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

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 application relates to the field of vehicle control technology, and in particular to a vehicle control method, a vehicle machine, a vehicle and a storage medium.

Background technique

As people's requirements for vehicle safety and comfort increase day by day, vehicle Electronic Brake Systems (EBS), as an important part of vehicle safety systems, are developing rapidly. EBS collects the vehicle's own status data such as the vehicle's wheel speed, steering wheel angle, and gravity based on speed sensors (such as four-wheel speed sensors), angle sensors (such as steering wheel angle sensors), and gravity sensors, and determines the vehicle based on its own status data The current value corresponding to the reference indicator corresponding to the abnormal state is executed, and the braking logic corresponding to the abnormal state is executed based on the current value and the reference value corresponding to the reference indicator, so that the vehicle can be processed accordingly when the vehicle encounters an abnormal state.

In the above method, the reference value corresponding to the reference indicator is obtained based on experiments and is a fixed value. However, under different road conditions, the degree of harm caused by the abnormal state of the vehicle is different. If the reference value corresponding to the above reference indicator is set too large or too small, it will affect the execution of the braking logic corresponding to the abnormal state of the vehicle, thereby affecting the user's driving safety.

Contents of the invention

Embodiments of the present application provide a vehicle control method, a vehicle machine, a vehicle and a storage medium.

In a first aspect, embodiments of the present application provide a vehicle control method, which is applied to a vehicle. The method includes: determining the first road surface of the first road area based on an image of the first road area where the vehicle is currently located collected by an image acquisition device. Information, wherein the road surface information includes the adhesion coefficient and the confidence level of the adhesion coefficient; determine the first value corresponding to the reference index of the vehicle according to the vehicle's own status information, and determine whether the vehicle is turning based on the first value and the first reference value. Understeer state, where the reference indicator is used to indicate the possibility that the vehicle is currently in an understeer state, and the first reference value is determined based on the first road surface information; when it is determined that the vehicle is in an understeer state, the corresponding understeer is executed Braking logic for a state where the braking logic is used to compensate for the understeer state of the vehicle.

It can be understood that the vehicle engine 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 obtained through dynamic adjustment based on the road surface information of the first road area where the vehicle is currently located. Compared with the situation where the first reference value is a fixed value, this method adjusts the size of the first reference value based on different road surface information, and the determination of the understeer state is more timely, which in turn makes the execution of the braking logic more timely.

In a possible implementation of the above first aspect, the reference index includes the difference between the vehicle's theoretical steering angle and the actual steering angle; and determining whether the vehicle is in an understeer state based on the first value and the first reference value includes: When the first value is greater than the first reference value within the first period of time, it is determined that the vehicle is currently in an understeer state.

In a possible implementation of the above first aspect, the first duration is determined based on the first road surface information.

For example, the first duration may be obtained based on the second duration, the second duration may be the duration corresponding to the second road surface information, and the second road surface information may be the second road located behind the first road area in the driving direction of the vehicle. The road surface information corresponding to the area. In this case, if the vehicle-machine determines that the confidence in the first road surface information is greater than the confidence threshold, and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the second road surface information, it means that the adhesion coefficient of the road decrease, the possibility of the vehicle developing an understeer state increases. At this time, the second duration can be reduced to the first duration, that is, the entry time to determine whether the vehicle is in an understeer state is shortened, so that the understeer state can be determined 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, it means that the possibility of the vehicle producing an understeer state is reduced, and the second time period can be increased to the first time period.

In a possible implementation of the above first aspect, the first reference value is determined based on the first road surface information, including: obtaining a second reference value corresponding to the stored reference index, wherein the second reference value is based on the second road surface Information determination; updating the second reference value to the first reference value based on the first road surface information and the second road surface information.

It can be understood that the second reference value is determined based on the second road surface information, where the second road surface information may be the road surface information corresponding to the second road area located behind the first road area in the driving direction of the vehicle. That is to say, 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 also be a type of road surface information determined in advance through tests 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 whether the vehicle is in an understeer state is determined based on the fixed second reference value during the driving of the vehicle.

In a possible implementation of the above 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: the confidence in the first road surface information is greater than the first confidence degree, and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the second road surface information, the second reference value is reduced to the first reference value; the confidence degree in the first road surface information is greater than the first reference value. A confidence level, and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the second road surface information, the second reference value is increased to the first reference value.

Taking the first reference value as the first UCL entry threshold corresponding to the first road area and the second reference value as the second UCL entry threshold corresponding to the second road area as an example, if from the second road area to the first In the road area, the road adhesion coefficient decreases, which means that the vehicle is more likely to understeer and then skid. At this time, the UCL entry threshold can be dynamically adjusted based on the first road surface information, such as lowering the second UCL entry threshold to the first UCL entry threshold, making the UCL control logic easier or earlier to be triggered. .

It can be understood that the premise for the execution of the above process is that the confidence level of the adhesion coefficient in the first road surface information is relatively high, for example, greater than the first confidence level. In this way, it can be ensured that the adhesion coefficient in the first road surface information is more accurate, thereby making the above-mentioned adjustment process more accurate.

Among them, the formula for determining the UCL entry threshold value is, UCL entry threshold value = (brake intervention basic threshold value - UCL offset value) × correction coefficient. The correction coefficient is obtained based on the product of the road condition judgment correction factor, the lateral acceleration correction factor and the turning radius correction factor. Therefore, from the above formula, it can be seen that the road condition judgment correction factor has a positive correlation with the UCL entry threshold value.

Therefore, if the road adhesion coefficient decreases 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 can be reduced, that is, the second UCL entry threshold can be reduced. The limit is lowered to the first UCL entry threshold, making the UCL control logic easier or earlier to trigger.

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

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

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

It can be understood that the method provided by this application can also pre-finely adjust the UCL entry threshold by judging road surface information when the adhesion coefficient of the road ahead of the vehicle is about to change suddenly. 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, and the adhesion coefficient of the first road area is is less than the adhesion coefficient of the second road area (that is, the adhesion coefficient is about to drop suddenly), at this time, the current third UCL entry threshold value (that is, the third reference value) can be reduced to the second UCL entry threshold value ( That is, the second reference value), you can prepare for sudden changes in road surface information in advance. When the vehicle is traveling on the first road area, the UCL entry threshold can be further reduced based on the second road surface information and the first road surface information, that is, the second reference value is reduced to the first reference value.

However, in order to prevent the UCL entry threshold value from being adjusted too large in advance and affecting the current driving status of the vehicle, the value of the pre-adjusted UCL entry threshold value needs to be smaller than the current adjustment value of the UCL entry threshold value. That is to say, the second The difference between the 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 a possible implementation of the above first aspect, when it is determined that the vehicle is in an understeer state, executing braking logic corresponding to the understeer state includes: determining a second torque corresponding to the vehicle's own state information; corresponding to When the second torque is greater than the first torque threshold corresponding to the engine of the vehicle, the torque output by the engine of the vehicle is reduced from the first torque to the second torque; when the second torque is less than or equal to the first torque threshold corresponding to the engine, the torque output by the vehicle is reduced The torque output by the engine is reduced from the first torque to the first torque threshold.

In a possible implementation of the above first aspect, the first torque threshold is determined based on the following method: obtaining a stored second torque threshold corresponding to the engine of the vehicle, and the second torque threshold is obtained based on the third road surface information; The first road surface information and the third road surface information update the second torque threshold to the first torque threshold, wherein the third road surface information is the road surface information corresponding to the second torque threshold.

It can be 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 driving direction of the vehicle. That is to say, at this time, the second torque threshold is also dynamically determined based on the third road surface information. In addition, the third road surface information may also be a kind of road surface information determined in advance through tests before the vehicle leaves the factory. In this case, the second torque threshold is a fixed value obtained based on the third road surface information, so that a specific torque reduction operation can be performed based on the fixed second torque threshold during driving of the vehicle.

In a possible implementation of the above 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: the confidence in the first road surface information is greater than the second confidence degree, and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the third road surface information, the second torque threshold is increased to the first torque threshold; the confidence in the first road surface information is greater than the second confidence, and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the third road surface information, the second torque threshold is reduced to the first torque threshold.

Taking the first torque threshold as the first torque minimum limit value corresponding to the first road area and the second torque threshold as the second torque minimum limit value corresponding to the third road area as an example, if from the third road area to the first road area , the road adhesion coefficient decreases, which means that the vehicle's understeer state is more obvious at this time, and the engine torque needs to be further reduced. At this time, in order to prevent the torque from being reduced too small, the minimum torque limit value can be dynamically adjusted, such as increasing the second minimum torque limit value to the first minimum torque limit value.

It can be understood that the premise for the execution of the above process is that the confidence level of the adhesion coefficient in the first road surface information is relatively high, for example, greater than the second confidence level. In this way, it can be ensured that the adhesion coefficient in the first road surface information is more accurate, thereby making the above-mentioned adjustment process more accurate. In addition, the values of the first confidence level and the second confidence level may be the same or different.

Among them, the formula for determining the minimum torque limit value is, MMin, Friction=f(Engine_min_tq_tab,Engine_min_tq_mu_tab). Among them, MMin, Friction represents the minimum torque limit value based on the friction coefficient; f represents the friction coefficient of the engine; the Engine_min_tq_tab parameter represents the reference torque of the four wheels of the vehicle; the Engine_min_tq_mu_tab parameter represents the reference torque adjustment coefficient of the four wheels of the vehicle. It can be seen from the above formula that the minimum torque limit value is positively correlated with Engine_min_tq_tab or Engine_min_tq_mu_tab.

Therefore, if the road adhesion coefficient decreases from the third road area to the first road area, the value of Engine_min_tq_tab or Engine_min_tq_mu_tab can be increased. In this way, the minimum torque limit value can be increased to avoid reducing the engine torque too small.

In the same way, if the road adhesion coefficient increases from the third road area to the first road area, you can reduce the minimum torque limit value by reducing the value of Engine_min_tq_tab or Engine_min_tq_mu_tab.

In a second aspect, this application provides a vehicle machine, including: one or more processors; one or more memories; one or more memories store one or more programs. When one or more programs are used by one or more When the processor is executed, the vehicle machine is caused to execute the first aspect and any possible vehicle control method of the first aspect.

In a third aspect, the present application provides a vehicle, and the vehicle includes the vehicle engine related to the aforementioned second aspect.

In a fourth aspect, the present application provides a computer-readable storage medium on which instructions are stored, which when executed on a computer causes the computer to execute the first aspect and any possible vehicle control method of the first aspect.

In a fifth aspect, this application provides a computer program product, including: execution instructions. The execution instructions are stored in a readable storage medium. At least one processor of the vehicle machine can read the execution instructions from the readable storage medium. The at least one processor Executing the execution instruction enables the vehicle machine to implement the first aspect and any possible vehicle control method of the first aspect.

The technical solutions provided by the embodiments of this application at least bring the following beneficial effects:

In this embodiment of the present application, the vehicle-machine determines the first reference value corresponding to the reference index based on the first road surface information (such as adhesion coefficient, confidence level) of the road the vehicle is currently on, and determines the first reference value corresponding to the reference index based on the vehicle's own status information (such as the wheel's Steering angle) determines the first value corresponding to the reference index, and determines whether the vehicle is currently in an understeer state based on the first value and the first reference value. If so, executes the braking logic corresponding to the understeer state to compensate for the understeer of the vehicle. state. Compared with the situation where the first reference value is a fixed value, in this method, the first reference value can be obtained through dynamic adjustment based on the first road surface information, and the determination of the understeer state is more timely, which in turn makes the execution of the braking logic more timely. .

Description of drawings

Figure 1 shows a data processing flow chart of a traditional electronic braking system according to some embodiments of the present application;

Figure 2 shows a schematic flowchart of a vehicle control method according to some embodiments of the present application;

Figure 3 shows a schematic diagram of the front area in the driving direction of the vehicle according to some embodiments of the present application;

Figure 4 shows a schematic diagram of calibration parameters included in a braking function control module according to some embodiments of the present application;

Figure 5 shows a schematic diagram of parameters included in a correction coefficient according to some embodiments of the present application;

Figure 6 shows a schematic diagram of an adjustment method of a calibration parameter mapping table according to some embodiments of the present application;

Figure 7 shows a flow chart for adjusting the calibration parameter mapping table in the case of sudden changes in road surface according to some embodiments of the present application;

Figure 8 shows a data processing flow chart of an electronic braking system corresponding to a vehicle control method according to some embodiments of the present application;

Figure 9 shows a data processing flow chart of an electronic braking system corresponding to another vehicle control method according to some embodiments of the present application;

Figure 10 shows a schematic system diagram of a vehicle machine according to some embodiments of the present application.

Detailed ways

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

The following first briefly explains the principle of the electronic braking system inside the vehicle.

Figure 1 shows a data processing flow chart of a traditional electronic braking system. It can be understood that taking the vehicle as a four-wheeled vehicle as an example, in Figure 1, the four-wheel speed sensor is used to obtain the wheel speed signal of each of the four wheels of the vehicle; the steering wheel angle sensor is used to determine the angle of the steering wheel when the vehicle turns. Rotation angle signal and rotation direction signal; gravity sensor is used to determine the vehicle's center of gravity signal based on the vehicle's gravity.

Therefore, after the four-wheel speed sensor obtains the wheel speed signal of each wheel, the steering wheel angle sensor obtains the rotation angle signal and rotation direction signal of the steering wheel, and the gravity sensor obtains the center of gravity of the vehicle, the above signals can be input to the vehicle. In the motion model, the result data such as the vehicle's wheel speed, center of gravity position, rotation angle, and direction of rotation can be obtained. The result data such as the vehicle's transverse and longitudinal acceleration, yaw angular velocity, etc. can also be further calculated through calculation.

Among them, the lateral acceleration of the vehicle refers to the acceleration caused by the centrifugal force generated when the vehicle turns; the longitudinal acceleration of the vehicle refers to the acceleration in the driving direction of the vehicle. Yaw angular velocity refers to the angular velocity of the vehicle rotating around the Z-axis perpendicular to the ground.

In addition, based on the pedal status signal and hydraulic pressure signal collected by the pedal sensor, hydraulic pressure sensor, etc. inside the vehicle, the vehicle's pedal status data (for example, determined by the displacement of the pedal) and various components inside the vehicle can be obtained based on the vehicle's motion model. Connect result data such as hydraulic pressure data from the pump.

Then, the result data output by the vehicle's motion model and the vehicle's calibration parameter mapping table (hereinafter referred to as the mapping table) are input to the input signal preprocessing module to perform data preprocessing operations to obtain preprocessed data. The preprocessing operation may be, for example, adjusting the format of the data to a data type that can be called by the braking function module in the electronic braking system, and removing noise data in the data.

Among them, the calibration parameter mapping table is used to represent the one-to-one correspondence between each control logic in the input signal preprocessing module, the braking function control module and the arbitration algorithm module and the corresponding parameter size. The preprocessing module, braking function control module and arbitration algorithm module can all assist in realizing their respective algorithms and functions by looking up the mapping table.

Taking the braking function control module as an example, the braking function control module includes multiple systems, such as Active Yaw Control (AYC) system, Anti-lock Brake System (Anti-lock Brake System), etc. These systems can be based on The data obtained after the above preprocessing calculates the respective functional requirements. For example, the AYC system can actively brake the wheels to generate additional yaw moment, thereby controlling the vehicle's yaw rate and yaw rate, and improving the vehicle's stability and handling performance. The system has judgment logic such as understeer control logic (UCL), and the parameters corresponding to the understeer control logic further include UCL entry threshold (UCL_THRESHOLD_IN), UCL exit threshold (UCL_THRESHOLD_OUT), UCL entry threshold The confirmation time and the confirmation time for exiting UCL, etc. For example, the UCL entry threshold corresponds to the first value, the UCL exit threshold corresponds to the second value, the confirmation time for entering UCL corresponds to the first time period, the confirmation time for exiting UCL corresponds to the second time period, etc. Among them, the UCL entry threshold value and the first value can constitute the calibration parameter mapping table.

It should be understood that the understeer state means that when the steering wheel angle of the vehicle is fixed, if the vehicle's driving speed is changed, the actual turning radius of the vehicle is larger than the theoretical turning radius, and the vehicle cannot turn according to the theoretical turning radius based on the steering wheel angle. , that is, the vehicle slides to the outside when turning.

For example, if it is determined based on the vehicle's own state data (steering wheel steering angle, wheel steering angle, etc.) that the first relevant parameter is greater than the first value and continues for the first period of time, it means that the current state of the vehicle is an understeer state, and it is required Execute braking logic, such as calculating the target speed to which the vehicle needs to decelerate to compensate for the vehicle's understeer state by decelerating, or reducing the vehicle's engine torque to ensure vehicle driving safety. Similarly, if it is determined based on the vehicle's own state data that the second relevant parameter is greater than the second value and continues for the second period of time, it means that the current vehicle is in a non-understeer state, that is, there is no need to execute the braking logic.

When the vehicle appears to be in an understeer state, the braking function control module calculates the target speed or target torque, then issues a deceleration request or torque reduction request (i.e., a function request), and submits it to the arbitration algorithm module for processing.

The arbitration algorithm module conducts arbitration based on the functional requirements of each system and the preprocessed data output by the input signal preprocessing module, and obtains the arbitration conclusion. For example, if the vehicle's anti-lock braking system determines that the functional requirement of the anti-lock braking system is to request greater wheel end pressure based on the current vehicle state, and the active yaw control module determines that its functional requirement is to request smaller Wheel end pressure, and because the same wheel of the vehicle can only output one wheel end pressure at the same time, the arbitration algorithm module is required to arbitrate the different wheel end pressures requested by the anti-lock braking system and the active yaw control module. , to obtain the final wheel end pressure.

Based on the above content, after the arbitration algorithm module obtains the arbitration conclusion, it will be handed over to the lower-level execution module for execution. For example, the arbitration conclusion is to set the wheel end pressure of the left front wheel of the vehicle to M Newton, then the lower-level execution module can be based on The arbitration concluded that a wheel end pressure of M Newtons should be applied to the left front wheel of the vehicle. At this point, the data processing process of the electronic braking system ends.

Based on the above process, it can be seen that the reference value corresponding to the reference index corresponding to the abnormal state of the vehicle is fixed, but under different road conditions, the degree of harm of the abnormal state of the vehicle is different. If the reference value corresponding to the reference indicator is set too large or too small, it will affect the execution of the braking logic corresponding to the abnormal state of the vehicle, thereby affecting the user's driving safety. Taking the current value corresponding to the reference index as the first relevant parameter mentioned above as an example, after the vehicle engine determines the first relevant parameter based on the vehicle's own status data, if it is determined that the first relevant parameter is greater than the first value (UCL entry threshold value), it can be determined that the vehicle is in an understeer state, and then the understeer state can be processed. However, if the first value is set too large, it will be determined that the vehicle is in an understeer state only when the vehicle is in a more serious understeer state, and then the understeer state will be processed. At this time, the user's driving safety will not be guaranteed. Assure.

In order to solve the above technical problems, embodiments of the present application provide a vehicle control method. In this method, the vehicle-machine can determine the road surface condition (for example, the adhesion coefficient of the road surface, the confidence level of the adhesion coefficient, etc.) based on the image of the road surface where the vehicle is currently located collected by the image acquisition device. Then, the vehicle engine can determine the reference value (i.e., the first reference value) corresponding to the reference indicator of the vehicle's abnormal state based on the road conditions, and determine the value based on the vehicle's own state data (such as steering wheel steering angle, wheel steering angle, etc.) The current value corresponding to the reference index (i.e., the first value), and then based on the current value and the reference value, the braking logic corresponding to the abnormal state is executed (for example, when the current value is greater than the reference value, it is determined that the vehicle is in an abnormal state, and the corresponding braking is executed. dynamic logic, such as reducing the torque of the vehicle engine, etc.) to intervene in the abnormal state of the vehicle and ensure the driving safety of the vehicle.

In some embodiments, the vehicle-machine can input at least one image of the road surface where the vehicle is currently located based on the image acquisition device into a pre-trained adhesion determination model to obtain the road conditions of the road surface where the vehicle is currently located, such as the adhesion coefficient and Confidence of adhesion coefficient, etc.

It should be understood that the adhesion determination model can be any neural network model that can process images, such as a convolutional neural network model (CNN). Taking the adhesion determination model as a convolutional neural network model as an example, after the vehicle inputs at least one image into the convolutional neural network, the convolutional neural network model determines the adhesion coefficient of the road surface by extracting the pavement features in the image, and Output the associated confidence. Among them, the confidence level is used to express the reliability of the adhesion coefficient, which can be expressed as a percentage.

It can be understood that a low road adhesion coefficient means that the road surface is relatively smooth, such as an ice and snow road; a high road surface adhesion coefficient means that the road surface is rough, such as an ordinary asphalt road or a gravel road.

In some embodiments, the vehicle computer can input the obtained vehicle's own status data into the algorithm of the current value corresponding to the specific reference indicator to obtain the current value corresponding to the reference indicator. It should be understood that the algorithm used to reference the current value corresponding to the indicator can be any algorithm that can determine the current value.

In some embodiments, the vehicle-machine determines the reference value corresponding to the reference indicator of the vehicle's abnormal state based on the road condition. The method may be to determine the reference value of the rear road surface of the current road surface corresponding to the reference indicator inside the vehicle based on the road condition. Adjust in real time to obtain the reference value of the current road surface corresponding to the reference indicator.

For example, taking the understeer state as an example, when it is determined that the adhesion coefficient of the road on which the vehicle is traveling is reduced, it means that the possibility of the vehicle experiencing understeer and then slipping increases. At this time, the UCL entry threshold can be lowered, and It is possible to determine the understeer condition of the vehicle earlier, thus enabling the abnormal condition of the vehicle to be processed in a more timely manner.

In some embodiments, when a sudden change in adhesion is determined based on the image acquisition device, such as when the road ahead of the vehicle changes from a high-adhesion road to a low-adhesion road, the reference value corresponding to the reference index can also be fine-tuned in advance, for example, in advance Lower the UCL entry threshold. In addition, the confirmation time for entering UCL can also be adjusted in advance, such as reducing the confirmation time for entering UCL, to further speed up the intervention of understeer logic. This method can handle the abnormal state of the vehicle in a timely manner by pre-adjusting the reference value corresponding to the reference index, and reduce the severity of the abnormal state of the vehicle caused by sudden changes in road adhesion.

It can be understood that the vehicle control method provided by the embodiment of the present application can be applied to vehicle machines. It can be understood that the vehicle machine is any device in the vehicle that can execute the method provided by this application, such as the processor of the vehicle.

In order to make the purpose and technical solutions of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and in detail below with reference to the accompanying drawings. FIG. 2 shows a schematic flowchart of a vehicle control method according to an embodiment of the present application. In addition, the execution subjects of each of the following steps are all vehicle machines. For convenience of description, they are not shown one by one. As shown in Figure 2, the process includes but is not limited to the following steps:

201: Determine the first road surface information of the first road area based on the image of the first road area where the vehicle is currently located, collected by the image acquisition device.

In the embodiment of the present application, the first road surface information includes but is not limited to the adhesion coefficient of the road surface (used to represent the adhesion strength of the road surface) and the confidence level (or degree of certainty) of the adhesion coefficient. It can be understood that the confidence level is used for Indicates the reliability of the adhesion coefficient.

In an exemplary embodiment, if the vehicle-machine wants to obtain the road surface information of the first road area where the vehicle is currently located, it can first obtain the area in front of the vehicle in the direction of travel (ie, the area in front of the first road area) based on the image acquisition device. road surface information. Then, based on the road surface information of the front area, the distance between the front area and the vehicle's current position, the vehicle's current speed and other information, the vehicle-machine can determine when the vehicle is in the aforementioned front area, and store the above information in a database inside the vehicle-machine. Therefore, when the vehicle travels to the aforementioned front area, it can obtain the road surface information of the road where the vehicle is currently located by querying the database.

The method by which the vehicle-machine acquires the road surface information of the front area in the vehicle's traveling direction based on the image acquisition device includes, but is not limited to, the vehicle-machine acquires at least one of the road surface information of the front area in the vehicle's traveling direction based on the image acquisition device located on the vehicle. After the image is taken, at least one image can be input into the pre-trained adhesion determination model, and the adhesion determination model can output the adhesion coefficient and adhesion force of the road surface corresponding to the front area in the vehicle's driving direction based on the input at least one image. The confidence level of the coefficient (can also be understood as the confidence level of the adhesion determination model).

The adhesion determination model can be any neural network model that can process images, such as a convolutional neural network model (CNN). Taking the adhesion determination model as a convolutional neural network model as an example, after the vehicle inputs at least one image into the convolutional neural network, the convolutional neural network model determines the adhesion coefficient of the road surface by extracting the pavement features in the image, and Output the associated confidence.

It can be understood that the aforementioned front area can be directly in front of the vehicle in the direction of travel, or can be diagonally in front of the vehicle in the direction of travel. The range of the front area can be set based on experience, and can also be flexibly adjusted according to actual application scenarios.

Figure 3 shows a schematic diagram of the front area in the direction of vehicle travel. As shown in Figure 3, the front area in the vehicle traveling direction is divided into multiple different sub-areas. Among them, sub-regions A1, A2 and A3 can be regarded as different areas directly in front of the right wheel in the direction of vehicle travel; similarly, sub-regions B1, B2 and B3 can be regarded as different areas diagonally in front of the right wheel in the direction of vehicle travel. . The same applies to the area directly in front of the left wheel in the direction of vehicle travel and the area diagonally ahead, and will not be described again here.

Based on the content of Figure 3, after the vehicle-machine acquires at least one image of the front area in the vehicle's driving direction based on the image acquisition device, it inputs at least one image into the adhesion determination model, and the adhesion determination model can output the vehicle's driving direction. The adhesion coefficient of the road surface corresponding to each sub-area and the confidence level of the adhesion coefficient. It can be understood that the adhesion determination model can also output the reference distance between each sub-region and the current location of the vehicle based on at least one image.

After the vehicle-machine determines each time the vehicle arrives at each sub-area based on information such as the reference distance and the vehicle's current speed, it can store the adhesion coefficient and confidence level of the road surface corresponding to each time and each sub-area in the database. When it is determined based on each time that the vehicle has traveled to the corresponding sub-area, the road surface information of the road where the vehicle is currently located can be obtained by querying the database.

In an exemplary embodiment, the distance range of the sub-region, the adhesion coefficient of the road surface, and the degree of confidence (certainty) can be seen in Table 1 below.

Table 1

It can be seen from the above Table 1 that for the distance range of the sub-regions, the area directly in front of the left and right wheels of the vehicle and diagonally in front of the vehicle is divided into three sub-regions, with 5 meters, 15 meters and 25 meters as the boundaries respectively. For the pavement adhesion coefficient, if the pavement is a dry new road of concrete, then this pavement corresponds to one reference adhesion coefficient; if the pavement is an old, dry concrete road, it corresponds to another reference adhesion coefficient. The same applies to other situations. I won’t go into details one by one. Regarding the degree of confidence, taking the determination of the degree of certainty through the adhesion determination model as an example, the adhesion determination model can output a visual reference weight ratio, that is, the degree of certainty, according to the complexity of the information in the image input to the model. It can be understood that in the embodiment of the present application, because the road surface information obtained based on the adhesion determination model only serves to assist in determining the driving state of the vehicle, the value range of the confidence level may be 0%-50%.

It can be understood that the relevant data involved in the above-mentioned Table 1 are only illustrative and do not constitute a complete limitation of the present application. That is to say, data such as the degree of confidence can be flexibly adjusted according to actual application conditions.

202: Determine the first value corresponding to the vehicle's reference indicator based on the vehicle's own status information, and determine whether the vehicle is in an understeer state based on the first value and the first reference value, where the reference indicator is used to indicate that the vehicle is currently in an understeer state. The first reference value is determined based on the first road surface information.

It can be understood that the reference index can refer to the calibration parameter mentioned above (such as the difference between the theoretical steering angle and the actual steering angle of the vehicle). In this case, the reference index and the first reference value corresponding to the reference index can constitute Calibration parameter mapping table. In this embodiment of the present application, the calibration parameter mapping table includes all calibration parameters inside the vehicle and reference values corresponding to each calibration parameter. Taking the electronic braking system in a vehicle as an example, the input signal preprocessing module, braking function control module and arbitration algorithm module in the electronic braking system each correspond to multiple calibration parameters. These calibration parameters can assist each module in executing Respective braking logic is used to implement the vehicle's braking function.

Taking the braking function control module as an example, Figure 4 shows a schematic diagram of the calibration parameters included in the braking function control module. As shown in Figure 4, the braking function control module includes multiple control systems, such as Anti-lock Brake System (ABS), Active Yaw Control (AYC) system, and Traction Control System (Traction Control System). , TCS), Diesel Injection Electronic Control (Electric Diesel Control, EDC) system, Hill Start Assist (HAS) system, Intelligent Integrated Power Brake (IPB) system, Hill Descent Control (Hill Descent) Control) system, etc.

Take the Active Yaw Control (AYC) system among multiple control systems as an example. This system also includes multiple control logics, such as yaw rate control logic (BetaP) and yaw rate deviation control logic (DpsiP). , stationary operating angle deviation control logic (Dstangle), lane change yaw rate deviation control logic (LCL), sensitive body stability logic (SESP), active rollover protection logic (ARP), understeer control logic (UCL), trailer stability Auxiliary logic (TSA), dynamic torque conversion logic (DTV), etc. Take UCL control logic as an example. UCL control logic is usually triggered when the vehicle has obvious understeer. This logic contains multiple calibration parameters, such as UCL entry threshold (UCL_THRESHOLD_IN), UCL exit threshold ( UCL_THRESHOLD_OUT), the confirmation time for entering UCL and the confirmation time for exiting UCL, etc.

It should be understood that in the embodiment of the present application, the reference index may include the difference between the theoretical steering angle (for example, front wheel steering angle) and the actual steering angle (front wheel steady steering angle) of the vehicle on the first road area. In this case, , the first reference value can be the value corresponding to the UCL entry threshold mentioned above.

Among them, the measured value of the front wheel steering angle is obtained by measuring the steering wheel angle and dividing it by the steering ratio of the steering system, which can also be understood as the turning angle of the vehicle rim; the front wheel steady-state steering angle is the system calculated value, which can be understood as The angle at which a vehicle's tire tread rotates in contact with the road.

When the reference index includes the 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: the first value is greater than the first value within the first time period. In the case of a reference value, it is determined that the vehicle is currently in an understeer state.

Among them, the first duration may refer to the confirmation duration of entering UCL. It can be understood that if the first value is greater than the first reference value and lasts for the first time, it can be determined that the vehicle is currently in an understeer state.

Normally, the reference values corresponding to the above-mentioned calibration parameters are fixed values. However, in the embodiment of the present application, the reference values corresponding to the calibration parameters can also be dynamically adjusted based on road surface information to change the triggering or execution conditions of each braking logic. .

Therefore, in a possible implementation, the method of determining the first reference value includes but is not limited to: obtaining the second reference value corresponding to the stored reference index, wherein the second reference value is determined based on the second road surface information; The first road surface information and the second road surface information update the second reference value to the first reference value.

It can be understood that in the embodiment of the present application, the second reference value can be updated to the first reference value based on the first road surface information and the second road surface information, that is, the reference index correspondence is determined based on the first road surface information and the second road surface information. The process of the first reference value is a dynamic adjustment process. Further, the methods of updating the second reference value to the first reference value based on the first road surface information and the second road surface information include the following two methods:

Method 1: When the confidence level in the first road surface information is greater than the first confidence level, and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the second road surface information, reduce the second reference value to The first reference value.

Method 2: When the confidence level in the first road surface information is greater than the first confidence level, and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the second road surface information, increase the second reference value to the third A reference value.

The second road surface information is the road surface information corresponding to the 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.

For the above method 1, in the embodiment of the present application, the first reference value is the first UCL entry threshold value corresponding to the first road area, and the second reference value is the second UCL entry threshold value corresponding to the second road area. For example, if the road adhesion coefficient decreases from the second road area to the first road area, it means that the vehicle is more likely to understeer and then slip. At this time, the UCL entry threshold can be dynamically adjusted based on the first road surface information, such as lowering the second UCL entry threshold to the first UCL entry threshold, making the UCL control logic easier or earlier to be triggered. .

In addition, the premise for the execution of the above process is that the confidence level of the adhesion coefficient in the first road surface information is relatively high, for example, greater than the first confidence level. In this way, it can be ensured that the adhesion coefficient in the first road surface information is more accurate, thereby making the above-mentioned adjustment process more accurate.

In an exemplary embodiment, the formula for determining the UCL entry threshold is as follows:

UCL entry threshold value = (brake intervention basic threshold value – UCL offset value) × correction coefficient formula (1)

In the traditional way of determining the UCL entry threshold value, parameters such as the basic brake intervention threshold value, UCL offset value and correction coefficient in the above formula (1) are all fixed values, and each parameter can be obtained based on experiments. Among them, the basic threshold value for braking intervention is determined based on the difference between the theoretical steering angle and the actual steering angle of the vehicle, and the correction coefficient includes two aspects: the lateral acceleration correction factor and the turning radius correction factor. For example, the correction coefficient may be a product of a lateral acceleration correction factor and a 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 the parameter of the road condition judgment correction factor can be added to the correction coefficient. That is to say, 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 judgment correction factor, the lateral acceleration correction factor and the turning radius correction factor. Therefore, the embodiment of the present 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, and then combine the determined road condition judgment correction factor with the lateral acceleration correction factor and the turning radius correction factor. Multiply to obtain the correction coefficient, and then obtain the first UCL entry threshold value based on the above formula (1). It can be understood that when the basic braking intervention threshold value, UCL offset value, lateral acceleration correction factor and turning radius correction factor are fixed, the road condition judgment correction factor has a positive correlation with the UCL entry threshold value. Therefore, in this method, the road condition judgment correction factor can be dynamically adjusted based on the first road surface information, thereby achieving the purpose of adjusting the UCL entry threshold (ie, determining the first UCL entry threshold).

For example, the corresponding relationship between road surface information (such as first road surface information) and road condition judgment correction factors can be seen in Table 2 below.

Table 2

Based on the above table, it can be understood that if the current road surface has a low adhesion coefficient and the adhesion coefficients of the two front tires of the vehicle are approximately the same, it means that the vehicle may understeer, and the road condition judgment can be corrected The factor is adjusted to 90%-100%, that is, the road condition judgment correction factor is reduced to reduce the UCL entry threshold. In addition, in this case, as long as the adhesion coefficient of the road surface is smaller, the selected value of the road condition judgment correction factor will be smaller. This can reduce the adhesion coefficient of the road surface and increase the possibility of understeer. The UCL entry threshold makes it easier for UCL control logic to enter.

In the same way, for the above method 2, if the adhesion coefficient of the road surface increases, the value of the road condition judgment correction factor can be appropriately increased. In this way, when the possibility of the vehicle understeer is reduced, the UCL entry threshold can be appropriately increased. value.

If the current road surface has a low adhesion coefficient and the road adhesion corresponding to the wheel in the steering direction currently requested by the vehicle is lower than the road adhesion corresponding to the wheel on the other side, it means that the vehicle is more likely to understeer. At this time The road condition judgment correction factor can be adjusted to 80%-90%, and the road condition judgment correction factor can be reduced to a greater extent to reduce the UCL entry threshold. If the current road surface has a low adhesion coefficient, but the road adhesion corresponding to the wheel in the steering direction currently requested by the vehicle is higher than the road adhesion corresponding to the wheel on the other side, it means that the vehicle is less likely to understeer. In this case, you can Adjust the road condition judgment correction factor to 100%-105% and increase the road condition judgment correction factor to increase the UCL entry threshold.

The above table only exemplifies the relationship between different road surface information and road condition judgment correction factors, and is only for the purpose of clearly showing the adhesion of the road surface (which can indicate the difficulty of the vehicle understeer) and the UCL entry threshold value. The relationship between the adjustment trends does not constitute all limitations on the embodiments of the present application. It can be understood that the specific value of the road condition judgment correction factor can be determined based on the specific adhesion coefficient and confidence level. For example, road surface information such as adhesion coefficient and confidence level can be input into 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 Figure 3, in the embodiment of the present application, the vehicle-machine can adjust the road condition judgment correction factors corresponding to all sub-areas in the above manner, and then adjust the UCL entry threshold value (that is, every time the vehicle is in a sub-area, the road condition judgment correction factor is adjusted based on the road surface information of the current sub-area, and then the UCL entry threshold is adjusted). In addition, the vehicle computer can also determine the target sub-area where the vehicle is most likely to understeer during driving based on information such as road surface information, current vehicle wheel speed, theoretical steering value, and actual value difference, and only determine the target sub-area when the vehicle is driving in the target sub-area. When entering the area, the road condition judgment correction factor is adjusted based on the road surface information of the target sub-area, and then the UCL entry threshold is adjusted. Compared with the method of adjusting the road condition judgment correction factor corresponding to each sub-region, this method can reduce the amount of calculation, reduce the amount of storage of road surface information, etc., and save storage space.

Figure 6 shows a schematic diagram of an adjustment method of the calibration parameter mapping table. As shown in Figure 6, taking UCL control logic as an example, based on the traditional calibration parameter mapping table, no matter 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 appear In the understeer state, the UCL entry threshold can be reduced, the UCL exit threshold can be increased, and the confirmation time for entering UCL can also be correspondingly reduced, or the confirmation time for exiting UCL can be increased. Then based on the above adjustment process, the adjusted calibration parameter mapping table is obtained.

In some other embodiments, the present application can also pre-finely adjust the calibration parameter mapping table by judging the road surface information when the adhesion coefficient of the road ahead of the vehicle is about to change suddenly.

In this case, the determination method of the aforementioned second reference value includes but is not limited to: 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 the threshold value, and the difference in the adhesion coefficient in the first road surface information is When the adhesion coefficient of is less than the adhesion coefficient in the second road surface information, the second reference value is obtained by reducing the third reference value; or, the adhesion coefficient in the first road surface information is different from the adhesion coefficient in the second road surface information. When the difference in adhesion coefficient is greater than the threshold, and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the second road surface information, the second reference value is obtained by adding the third reference value; where, the third reference value The difference between the numerical 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 engine determines that there is a sudden change in road information in front of the vehicle, for example, the road ahead of the vehicle is about to change from a high-adhesion road to a low-adhesion road, the calibration parameter mapping table can be pre-set Fine-tuning is performed, that is, the understeer entry threshold (UCL entry threshold) is adjusted at the current moment, and the third reference value is reduced to the second reference value. It is understandable that the UCL entry threshold can still be fine-tuned by changing the road condition judgment correction factor.

Among them, the corresponding relationship between sudden changes in road surface and road condition judgment correction factors can be seen in Table 3 below.

table 3

Sudden changes in road surface Road condition judgment correction factor Driving from a high-visibility road to a low-resistance road suddenly changes 95%-100% Driving from a low-visibility road to a high-resistance road suddenly changes 100%-105%

It can be understood that if the vehicle is about to drive from a high-adhesion road to a low-adhesion road, it means that the vehicle is likely to understeer. At this time, the value of the road condition judgment correction factor can be selected to be 95%-100%, that is, through This method and the aforementioned formula (1) pre-fine adjustment of the UCL entry threshold can, to a certain extent, prevent the vehicle from suddenly driving from a high-adhesion road to a low-adhesion road and causing severe understeer when turning. Then, after the vehicle completely drives onto the low-adhesion road surface, the road condition judgment correction factor can be further reduced according to the corresponding relationship in Table 2, the UCL entry threshold value can be reduced, and the UCL control logic can be executed in a timely manner.

In addition, if the vehicle is about to drive from a low-adhesion road to a high-adhesion road, it means that the vehicle is less likely to understeer when entering the high-adhesion road. In this case, the road condition judgment correction factor can be selected to be 100 %-105%, that is, slightly increasing the UCL entry threshold value can not only prepare for sudden changes in road surface information in advance, but also try to avoid affecting the current driving status of the vehicle.

In the embodiment of the present application, when the road surface in front of the vehicle has a sudden change, for example, when the vehicle is about to drive from a high-adhesion road to a low-adhesion road, the confirmation time for entering UCL (i.e., the first duration) can be reduced in advance. . In other words, the first duration can also be adjusted based on the first road surface information.

For example, if it is determined based on the vehicle's current speed and other information that the vehicle's driving road surface will change from a high-adhesion road surface to a low-adhesion road surface after 200 milliseconds, and if the confirmation time for entering UCL is originally 500 milliseconds, then it can be Acknowledgment time for entering UCL is reduced to 300 milliseconds. In this way, the confirmation time for entering UCL can be reduced, and it can be confirmed earlier that the vehicle is in an understeer state, and then the corresponding braking logic can be executed. In addition, when the vehicle is about to drive from a low-adhesion road to a high-adhesion road, the confirmation time for entering UCL can be increased in advance.

Figure 7 shows a flow chart for adjusting the calibration parameter mapping table in the case of sudden changes in road surface. As shown in Figure 7, the vehicle engine can identify pre-correction enablement on the auxiliary correction interface, where the auxiliary correction interface is used to input road surface information to the braking module (such as a preprocessing module) of the vehicle engine. For example, when a sudden change in the road surface occurs in front of the vehicle in the direction of travel, the pre-correction enable value of the auxiliary correction interface identifier can be set to 1. When there is no sudden change in the road surface in the front of the vehicle in the direction of travel, pre-correction is enabled. The value can be set to 0. In this way, when a sudden change in the road surface occurs, the vehicle can determine whether the change in adhesion coefficient exceeds the threshold based on each braking module. If so, each braking module can set up a risk identification position (or risk identification position) to indicate that the vehicle has turned. Insufficient risk, and then adjust the calibration parameter mapping table, such as UCL entry threshold, etc. If not, the risk flag bit is cleared and there is no need to adjust the calibration parameter mapping table.

The embodiment of this application only explains the adjustment method of the UCL entry threshold and the confirmation time for entering UCL, but this does not constitute a complete limitation of this application. For example, the UCL exit threshold and the UCL exit threshold can also be adjusted accordingly. Confirmation time for exiting UCL, etc.

In this method, when there is a sudden change in the road surface information in front of the vehicle, the UCL entry threshold can be fine-tuned in advance to prepare for the sudden change in the road surface information while trying to avoid affecting the current driving state of the vehicle. It can avoid to a certain extent sudden changes in the road conditions on which the vehicle is driving, resulting in severe understeer when turning.

203: When it is determined that the vehicle is in an understeer state, execute braking logic corresponding to the understeer state, where the braking logic is used to compensate for the understeer state of the vehicle.

It can be understood that when it is determined that the vehicle is in an understeer state, the torque reduction braking logic corresponding to the understeer state can be executed, wherein the execution method of the torque reduction braking logic includes: determining the second torque corresponding to the vehicle's own state information. Torque; corresponding to the second torque being greater than the first torque threshold corresponding to the engine of the vehicle, reducing the torque output by the engine of the vehicle from the first torque to the second torque; corresponding to the second torque being less than or equal to the first torque threshold corresponding to the engine , reducing the torque output by the vehicle's engine from the first torque to the first torque threshold.

It can be understood that the vehicle engine can determine the second torque based on the vehicle's own state information, such as steering wheel angle, wheel angle, etc., where the second torque is requested by the vehicle engine and can compensate for the torque of the engine in the understeer state of the vehicle, and The second torque is smaller than the first torque, where the first torque may be the torque of the engine when the vehicle is in a non-understeer state. However, regardless of the size of the second torque requested by the vehicle engine, the torque reduction braking logic itself will impose certain limits on the minimum value of the final torque output by the engine to prevent the final torque from being too small.

Therefore, the final torque requested by the torque reduction braking logic is equal to the calculated maximum value of the second torque and the torque minimum limit value (first torque threshold), which can also be expressed as MReq_1=Max(MReq_2, MMin). Among them, MReq_1 represents the final requested final torque, MReq_2 represents the second torque, and MMin represents the minimum torque limit value (first torque threshold). The embodiment of the present application does not limit the calculation method 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 vehicle's own state data.

For example, the calculation method of the minimum torque limit value can be referred to the following formula (2).

MMin,Friction = f (Engine_min_tq_tab, Engine_min_tq_mu_tab) Formula (2)

Among them, MMin, Friction represents the minimum torque limit value based on the friction coefficient; f represents the friction coefficient of the engine; the Engine_min_tq_tab parameter represents the reference torque of the four wheels of the vehicle, and is the calibration parameter corresponding to the torque reduction braking logic; Engine_min_tq_mu_tab The parameter represents the reference torque adjustment coefficient of the four wheels of the vehicle, and is also the calibration parameter corresponding to the torque reduction braking logic. It can be seen from the above formula that when the friction coefficient f remains unchanged, the Engine_min_tq_tab parameter and Engine_min_tq_mu_tab parameter are positively correlated with the minimum torque limit value MMin, Friction respectively.

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, thereby achieving the purpose of adjusting the minimum torque limit value. Therefore, in a possible implementation, the first torque threshold is determined based on: obtaining a stored second torque threshold corresponding to the engine of the vehicle; and converting the second torque threshold based on the first road surface information and the third road surface information. Updated to the first torque threshold, the third road surface information is road surface information corresponding to the second torque threshold.

Wherein, when the confidence level in the first road surface information is greater than the second confidence level, and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the third road surface information, the second torque threshold is increased to the first Torque threshold; when the confidence in the first road surface information is greater than the second confidence, and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the third road surface information, the second torque threshold is reduced to First torque threshold.

It can be understood that if the adhesion coefficient of the first road area where the vehicle is currently located is less than the adhesion coefficient of the vehicle's third road area, it means that the vehicle is more prone to understeer and needs to reduce the torque. However, in order to avoid the torque being too small , you can increase the minimum torque limit value based on the above formula (2) by increasing the reference value of the Engine_min_tq_tab parameter or Engine_min_tq_mu_tab parameter.

Taking only modifying the Engine_min_tq_tab parameter as an example, since this formula pays more attention to high adhesion road surfaces, the Engine_min_tq_tab correction factor can be designed as shown in Table 4:

Table 4

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

It can be seen from Table 4 that if the current road surface has a high adhesion coefficient, the selected value of the Engine_min_tq_tab correction factor can be 100%-120%. It is also possible to increase the reference value of the Engine_min_tq_tab parameter by increasing the correction factor of Engine_min_tq_tab, and then based on the above formula (2 ) Increase the minimum torque limit value. For example, it can be understood that the traditional value of the Engine_min_tq_tab parameter can be: (60,80,100,120). Taking the correction factor as 110% as an example, multiply the correction factor by the traditional Engine_min_tq_tab parameter size, that is, (60,80,100,120), then The corrected Engine_min_tq_tab parameter size can be obtained as (66,88,110,132). In this case, the parameter size of Engine_min_tq_tab increases, and based on formula (2), it can be seen that the parameter size of Engine_min_tq_tab is positively correlated with the minimum torque limit value, so the minimum torque limit value also increases. This adjustment method of calibration parameters can avoid excessive torque reduction of the vehicle's engine when understeer occurs on high-adhesion roads.

Figure 8 shows a data processing flow chart of the electronic braking system corresponding to the method provided by the embodiment of the present application. After the vehicle-machine acquires at least one image of the road surface based on the image acquisition device, it inputs at least one image into the adhesion determination model (which can also be understood as machine vision analysis) to obtain the current position of the vehicle's left front wheel and right front wheel respectively. The road surface information of the road surface (for example, it may include the adhesion coefficient of the road surface, the confidence level of the adhesion coefficient, etc.), and then sends the road surface information to the input signal preprocessing module for preprocessing based on the auxiliary correction interface.

In addition, the vehicle computer can also input signals such as the wheel speed signal of each wheel obtained by the four-wheel speed sensor, the rotation angle signal and rotation direction signal of the steering wheel obtained by the steering wheel angle sensor, and the center of gravity of the vehicle obtained by the gravity sensor. Into the vehicle's motion model, the vehicle's own status information such as the vehicle's wheel speed, center of gravity position, rotation angle, and direction of rotation are obtained. Then, the vehicle's own status information is input to the 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, etc.

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

Then, the vehicle machine sends the preprocessed data to the braking function control module based on the input signal preprocessing module. The braking function control module calculates the function request based on the preprocessed data. For example, when the vehicle is in an understeer state, the request is to reduce The speed of the vehicle, or increasing the minimum required torque in the torque reduction braking logic, etc., then outputs the function request to the arbitration algorithm module for arbitration.

Among them, in addition to receiving function requests sent by the braking function control module, the arbitration algorithm module can also be based on the preprocessed data output by the input signal preprocessing module and various requests output on the vehicle's bus signal, such as engine control requests. , gear control request, torque distribution request, steering execution request, motor control request, etc. After the arbitration algorithm module arbitrates the above information, it obtains the arbitration result and hands the arbitration structure to the lower-level execution module for execution.

Figure 9 shows another data processing flow chart of the electronic braking system corresponding to the method provided by the embodiment of the present application. It can be understood that in Figure 9, the vehicle-machine sends the acquired road surface information to the input signal preprocessing module based on the auxiliary correction interface. The information input to the input signal preprocessing module also includes the adjusted calibration parameter mapping table and the vehicle-based wheel wheel information. The vehicle's own status information (data) is obtained from the speed sensor, steering wheel angle sensor, gravity sensor and vehicle motion model. After the input signal preprocessing module preprocesses the received information, the preprocessed information is handed over to various systems in the braking function control module, such as the anti-lock braking system. Each system determines the function request of each system based on the preprocessed information, and then submits the function request to the braking system function arbitration module (that is, the arbitration algorithm module mentioned above) for arbitration, obtains the arbitration result, and finally submits the arbitration result to Executed by lower-level execution modules.

It can be understood that the above embodiment only describes the method provided by the present application as an example of determining whether the vehicle is in an understeer state and using torque reduction braking logic to compensate for the understeer state when the vehicle is in the understeer state. However, it should be understood that the method provided by this application is not limited to determining whether the vehicle is in an understeer state. For example, it can also be determined whether the vehicle is in an abnormal state such as oversteer, and both can reduce the reference index of the abnormal state when the adhesion coefficient is reduced. The corresponding reference value (such as determining the threshold value for entering the abnormal state, etc.) makes the judgment of the abnormal state more timely.

In this embodiment of the present application, the vehicle-machine determines the first reference value corresponding to the reference index based on the first road surface information (such as adhesion coefficient, confidence level) of the road the vehicle is currently on, and determines the first reference value corresponding to the reference index based on the vehicle's own status information (such as the wheel's Steering angle) determines the first value corresponding to the reference index, and determines whether the vehicle is currently in an understeer state based on the first value and the first reference value. If so, executes the braking logic corresponding to the understeer state to compensate for the understeer of the vehicle. state. Compared with the situation where the first reference value is a fixed value, in this method, the first reference value can be obtained through dynamic adjustment based on the first road surface information, and the determination of the understeer state is more timely, which in turn makes the execution of the braking logic more timely. .

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

In some embodiments, processor 1404 may include one or more single-core or multi-core processors. In some embodiments, processor 1404 may include any combination of general-purpose processors and special-purpose processors (eg, graphics processors, applications processors, baseband processors, etc.). In an embodiment where the vehicle machine 1400 adopts an eNB (Evolved Node B, enhanced base station) or a RAN (Radio Access Network, radio access network) controller, the processor 1404 may be configured to execute various conforming embodiments, for example, One or more of the multiple embodiments shown in FIG. 2 .

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

In some embodiments, system control logic 1408 may include one or more memory controllers to provide an interface to system memory 1412 . System memory 1412 may be used to load and store data and/or instructions. In some embodiments, memory 1412 of vehicle engine 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 a hard disk drive (Hard Disk Drive, HDD), a compact disk (Compact Disc) , CD) drive, at least one of a Digital Versatile Disc (Digital Versatile Disc, DVD) drive.

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

In particular, system memory 1412 and NVM/storage 1416 may include temporary and permanent copies of instructions 1424, respectively. Instructions 1424 may include instructions that, when executed by at least one of the processors 1404, cause the vehicle engine 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 placed in system control logic 1408, communications interface 1420, and/or processor 1404.

The communication interface 1420 may include a transceiver for providing a radio interface for the vehicle machine 1400 to communicate with any other suitable devices (such as front-end modules, antennas, etc.) through one or more networks. For example, the communication interface 1420 may be the aforementioned auxiliary correction interface. The communication interface 1420 can be connected to an image collection device to receive images of the road surface where the vehicle is currently located collected by the image collection device, and send the received images to subsequent processing modules and the like. In some embodiments, the communication interface 1420 may be integrated with other components of the vehicle machine 1400 . For example, communication interface 1420 may be integrated with at least one of processor 1404, system memory 1412, NVM/memory 1416, and a firmware device (not shown) with instructions that when at least one of processor 1404 executes said When instructed, the vehicle computer 1400 implements the method shown in Figure 2.

Among them, the image collection device can be a vehicle-mounted camera, a vehicle-mounted camera, a vehicle-mounted scanner, or other devices with shooting functions, such as mobile phones, tablets, etc.

In one embodiment, at least one of the processors 1404 may be packaged 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 a chip (SoC).

Vehicle engine 1400 may further include input/output (I/O) devices 1432 . The I/O device 1432 may include a user interface to enable the user to interact with the vehicle computer 1400; the peripheral component interface is designed to enable peripheral components to also interact with the vehicle computer 1400. In some embodiments, the vehicle machine 1400 further includes a sensor for determining at least one of environmental conditions and location information related to the vehicle machine 1400 .

In some embodiments, sensors may include, but are not limited to, gyroscope sensors, accelerometers, proximity sensors, ambient light sensors, and positioning units. The positioning unit may also be part of or interact with the communication interface 1420 to communicate with components of the positioning network (eg, Global Positioning System (GPS) satellites). It can be understood that the sensor can be used to collect the vehicle's own status data such as the wheel speed signal of the wheel, the rotation angle signal of the steering wheel, and the rotation direction signal mentioned above.

It can be understood that the structure of the vehicle engine involved in the above content is only an exemplary structure. This application does not specifically limit the structure of the vehicle engine, as long as the method provided by the application can be executed. For example, the vehicle engine can also be a vehicle processing unit. Devices etc.

It will be understood 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 grouped) that executes one or more software or firmware programs and or may be part of memory, combinational logic circuitry, and/or other suitable hardware components that provide the functionality described.

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

Various embodiments disclosed in this application may be implemented in hardware, software, firmware, or a combination of these implementation methods. Embodiments of the present application may be implemented as a computer program or program code executing 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 to generate output information. Output information can be applied to one or more output devices in a known manner. For the purposes of this application, a processing system includes any system having a processor such as, for example, a digital signal processor (DSP), a microcontroller, an application specific integrated circuit (ASIC), or a microprocessor.

Program code may be implemented in a high-level procedural language or an object-oriented programming language to communicate with the processing system. When necessary, assembly language or machine language can also be used to implement program code. In fact, the mechanisms described in this application are not limited to the scope of 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 on or stored on one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be operated by one or more processors Read and execute. For example, instructions may be distributed over a network or through other computer-readable media. Thus, machine-readable media 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 disks, optical disks, optical disks, read-only memories (CD-ROMs), magnetic Optical disk, read-only memory (ROM), random-access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic or optical card, flash memory, or Tangible machine-readable storage used to transmit information (e.g., carrier waves, infrared signals, digital signals, etc.) using electrical, optical, acoustic, or other forms of propagated signals over the Internet. Thus, machine-readable media includes any type of machine-readable media suitable for storing or transmitting electronic instructions or information in a form readable by a machine (eg, computer).

In the drawings, some structural or methodological features may be shown in specific arrangements and/or orders. However, it should be understood that such specific arrangement and/or ordering may not be required. Rather, in some embodiments, the 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 these features may not be included or may be combined with other features.

It should be noted that each unit/module mentioned in each device embodiment of this application is a logical unit/module. Physically, a logical unit/module can be a physical unit/module, or it can be a physical unit/module. Part of the module can also be implemented as a combination of multiple physical units/modules. The physical implementation of these logical units/modules is not the most important. The combination of functions implemented by these logical units/modules is what solves the problem of this application. Key technical issues raised. In addition, in order to highlight the innovative part of this application, the above-mentioned equipment embodiments of this application do not introduce units/modules that are not closely related to solving the technical problems raised by this application. This does not mean that the above-mentioned equipment embodiments do not exist. Other units/modules.

It should be noted that in the examples and descriptions of this application, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply There is no such actual relationship or sequence between these entities or operations. Furthermore, the terms "comprises," "comprises," or any other variations thereof are intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but also those not expressly listed other elements, or elements inherent to the process, method, article or equipment. Without further limitation, an element defined by the statement "comprises a" does not exclude the presence of additional identical elements in a process, method, article, or device that includes the stated element.

Although the present application has been illustrated and described with reference to certain preferred embodiments thereof, it will be understood by those of ordinary skill in the art that various changes may be made in form and detail without departing from the present invention. Scope of application.

Claims (13)

1. A vehicle control method, applied to vehicles and machines, characterized in that the method includes: Determine the first road surface information of the first road area based on the image of the first road area where the vehicle is currently located collected by the image acquisition device, where the road surface information includes an adhesion coefficient and a confidence level of the adhesion coefficient; Determine the first value corresponding to the reference index of the vehicle according to the vehicle's own status information, and determine whether the vehicle is in an understeer state based on the first value and the first reference value, where the reference index is In order to indicate the possibility that the vehicle is currently in the understeer state, the first reference value is determined based on the first road surface information; If it is determined that the vehicle is in the understeer state, braking logic corresponding to the understeer state is executed, wherein the braking logic is used to compensate for the understeer state of the vehicle. 2. The method according to claim 1, wherein the reference index includes the difference between the theoretical steering angle and the actual steering angle of the vehicle; and, Determining whether the vehicle is in an understeer state based on the first value and the first reference value includes: If the first value is greater than the first reference value within a first period of time, it is determined that the vehicle is currently in the understeer state. 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, including: Obtain the second reference value corresponding to the stored reference index, wherein the second reference value is determined based on the second road surface 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. 5. The method of claim 4, wherein updating the second reference value to the first reference value based on the first road surface information and the second road surface information includes: In the case where the confidence level in the first road surface information is greater than the first confidence level and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the second road surface information, the second road surface information is The reference value is reduced to the first reference value; In the case where the confidence level in the first road surface information is greater than the first confidence level, and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the second road surface information, the The second reference value is increased to the first reference value. 6. The method of claim 5, wherein 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 stored third reference value corresponding to the reference index and the second road surface information. 7. The method according to claim 6, wherein the second reference value is determined based on the pre-stored third reference value corresponding to the reference index and the second road surface information, including: The second reference value is that 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 less than In the case of the adhesion coefficient in the second road surface information, it is obtained by reducing the third reference value; or, The second reference value is that 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 In the case of the adhesion coefficient in the second road surface information, it is obtained by adding the third reference value; 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, characterized in that, when it is determined that the vehicle is in the understeer state, executing braking logic corresponding to the understeer state, include: Determine the second torque corresponding to the vehicle's own state information; Corresponding to the second torque being greater than the first torque threshold corresponding to the engine of the vehicle, reducing the torque output by the engine of the vehicle from the first torque to the second torque; Corresponding to the second torque being less than or equal to the first torque threshold corresponding to the engine, the torque output by the engine of the vehicle is reduced from the first torque to the first torque threshold. 9. The method of claim 8, wherein the first torque threshold is determined based on: Obtain the stored second torque threshold corresponding to the engine of the vehicle; The second torque threshold is updated to the first torque threshold based on the first road surface information and third road surface information, where the third road surface information is road surface information corresponding to the second torque threshold. 10. The method of claim 9, wherein updating the second torque threshold to the first torque threshold based on the first road surface information and the third road surface information includes: In the case where the confidence level in the first road surface information is greater than the second confidence level, and the adhesion coefficient in the first road surface information is less than the adhesion coefficient in the third road surface information, the second road surface information is The torque threshold is increased to the first torque threshold; In the case where the confidence level in the first road surface information is greater than the second confidence level, and the adhesion coefficient in the first road surface information is greater than the adhesion coefficient in the third road surface information, the second road surface information is The torque threshold is reduced to the first torque threshold. 11. A vehicle machine, characterized in that it includes: one or more processors; one or more memories; the one or more memories store one or more programs. When the one or more programs are When the one or more processors are executed, the vehicle machine is caused to execute the vehicle control method according to any one of claims 1 to 10. 12. A vehicle, characterized in that the vehicle includes the vehicle engine according to claim 11. 13. A computer-readable storage medium, characterized in that instructions are stored on the computer-readable storage medium, and when the instructions are executed on a computer, they cause the computer to execute any one of claims 1 to 10. vehicle control method.