Method for estimating vehicle speed, estimation device, and vehicle

Abstract

The application provides a vehicle speed estimation method, an estimation device and a vehicle. The method relates to the field of vehicles and comprises the following steps: obtaining wheel center speeds of wheels in a vehicle, a longitudinal acceleration of the vehicle and driving state information of the vehicle; wherein the driving state information is used to indicate whether the vehicle is in a slip state; obtaining an initial longitudinal vehicle speed of the vehicle based on the longitudinal acceleration; determining a first weight coefficient of each wheel and a second weight coefficient of the vehicle based on the driving state information; and determining a target longitudinal vehicle speed of the vehicle based on the wheel center speeds, the first weight coefficient, the initial longitudinal vehicle speed and the second weight coefficient. The method can improve the accuracy of the estimated longitudinal vehicle speed, thereby improving the safety of the vehicle.

Description

Technical Field

[0001] This application relates to the field of vehicles, and more specifically, to a method, apparatus and vehicle for estimating vehicle speed. Background Technology

[0002] The longitudinal speed of a vehicle refers to the velocity component along the forward or backward direction of the vehicle during travel. The accuracy of the longitudinal speed is crucial for the safe control of the vehicle. However, in the existing technology, the calculation of the longitudinal speed of a vehicle is easily affected by interference factors (such as signal noise, zero-point drift, wheel slip ratio, and wheel rolling radius), resulting in low accuracy in the calculation of the longitudinal speed of the vehicle.

[0003] Therefore, improving the accuracy of estimated longitudinal vehicle speed, thereby enhancing vehicle safety, is a technical problem that needs to be solved. Summary of the Invention

[0004] This application provides a method, device, and vehicle for estimating vehicle speed. The method can determine a first weighting coefficient and a second weighting coefficient based on the vehicle's driving state information (whether the vehicle is in a slipping state); determine the vehicle's longitudinal speed based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient; ensure that the influence of vehicle slippage on the longitudinal speed is taken into account, improve the accuracy of the longitudinal speed, and thus improve vehicle safety.

[0005] Firstly, a method for estimating vehicle speed is provided, which includes:

[0006] The system acquires the wheel center velocity of each wheel in the vehicle, the longitudinal acceleration of the vehicle, and the vehicle's driving status information; among which, the driving status information is used to indicate whether the vehicle is in a slipping state.

[0007] The initial longitudinal speed of the vehicle is obtained based on the longitudinal acceleration.

[0008] Based on driving status information, a first weighting coefficient for each wheel and a second weighting coefficient for the vehicle are determined; wherein, the first weighting coefficient is used to represent the weighting coefficient corresponding to the wheel center velocity of each wheel in the vehicle, and the second weighting coefficient is used to represent the weighting coefficient corresponding to the initial longitudinal vehicle speed.

[0009] The target longitudinal speed of the vehicle is determined based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient.

[0010] It should be noted that the reliability of the vehicle's wheel center speed and longitudinal acceleration differs depending on the vehicle's driving status information (whether the vehicle is in a slipping state or not); where reliability is used to indicate the reliability and accuracy of the data.

[0011] In the embodiments of this application, a first weighting coefficient for each wheel and a second weighting coefficient for the vehicle are determined based on the vehicle's driving state information. The target longitudinal speed of the vehicle is determined based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient. Since the reliability of the wheel center speed and the vehicle's longitudinal acceleration varies depending on the vehicle's driving state information, the first and second weighting coefficients are determined based on the vehicle's driving state information. This ensures that the influence of the vehicle's driving state information on the wheel center speed and longitudinal acceleration is taken into account, i.e., it ensures that the influence of the vehicle's slippage state on the vehicle's wheel center speed and longitudinal acceleration is taken into account. Compared with the prior art, which directly determines the vehicle's longitudinal speed based on the wheel center speed and / or longitudinal acceleration, this solution, by considering the influence of vehicle slippage on the relevant measurement data of the vehicle's wheel center speed and longitudinal acceleration, can calculate a more accurate target longitudinal speed.

[0012] Furthermore, since longitudinal speed is a fundamental input to vehicle dynamics control systems, it can be applied to vehicle anti-lock braking systems, traction control systems, electronic stability control systems, and adaptive cruise control to ensure vehicle stability and safety during driving. Therefore, this solution can obtain a more accurate target longitudinal speed and use this more accurate target longitudinal speed as a fundamental input in the aforementioned vehicle control systems, thereby effectively improving vehicle safety and stability.

[0013] In conjunction with the first aspect, in certain implementations of the first aspect, based on driving state information, a first weighting coefficient for each wheel and a second weighting coefficient for the vehicle are determined, including:

[0014] If the driving status information indicates that the vehicle is in a skidding state, the first preset value is determined as the first weighting coefficient, and the second preset value is determined as the second weighting coefficient;

[0015] If the driving status information indicates that the vehicle is not in a slipping state, a first weighting coefficient and a second weighting coefficient are determined based on the vehicle's first parameter;

[0016] The first parameter includes: the road surface adhesion coefficient of the vehicle under the current road conditions, the vehicle's current actual speed, and the rate of change of current acceleration.

[0017] For example, the first preset value can be zero.

[0018] In the embodiments of this application, if the vehicle is in a slipping state, i.e., the vehicle is skidding, the wheel center velocity of the vehicle is completely unreliable; therefore, a first preset value (e.g., zero value) is determined as the first weighting coefficient, and a second preset value is determined as the second weighting coefficient. If the vehicle is not in a slipping state, the reliability of the vehicle's wheel center velocity and longitudinal acceleration will be affected by the vehicle's slip ratio; therefore, the first weighting coefficient and the second weighting coefficient of the vehicle are determined according to the first parameter; ensuring that the first weighting coefficient and the second weighting coefficient can be determined in different ways based on the vehicle's driving state information and taking into account the vehicle's slip ratio.

[0019] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the first weighting coefficient and the second weighting coefficient are determined based on the first parameter of the vehicle, including:

[0020] The initial first weighting coefficient and the initial second weighting coefficient are determined based on the road surface adhesion coefficient;

[0021] Based on the current actual vehicle speed and the current rate of change of acceleration, determine the first adjustment amount corresponding to the initial first weighting coefficient and the second adjustment amount corresponding to the initial second weighting coefficient;

[0022] The initial first weight coefficient is adjusted based on the first adjustment amount to obtain the first weight coefficient, and the initial second weight coefficient is adjusted based on the second adjustment amount to obtain the second weight coefficient.

[0023] In the embodiments of this application, since the vehicle's slip ratio varies with different road surface adhesion coefficients, i.e., the risk of vehicle skidding varies, different road surface adhesion coefficients have different impacts on the reliability of the vehicle's wheel center speed and longitudinal acceleration. Initial weighting coefficients are set based on the road surface adhesion coefficient to obtain initial first weighting coefficients and initial second weighting coefficients, ensuring that the influence of the road surface adhesion coefficient is taken into account. Adjustments are made based on the initial first and second weighting coefficients to obtain second weighting coefficients, ensuring that the influence of multiple factors such as the vehicle's actual speed and rate of change of acceleration on the first and second weighting coefficients is considered simultaneously.

[0024] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the first weighting coefficient and the second weighting coefficient are determined based on the first parameter of the vehicle, including:

[0025] Based on the vehicle's first parameters and the first mapping relationship, a first weighting coefficient is determined; wherein, in the first mapping relationship, the first weighting coefficient is positively correlated with the road surface adhesion coefficient, negatively correlated with the vehicle's actual speed, and negatively correlated with the vehicle's rate of change of acceleration.

[0026] Based on the first parameter of the vehicle and the second mapping relationship, the second weighting coefficient is determined; wherein, in the second mapping relationship, the second weighting coefficient is negatively correlated with the road adhesion coefficient, positively correlated with the actual vehicle speed, and positively correlated with the vehicle's rate of change of acceleration.

[0027] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the target longitudinal speed of the vehicle is determined based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient, including:

[0028] Based on the wheel center speed and the first weighting coefficient, determine the first value corresponding to each wheel; based on the initial longitudinal vehicle speed and the second weighting coefficient, determine the second value.

[0029] The sum of the first and second values ​​is determined as the third value; the sum of the first and second weighting coefficients of each wheel is determined as the fourth value.

[0030] The ratio of the third value to the fourth value is determined as the target longitudinal speed.

[0031] In the embodiments of this application, since the first weighting coefficient is the weighting coefficient corresponding to the wheel center speed, and the second weighting coefficient is the weighting coefficient of the initial longitudinal vehicle speed; therefore, a first value corresponding to the weighted wheel center speed is obtained based on the wheel center speed and the first weighting coefficient, and a second value corresponding to the weighted initial longitudinal vehicle speed is obtained based on the initial longitudinal vehicle speed and the second weighting coefficient. The sum of the first value and the second value is determined as the third value; the ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed, ensuring that the target longitudinal vehicle speed can be calculated based on the wheel center speed, the first weighting coefficient, the initial longitudinal vehicle speed, and the second weighting coefficient.

[0032] In conjunction with the first aspect and the above implementation methods, some implementation methods of the first aspect also include:

[0033] Based on the vehicle's slip ratio and / or the wheel radius of each wheel, determine the correction factor for each wheel.

[0034] Obtain the wheel center velocity of each wheel in the vehicle, including:

[0035] Based on the third parameter and correction coefficient, the wheel center velocity of each wheel is determined; the third parameter includes the vehicle's track width, the wheel angle of each wheel, the vehicle's yaw rate, and the wheel linear velocity of each wheel.

[0036] In the embodiments of this application, the wheel center speed of each wheel is determined according to the third parameter and the correction coefficient. Since the correction coefficient is a correction coefficient obtained based on the vehicle's slip ratio and / or wheel radius, it ensures that the error caused by the slip ratio can be compensated and the wheel radius error can be corrected when calculating the wheel center speed. This ensures that a more accurate wheel center speed can be obtained, and a more accurate target longitudinal vehicle speed can be obtained based on the more accurate wheel center speed.

[0037] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, obtaining the vehicle's driving status information includes:

[0038] Based on the wheel center velocity and / or wheel center acceleration of each wheel, determine whether each wheel is in a slipping state;

[0039] If all wheels in the vehicle are in a slipping state, the driving status information indicates that the vehicle is in a slipping state;

[0040] If none of the wheels in the vehicle are slipping, the driving status information indicates that the vehicle is not slipping.

[0041] In the embodiments of this application, the slip state of the vehicle is determined based on the slip state of each wheel, ensuring that the slip state of the vehicle can be judged based on the basic parameters of the wheels (wheel center speed or wheel center acceleration), thereby determining the vehicle's driving state information.

[0042] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, obtaining the vehicle's driving status information includes:

[0043] Based on the vehicle's operating conditions, the target wheel among all wheels is determined; where operating conditions include the vehicle's braking and driving conditions, and the target wheel is the wheel with the highest wheel center speed or the wheel with the lowest wheel center speed among all wheels.

[0044] If the target wheel is in a slipping state, the driving status information indicates that the vehicle is in a slipping state.

[0045] In the embodiments of this application, the vehicle's slip state is determined based on the slip state of the target wheel; that is, when it is determined that the target wheel is in a slip state, the vehicle is determined to be in a slip state. Compared to determining the vehicle's slip state based on the slip state of each wheel, this solution calculates based on the slip state of the target wheel, which requires less computation and can effectively improve the efficiency of determining the vehicle's slip state.

[0046] Combining the first aspect and the above implementation methods, in some implementation methods of the first aspect, the initial longitudinal speed of the vehicle is obtained based on longitudinal acceleration, including:

[0047] The initial longitudinal speed of the vehicle is determined based on the second parameter and the longitudinal acceleration.

[0048] The second parameter includes the vehicle's longitudinal speed at the first moment, the vehicle's longitudinal acceleration, and the preset duration; the first moment is the moment before the current moment, and the preset duration is the time difference between the previous moment and the current moment.

[0049] In the embodiments of this application, the longitudinal acceleration is a measured value, and the initial longitudinal acceleration is the longitudinal acceleration calculated based on the measured longitudinal acceleration.

[0050] Secondly, a vehicle speed estimation device is provided, the device comprising:

[0051] The acquisition module is used to acquire the wheel center velocity of each wheel in the vehicle, the longitudinal acceleration of the vehicle, and the vehicle's driving status information; among which, the driving status information is used to indicate whether the vehicle is in a slipping state.

[0052] The processing module is used to obtain the initial longitudinal speed of the vehicle based on longitudinal acceleration; determine the first weighting coefficient of each wheel and the second weighting coefficient of the vehicle based on driving state information; wherein the first weighting coefficient is used to represent the weighting coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weighting coefficient is used to represent the weighting coefficient corresponding to the initial longitudinal speed; and determine the target longitudinal speed of the vehicle based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed and the second weighting coefficient.

[0053] In conjunction with the second aspect, in some implementations of the second aspect, the processing module is specifically used to: if the driving status information indicates that the vehicle is in a slipping state, determine the first preset value as the first weighting coefficient and the second preset value as the second weighting coefficient; if the driving status information indicates that the vehicle is not in a slipping state, determine the first weighting coefficient and the second weighting coefficient based on the vehicle's first parameters; wherein, the first parameters include: the road surface adhesion coefficient of the current road conditions, the vehicle's current actual speed, and the rate of change of acceleration.

[0054] In combination with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine the initial first weight coefficient and the initial second weight coefficient based on the road surface adhesion coefficient; determine the first adjustment amount corresponding to the initial first weight coefficient and the second adjustment amount corresponding to the initial second weight coefficient based on the current actual vehicle speed and the current rate of change of acceleration; adjust the initial first weight coefficient based on the first adjustment amount to obtain the first weight coefficient, and adjust the initial second weight coefficient based on the second adjustment amount to obtain the second weight coefficient.

[0055] In conjunction with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine a first weighting coefficient based on the first parameters of the vehicle and a first mapping relationship; wherein, in the first mapping relationship, the first weighting coefficient is positively correlated with the road surface adhesion coefficient, negatively correlated with the actual vehicle speed, and negatively correlated with the vehicle's rate of change of acceleration; and determine a second weighting coefficient based on the first parameters of the vehicle and a second mapping relationship; wherein, in the second mapping relationship, the second weighting coefficient is negatively correlated with the road surface adhesion coefficient, positively correlated with the actual vehicle speed, and positively correlated with the rate of change of acceleration.

[0056] Combining the second aspect and the above implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine the first value corresponding to each wheel based on the wheel center speed and the first weighting coefficient; determine the second value based on the initial longitudinal vehicle speed and the second weighting coefficient; determine the sum of the first value and the second value as the third value; determine the sum of the first weighting coefficient and the second weighting coefficient of each wheel as the fourth value; and determine the ratio of the third value and the fourth value as the target longitudinal vehicle speed.

[0057] In conjunction with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the acquisition module is further used to: determine the correction coefficient of each wheel based on the slip ratio of the vehicle and / or the wheel radius of each wheel; determine the wheel center velocity of each wheel based on the third parameter and the correction coefficient; wherein the third parameter includes the wheel track of the vehicle, the wheel turning angle of each wheel, the yaw rate of the vehicle, and the wheel linear velocity of each wheel.

[0058] In conjunction with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the acquisition module is specifically used to: determine the target wheel among the wheels based on the vehicle's operating conditions; wherein, the operating conditions include the vehicle's braking conditions and driving conditions, and the target wheel is the wheel with the highest wheel center speed or the wheel with the lowest wheel center speed among the wheels; if at least one wheel is in a slipping state, determine whether at least one wheel includes the target wheel; if at least one wheel includes the target wheel, determine that the driving state information indicates that the vehicle is in a slipping state.

[0059] In combination with the second aspect and the above implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine the initial longitudinal speed of the vehicle based on the second parameter and the longitudinal acceleration; wherein, the second parameter includes the longitudinal speed of the vehicle at the first moment, the longitudinal acceleration of the vehicle, and the preset duration; the first moment is the moment before the current moment, and the preset duration is the time difference between the previous moment and the current moment.

[0060] Thirdly, a vehicle is provided, including a memory and a processor, the memory for storing executable program code, and the processor for calling and running the executable program code from the memory, causing the vehicle to perform the methods of the first aspect or any possible implementation thereof.

[0061] Fourthly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0062] Fifthly, a computer-readable storage medium is provided that stores a computer program, which, when executed, implements the method described in the first aspect or any possible implementation thereof. Attached Figure Description

[0063] Figure 1 This is a dynamic model diagram provided in an embodiment of this application;

[0064] Figure 2 This is a schematic flowchart illustrating a method for estimating vehicle speed provided in an embodiment of this application;

[0065] Figure 3 This is a schematic flowchart illustrating another method for estimating vehicle speed provided in an embodiment of this application;

[0066] Figure 4 This is a schematic diagram of the structure of a vehicle speed estimation device provided in an embodiment of this application;

[0067] Figure 5 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application. Detailed Implementation

[0068] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0069] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0070] The longitudinal speed of a vehicle refers to the velocity component along the forward or backward direction of the vehicle during travel. The accuracy of the longitudinal speed is crucial for vehicle safety control. However, in existing technologies, the calculation of longitudinal speed is easily affected by interference factors (such as signal noise, zero-point drift, wheel slip ratio, and wheel rolling radius), resulting in low accuracy. Therefore, improving the accuracy of estimated longitudinal speed to enhance vehicle safety is a current technical problem that needs to be solved.

[0071] In view of this, this application provides a method, device, and vehicle for estimating vehicle speed. The method determines a first weighting coefficient and a second weighting coefficient based on the vehicle's driving state information (whether the vehicle is in a slipping state). The longitudinal speed of the vehicle is determined based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient. The estimation method of this application ensures that the influence of vehicle slippage on the longitudinal speed is taken into account, improving the accuracy of the longitudinal speed and thus enhancing vehicle safety.

[0072] Figure 1 This is a dynamic model diagram provided in an embodiment of this application.

[0073] like Figure 1 The vehicle dynamics model 100 is shown; where 110 represents the front wheels, 120 represents the rear wheels, 130 represents the center of mass, and δ... r Represents the rear wheel steering angle, δ f V represents the front wheel steering angle. y V represents the lateral speed of the vehicle. x The vehicle's longitudinal speed is represented by V, its actual speed (i.e., the resultant speed), and its wheelbase (the distance between the front and rear axles) by L. r This indicates the vehicle's overall yaw rate.

[0074] The following is combined Figure 1 The dynamic model in Figure 2 The method for estimating vehicle speed will be further explained.

[0075] Figure 2 This is a schematic flowchart illustrating a method for estimating vehicle speed provided in an embodiment of this application.

[0076] For example, Figure 2 The method 200 shown can be performed by a vehicle; or it can be performed by a processor or chip in the vehicle.

[0077] like Figure 2As shown, the vehicle speed estimation method 200 includes S210 to S240, which are described in detail below.

[0078] S210: Obtain the wheel center velocity of each wheel in the vehicle, the longitudinal acceleration of the vehicle, and the vehicle's driving status information.

[0079] Among them, the wheel center speed refers to the translational speed of the wheel center point relative to the ground, which reflects the actual motion state of the vehicle and is related to the longitudinal speed of the vehicle.

[0080] It is understandable that there is a difference between the vehicle's wheel center speed and the vehicle's wheel linear speed. Wheel linear speed refers to the instantaneous linear speed at the point of contact between the tire tread and the ground, reflecting the relative motion between the tire and the ground. Wheel linear speed can be directly measured by wheel speed sensors installed at the wheels, while wheel center speed can be calculated by combining it with wheel linear speed. The method for determining the wheel center speed of each wheel is explained in detail below.

[0081] In one implementation, a correction coefficient for each wheel is determined based on the vehicle's slip ratio and / or the wheel radius of each wheel; the wheel center velocity of each wheel is determined based on a third parameter and the correction coefficient; wherein the third parameter includes the vehicle's track width, the wheel angle of each wheel, the vehicle's yaw rate, and the wheel linear velocity of each wheel.

[0082] For example, correction factors for each wheel are determined based on the vehicle's slip ratio and / or wheel radius. For instance, the correction factor for each wheel is determined based on the vehicle's wheel radius, which may change due to variations in tire pressure, wear, or load. The correction factor is used to compensate for radius errors; the tire radius is estimated by working backwards from the known vehicle speed when the vehicle is stationary, or determined in real-time based on sensor data; the ratio of the tire's nominal radius (standard tire radius) to its actual radius is determined as the correction factor. For example, the correction factor is determined based on the slip ratio, and the slip ratio and a third parameter are used as historical data for model training to predict the correction factor; where the input correction factor is positively correlated with the slip ratio.

[0083] It is understandable that wheel wear and vehicle slippage will cause a difference between the theoretical and actual wheel center speeds. Correction coefficients are used to eliminate the error between the theoretical and actual wheel center speeds. Specifically, the correction coefficient determined based on the wheel radius is used to compensate for the error between the theoretical and actual wheel center speeds caused by wheel wear, while the correction coefficient determined based on the vehicle's slip ratio is used to eliminate the error between the theoretical and actual wheel center speeds caused by vehicle slippage. The correction coefficient determined based on the vehicle's slip ratio and wheel radius is used to eliminate the errors caused by both wheel wear and vehicle slippage.

[0084] For example, after determining the correction coefficient for each wheel, the wheel center speed of each wheel is calculated using Formulas 1 to 4 based on the third parameter and the correction coefficient; where Formula 1 is the formula for calculating the wheel center speed of the left front wheel, Formula 2 is the formula for calculating the wheel center speed of the right front wheel, Formula 3 is the formula for calculating the wheel center speed of the left rear wheel, and Formula 4 is the formula for calculating the wheel center speed of the right rear wheel.

[0085]

[0086] Among them, v fl_cog v represents the speed at the center of the left front wheel of the vehicle. fl δ represents the linear velocity of the left front wheel. fl Fct indicates the steering angle of the left front wheel. fl b represents the correction factor for the left front wheel. f Indicates the front wheel track, ω r This represents the yaw rate of the entire vehicle.

[0087]

[0088] Among them, v fr_cog v represents the speed at the center of the right front wheel of the vehicle. fr δ represents the linear velocity of the right front wheel. fr Indicates the steering angle of the right front wheel, Fct fr b represents the correction factor for the right front wheel. f Indicates the front wheel track, ω r This represents the yaw rate of the entire vehicle.

[0089]

[0090] Among them, v rl_cog v represents the speed at the center of the left rear wheel of the vehicle. rl δ represents the linear velocity of the left rear wheel. rl Fct indicates the left rear wheel steering angle. rl b represents the correction factor for the left rear wheel. r Represents the rear wheel track, ω r This represents the yaw rate of the entire vehicle.

[0091]

[0092] Among them, v rr_cong v represents the speed at the center of the left rear wheel of the vehicle. rr δ represents the linear velocity of the left rear wheel. rr Fct indicates the left rear wheel steering angle. rr b represents the correction factor for the left rear wheel. r Represents the rear wheel track, ω r This represents the yaw rate of the entire vehicle.

[0093] In the embodiments of this application, the wheel center speed of each wheel is determined according to the third parameter and the correction coefficient. Since the correction coefficient is a correction coefficient obtained based on the vehicle's slip ratio and / or wheel radius, it ensures that the error caused by the slip ratio can be compensated and the wheel radius error can be corrected when calculating the wheel center speed. This ensures that a more accurate wheel center speed can be obtained, and a more accurate target longitudinal vehicle speed can be obtained based on the more accurate wheel center speed.

[0094] In one possible implementation, the wheel center velocity of each wheel is determined based on the wheel rotation angle of each wheel, the wheel linear velocity of each wheel, the front wheel track, the rear wheel track, the overall vehicle yaw rate, and the vehicle's wheelbase.

[0095] Specifically, based on the average steering angle of the front wheels (i.e., the average steering angle of the left front wheel and the right front wheel) and the average steering angle of the rear wheels (i.e., the average steering angle of the left rear wheel and the right rear wheel) and the vehicle's wheelbase (the distance from the front axle to the rear axle, such as...), Figure 1 The first and second coefficients are determined based on the wheelbase L shown; the wheel center velocities of the left and right front wheels are determined based on the turning angle of each wheel, the wheel linear velocity of each wheel, the front wheel track, the first coefficient, and the overall vehicle yaw rate; the wheel center velocities of the left and right rear wheels are determined based on the turning angle of each wheel, the wheel linear velocity of each wheel, the rear wheel track, the second coefficient, and the overall vehicle yaw rate.

[0096] For example, based on the average steering angle of the front wheels, the average steering angle of the rear wheels, and the vehicle's wheelbase, the first coefficient is calculated using Formula 5, and the second coefficient is calculated using Formula 6:

[0097]

[0098] Among them, L ɑ L represents the first coefficient. b The second coefficient is represented by L, which represents the wheelbase, and δ. f Indicates the average steering angle of the front wheels; δ r This indicates the average steering angle of the rear wheels.

[0099] For example, based on the turning angle of each wheel, the linear velocity of each wheel, the track width of the front wheel, the first coefficient and the yaw rate of the whole vehicle, the wheel center velocity of the left front wheel is calculated using Formula 7, and the wheel center velocity of the right front wheel is calculated using Formula 8.

[0100]

[0101] Among them, v fl_cong v represents the speed at the center of the left front wheel of the vehicle. fl δ represents the linear velocity of the left front wheel. fl Indicates the left front wheel steering angle, b f L represents the front wheel track. ɑ ω represents the first coefficient. rThis represents the yaw rate of the entire vehicle.

[0102]

[0103] Among them, v fr_cog v represents the speed at the center of the right front wheel of the vehicle. fr δ represents the linear velocity of the right front wheel. fr Indicates the steering angle of the right front wheel, b f L represents the front wheel track. ɑ ω represents the first coefficient. r This represents the yaw rate of the entire vehicle.

[0104]

[0105] Among them, v rl_cog v represents the speed at the center of the left rear wheel of the vehicle. rl δ represents the linear velocity of the left rear wheel. rl Indicates the left rear wheel steering angle, b r L represents the rear wheel track. b ω represents the second coefficient. r This represents the yaw rate of the entire vehicle.

[0106]

[0107] Among them, v rr_cog v represents the speed at the center of the left rear wheel of the vehicle. rr δ represents the linear velocity of the left rear wheel. rr Indicates the left rear wheel steering angle, b r L represents the rear wheel track. b ω represents the second coefficient. r This represents the yaw rate of the entire vehicle.

[0108] Optionally, determining the vehicle's driving status information includes: determining whether each wheel is in a slipping state based on the wheel center velocity and / or wheel center acceleration of each wheel; if all wheels in the vehicle are in a slipping state, determining the driving status information indicates that the vehicle is in a slipping state; if none of the wheels in the vehicle are in a slipping state, determining the driving status information indicates that the vehicle is not in a slipping state.

[0109] For example, determining whether a wheel is slipping based on its wheel center speed: calculate the wheel center speed of each wheel in the vehicle, and determine the average wheel center speed over a preset number of cycles; calculate the first difference between the wheel center speed and the average wheel center speed; if the absolute value of the first difference is greater than a preset value of 1, determine that the wheel is slipping (slipping).

[0110] The period can be the data acquisition period or the wheel center speed calculation period. For example, if the third parameter is acquired and the wheel center speed is calculated every 5 milliseconds (ms), the period is 5ms. If the preset quantity is 4, then the average wheel center speed within the most recent 4 periods is calculated. The preset value 1 is a preset value determined according to the calibration table. The calibration table is a table obtained by testing and calibrating in a real vehicle or simulation environment covering all working conditions (acceleration, braking, coasting) and the full speed range of vehicle travel (from minimum speed to maximum speed).

[0111] For example, the system collects the wheel center speed of each wheel, estimates the longitudinal vehicle speed (based on multi-sensor fusion), the actual longitudinal acceleration, and the road adhesion coefficient (reference value, which can be set through experiments or simulations). It then calculates the average wheel center speed, calculates the deviation between the actual wheel center speed and the average value, and labels slip events. Using the estimated longitudinal speed and actual longitudinal acceleration as inputs and the slip threshold (preset value 1) as output, Table 1 is obtained. The table showing the determination of the preset value 1 is as follows:

[0112] Table 1

[0113] Estimate longitudinal vehicle speed (km / h) <![CDATA[Actual longitudinal acceleration (m / s 2 )]]> Default value 1 <![CDATA[V1]]> <![CDATA[a1]]> <![CDATA[b1]]> <![CDATA[V2]]> <![CDATA[a2]]> <![CDATA[b2]]>

[0114] For example, if the current estimated longitudinal vehicle speed is V1 and the actual longitudinal acceleration is a1, then when the absolute value of the first difference is detected to be greater than b1, it is determined that the wheel is in a slipping state.

[0115] Understandably, when the first difference between the wheel center speed and the average wheel center speed is greater than a preset value of 1, it indicates that the wheel may be slipping (driving slippage or brake lock-up).

[0116] It should be noted that, under the current estimated longitudinal speed and actual longitudinal acceleration, different first differences (i.e., the speed difference between the wheel center speed and the average wheel center speed) are determined by changing the wheel center speed; and the slip state of the wheel is marked under different first differences, thereby determining the critical value of the wheel being in a slip state. This critical value is the preset value 1 corresponding to the estimated longitudinal speed and actual longitudinal acceleration; by changing the estimated longitudinal speed and actual longitudinal acceleration, the preset value 1 under different estimated longitudinal speeds and actual longitudinal accelerations is determined, thus obtaining the correspondence shown in Table 1.

[0117] For example, the slip state of a wheel is determined based on the wheel center acceleration of each wheel: the wheel center acceleration is determined by differentiating the wheel speed, and the actual longitudinal acceleration of the vehicle is determined; the second difference between the wheel center acceleration and the actual longitudinal acceleration is calculated; if the absolute value of the second difference is greater than a preset value 2, the wheel is determined to be in a slip state; wherein, the preset value 2 is a preset value determined according to a calibration table, wherein the calibration table is a table obtained by testing and calibrating in a real vehicle or simulation environment covering all working conditions (acceleration, braking, and coasting) and the entire speed range.

[0118] Understandably, if the wheel's center acceleration deviates significantly from the vehicle's actual longitudinal acceleration, it indicates that the wheel may be slipping. The table for determining preset value 2 is shown in Table 2:

[0119] Table 2

[0120] Estimate longitudinal vehicle speed (km / h) <![CDATA[Actual longitudinal acceleration (m / s 2 )]]> Preset value 2 <![CDATA[V1]]> <![CDATA[a1]]> <![CDATA[c1]]> <![CDATA[V2]]> <![CDATA[a2]]> <![CDATA[c2]]>

[0121] It should be noted that, under the current estimated longitudinal speed and actual longitudinal acceleration, different second differences (i.e., the acceleration difference between the wheel center acceleration and the actual longitudinal acceleration) are determined by changing the wheel center acceleration; and under different second differences, the wheel slip state is marked, thereby determining the critical value at which the wheel is in a slip state. This critical value is the preset value 2 corresponding to the estimated longitudinal speed and actual longitudinal acceleration; by changing the estimated longitudinal speed and actual longitudinal acceleration, the preset value 2 under different estimated longitudinal speeds and actual longitudinal accelerations is determined, resulting in the table shown in Table 2.

[0122] For example, if all wheels in the vehicle are in a slipping state, the vehicle is determined to be in a slipping state; if none of the wheels in the vehicle are in a slipping state, the vehicle is determined not to be in a slipping state. If some wheels in the vehicle are in a slipping state and some wheels are not in a slipping state, further judgment is required.

[0123] Specifically, obtaining vehicle driving status information includes: determining the target wheel among all wheels based on the vehicle's operating conditions; wherein, the operating conditions include the vehicle's braking conditions and driving conditions, and the target wheel is the wheel with the highest wheel center speed or the wheel with the lowest wheel center speed among all wheels; if the target wheel is in a slipping state, determining that the driving status information indicates that the vehicle is in a slipping state; or if at least one wheel is in a slipping state, determining whether at least one wheel includes the target wheel; if at least one wheel includes the target wheel, determining that the driving status information indicates that the vehicle is in a slipping state.

[0124] For example, if the vehicle is in a driving state, the wheel with the highest wheel center speed is identified as the target wheel; if the vehicle is in a braking state, the wheel with the lowest wheel center speed is identified as the target wheel. It is then determined whether the target wheel is in a slipping state. If the target wheel is in a slipping state, the vehicle is determined to be in a slipping state; if the target wheel is not in a slipping state, the vehicle is determined not to be in a slipping state.

[0125] In the embodiments of this application, the vehicle's slip state is determined based on the slip state of the target wheel; that is, when it is determined that the target wheel is in a slip state, the vehicle is determined to be in a slip state. Compared to determining the vehicle's slip state based on the slip state of each wheel, this solution calculates based on the slip state of the target wheel, which requires less computation and can effectively improve the efficiency of determining the vehicle's slip state.

[0126] Optionally, the activation state of the lifting torque for slip control of the front and rear axles of the vehicle is determined; based on the activation state of the lifting torque of the front and rear axles, the slip state of the vehicle is determined; if the front axle lifting torque is activated, the front wheels (left and right front wheels) of the vehicle are determined to be in a slip state (slipping state); if the rear axle lifting torque is activated, the rear wheels (left and right rear wheels) of the vehicle are determined to be in a slip state; where slip control is a key function to prevent wheel slippage, which is usually achieved by adjusting the drive torque or braking force. The activation of the front and rear axle lifting torques is a strategy in slip control used to determine whether the front or rear wheels have entered a slipping state.

[0127] It should be noted that when the front wheels of the vehicle enter a slipping state, the system suppresses slippage by reducing the front axle drive torque or increasing the front axle braking force; that is, the front axle lift torque is activated. When the rear wheels of the vehicle enter a slipping state, the system suppresses slippage by reducing the rear axle drive torque or increasing the rear axle braking force; that is, the rear axle lift torque is activated. Therefore, the slipping state of the front and rear wheels of the vehicle can be determined by observing the lift torque states of the front and rear axles.

[0128] In one implementation, the system determines whether a wheel has exited the slip state based on the vehicle's wheel center speed, the average wheel center speed, wheel center acceleration, the lifting torque state of the front and rear axles, and the difference between the wheel center speed and the estimated longitudinal vehicle speed. If the difference between the actual wheel speed and the average wheel speed over the most recent n cycles is less than or equal to a preset value 1, the difference between the wheel center acceleration and the actual longitudinal acceleration is less than or equal to a preset value 2, the lifting torque state of both the front and rear axles is inactive, and the difference between the wheel center speed and the estimated longitudinal vehicle speed is less than or equal to a preset value 3; where preset value 3 is obtained through real-vehicle simulation calibration based on the absolute value of the estimated longitudinal vehicle speed and the absolute value of the actual longitudinal acceleration.

[0129] In one possible implementation, if none of the vehicle's wheels are slipping, or if the vehicle is stationary (the estimated longitudinal speed is less than a preset value, which is a smaller speed value), it is determined that the vehicle is not slipping; or if the difference between the wheel center speed of each wheel and the wheel center speed of the target vehicle speed is less than a preset value of 4, it is determined that the vehicle is not slipping; wherein, the preset value of 4 is obtained by real vehicle simulation calibration based on the absolute value of the estimated longitudinal speed and the absolute value of the actual longitudinal acceleration.

[0130] Optionally, the process for determining preset value 3 and preset value 4 can be found in the relevant description of the process for determining preset value 1 and preset value 2, and will not be repeated here.

[0131] S220, based on longitudinal acceleration, obtains the initial longitudinal speed of the vehicle.

[0132] In one implementation, the initial longitudinal speed of the vehicle is determined based on a second parameter and longitudinal acceleration; wherein the second parameter includes the longitudinal speed of the vehicle at a first moment, the longitudinal acceleration of the vehicle, and a preset duration; the first moment is the moment before the current moment, and the preset duration is the time difference between the previous moment and the current moment.

[0133] Specifically, the product of the longitudinal acceleration and the duration of the preset time period is determined as the change in longitudinal speed; the sum of the longitudinal speed at the first moment and the change in longitudinal speed is determined as the initial longitudinal speed of the vehicle. For example, Formula 11 can be used to calculate the initial longitudinal speed of the vehicle:

[0134] V x初始 =(V x (k-1)+a x ΔT); (Formula 11)

[0135] Among them, V x初始 V represents the initial longitudinal vehicle speed. x (k-1) represents the longitudinal vehicle speed at the first moment, a x ΔT represents the longitudinal acceleration, and ΔT represents the preset time period (the time difference from the first moment to the current moment).

[0136] S230 determines the first weighting coefficient of each wheel and the second weighting coefficient of the vehicle based on driving status information.

[0137] The first weighting coefficient represents the weighting coefficient corresponding to the wheel center velocity of each wheel in the vehicle, and the second weighting coefficient represents the weighting coefficient corresponding to the initial longitudinal vehicle speed. The method for determining the first and second weighting coefficients is explained in detail below.

[0138] In one implementation, if the driving status information indicates that the vehicle is in a slipping state, a first preset value is determined as a first weighting coefficient, and a second preset value is determined as a second weighting coefficient; if the driving status information indicates that the vehicle is not in a slipping state, the first weighting coefficient and the second weighting coefficient are determined based on the vehicle's first parameters; wherein, the first parameters include: the road surface adhesion coefficient of the current road conditions, the vehicle's current actual speed, and the current rate of change of acceleration.

[0139] It is understandable that the vehicle's current actual speed is the vehicle's current travel speed, that is, the vehicle's longitudinal speed V. x With the vehicle's lateral speed V y The resultant velocity (e.g., Figure 1 The vehicle speed V in the middle.

[0140] For example, if the vehicle is in a slipping state, i.e., the vehicle is skidding, the wheel center velocity of the vehicle is completely unreliable; therefore, a first preset value (e.g., zero value) is determined as the first weighting coefficient, and a second preset value is determined as the second weighting coefficient. If the vehicle is not in a slipping state, the reliability of the vehicle's wheel center velocity and longitudinal acceleration will be affected by the vehicle's slip ratio; therefore, the first weighting coefficient and the second weighting coefficient of the vehicle are determined according to the first parameter; ensuring that the first weighting coefficient and the second weighting coefficient can be determined in different ways based on the vehicle's driving state information and taking into account the vehicle's slip ratio.

[0141] For example, if the vehicle is in a skidding state, the wheel linear velocity is in an unreliable state, that is, the wheel center velocity calculated based on the wheel linear velocity is in an unreliable state. Therefore, the first weighting coefficient corresponding to the wheel center velocity is 0, and the acceleration weighting coefficient is 1.

[0142] For example, there are two possible implementation methods when determining the first weight coefficient and the second weight coefficient based on the first parameter. These two implementation methods will be explained below.

[0143] Implementation Method 1: Determine the initial first weight coefficient and the initial second weight coefficient based on the road surface adhesion coefficient; determine the first adjustment amount corresponding to the initial first weight coefficient and the second adjustment amount corresponding to the initial second weight coefficient based on the current actual vehicle speed and the current rate of change of acceleration; adjust the initial first weight coefficient based on the first adjustment amount to obtain the first weight coefficient, and adjust the initial second weight coefficient based on the second adjustment amount to obtain the second weight coefficient.

[0144] Among them, the initial first weighting coefficient is positively correlated with the road surface adhesion coefficient, and the initial second weighting coefficient is negatively correlated with the road surface adhesion coefficient.

[0145] For example, since the vehicle's slip ratio varies with different road surface adhesion coefficients, meaning the risk of skidding differs, the impact on the reliability of the vehicle's wheel center speed and longitudinal acceleration also varies depending on the road surface adhesion coefficient. Initial weighting coefficients are set based on the road surface adhesion coefficient to obtain initial first and second weighting coefficients, ensuring that the influence of the road surface adhesion coefficient is taken into account. Adjustments are then made to these initial first and second weighting coefficients to obtain second weighting coefficients that simultaneously consider the influence of multiple factors, including the vehicle's actual speed and the rate of change of vehicle acceleration, on both the first and second weighting coefficients.

[0146] For example, initial settings are first made based on road surface adhesion conditions. The initial first weighting coefficient for high adhesion coefficient is 0.8, and the initial second weighting coefficient is 0.2; the initial first weighting coefficient for low adhesion coefficient is 0.7, and the initial second weighting coefficient is 0.3. When the vehicle is traveling on a low-adhesion road surface, if the vehicle is traveling smoothly at a low to medium speed (i.e., the actual vehicle speed is less than a preset speed threshold, and the rate of change of acceleration is less than a preset threshold), the initial settings remain unchanged. If the vehicle is traveling smoothly at a high speed (e.g., the actual vehicle speed is detected to be greater than a preset speed threshold, and the rate of change of acceleration is less than a preset threshold), the first adjustment amount of the corresponding initial first weighting coefficient is +0.05, and the second adjustment amount of the initial second weighting coefficient is -0.05. The initial first weighting coefficient is adjusted according to the first adjustment amount, and the first weighting coefficient is determined to be 0.75. The initial second weighting coefficient is adjusted according to the second adjustment amount, and the second weighting coefficient is determined to be 0.25.

[0147] It should be noted that the above is an illustrative explanation of the values ​​of the first weighting coefficient and the second weighting coefficient, and this application does not specifically limit the values ​​of the first weighting coefficient and the second weighting coefficient.

[0148] Implementation Method 2: Based on the vehicle's first parameters and the first mapping relationship, determine the first weighting coefficient; wherein, in the first mapping relationship, the first weighting coefficient is positively correlated with the road surface adhesion coefficient, negatively correlated with the vehicle's actual speed, and negatively correlated with the vehicle's rate of change of acceleration; based on the vehicle's first parameters and the second mapping relationship, determine the second weighting coefficient; wherein, in the second mapping relationship, the second weighting coefficient is negatively correlated with the road surface adhesion coefficient, positively correlated with the vehicle's actual speed, and positively correlated with the vehicle's rate of change of acceleration.

[0149] The first mapping relationship is used to represent the mapping relationship between different first parameters and the weight coefficients corresponding to the wheel center speed; the second mapping relationship is used to represent the mapping relationship between different first parameters and the weight coefficients corresponding to the initial longitudinal vehicle speed.

[0150] Understandably, based on the vehicle's current first parameters (including the road surface adhesion coefficient, current actual vehicle speed, and current acceleration change) and the first mapping relationship, the weighting coefficient corresponding to the vehicle's current wheel center speed is determined, i.e., the vehicle's first weighting coefficient is determined. Based on the vehicle's current first parameters and the second mapping relationship, the weighting coefficient corresponding to the vehicle's current initial longitudinal speed is determined, i.e., the vehicle's second weighting coefficient is determined.

[0151] For example, low-adhesion road surfaces (e.g., wet or icy surfaces) easily cause wheels to slip (wheel slippage). In this case, the wheel speed weighting coefficient should be appropriately reduced. When the vehicle speed is high, considering the accuracy of the wheel speed sensor, the calculated wheel speed is affected by noise. Appropriately reducing the first weighting coefficient reduces the risk of wheel slippage, but the acceleration change is more significant. Therefore, the acceleration weighting coefficient can be increased. When the longitudinal acceleration change rate of the vehicle is large (e.g., during rapid acceleration or deceleration), the acceleration weighting coefficient is increased to more accurately reflect the dynamic changes of the vehicle. Based on this, the relationship between the first parameter and the first weighting coefficient is determined (the first weighting coefficient is positively correlated with the road adhesion coefficient, negatively correlated with the actual vehicle speed, and negatively correlated with the vehicle's acceleration change rate) and the relationship between the first parameter and the second weighting coefficient are determined (the second weighting coefficient is negatively correlated with the road adhesion coefficient, positively correlated with the actual vehicle speed, and positively correlated with the vehicle's acceleration change rate).

[0152] Optionally, the first mapping relationship and the second mapping relationship can be a mapping relationship in tabular form, a mapping relationship in mathematical function form, or other forms of mapping relationship. This application does not limit the specific form of the mapping relationship.

[0153] S240 determines the target longitudinal speed of the vehicle based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient.

[0154] Wherein, the target longitudinal speed of the vehicle represents the longitudinal speed at the vehicle's center of gravity; such as Figure 1 V in x As shown.

[0155] In one implementation, a first value corresponding to each wheel is determined based on the wheel center speed and a first weighting coefficient; a second value is determined based on the initial longitudinal vehicle speed and a second weighting coefficient; the sum of the first value and the second value is determined as a third value; the sum of the first weighting coefficient and the second weighting coefficient of each wheel is determined as a fourth value; and the ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed.

[0156] Specifically, the target longitudinal speed of the vehicle can be calculated using Formula 12:

[0157]

[0158] Among them, V x (k) represents the target vehicle speed threshold at time k (the current time), k i k represents the first weighting coefficient for each wheel. ax a represents the second weighting coefficient. x V represents the longitudinal acceleration of a vehicle. x (k-1) represents the longitudinal vehicle speed at the first moment (the moment before the current moment), a x V represents longitudinal acceleration, ΔT represents the preset time period (the time interval from the first moment to the current moment), and V represents the longitudinal acceleration. x_cog This represents the speed at the center of each wheel, where i represents each wheel in the vehicle.

[0159] Alternatively, Formula 13 can be used to calculate the target longitudinal speed of the vehicle:

[0160]

[0161] Where, k i k represents the first weighting coefficient for each wheel. ax V represents the second weighting coefficient. x_cog V represents the speed at the center of each wheel, where i represents the speed of each wheel in the vehicle. x初始 This indicates the initial longitudinal speed.

[0162] In the embodiments of this application, since the first weighting coefficient is the weighting coefficient corresponding to the wheel center speed, and the second weighting coefficient is the weighting coefficient of the initial longitudinal vehicle speed; therefore, a first value corresponding to the weighted wheel center speed is obtained based on the wheel center speed and the first weighting coefficient, and a second value corresponding to the weighted initial longitudinal vehicle speed is obtained based on the initial longitudinal vehicle speed and the second weighting coefficient. The sum of the first value and the second value is determined as the third value; the ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed, ensuring that the target longitudinal vehicle speed can be calculated based on the wheel center speed, the first weighting coefficient, the initial longitudinal vehicle speed, and the second weighting coefficient.

[0163] In one possible implementation, if the vehicle is not in a fully slipping state, the first wheel in the vehicle that is in a slipping state is identified; the first weighting coefficient of the first wheel and the second weighting coefficient of the vehicle are adjusted; wherein, the vehicle not being in a fully slipping state means that there are wheels in the vehicle that are both in a slipping state and wheels that are not in a slipping state.

[0164] Specifically, if the vehicle is not in a fully slipping state, the first wheel in the slipping state is identified; the first weighting coefficient of the first wheel is negatively correlated with the longitudinal slip rate of the first wheel, the first weighting coefficient of the first wheel is positively correlated with the acceleration change rate of the first wheel, the second weighting coefficient of the first wheel is positively correlated with the longitudinal slip rate of the first wheel, and the second weighting coefficient of the first wheel is positively correlated with the acceleration change rate of the first wheel.

[0165] For example, the road adhesion coefficient corresponds to an initial first weighting coefficient of 0.7 and an initial second weighting coefficient of 0.3. Assuming that the left front wheel slips and the longitudinal acceleration change rate is greater than the preset value, the left front wheel enters the unsteady state region. When the longitudinal slip rate of the left front wheel is greater than 70%, the first weighting coefficient is reduced to 0, and the second weighting coefficient is increased to 1.

[0166] It should be noted that the above are examples of the first weighting coefficient and the second weighting coefficient, and this application does not specify the specific values ​​of the first weighting coefficient and the second weighting coefficient.

[0167] In the embodiments of this application, when some wheels of the vehicle are in a slipping state (i.e. there are unsteady wheels in the vehicle), based on the longitudinal slip rate and longitudinal acceleration change rate of the slipping wheel, the first weighting coefficient corresponding to the unsteady wheel is gradually reduced as the longitudinal slip rate increases, while the second weighting coefficient is increased, to ensure that the impact of wheel slip on the accuracy of the target longitudinal vehicle speed estimation can be reduced.

[0168] Optionally, when determining the target longitudinal vehicle speed, to avoid abrupt changes in the estimated target longitudinal vehicle speed, a smoothing process is performed. For example, the smoothing process is achieved by averaging the target longitudinal vehicle speed over a preset time period based on a time series. For instance, a queue (or list) of fixed length is defined to store several recent speed values. Each time the target longitudinal vehicle speed for a calculation period is obtained, it is added to the queue, the oldest value is removed, and the average of all values ​​in the queue is taken as the current smoothed speed value.

[0169] It should be noted that due to sensor noise, signal delay, and changes in road conditions, the estimated longitudinal vehicle speed may change abruptly or become discontinuous, thus affecting the performance of the control system. This solution effectively solves the problem of abrupt changes or discontinuities in longitudinal vehicle speed by smoothing the target longitudinal vehicle speed.

[0170] In the above embodiments, a first weighting coefficient for each wheel and a second weighting coefficient for the vehicle are determined based on the vehicle's driving state information. The target longitudinal speed of the vehicle is determined based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient. Since the reliability of the wheel center speed and the vehicle's longitudinal acceleration varies depending on the vehicle's driving state information, the first and second weighting coefficients are determined based on the vehicle's driving state information. This ensures that the influence of the vehicle's driving state information on the wheel center speed and longitudinal acceleration is considered, i.e., it ensures that the influence of the vehicle's slippage state on the wheel center speed and longitudinal acceleration is considered. Compared with the prior art, which directly determines the vehicle's longitudinal speed based on the wheel center speed and / or longitudinal acceleration, this solution, by considering the influence of vehicle slippage on the vehicle's measurement data, can calculate a more accurate target longitudinal speed.

[0171] Figure 3 This is a schematic flowchart illustrating another method for estimating vehicle speed provided in an embodiment of this application.

[0172] Figure 3 The method 300 shown can be performed by a vehicle; or it can be performed by a processor or chip in the vehicle.

[0173] like Figure 3 As shown, the vehicle speed estimation method 300 includes S301 to S310, and S301 to S310 are described in detail below.

[0174] S301, obtain the vehicle's longitudinal acceleration, third parameter, and correction coefficients for each wheel.

[0175] For example, the longitudinal acceleration of the vehicle is the acceleration measured by an acceleration sensor in the vehicle; the third parameter includes the wheel track of the vehicle, the wheel angle of each wheel, the yaw rate of the vehicle, and the wheel linear velocity of each wheel; the correction coefficient of each wheel is a correction coefficient determined according to the slip ratio and / or wheel radius of the vehicle, and different wheels may correspond to different correction coefficients.

[0176] S302 determines the wheel center speed of each wheel based on the vehicle's third parameter and the correction coefficient of each wheel.

[0177] For example, the third parameter of the vehicle and the correction coefficient of each wheel are substituted into the calculation formula of the wheel center speed in S210 to calculate the wheel center speed of each wheel.

[0178] Alternatively, the implementation methods of S301 and S302 can be found in [reference needed]. Figure 2 The relevant description of S210 will not be repeated here.

[0179] S303, the initial longitudinal speed is determined based on the longitudinal acceleration.

[0180] For example, the initial longitudinal speed of the vehicle is calculated according to the calculation method in Formula 11.

[0181] S304 determines the slip state of each wheel based on the wheel center speed of each wheel.

[0182] For example, the wheel center speed of each wheel in the vehicle is calculated, and the average value of the wheel center speed within a preset number of cycles is determined; the first difference between the wheel center speed and the average value of the wheel center speed is calculated; if the absolute value of the first difference is greater than a preset value of 1, it is determined that the wheel is in a slipping state.

[0183] S305 determines the vehicle's driving status information based on the wheel slippage state.

[0184] For example, if all wheels in the vehicle are in a slipping state, the vehicle is determined to be in a slipping state; if none of the wheels in the vehicle are in a slipping state, the vehicle is determined to be in a slipping state; if some wheels in the vehicle are in a slipping state, it is determined whether the wheels in the slipping state include the target wheel; if the target wheel is included, the vehicle is determined to be in a slipping state; if the target wheel is not included, the vehicle is determined to be in a slipping state.

[0185] S306, determine whether the driving status information indicates that the vehicle is in a skidding state; if yes, proceed to S307; if no, proceed to S308.

[0186] For example, it is determined whether the driving status information indicates that the vehicle is in a skidding state; if so, a first weighting coefficient and a second weighting coefficient are determined according to the first parameter; if the driving status information does not indicate that the vehicle is in a skidding state, a first preset value is determined as the first weighting coefficient and a second preset value is determined as the second weighting coefficient.

[0187] S307, Based on the first parameter, determine the first weighting coefficient and the second weighting coefficient.

[0188] Alternatively, the implementation of S307 can be found in [reference needed]. Figure 2 The relevant descriptions of implementation method 1 and implementation method 2 in S230 will not be repeated here.

[0189] S308, the first preset value is determined as the first weighting coefficient, and the second preset value is determined as the second weighting coefficient.

[0190] For example, if the vehicle is not in a slipping state, a first preset value is determined as a first weighting coefficient, and a second preset value is determined as a second weighting coefficient; wherein, the first preset value can be 0; to ensure that when the vehicle is in a slipping state, the wheel speed in an unreliable state will not affect the target longitudinal speed of the vehicle.

[0191] S309, determine the first value of each wheel based on the wheel center speed and the first weighting coefficient, and determine the second value based on the second weighting coefficient and the initial longitudinal vehicle speed.

[0192] For example, the product of the wheel center speed and the first weighting coefficient is determined, and the product of the wheel center speed and the first weighting coefficient is determined as the first value of each wheel, and the product of the second weighting coefficient and the initial longitudinal vehicle speed is determined as the second value.

[0193] S310, based on the first value, the second value, the first weighting coefficient, and the second weighting coefficient, determine the target longitudinal vehicle speed.

[0194] Alternatively, the implementation of S310 can be found in [reference needed]. Figure 2 The relevant description of S240 will not be repeated here.

[0195] It should be noted that estimating longitudinal vehicle speed using only wheel linear velocity or longitudinal acceleration has certain limitations. For example, when estimating longitudinal vehicle speed using wheel linear velocity, integration is not required, avoiding cumulative errors caused by signal noise or zero-point drift. However, factors such as changes in the vehicle's wheel rolling radius and wheel slip ratio can affect the estimation accuracy. When estimating vehicle speed based on the integral of longitudinal acceleration, signal noise or zero-point drift can also affect the estimation accuracy. Therefore, this application estimates longitudinal vehicle speed by fusing wheel linear velocity and longitudinal acceleration, taking into account the weights of the integral vehicle speed of wheel linear velocity and longitudinal acceleration. This reduces the error of a single method and improves the estimation accuracy.

[0196] In the embodiments of this application, the wheel center speed of each wheel is determined based on the third parameter and the correction coefficient, ensuring that the influence of the vehicle's slip ratio and / or wheel radius on the wheel center speed is taken into account, thereby obtaining a more accurate wheel center speed. Furthermore, a first weighting coefficient and a second weighting coefficient are determined based on the vehicle's driving state information; ensuring that the influence of the vehicle's driving state information on the wheel center speed and longitudinal acceleration is taken into account, thereby obtaining a more accurate first weighting coefficient and a more accurate second weighting coefficient, and thus obtaining a more accurate target longitudinal vehicle speed.

[0197] Optionally, before estimating the longitudinal speed of the vehicle, it is determined whether the wheel speed sensor and the inertial measurement unit (IMU) of the vehicle are fault-free and have valid signals. If both the wheel speed sensor and the inertial sensor are fault-free and have valid signals, the longitudinal speed estimation method is implemented. If the wheel speed sensor and / or the inertial sensor are faulty, a prompt message is output. The prompt message is used to display the fault information of the wheel speed sensor and / or the inertial sensor.

[0198] It is understood that the solution in this application is based on the integration of wheel speed and acceleration to estimate longitudinal vehicle speed. The reliability of wheel speed signal and acceleration signal is evaluated according to the current vehicle driving state. The vehicle speed obtained by integrating wheel speed and acceleration is weighted and averaged to improve the accuracy of longitudinal vehicle speed estimation.

[0199] The above text combined Figures 1 to 3 The method for estimating vehicle speed provided in the embodiments of this application is described in detail below; the following will be combined with Figure 4 and Figure 5 The apparatus embodiments of this application are described in detail below. It should be understood that the apparatus in the embodiments of this application can perform the various methods described in the foregoing embodiments of this application, that is, the specific working processes of the various products described below can be referred to the corresponding processes in the foregoing method embodiments.

[0200] Figure 4 This is a schematic diagram of the structure of a vehicle speed estimation device provided in an embodiment of this application.

[0201] For example, such as Figure 4 As shown, the vehicle speed estimation device 400 includes:

[0202] The acquisition module 410 is used to acquire the wheel center velocity of each wheel in the vehicle, the longitudinal acceleration of the vehicle, and the driving status information of the vehicle; wherein, the driving status information is used to indicate whether the vehicle is in a slipping state.

[0203] The processing module 420 is used to obtain the initial longitudinal speed of the vehicle based on the longitudinal acceleration; determine the first weight coefficient and the second weight coefficient of the vehicle based on the driving state information; wherein the first weight coefficient is used to represent the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent the weight coefficient corresponding to the initial longitudinal speed; and determine the target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient.

[0204] Optionally, as an embodiment, the processing module 420 is specifically used to: if the driving status information indicates that the vehicle is in a slipping state, determine a first preset value as a first weighting coefficient and a second preset value as a second weighting coefficient; if the driving status information indicates that the vehicle is not in a slipping state, determine the first weighting coefficient and the second weighting coefficient based on the vehicle's first parameters; wherein, the first parameters include: the road surface adhesion coefficient of the vehicle's current road conditions, the vehicle's current actual speed, and the current rate of change of acceleration.

[0205] Optionally, as an embodiment, the processing module 420 is specifically used to: determine an initial first weight coefficient and an initial second weight coefficient based on the road surface adhesion coefficient; determine a first adjustment amount corresponding to the initial first weight coefficient and a second adjustment amount corresponding to the initial second weight coefficient based on the current actual vehicle speed and the current rate of change of acceleration; adjust the initial first weight coefficient based on the first adjustment amount to obtain the first weight coefficient, and adjust the initial second weight coefficient based on the second adjustment amount to obtain the second weight coefficient.

[0206] Optionally, as an embodiment, the processing module 420 is specifically used to: determine a first weighting coefficient based on the first parameters of the vehicle and a first mapping relationship; wherein, in the first mapping relationship, the first weighting coefficient is positively correlated with the road surface adhesion coefficient, negatively correlated with the actual vehicle speed, and negatively correlated with the vehicle's rate of change of acceleration; and determine a second weighting coefficient based on the first parameters of the vehicle and a second mapping relationship; wherein, in the second mapping relationship, the second weighting coefficient is negatively correlated with the road surface adhesion coefficient, positively correlated with the actual vehicle speed, and positively correlated with the vehicle's rate of change of acceleration.

[0207] Optionally, as an embodiment, the processing module 420 is specifically used to: determine a first value corresponding to each wheel based on the wheel center speed and a first weighting coefficient; determine a second value based on the initial longitudinal vehicle speed and a second weighting coefficient; determine a third value by the sum of the first value and the second value; determine a fourth value by the sum of the first weighting coefficient and the second weighting coefficient of each wheel; and determine the ratio of the third value to the fourth value as the target longitudinal vehicle speed.

[0208] Optionally, as an embodiment, the acquisition module 410 is further configured to: determine the correction coefficient of each wheel based on the slip ratio of the vehicle and / or the wheel radius of each wheel; and determine the wheel center velocity of each wheel based on the third parameter and the correction coefficient; wherein the third parameter includes the wheel track of the vehicle, the wheel angle of each wheel, the yaw rate of the vehicle, and the wheel linear velocity of each wheel.

[0209] Optionally, as an embodiment, the acquisition module 410 is specifically used to: determine the target wheel among the wheels based on the vehicle's operating conditions; wherein, the operating conditions include the vehicle's braking conditions and driving conditions, and the target wheel is the wheel with the highest wheel center speed or the wheel with the lowest wheel center speed among the wheels; if at least one wheel is in a slipping state, determine whether the target wheel is included in at least one wheel; if the target wheel is included in at least one wheel, determine that the driving state information indicates that the vehicle is in a slipping state.

[0210] Optionally, as an embodiment, the processing module 420 is specifically used to: determine the initial longitudinal speed of the vehicle based on the second parameter and the longitudinal acceleration; wherein, the second parameter includes the longitudinal speed of the vehicle at the first moment, the longitudinal acceleration of the vehicle, and a preset duration; the first moment is the moment before the current moment, and the preset duration is the time difference between the previous moment and the current moment.

[0211] It should be noted that the aforementioned vehicle speed estimation device is implemented in the form of a functional unit. The term "module" here can be implemented in software and / or hardware, without specific limitations.

[0212] For example, a "module" can be a software program, hardware circuit, or a combination of both that implements the above functions. Hardware circuits may include application-specific integrated circuits (ASICs), electronic circuits, processors (e.g., shared processors, proprietary processors, or group processors) and memory for executing one or more software or firmware programs, combined logic circuits, and / or other suitable components that support the described functions.

[0213] Therefore, the units of the various examples described in the embodiments of this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0214] Figure 5 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application.

[0215] For example, vehicle 500 includes processor 510, memory 520 and executable program code 530.

[0216] For example, vehicle 500 includes one or more processors 510 that can support the vehicle speed estimation method in the method embodiment. Processor 510 can be a general-purpose processor or a special-purpose processor. For example, processor 510 can be a central processing unit (CPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0217] For example, processor 510 can be used to control vehicle 500, execute software programs, and process data from the software programs. Vehicle 500 may also include a communication unit for receiving and transmitting signals.

[0218] For example, the vehicle 500 may include one or more memories 520, on which executable program code 530 is stored. The executable program code 530 can be run by the processor 510 to generate instructions, causing the processor 510 to execute the vehicle speed estimation method described in the above method embodiments according to the instructions.

[0219] Optionally, the memory 520 may also store data. Optionally, the processor 510 may also read data stored in the memory 520, which may be stored at the same memory address as the executable program code 530, or the data may be stored at a different memory address than the executable program code 530.

[0220] For example, the processor 510 and memory 520 can be configured separately or integrated together, for example, integrated on the system on chip (SOC) of the terminal device.

[0221] For example, the memory 520 can be used to store related programs of the vehicle speed estimation method provided in the embodiments of this application. The processor 520 can be used to call the executable program code 530 stored in the memory 520 when controlling the vehicle to execute the vehicle speed estimation method of the embodiments of this application. For example, the processor can obtain the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle, and the driving state information of the vehicle. The driving state information is used to indicate whether the vehicle is in a slip state. Based on the longitudinal acceleration, the initial longitudinal speed of the vehicle is obtained. Based on the driving state information, the processor can determine the first weight coefficient of each wheel and the second weight coefficient of the vehicle. The first weight coefficient is used to represent the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent the weight coefficient corresponding to the initial longitudinal speed. Based on the wheel center speed, the first weight coefficient, the initial longitudinal speed, and the second weight coefficient, the processor can determine the target longitudinal speed of the vehicle.

[0222] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vehicle speed estimation method of any of the foregoing embodiments.

[0223] The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, Digital Video Discs (DVDs), Compact Disc Read-Only Memory (CD-ROM), microdrives, and magneto-optical disks, read-only memory (ROM), random access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), dynamic random access memory (DRAM), video random access memory (VRAM), flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0224] This application also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement a vehicle speed estimation method as described in the above embodiments.

[0225] In addition, the vehicle provided in the embodiments of this application may specifically be a chip, component or module. The vehicle may include a connected processor and a memory. The memory is used to store instructions. When the vehicle is running, the processor may call and execute the instructions to make the chip execute a vehicle speed estimation method in the above embodiments.

[0226] The vehicle, computer-readable storage medium, computer program product, or chip provided in this application are all used to execute the corresponding vehicle speed estimation method provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects in the corresponding vehicle speed estimation method provided above, and will not be repeated here.

[0227] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0228] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0229] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for estimating vehicle speed, characterized in that, The method includes: The vehicle acquires the wheel center velocity of each wheel, the longitudinal acceleration of the vehicle, and the vehicle's driving state information; wherein the driving state information is used to indicate whether the vehicle is in a slipping state. Based on the longitudinal acceleration, the initial longitudinal speed of the vehicle is obtained; If the driving status information indicates that the vehicle is in the slip state, a first preset value is determined as a first weighting coefficient, and a second preset value is determined as a second weighting coefficient; wherein, the first weighting coefficient is used to represent the weighting coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weighting coefficient is used to represent the weighting coefficient corresponding to the initial longitudinal vehicle speed; If the driving status information indicates that the vehicle is not in the slip state, the first weighting coefficient and the second weighting coefficient are determined based on the first parameters of the vehicle; the first parameters include: the road surface adhesion coefficient of the vehicle under the current road conditions, the vehicle's current actual speed, and the current rate of change of acceleration. The target longitudinal speed of the vehicle is determined based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient. Determining the first weighting coefficient and the second weighting coefficient based on the first parameter of the vehicle includes: Based on the first parameters of the vehicle and the first mapping relationship, the first weighting coefficient is determined; wherein, in the first mapping relationship, the first weighting coefficient is positively correlated with the road surface adhesion coefficient, negatively correlated with the actual vehicle speed, and negatively correlated with the vehicle's rate of change of acceleration. Based on the first parameter and the second mapping relationship of the vehicle, the second weighting coefficient is determined; wherein, in the second mapping relationship, the second weighting coefficient is negatively correlated with the road surface adhesion coefficient, positively correlated with the actual vehicle speed, and positively correlated with the vehicle's rate of change of acceleration.

2. The method according to claim 1, characterized in that, Determining the first weighting coefficient and the second weighting coefficient based on the first parameter of the vehicle includes: The initial first weighting coefficient and the initial second weighting coefficient are determined based on the road surface adhesion coefficient; Based on the current actual vehicle speed and the current rate of change of acceleration, determine the first adjustment amount corresponding to the initial first weighting coefficient and the second adjustment amount corresponding to the initial second weighting coefficient; The initial first weight coefficient is adjusted based on the first adjustment amount to obtain the first weight coefficient, and the initial second weight coefficient is adjusted based on the second adjustment amount to obtain the second weight coefficient.

3. The method according to claim 1, characterized in that, Determining the target longitudinal speed of the vehicle based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient includes: Based on the wheel center speed and the first weighting coefficient, a first value corresponding to each wheel is determined; based on the initial longitudinal vehicle speed and the second weighting coefficient, a second value is determined. The sum of the first value and the second value is determined as the third value; the sum of the first weighting coefficient and the second weighting coefficient of each wheel is determined as the fourth value; The ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed.

4. The method according to claim 1, characterized in that, Also includes: Based on the slip ratio of the vehicle and / or the wheel radius of each wheel, a correction factor for each wheel is determined. The process of obtaining the wheel center velocity of each wheel in the vehicle includes: Based on the third parameter and the correction coefficient, the wheel center velocity of each wheel is determined; wherein, the third parameter includes the wheel track of the vehicle, the wheel turning angle of each wheel, the yaw rate of the vehicle, and the wheel linear velocity of each wheel.

5. The method according to claim 1, characterized in that, Obtaining the vehicle's driving status information includes: Based on the vehicle's operating conditions, a target wheel among the wheels is determined; wherein, the operating conditions include the vehicle's braking and driving conditions, and the target wheel is the wheel with the highest wheel center speed or the wheel with the lowest wheel center speed among the wheels. If the target wheel is in a slipping state, the driving status information indicates that the vehicle is in the slipping state.

6. The method according to claim 1, characterized in that, The process of obtaining the initial longitudinal speed of the vehicle based on the longitudinal acceleration includes: Based on the second parameter and the longitudinal acceleration, the initial longitudinal speed of the vehicle is determined; wherein, the second parameter includes the longitudinal speed of the vehicle at a first moment, the longitudinal acceleration of the vehicle, and a preset duration; the first moment is the moment before the current moment, and the preset duration is the time difference between the previous moment and the current moment.

7. A vehicle speed estimation device, characterized in that, The device includes: The acquisition module is used to acquire the wheel center velocity of each wheel in the vehicle, the longitudinal acceleration of the vehicle, and the driving state information of the vehicle; wherein the driving state information is used to indicate whether the vehicle is in a slipping state. The processing module is configured to obtain the initial longitudinal speed of the vehicle based on the longitudinal acceleration; if the driving status information indicates that the vehicle is in the slip state, determine a first preset value as a first weighting coefficient and a second preset value as a second weighting coefficient; wherein, the first weighting coefficient is used to represent the weighting coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weighting coefficient is used to represent the weighting coefficient corresponding to the initial longitudinal speed; if the driving status information indicates that the vehicle is not in the slip state, determine the first weighting coefficient and the second weighting coefficient based on the first parameters of the vehicle; the first parameters include: the road surface adhesion coefficient of the current road condition of the vehicle, the current actual speed of the vehicle, and the current rate of change of acceleration; and determine the target longitudinal speed of the vehicle based on the wheel center speed, the first weighting coefficient, the initial longitudinal speed, and the second weighting coefficient. The processing module is specifically used for: determining a first weighting coefficient based on a first parameter of the vehicle and a first mapping relationship; wherein, in the first mapping relationship, the first weighting coefficient is positively correlated with the road surface adhesion coefficient, negatively correlated with the actual vehicle speed, and negatively correlated with the vehicle's rate of change of acceleration; and determining a second weighting coefficient based on a first parameter of the vehicle and a second mapping relationship; wherein, in the second mapping relationship, the second weighting coefficient is negatively correlated with the road surface adhesion coefficient, positively correlated with the actual vehicle speed, and positively correlated with the vehicle's rate of change of acceleration.

8. A vehicle, characterized in that, The vehicles include: Memory, used to store executable program code; A processor for calling and running the executable program code from the memory, causing the vehicle to perform the method as described in any one of claims 1 to 6.

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