer state is increased, the UCL entering threshold value is reduced, and the UCL control logic is easier to enter.

Similarly, for the second mode, if the adhesion coefficient of the road surface increases, the value of the road condition determination correction factor can be appropriately increased, so that the UCL entry threshold value can be appropriately increased when the possibility of occurrence of an understeer condition of the vehicle decreases.

If the current road surface is low in adhesion coefficient and the adhesion of the road surface corresponding to the wheel in the steering direction of the vehicle is lower than that of the road surface corresponding to the wheel at the other side, the possibility of understeer of the vehicle is higher, and the road condition judgment correction factor can be adjusted to 80% -90% at the moment, so that the road condition judgment correction factor is reduced to a larger extent, and the UCL entry threshold value is reduced. If the current road surface is low in adhesion coefficient, but the adhesion of the road surface corresponding to the wheel in the steering direction of the vehicle is higher than that of the road surface corresponding to the wheel at the other side, the possibility of understeer of the vehicle is smaller, and the road condition judgment correction factor can be adjusted to be 100% -105% at the moment, so that the road condition judgment correction factor is improved, and the UCL entry threshold value is improved.

The above table is merely illustrative of the relationship between different road surface information and road condition determination correction factors, and is merely for clearly showing the relationship between the magnitude of the adhesion of the road surface (which may indicate the ease of occurrence of understeer of the vehicle) and the trend of adjustment of the UCL entry threshold, and does not constitute all limitations of the embodiments of the present application. It can be understood that the specific value of the road condition judgment correction factor can be determined according to the specific adhesion coefficient, the confidence coefficient and the like. For example, the road surface information such as the adhesion coefficient and the confidence coefficient may be input to a pre-trained correction factor determination model to output a specific selected value of the road condition judgment correction factor.

It can be understood that, based on the situation shown in fig. 3, in the embodiment of the present application, the vehicle may adjust the road condition judgment correction factors corresponding to all the sub-areas according to the above manner, so as to adjust the UCL entry threshold value (that is, each time the vehicle is in a sub-area, the road condition judgment correction factors are adjusted based on the road surface information of the current sub-area, so as to adjust the UCL entry threshold value). In addition, the vehicle machine can also determine a target subarea which is most likely to generate understeer in the running process of the vehicle based on the road surface information, the wheel speed of the current vehicle, the steering theoretical value, the actual value difference and the like, and adjust the road condition judgment correction factor based on the road surface information of the target subarea only when the vehicle runs in the target subarea, so as to adjust the UCL entering threshold value. Compared with the mode of adjusting the road condition judgment correction factors corresponding to each sub-area, the road condition judgment correction factor adjustment method can reduce the calculated amount, can also reduce the storage amount of road surface information and the like, and saves the storage space.

Fig. 6 shows a schematic diagram of an adjustment manner of the calibration parameter map. As shown in fig. 6, taking UCL control logic as an example, on the basis of a conventional calibration parameter mapping table, whenever the adhesion coefficient of the current road surface is low or high, as long as the confidence of the adhesion coefficient is high and the vehicle is prone to an understeer state, the UCL entering threshold value can be reduced, the UCL exiting threshold value can be increased, and the confirmation time for entering the UCL can be correspondingly reduced, or the confirmation time for exiting the UCL can be correspondingly increased. And then obtaining an adjusted calibration parameter mapping table based on the adjustment process.

In other embodiments, the application may further perform pre-fine adjustment on the calibration parameter mapping table by determining the road surface information when the adhesion coefficient of the road surface in front of the vehicle is about to break.

In this case, the determination manners of the aforementioned second reference value include, but are not limited to: obtaining a second reference value by reducing the third reference value under the condition that the difference value between the adhesion coefficient in the first road surface information and the adhesion coefficient in the second road surface information is larger than a threshold value and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the second road surface information; or when the difference value between the adhesion coefficient in the first road surface information and the adhesion coefficient in the second road surface information is larger than a threshold value and the adhesion coefficient in the first road surface information is larger than the adhesion coefficient in the second road surface information, obtaining a second reference value by adding a third reference value; the difference between the third reference value and the second reference value is smaller than the difference between the second reference value and the first reference value.

For example, in the understeer control logic, when the vehicle determines that a sudden change of road surface information occurs in front of the running of the vehicle, for example, the vehicle is about to break from a high-adhesion road surface to a low-adhesion road surface, the calibration parameter map may be fine-tuned in advance, that is, the understeer entry threshold value (UCL entry threshold value) is adjusted at the current time, and the third reference value is reduced to the second reference value. It can be understood that the UCL entry threshold value can still be finely adjusted by changing the road condition judgment correction factor.

The corresponding relationship between the road abrupt change condition and the road condition judgment correction factor can be seen in the following table 3.

TABLE 3 Table 3

Abrupt pavement condition	Road condition judgment correction factor
		Abrupt change from high-grade road surface to low-grade road surface	95％-100％
Abrupt change from low-grade road to high-grade road	100％-105％

It can be understood that if the vehicle is about to drive into the low-adhesion road surface from the high-adhesion road surface, it is indicated that the vehicle is likely to have an understeer condition, and the value of the road condition judgment correction factor can be selected to be 95% -100% at this time, that is, the UCL entry threshold value is finely adjusted in advance by the above formula (1) and the phenomenon that the vehicle suddenly drives into the low-adhesion road surface from the high-adhesion road surface and has a serious understeer phenomenon during the steering can be avoided to a certain extent. Then, after the vehicle completely enters the low-adhesion road surface, the road condition judgment correction factor can be further reduced according to the corresponding relation in the table 2, the UCL entry threshold value is reduced, and the UCL control logic is executed in time.

In addition, if the vehicle is about to drive into the high-adhesion road surface from the low-adhesion road surface, the possibility that the vehicle is in an understeer condition when driving into the high-adhesion road surface is smaller, and the value of the road condition judgment correction factor can be selected to be 100% -105%, namely the UCL entry threshold value is slightly increased, so that preparation can be made for abrupt change of road surface information in advance, and the current running state of the vehicle can be prevented from being influenced as much as possible.

In this embodiment of the present application, when the road surface in front of the vehicle driving has a sudden change phenomenon, for example, when the vehicle is about to drive from a high-adhesion road surface to a low-adhesion road surface, the confirmation time for entering the UCL (i.e., the first time period) may be reduced in advance. That is, the first duration may also be adjusted according to the first road surface information.

For example, if the traveling road surface of the vehicle is about to be changed from the high-adhesion road surface to the low-adhesion road surface after 200 milliseconds is determined based on the information of the current speed of the vehicle or the like, and if the confirmation time for entering the UCL is originally 500 milliseconds, the confirmation time for entering the UCL may be reduced to 300 milliseconds. Thus, the confirmation time for entering the UCL is reduced, and the vehicle can be confirmed to be in an understeer state earlier, so that corresponding braking logic is executed. In addition, the confirmation time of entering the UCL may be advanced when the vehicle is about to drive from the low-adhesion road surface to the high-adhesion road surface.

Fig. 7 shows a flow chart for adjusting the calibration parameter map in the case of abrupt pavement changes. As shown in fig. 7, the vehicle may identify a pre-correction enable at an auxiliary correction interface for inputting road surface information to a braking module (e.g., a preprocessing module) of the vehicle. For example, when a road surface abrupt condition occurs in front of the vehicle traveling direction, the value of the pre-correction enable of the auxiliary correction interface flag may be set to 1, and when there is no road surface abrupt condition in front of the vehicle traveling direction, the value of the pre-correction enable may be set to 0. Therefore, when the condition of abrupt pavement change occurs, the vehicle machine can judge whether the change of the adhesion coefficient exceeds a threshold value based on each braking module, if so, each braking module can set up a risk identification position (or risk identification position), the risk of understeer of the vehicle is identified, and then a calibration parameter mapping table, such as UCL entering threshold value, is adjusted. If not, clearing the risk identification bit without adjusting the calibration parameter mapping table.

The embodiment of the application only explains the adjustment modes of the UCL entry threshold value and the confirmation time length of entering the UCL, but this does not form the whole limitation of the application, and the UCL exit threshold value, the confirmation time length of exiting the UCL, and the like can be correspondingly adjusted by way of example.

In the method, when the road surface information in front of the vehicle running suddenly changes, the UCL can be pre-finely adjusted to enter the threshold value, and under the condition of avoiding influencing the current running state of the vehicle as much as possible, the preparation is made for the suddenly changing of the road surface information in advance, so that the sudden changing of the road surface condition of the vehicle running can be avoided to a certain extent, and the serious understeer phenomenon occurring during the steering is avoided.

203: in the event that it is determined that the vehicle is in an understeer condition, braking logic corresponding to the understeer condition is executed, wherein the braking logic is operable to compensate for the understeer condition of the vehicle.

It will be appreciated that in the event that it is determined that the vehicle is in an understeer condition, the torque down brake logic corresponding to the understeer condition may be executed, wherein the torque down brake logic is executed in a manner that includes: determining a second torque corresponding to the self-state information of the vehicle; reducing the torque output by the engine of the vehicle from the first torque to a second torque corresponding to the second torque being greater than a first torque threshold corresponding to the engine of the vehicle; and reducing the torque output by the engine of the vehicle from the first torque to a first torque threshold corresponding to the second torque being less than or equal to the first torque threshold corresponding to the engine.

It will be appreciated that the vehicle may determine the second torque based on information about the state of the vehicle, such as steering wheel angle, etc., where the second torque is a torque requested by the vehicle that may compensate for an engine in an understeer condition of the vehicle, and the second torque is less than the first torque, where the first torque may be a torque of the engine when the vehicle is in a non-understeer condition. However, the torque reduction braking logic itself places a limit on the minimum value of the final torque output by the engine to prevent the final torque from being too small, regardless of the magnitude of the second torque requested by the vehicle.

Thus, the final torque requested by the torque-down brake logic is equal to the maximum of the calculated second torque and torque minimum limit (first torque threshold), also denoted mreq_1=max (mreq_2, mmin). Where MReq_1 represents the final torque of the final request, MReq_2 represents the second torque, and MMin represents the torque minimum limit (first torque threshold). The embodiment of the present application does not limit the calculation manner of the second torque, as long as the second torque of the engine that can compensate for the current understeer state of the vehicle can be obtained based on the self-state data of the vehicle.

For example, the torque minimum limit value may be calculated by the following formula (2).

MMin, friction=f (Engine_min_tq_tab, engine_min_tq_mu_tab) equation (2)

Wherein MMin and Friction represent torque minimum limit values obtained based on Friction coefficients; f represents the friction coefficient of the engine; the Engine_min_tq_tab parameter represents the reference torque of four wheels of the vehicle and is a calibration parameter corresponding to the torque reduction braking logic; the Engine_min_tq_mu_tab parameter represents the reference torque adjustment coefficients of the four wheels of the vehicle and is also a calibration parameter corresponding to the torque reduction braking logic. From the above formula, it can be seen that the engine_min_tq_tab parameter and the engine_min_tq_mu_tab parameter are respectively in positive correlation with the torque minimum limit value MMin and the Friction under the condition that the Friction coefficient f is unchanged.

Therefore, the engine_min_tq_tab parameter or the engine_min_tq_mu_tab parameter can be adjusted in real time based on the first road surface information, so that the purpose of adjusting the torque minimum limit value is achieved. Thus, in one possible implementation, the first torque threshold is determined based on: acquiring a second torque threshold corresponding to the stored engine of the vehicle; and updating the second torque threshold value to be the first torque threshold value based on the first road surface information and the third road surface information, wherein the third road surface information is road surface information corresponding to the second torque threshold value.

The method comprises the steps of increasing a second torque threshold to be a first torque threshold under the condition that the confidence coefficient in the first road surface information is larger than the second confidence coefficient and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the third road surface information; and reducing the second torque threshold to the first torque threshold under the condition that the confidence coefficient in the first road surface information is larger than the second confidence coefficient and the adhesion coefficient in the first road surface information is larger than the adhesion coefficient in the third road surface information.

It will be appreciated that if the adhesion coefficient of the first road area where the vehicle is currently located is smaller than that of the third road area, it is indicated that the vehicle is more likely to be in an understeer state, and the torque needs to be reduced, but in order to avoid the understeer, the torque minimum limit value may be further raised based on the above formula (2) by raising the engine_min_tq_tab parameter or the reference value of the engine_min_tq_mu_tab parameter.

Taking the modification of the Engine_min_tq_tab parameter alone as an example, since the formula focuses more on high adhesion roadways, the Engine_min_tq_tab modifier can be designed as follows Table 4:

TABLE 4 Table 4

Road surface information	Engine_min_tq_tab correction factor
		The current road surface is at a high levelCoefficient of adhesion	100％-120％
Other road conditions	100％

As can be seen from Table 4, if the current road surface is a high adhesion coefficient, the selected value of the Engine_min_tq_tab correction factor may be 100% -120%, or the reference value of the Engine_min_tq_tab parameter may be increased by increasing the engine_min_tq_tab correction factor, so as to increase the torque minimum limit value based on the above formula (2). For example, it will be appreciated that the conventional value of the Engine_min_tq_tab parameter may be: (60,80,100,120) taking 110% as an example, the modified engine_min_tq_tab parameter is obtained by multiplying the modifying factor by the conventional engine_min_tq_tab parameter, i.e., (60,80,100,120), respectively (66,88,110,132). In this case, the parameter of engine_min_tq_tab increases, and based on equation (2), it is known that the parameter of engine_min_tq_tab has a positive correlation with the torque minimum limit value, so the torque minimum limit value also increases. The adjustment mode of the calibration parameters can avoid excessive torque reduction of the engine of the vehicle when the understeer phenomenon occurs on the high-adhesion road surface.

Fig. 8 shows a data processing flow chart of an electronic brake system corresponding to the method provided in the embodiment of the application. After the vehicle machine acquires at least one image of the road surface based on the image acquisition equipment, the at least one image is input into an adhesion force determination model (can be understood as being subjected to machine vision analysis), road surface information (such as adhesion force coefficients of the road surface, confidence coefficient of the adhesion force coefficients and the like) of the road surface where the left front wheel and the right front wheel of the vehicle are located at present is obtained respectively, and then the road surface information is sent to an input signal preprocessing module for preprocessing based on an auxiliary correction interface.

In addition, the vehicle machine may input the wheel speed signal of each wheel acquired based on the four-wheel speed sensor, the rotation angle signal and rotation direction signal of the steering wheel acquired by the steering wheel angle sensor, and the signal such as the center of gravity of the vehicle acquired by the gravity sensor into the motion model of the vehicle, so as to obtain the self-state information of the vehicle such as the wheel speed, the center of gravity position, the rotation angle, and the rotation direction of the vehicle. Then, the self-state information of the vehicle is input to an input signal preprocessing module for preprocessing. The input signal preprocessing module can also receive bus signals sent to the network by other controllers, such as engine information, gear information, steering drive information and the like.

In the embodiment of the application, the vehicle machine can dynamically adjust the relevant parameters in the calibration parameter mapping table based on the road surface information to obtain an adjusted calibration parameter mapping table, and then the adjusted calibration parameter mapping table is also input into the input signal preprocessing module for preprocessing.

Then, the vehicle machine sends the preprocessed data to the brake function control module based on the input signal preprocessing module, the brake function control module calculates a function request based on the preprocessed data, for example, when the vehicle is in an understeer state, the vehicle is requested to reduce the speed of the vehicle, or the minimum required torque in the torque reducing brake logic is increased, and the like, and then the function request is output to the arbitration algorithm module for arbitration.

The arbitration algorithm module may receive, in addition to the function request sent by the brake function control module, the preprocessed data output by the input signal preprocessing module, and various requests output on the bus signal of the vehicle, for example, an engine control request, a gear control request, a torque distribution request, a steering execution request, a motor control request, and the like. And after the arbitration algorithm module arbitrates the information, an arbitration result is obtained, and the arbitration structure is transmitted to the lower execution module for execution.

Fig. 9 shows a data processing flow chart of an electronic brake system corresponding to another method provided in an embodiment of the present application. It can be understood that in fig. 9, the vehicle machine sends the acquired road surface information to the input signal preprocessing module based on the auxiliary correction interface, and the information input to the input signal preprocessing module further includes the adjusted calibration parameter mapping table and the vehicle state information (data) obtained based on the wheel speed sensor, the steering wheel angle sensor, the gravity sensor and the motion model of the vehicle. After the input signal preprocessing module performs preprocessing operation on the received information, the preprocessed information is transmitted to each system in the brake function control module, such as an anti-lock system and the like. Each system determines the function request of each system based on the preprocessed information, then sends the function request to a brake system function arbitration module (namely the arbitration algorithm module described above) for arbitration, and finally sends the arbitration result to a subordinate execution module for execution.

It will be appreciated that the above embodiments have been described with respect to a method of determining whether an understeer condition of a vehicle has occurred and employing torque-reducing braking logic to compensate for the understeer condition when the vehicle has occurred. However, it should be understood that the method provided in the present application is not limited to determining whether the vehicle is in an understeer state, for example, whether the vehicle is in an oversteer abnormal state or not may also be determined, and in the case of a reduced adhesion coefficient, the reference value (for example, determining the threshold value for entering the abnormal state) corresponding to the reference index of the abnormal state may be reduced, so that the determination of the abnormal state is more timely.

Fig. 10 shows a block diagram of a vehicle machine 1400 according to an embodiment of the present application. In one embodiment, the vehicle 1400 may include one or more processors 1404, system control logic 1408 coupled to at least one of the processors 1404, a system memory 1412 coupled to the system control logic 1408, a non-volatile memory (NVM) 1416 coupled to the system control logic 1408, and a communication interface 1420 coupled to the system control logic 1408.

In some embodiments, the processor 1404 may include one or more single-core or multi-core processors. In some embodiments, the processor 1404 may include any combination of general-purpose processors and special-purpose processors (e.g., graphics processors, application processors, baseband processors, etc.). In embodiments where the vehicle 1400 employs an eNB (enhanced Node B) or RAN (Radio Access Network ) controller, the processor 1404 may be configured to perform various conforming embodiments, such as one or more of the multiple embodiments shown in fig. 2.

In some embodiments, the system control logic 1408 may include any suitable interface controller to provide any suitable interface to at least one of the processors 1404 and/or any suitable device or component in communication with the system control logic 1408.

In some embodiments, the system control logic 1408 may include one or more memory controllers to provide an interface to the system memory 1412. The system memory 1412 may be used for loading and storing data and/or instructions. In some embodiments, memory 1412 of car machine 1400 may include any suitable volatile memory, such as suitable Dynamic Random Access Memory (DRAM).

NVM/memory 1416 may include one or more tangible, non-transitory computer-readable media for storing data and/or instructions. In some embodiments, NVM/memory 1416 may include any suitable non-volatile memory, such as flash memory, and/or any suitable non-volatile storage device, such as at least one of a Hard Disk Drive (HDD), compact Disc (CD) Drive, digital versatile Disc (Digital Versatile Disc, DVD) Drive.

NVM/memory 1416 may include a portion of the storage resources on the device on which the car machine 1400 is installed, or it may be accessed by, but is not necessarily part of, the apparatus. For example, NVM/memory 1416 may be accessed over a network via communication interface 1420.

In particular, the system memory 1412 and NVM/storage 1416 may include: a temporary copy and a permanent copy of instructions 1424. The instructions 1424 may include: instructions that, when executed by at least one of the processors 1404, cause the vehicle machine 1400 to implement the method shown in fig. 2. In some embodiments, instructions 1424, hardware, firmware, and/or software components thereof may additionally/alternatively be disposed in system control logic 1408, communication interface 1420, and/or processor 1404.

Communication interface 1420 may include a transceiver to provide a radio interface for vehicle 1400 to communicate over one or more networks to any other suitable device (e.g., front end module, antenna, etc.). Illustratively, the communication interface 1420 may be the auxiliary correction interface mentioned previously. The communication interface 1420 may be connected to an image capturing device to receive an image of a road surface of a road where the vehicle is currently located, which is captured by the image capturing device, and transmit the received image to a subsequent processing module or the like. In some embodiments, communication interface 1420 may be integrated with other components of vehicle 1400. For example, communication interface 1420 may be integrated with at least one of processor 1404, system memory 1412, nvm/storage 1416, and a firmware device (not shown) having instructions which, when executed by at least one of processor 1404, cause vehicle 1400 to implement a method as shown in fig. 2.

The image capturing device may be a vehicle-mounted camera, a vehicle-mounted scanner or other devices with shooting functions, such as a mobile phone, a tablet personal computer, etc.

In one embodiment, at least one of the processors 1404 may be packaged together with logic for one or more controllers of the system control logic 1408 to form a System In Package (SiP). In one embodiment, at least one of the processors 1404 may be integrated on the same die with logic for one or more controllers of the system control logic 1408 to form a system on chip (SoC).

The car machine 1400 may further include: input/output (I/O) devices 1432.I/O devices 1432 may include a user interface to enable a user to interact with the truck 1400; the design of the peripheral component interface enables the peripheral component to also interact with the vehicle machine 1400. In some embodiments, the vehicle 1400 further includes a sensor for determining at least one of environmental conditions and location information associated with the vehicle 1400.

In some embodiments, the sensors may include, but are not limited to, gyroscopic sensors, accelerometers, proximity sensors, ambient light sensors, and positioning units. The positioning unit may also be part of the communication interface 1420 or interact with the communication interface 1420 to communicate with components of a positioning network, such as Global Positioning System (GPS) satellites. It will be appreciated that the sensor may be used to collect vehicle state data such as wheel speed signals of the wheels, rotation angle signals and rotation direction signals of the steering wheel as referred to above.

It should be understood that the structure of the vehicle apparatus in the foregoing disclosure is merely an exemplary structure, and the present application does not specifically limit the structure of the vehicle apparatus, so long as the method provided in the present application may be executed, for example, the vehicle apparatus may also be a processor of a vehicle, or the like.

It is to be appreciated that as used herein, the term module may refer to or include an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and/or memory that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable hardware components that provide the described functionality.

It is to be appreciated that in various embodiments of the present application, the processor may be a microprocessor, a digital signal processor, a microcontroller, or the like, and/or any combination thereof. According to another aspect, the processor may be a single core processor, a multi-core processor, or the like, and/or any combination thereof.

Embodiments disclosed herein may be implemented in hardware, software, firmware, or a combination of these implementations. Embodiments of the present application may be implemented as a computer program or program code that is executed on a programmable system including at least one processor, a storage system (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device.

Program code may be applied to input instructions to perform the functions described herein and generate output information. The output information may be applied to one or more output devices in a known manner. For purposes of this application, a processing system includes any system having a processor such as, for example, a Digital Signal Processor (DSP), microcontroller, application Specific Integrated Circuit (ASIC), or microprocessor.

The program code may be implemented in a high level procedural or object oriented programming language to communicate with a processing system. Program code may also be implemented in assembly or machine language, if desired. Indeed, the mechanisms described in the present application are not limited in scope to any particular programming language. In either case, the language may be a compiled or interpreted language.

In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried by or stored on one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be read and executed by one or more processors. For example, the instructions may be distributed over a network or through other computer readable media. Thus, a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), including but not limited to floppy diskettes, optical disks, read-only memories (CD-ROMs), magneto-optical disks, read-only memories (ROMs), random Access Memories (RAMs), erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), magnetic or optical cards, flash memory, or tangible machine-readable memory for transmitting information (e.g., carrier waves, infrared signal digital signals, etc.) in an electrical, optical, acoustical or other form of propagated signal using the internet. Thus, a machine-readable medium includes any type of machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).

In the drawings, some structural or methodological features may be shown in a particular arrangement and/or order. However, it should be understood that such a particular arrangement and/or ordering may not be required. Rather, in some embodiments, these features may be arranged in a different manner and/or order than shown in the illustrative figures. Additionally, the inclusion of structural or methodological features in a particular figure is not meant to imply that such features are required in all embodiments, and in some embodiments, may not be included or may be combined with other features.

It should be noted that, in the embodiments of the present application, each unit/module is a logic unit/module, and in physical aspect, one logic unit/module may be one physical unit/module, or may be a part of one physical unit/module, or may be implemented by a combination of multiple physical units/modules, where the physical implementation manner of the logic unit/module itself is not the most important, and the combination of functions implemented by the logic unit/module is the key to solve the technical problem posed by the present application. Furthermore, to highlight the innovative part of the present application, the above-described device embodiments of the present application do not introduce units/modules that are less closely related to solving the technical problems presented by the present application, which does not indicate that the above-described device embodiments do not have other units/modules.

It should be noted that in the examples and descriptions of the present application, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

While the present application has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the present application.

Claims

1. A vehicle control method applied to a vehicle machine, the method comprising:

determining first road surface information of a first road area based on an image of the first road area where a vehicle is currently located, wherein the road surface information comprises an adhesion coefficient and a confidence coefficient of the adhesion coefficient;

determining a first numerical value corresponding to a reference index of the vehicle according to the self-state information of the vehicle, and determining whether the vehicle is in an understeer state or not based on the first numerical value and a first reference numerical value, wherein the reference index is used for indicating the possibility that the vehicle is in the understeer state currently, and the first reference numerical value is determined based on the first road surface information;

in the event that it is determined that the vehicle is in the understeer state, executing braking logic corresponding to the understeer state, wherein the braking logic is operable to compensate for the understeer state of the vehicle.

2. The method of claim 1, wherein the reference indicator comprises a difference between a theoretical steering angle and an actual steering angle of the vehicle; and, in addition, the processing unit,

The determining whether the vehicle is in an understeer state based on the first value and a first reference value includes:

and determining that the vehicle is currently in the understeer state under the condition that the first values are larger than the first reference values in a first duration.

3. The method of claim 2, wherein the first duration is determined based on the first road surface information.

4. The method of claim 2, wherein the first reference value is determined based on the first road surface information, comprising:

acquiring a second reference value corresponding to the stored reference index, wherein the second reference value is determined based on second road surface information;

and updating the second reference value to the first reference value based on the first road surface information and the second road surface information.

5. The method of claim 4, wherein the updating the second reference value to the first reference value based on the first road surface information and the second road surface information comprises:

reducing the second reference value to the first reference value in the case that the confidence in the first road surface information is greater than the first confidence and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the second road surface information;

And increasing the second reference value to the first reference value when the confidence in the first road surface information is larger than the first confidence and the adhesion coefficient in the first road surface information is larger than the adhesion coefficient in the second road surface information.

6. The method of claim 5, wherein the second road surface information is road surface information corresponding to a second road region rearward of the first road region; and, in addition, the processing unit,

the second reference value is determined based on a third reference value corresponding to the stored reference index and the second road surface information.

7. The method of claim 6, wherein the second reference value is determined based on a third reference value corresponding to the reference index stored in advance and the second road surface information, comprising:

the second reference value is obtained by reducing the third reference value in the case where the difference between the adhesion coefficient in the first road surface information and the adhesion coefficient in the second road surface information is greater than a threshold value and the adhesion coefficient in the first road surface information is smaller than the adhesion coefficient in the second road surface information; or,

The second reference value is obtained by adding the third reference value in a case where a difference between the adhesion coefficient in the first road surface information and the adhesion coefficient in the second road surface information is greater than a threshold value and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the second road surface information;

wherein the difference between the third reference value and the second reference value is smaller than the difference between the second reference value and the first reference value.

8. The method according to any one of claims 1 to 7, wherein, in the event that it is determined that the vehicle is in the understeer state, executing braking logic corresponding to the understeer state comprises:

determining a second torque corresponding to the self-state information of the vehicle;

reducing the torque output by the engine of the vehicle from a first torque to a second torque corresponding to the second torque being greater than a first torque threshold corresponding to the engine of the vehicle;

and reducing the torque output by the engine of the vehicle from the first torque to a first torque threshold corresponding to the second torque being less than or equal to the first torque threshold corresponding to the engine.

9. The method of claim 8, wherein the first torque threshold is determined based on:

acquiring a stored second torque threshold corresponding to an engine of the vehicle;

updating the second torque threshold value to the first torque threshold value based on the first road surface information and third road surface information, wherein the third road surface information is road surface information corresponding to the second torque threshold value.

10. The method of claim 9, wherein the updating the second torque threshold to the first torque threshold based on the first and third road surface information comprises:

increasing the second torque threshold to the first torque threshold if the confidence in the first road surface information is greater than a second confidence and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the third road surface information;

and reducing the second torque threshold to the first torque threshold under the condition that the confidence coefficient in the first road surface information is larger than the second confidence coefficient and the adhesion coefficient in the first road surface information is larger than the adhesion coefficient in the third road surface information.

11. A vehicle machine, comprising: one or more processors; one or more memories; the one or more memories stores one or more programs that, when executed by the one or more processors, cause the vehicle to perform the vehicle control method of any of claims 1-10.

12. A vehicle comprising the vehicle machine of claim 11.

13. A computer readable storage medium having instructions stored thereon, which when executed on a computer, cause the computer to perform the vehicle control method of any one of claims 1 to 10.