Vehicle parameter updating method, vehicle parameter updating system and autonomous vehicle

Abstract

The application provides a vehicle parameter updating method, a vehicle parameter updating system and an automatic driving vehicle, and can be applied to the technical field of vehicle control. The method comprises the following steps: acquiring a current vehicle speed, a current steering input angle and a measured yaw rate of a target vehicle; determining a target parameter from an understeering coefficient and an equivalent wheelbase correction coefficient according to a comparison result of the current vehicle speed and a preset threshold vehicle speed; in response to the current steering input angle satisfying an excitation condition, calculating a theoretical yaw rate based on the understeering coefficient and the equivalent wheelbase correction coefficient, and determining a prediction error according to the measured yaw rate and the theoretical yaw rate; and updating the target parameter based on the prediction error.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, specifically to a vehicle parameter updating method, a vehicle parameter updating system, and an autonomous vehicle. Background Technology

[0002] In intelligent driving and assisted driving systems, the vehicle's lateral controller relies on an internal model to map steering inputs to yaw responses. The understeer coefficient and equivalent wheelbase correction coefficient in the model are key parameters used to calculate predicted yaw rates. However, these two parameters vary with operating conditions such as tire conditions, load, and road surface adhesion. Offline calibrated fixed parameters cannot cover the continuous changes in actual operation, necessitating online parameter updates to improve model accuracy.

[0003] In related technologies, the vehicle parameter update methods have low accuracy in the updated parameters, which affects the lateral control precision of the vehicle. Summary of the Invention

[0004] In view of the above problems, embodiments of this application provide a vehicle parameter update method, a vehicle parameter update system, and an autonomous vehicle.

[0005] According to a first aspect of this application, a vehicle parameter updating method is provided, comprising: acquiring the current vehicle speed, current steering input angle, and measured yaw rate of a target vehicle; determining target parameters from an understeer coefficient and an equivalent wheelbase correction coefficient based on a comparison between the current vehicle speed and a preset threshold vehicle speed; calculating a theoretical yaw rate based on the understeer coefficient and the equivalent wheelbase correction coefficient in response to the current steering input angle satisfying the excitation condition, and determining a prediction error based on the measured yaw rate and the theoretical yaw rate; and updating the target parameters based on the prediction error.

[0006] According to an embodiment of this application, the preset threshold speed includes a first threshold speed and a second threshold speed, wherein the first threshold speed is greater than the second threshold speed; based on the comparison result between the current speed and the preset threshold speed, a target parameter is determined from the understeer coefficient and the equivalent wheelbase correction coefficient, including: when the current speed is greater than the first threshold speed, determining the understeer coefficient as the target parameter; when the current speed is less than the second threshold speed, determining the equivalent wheelbase correction coefficient as the target parameter.

[0007] According to an embodiment of this application, updating the target parameter based on the prediction error includes: when the target parameter is the understeer coefficient and the absolute value of the prediction error is greater than a preset dead zone threshold, calculating a first parameter update amount based on the influence of the prediction error and the understeer coefficient on the theoretical yaw rate, and updating the understeer coefficient based on the first parameter update amount; when the target parameter is the equivalent wheelbase correction coefficient and the absolute value of the prediction error is greater than a preset dead zone threshold, calculating a second parameter update amount based on the influence of the prediction error and the equivalent wheelbase correction coefficient on the theoretical yaw rate, and updating the equivalent wheelbase correction coefficient based on the second parameter update amount.

[0008] According to an embodiment of this application, responding to the current steering input angle satisfying the excitation condition includes: determining that the excitation condition is satisfied when the absolute value of the current steering input angle is greater than a preset excitation threshold.

[0009] According to an embodiment of this application, the method further includes: when the current vehicle speed is less than or equal to a first threshold vehicle speed, adjusting the understeer coefficient to a preset first nominal value in each control cycle according to a preset regression rate, so that the understeer coefficient gradually approaches the first nominal value.

[0010] According to an embodiment of this application, the method further includes: when the current vehicle speed is greater than or equal to the second threshold speed and less than or equal to the first threshold speed, performing linear interpolation on the equivalent wheelbase correction coefficient based on the relative position of the current vehicle speed between the second threshold speed and the first threshold speed, such that the equivalent wheelbase correction coefficient takes the current value at the second threshold speed, takes the preset second nominal value at the first threshold speed, and is continuous at both ends.

[0011] According to an embodiment of this application, the method further includes: obtaining the lateral speed and longitudinal speed of the target vehicle; setting a lower limit for the longitudinal speed; calculating the sideslip angle based on the lateral speed and the longitudinal speed after setting the lower limit; determining a sideslip angle activation coefficient based on the relative position of the current vehicle speed with respect to a preset vehicle speed range; the sideslip angle activation coefficient characterizing the degree of participation of the sideslip angle in the heading state correction; scaling the sideslip angle using the sideslip angle activation coefficient; and using the scaled sideslip angle to correct the heading state of the target vehicle.

[0012] According to an embodiment of this application, the sideslip angle activation coefficient is determined based on the relative position of the current vehicle speed with respect to a preset speed range. This includes: when the current vehicle speed is less than or equal to the lower limit of the preset speed range, the sideslip angle activation coefficient is set to zero to prevent the scaled sideslip angle from correcting the heading state; when the current vehicle speed is greater than or equal to the upper limit of the preset speed range, the sideslip angle activation coefficient is set to one to allow the scaled sideslip angle to correct the heading state; when the current vehicle speed is within the preset speed range, a smoothing function with zero first derivatives at both ends is used to calculate the sideslip angle activation coefficient based on the relative position of the current vehicle speed within the preset speed range, so that the amount of correction of the heading state by the scaled sideslip angle increases continuously and smoothly as the vehicle speed increases.

[0013] According to a second aspect of this application, a vehicle parameter update system is provided, comprising: an acquisition unit for acquiring the current vehicle speed, current steering input angle, and measured yaw rate of a target vehicle; and a controller communicatively connected to the acquisition unit, the controller being configured to: determine target parameters from an understeer coefficient and an equivalent wheelbase correction coefficient based on a comparison between the current vehicle speed and a preset threshold vehicle speed; calculate a theoretical yaw rate based on the understeer coefficient and the equivalent wheelbase correction coefficient in response to the current steering input angle satisfying the excitation condition, and determine a prediction error based on the measured yaw rate and the theoretical yaw rate; and update the target parameters based on the prediction error.

[0014] According to a third aspect of this application, an autonomous vehicle is provided, including: the aforementioned vehicle parameter update system. Attached Figure Description

[0015] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0016] Figure 1 This illustration schematically depicts an application scenario of the vehicle parameter update method according to an embodiment of this application.

[0017] Figure 2 A flowchart illustrating a vehicle parameter update method according to an embodiment of this application is shown schematically.

[0018] Figure 3 A flowchart illustrating a vehicle parameter update method according to another embodiment of this application is shown schematically;

[0019] Figure 4 A flowchart illustrating a vehicle parameter updating method according to yet another embodiment of this application is shown schematically;

[0020] Figure 5 This schematic diagram illustrates a structural block diagram of a vehicle parameter updating device according to an embodiment of the present application;

[0021] Figure 6 A schematic block diagram of a vehicle parameter update system according to an embodiment of this application is shown. Detailed Implementation

[0022] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0023] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0024] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0025] Figure 1 The diagram illustrates an application scenario of the vehicle parameter update method according to an embodiment of this application.

[0026] like Figure 1 As shown, application scenario 100 according to an embodiment of this application may include an autonomous vehicle 101 and a controller 102. The autonomous vehicle 101 and the controller 102 can establish a communication connection via a network 103. The network 103 may be, for example, a controller local area network bus, an in-vehicle Ethernet, etc. The controller 102 can obtain the driving information of the autonomous vehicle 101 (such as the distance from the vehicle to the stop line, the vehicle's current speed, etc.) and send a target limit command to the autonomous vehicle 101 to control the autonomous vehicle 101 to travel at a speed not exceeding the target limit speed.

[0027] The autonomous vehicle 101 can be a passenger car, commercial vehicle, or other vehicle with autonomous driving capabilities. Passenger cars can include sedans, sport utility vehicles (SUVs), etc., while commercial vehicles can include driverless taxis, driverless buses, driverless trucks, etc. The autonomous vehicle 101 can be equipped with various sensors (such as cameras, lidar, millimeter-wave radar, ultrasonic radar, and positioning inertial navigation systems) to collect information about the surrounding environment and the vehicle's own status.

[0028] The controller 102 can be a computing device that provides autonomous driving decision-making and planning functions, such as an electronic controller, an autonomous driving domain controller, or a vehicle control domain controller. The controller 102 can be a physical controller that is an independent peripheral, an on-board controller integrated into the autonomous vehicle 101, or a distributed control system composed of multiple controllers. The controller 102 can interact with the sensors, actuators, etc., of the autonomous vehicle 101 via the network 103 to receive sensor data and send control commands to the actuators. The controller 102 can run a speed planning module to execute the vehicle steering control method provided in the embodiments of this application.

[0029] It should be understood that Figure 1 The number of autonomous vehicles and controllers shown is merely illustrative. Depending on the implementation requirements, there can be any number of autonomous vehicles and controllers, such as a fleet of multiple autonomous vehicles or a redundant computing platform consisting of multiple controllers.

[0030] In intelligent driving and assisted driving systems, the vehicle's lateral controller relies on an internal model to map steering commands issued by the driver or autonomous driving system into the vehicle's yaw response, thereby achieving lateral control functions such as lane keeping, automatic lane changing, and path tracking. Two key parameters in this internal model—the understeer coefficient and the equivalent wheelbase correction coefficient—directly determine the mapping relationship between the steering input angle and the yaw rate. The understeer coefficient reflects the degree of understeer during high-speed cornering, while the equivalent wheelbase correction coefficient reflects the deviation between the vehicle's actual steering geometry and its theoretical wheelbase. However, these two parameters are not fixed. The understeer coefficient changes with variations in tire lateral stiffness, load distribution, tire pressure, and road adhesion conditions; the equivalent wheelbase correction coefficient is affected by factors such as multi-axle arrangement, tire contact patch deformation, and steering mechanism wear. Offline calibrated fixed parameters cannot cover the continuous changes that occur during actual vehicle operation; therefore, these two parameters need to be updated online to ensure the accuracy of the lateral control model.

[0031] Vehicle parameter update methods in related technologies have several shortcomings during the update process. For example, some methods simultaneously identify two parameters across the entire speed range, but due to differences in the observability of the two parameters at different vehicle speeds, the identification results are coupled and have low accuracy. Furthermore, some methods continue to update parameters under low-excitation conditions (such as straight-line driving or slight steering), where the signal-to-noise ratio of the measurement signal is low, making the update operation susceptible to noise-driven parameter drift. The drifted erroneous parameters, once introduced into the control model, further amplify the control error. In addition, related technologies often retain outdated estimates after parameters leave their identifiable speed range. When operating conditions change, these outdated parameters continue to contaminate the control model, affecting lateral control accuracy.

[0032] The updated understeer coefficient and equivalent wheelbase correction coefficient are provided to the internal model of the vehicle's lateral controller to calculate the yaw gain and feedforward gain, thereby generating precise steering control commands. These commands can be used in lateral motion control of autonomous driving systems and lane centering in driver assistance systems, ensuring that the vehicle responds accurately and stably to steering commands under various operating conditions. Therefore, improving the accuracy of parameter updates is crucial for enhancing the vehicle's lateral control performance.

[0033] Figure 2 A flowchart illustrating a vehicle parameter update method according to an embodiment of this application is shown schematically. Figure 2 As shown, the vehicle parameter update method 200 according to an embodiment of this application may include steps S210 to S240.

[0034] In step S210, the current vehicle speed, current steering input angle, and measured yaw rate of the target vehicle are obtained.

[0035] In the embodiments of this application, the target vehicle refers to the vehicle to which this method is applied, which can be any vehicle that requires online updating of lateral dynamic parameters, such as passenger cars, commercial vehicles, or multi-axle vehicles.

[0036] In the embodiments of this application, the current vehicle speed refers to the current speed of the target vehicle, usually expressed in meters per second (m / s) or kilometers per hour (km / h). For example, if the vehicle is traveling at a speed of 10 m / s, then the current vehicle speed is 10 m / s.

[0037] In the embodiments of this application, the current steering input angle refers to the steering wheel angle or steering wheel angle applied by the driver or the autonomous driving system, typically expressed in radians (rad). For example, if the driver turns the steering wheel 0.3 rad, the current steering input angle is 0.3 rad.

[0038] In the embodiments of this application, the measured yaw rate refers to the rotational angular velocity of the vehicle about its vertical axis, actually measured by a sensor (such as an inertial measurement unit) installed on the target vehicle, and is expressed in radians per second (rad / s). For example, the sensor measures the vehicle's current yaw rate to be 0.2 rad / s.

[0039] In the embodiments of this application, the current vehicle speed, current steering input angle, and measured yaw rate of the target vehicle are obtained. These three physical quantities can be acquired in real time using sensors on the vehicle (such as vehicle speed sensor, steering wheel angle sensor, and yaw rate sensor).

[0040] For example, suppose at a certain moment, the vehicle speed sensor measures the current vehicle speed as 15 m / s, the steering wheel angle sensor measures the current steering input angle as 0.4 rad, and the yaw rate sensor measures the actual yaw rate as 0.18 rad / s. Then the obtained data would be: current vehicle speed 15 m / s, current steering input angle 0.4 rad, actual yaw rate 0.18 rad / s.

[0041] In step S220, the target parameters are determined from the understeer coefficient and the equivalent wheelbase correction coefficient based on the comparison between the current vehicle speed and the preset threshold vehicle speed.

[0042] In the embodiments of this application, the threshold speed refers to one or more preset speed thresholds used to divide different speed ranges so that the parameter to be updated can be selected according to the speed. The specific value of the threshold speed can be calibrated according to the vehicle model, tire characteristics, etc., for example, it can be set to 8 m / s.

[0043] In the embodiments of this application, the understeer coefficient is a parameter characterizing the degree of understeer when a vehicle is cornering at high speed, and its unit is seconds² / meter² (s² / m²). The larger the coefficient, the more the vehicle tends to understeer (pull forward) at high speeds. For example, the nominal value of the understeer coefficient for a certain vehicle model may be 0.005 s² / m².

[0044] In the embodiments of this application, the equivalent wheelbase correction factor is a dimensionless parameter characterizing the actual steering geometry of a vehicle, and is the ratio of the nominal wheelbase to the equivalent wheelbase. This parameter reflects the influence of factors such as tire deformation and steering mechanism clearance on the turning radius. For example, the equivalent wheelbase correction factor for a certain vehicle model may be 0.95 (indicating that the actual turning radius is slightly larger than the theoretical value).

[0045] In the embodiments of this application, the target parameter refers to the parameter that needs to be updated, i.e., selected from the understeer coefficient and the equivalent wheelbase correction coefficient. For example, under a certain vehicle speed condition, the target parameter is the understeer coefficient.

[0046] In the embodiments of this application, a target parameter is determined from the understeer coefficient and the equivalent wheelbase correction coefficient based on the comparison between the current vehicle speed and a preset threshold speed. The purpose of this embodiment is to determine which parameter to update based on the current vehicle speed's range. The preset threshold speed is a pre-calibrated value, such as 8 m / s. If the current vehicle speed is greater than the threshold speed, the target parameter is determined to be the understeer coefficient; if the current vehicle speed is less than the threshold speed, the target parameter is determined to be the equivalent wheelbase correction coefficient. Multiple threshold speeds can also be set according to actual needs, and the parameter to be updated is selected by comparing the relationship between the current vehicle speed and the threshold speed.

[0047] In step S230, in response to the current steering input angle satisfying the excitation condition, the theoretical yaw rate is calculated based on the understeer coefficient and the equivalent wheelbase correction coefficient, and the prediction error is determined based on the measured yaw rate and the theoretical yaw rate.

[0048] In the embodiments of this application, the excitation condition refers to the precondition that allows parameter updates, which is usually related to the steering input angle. For example, the vehicle is considered to be in a state of sufficient steering excitation only when the absolute value of the steering input angle is greater than a certain threshold, and only then is updating the parameters meaningful.

[0049] In the embodiments of this application, the theoretical yaw rate refers to the predicted yaw rate calculated by a vehicle lateral dynamics model based on the current values ​​of the current understeer coefficient and the equivalent wheelbase correction coefficient. This model reflects the relationship between the steering input angle, vehicle speed, and yaw rate.

[0050] In the embodiments of this application, the prediction error refers to the difference between the measured yaw rate and the theoretical yaw rate, which is used to measure the deviation between the current parameter estimate and the true value.

[0051] In the embodiments of this application, in response to the current steering input angle satisfying the excitation condition, the theoretical yaw rate is calculated based on the understeer coefficient and the equivalent wheelbase correction coefficient, and the prediction error is determined based on the measured yaw rate and the theoretical yaw rate. First, it is determined whether the excitation condition is satisfied; if so, calculation is performed. The excitation condition is usually related to the steering input angle. For example, the vehicle is considered to be in a state of sufficient steering excitation only when the absolute value of the steering input angle is greater than a preset excitation threshold (e.g., 0.2 rad), at which point the updated parameters are effective. This is because during straight-line driving or small turns, parameter changes have little impact on the yaw rate, and the update is easily affected by noise.

[0052] In the embodiments of this application, when the excitation conditions are met, the theoretical yaw rate is calculated using the current values ​​of the currently stored understeer coefficient and equivalent wheelbase correction coefficient through a vehicle lateral dynamics model. This model can be a steady-state yaw gain model, for example: Theoretical yaw rate = (Current steering input angle × Current vehicle speed) / (Nominal wheelbase × Steering system transmission ratio) × a certain correction factor, where the correction factor is jointly determined by the understeer coefficient and the equivalent wheelbase correction coefficient. Subtracting the theoretical yaw rate from the measured yaw rate yields the prediction error. This prediction error reflects the direction and magnitude of the deviation between the current parameter estimate and the true value.

[0053] Example: Assume the excitation threshold is 0.2 rad, the current steering input angle is 0.4 rad, which is greater than 0.2 rad, satisfying the excitation condition. The current understeer coefficient is 0.005 s² / m², the equivalent wheelbase correction coefficient is 0.98, and the theoretical yaw rate calculated by the model is 0.19 rad / s. The measured yaw rate is 0.18 rad / s, then the prediction error = 0.18 - 0.19 = -0.01 rad / s.

[0054] In step S240, the target parameters are updated based on the prediction error.

[0055] In the embodiments of this application, the target parameters are corrected using the prediction error. This can be achieved through gradient descent, for example, the new value of the target parameter = current value of the target parameter - learning rate × prediction error × sensitivity coefficient, where the sensitivity coefficient reflects the degree to which changes in the target parameter affect the theoretical yaw rate. In this way, the target parameters are adjusted in a direction that reduces the prediction error, thereby improving model accuracy.

[0056] Through the embodiments of this application, by selecting target parameters to be updated from the understeer coefficient and equivalent wheelbase based on the comparison between the current vehicle speed and the threshold vehicle speed, and only updating them when the steering input angle meets the excitation conditions, it is possible to avoid blindly updating parameters under inappropriate operating conditions and reduce noise interference. Simultaneously, updating the target parameters based on the prediction error allows the parameters to gradually approach the true values. This vehicle parameter update method improves the accuracy of parameter updates, thereby enhancing the precision of the vehicle lateral control model and improving the lateral control performance of intelligent driving or assisted driving systems.

[0057] Figure 3 A flowchart illustrating a vehicle parameter update method according to another embodiment of this application is shown schematically. Figure 3As shown in the embodiments of this application, the preset threshold speed includes a first threshold speed and a second threshold speed, wherein the first threshold speed is greater than the second threshold speed; the target parameter is determined from the understeer coefficient and the equivalent wheelbase correction coefficient based on the comparison result between the current speed and the preset threshold speed, which may include steps S310 to S320.

[0058] In step S310, if the current vehicle speed is greater than the first threshold vehicle speed, the understeer coefficient is determined as the target parameter.

[0059] In the embodiments of this application, the first threshold speed is a preset speed threshold used to delineate the high-speed identification domain. When the current vehicle speed is greater than this threshold, the vehicle is in the high-speed domain, and the understeer coefficient has good observability. The first threshold speed can be calibrated according to vehicle model, tire characteristics, etc., for example, it can be set to 8 m / s.

[0060] In the embodiments of this application, the second threshold speed is another preset speed threshold used to delineate the low-speed identification domain. When the current vehicle speed is less than this threshold, the vehicle is in the low-speed domain, and the equivalent wheelbase correction coefficient has good observability. The second threshold speed is less than the first threshold speed, for example, it can be set to 5 m / s. It should be noted that the first threshold speed is greater than the second threshold speed, and a speed range is formed between the two, which can be treated as a transition zone.

[0061] In the embodiments of this application, when the current vehicle speed is greater than a first threshold speed, the understeer coefficient is determined as the target parameter. When the current vehicle speed is high (greater than the first threshold speed), the vehicle is in the high-speed domain. In the high-speed domain, the understeer coefficient significantly affects the yaw rate through the square of the vehicle speed, and its observability is best, while the effect of the equivalent wheelbase correction coefficient is relatively weak and overlaps with other effects. Therefore, in this case, the understeer coefficient should be used as the target parameter to be updated, while the equivalent wheelbase correction coefficient should remain at its current value or be processed in other ways.

[0062] For example, assuming the first speed threshold is 8 m / s and the current speed is 15 m / s, which is greater than 8 m / s, the target parameter is determined to be the understeer coefficient. In this case, subsequent updates will be performed based on the understeer coefficient, and the equivalent wheelbase correction coefficient will not be included in this update.

[0063] In step S320, if the current vehicle speed is less than the second threshold vehicle speed, the equivalent wheelbase correction coefficient is determined as the target parameter.

[0064] In the embodiments of this application, when the current vehicle speed is less than the second threshold speed, the equivalent wheelbase correction coefficient is determined as the target parameter. When the current vehicle speed is low (less than the second threshold speed), the vehicle is in the low-speed domain. In the low-speed domain, tire side-slip effect is negligible, and the equivalent wheelbase correction coefficient directly determines the gain from steering angle to yaw rate, exhibiting the best observability, while the influence of the understeer coefficient approaches zero. Therefore, in this case, the equivalent wheelbase correction coefficient should be used as the target parameter to be updated, while the understeer coefficient should remain at its current value or be processed in other ways.

[0065] For example, assuming the second speed threshold is 5 m / s and the current speed is 3 m / s, which is less than 5 m / s, the target parameter is determined to be the equivalent wheelbase correction coefficient. In this case, subsequent update operations will be performed based on the equivalent wheelbase correction coefficient, and the understeer coefficient will not be included in this update.

[0066] Through the embodiments of this application, by setting a first threshold vehicle speed and a second threshold vehicle speed, and determining target parameters based on the comparison results between the current vehicle speed and the two, the understeer coefficient is updated in the high-speed domain and the equivalent wheelbase correction coefficient is updated in the low-speed domain. This avoids the coupling interference when the two parameters are jointly identified in the full-speed domain, and improves the accuracy of parameter updates.

[0067] In some embodiments, updating the target parameter based on the prediction error includes: when the target parameter is the understeer coefficient and the absolute value of the prediction error is greater than a preset dead zone threshold, calculating a first parameter update amount based on the influence of the prediction error and the understeer coefficient on the theoretical yaw rate, and updating the understeer coefficient based on the first parameter update amount; when the target parameter is the equivalent wheelbase correction coefficient and the absolute value of the prediction error is greater than a preset dead zone threshold, calculating a second parameter update amount based on the influence of the prediction error and the equivalent wheelbase correction coefficient on the theoretical yaw rate, and updating the equivalent wheelbase correction coefficient based on the second parameter update amount.

[0068] In the embodiments of this application, the dead zone threshold is a preset positive number used to determine whether the prediction error is large enough to warrant triggering a parameter update. The dead zone threshold is typically set based on the measurement noise level of the yaw rate sensor, for example, it can be set to 0.003 rad / s. Only when the absolute value of the prediction error exceeds this threshold is the deviation considered to be caused by parameter inaccuracy rather than measurement noise, and an update is performed; otherwise, the update is skipped to avoid noise-driven parameter drift.

[0069] In the embodiments of this application, the first parameter update amount refers to the adjustment amount calculated for the understeer coefficient, used to correct the current estimated value of the understeer coefficient. The first parameter update amount is calculated based on the prediction error and the degree of influence of the understeer coefficient on the theoretical yaw rate. The second parameter update amount refers to the adjustment amount calculated for the equivalent wheelbase correction coefficient, used to correct the current estimated value of the equivalent wheelbase correction coefficient. The second parameter update amount is calculated based on the prediction error and the degree of influence of the equivalent wheelbase correction coefficient on the theoretical yaw rate.

[0070] In the embodiments of this application, the degree of influence refers to the magnitude of the change in theoretical yaw rate when the target parameter changes by one unit, also known as sensitivity. For example, the degree of influence of the understeering coefficient on the theoretical yaw rate can be obtained by differentiation, which is used to convert the prediction error into a parameter update quantity.

[0071] In the embodiments of this application, when the target parameter is the understeer coefficient and the absolute value of the prediction error is greater than a preset dead zone threshold, the first parameter update amount is calculated based on the influence of the prediction error and the understeer coefficient on the theoretical yaw rate, and the understeer coefficient is updated based on the first parameter update amount.

[0072] In the embodiments of this application, when the target parameter is the understeering coefficient, the prediction error is first calculated. ;in, To measure the yaw rate, This is the theoretical yaw rate calculated based on the current understeer coefficient and the equivalent wheelbase correction coefficient. Then, it is determined... Is it greater than the preset dead zone threshold? .like No more than If the current deviation is mainly caused by noise, then no update is performed. Greater than If so, then the update will be performed.

[0073] In embodiments of this application, the update can employ the gradient descent method. First, the sensitivity of the understeer coefficient to the theoretical yaw rate is calculated. Theoretical yaw rate Where A is the intermediate quantity of geometric yaw gain. v is the current steering input angle, v is the current vehicle speed, and L is the nominal wheelbase. This refers to the overall gear ratio of the steering system. This represents the current insufficient turning coefficient. Then the sensitivity... This sensitivity reflects When changing by one unit The change in the understeering coefficient can then be updated using the following formula. ;in, The preset gain per second is used to control the convergence rate of the update step size, for example, 0.2 / s; To control the cycle; and These are the physical lower and upper limits of the understeer coefficient, respectively. Indicates will Limited to the range inside, if Then take ,like Then take Otherwise take The meaning of this formula is to first calculate the temporary update amount. Then, the value is clamped to this position using the clip operation. Within this process, the final updated parameters are obtained. The clip operation ensures that the parameters will never exceed the physically reasonable range at any time. Even if the sensor malfunctions or the algorithm diverges, the parameters will only stay within the limits and will not go out of control, thus ensuring the safety of the control model.

[0074] In the embodiments of this application, when the target parameter is the equivalent wheelbase correction coefficient and the absolute value of the prediction error is greater than the preset dead zone threshold, the second parameter update amount is calculated based on the influence of the prediction error and the equivalent wheelbase correction coefficient on the theoretical yaw rate, and the equivalent wheelbase correction coefficient is updated based on the second parameter update amount.

[0075] In the embodiments of this application, when the target parameter is the equivalent wheelbase correction coefficient, the prediction error is first calculated. ;in, This is the predicted value of the yaw rate in the low-speed domain. ;in, This is the current equivalent wheelbase correction factor. Then determine... Is it greater than the preset dead zone threshold? .like No more than If the current deviation is mainly caused by noise, then no update is performed. Greater than If so, then the update will be performed.

[0076] In the embodiments of this application, the sensitivity of the equivalent wheelbase correction factor to the theoretical yaw rate is... This sensitivity is directly proportional to the steering input angle and vehicle speed, and inversely proportional to the gear ratio and nominal wheelbase. The equivalent wheelbase correction factor can be updated using the following formula. ;in, Gain per second in the low-speed domain; and These represent the physical lower and upper limits of the equivalent wheelbase correction factor, respectively. Through the clip operation, the equivalent wheelbase correction factor is also limited to a reasonable range, ensuring that the parameters entering the control model are always safe and available.

[0077] Through the embodiments of this application, by setting a dead zone threshold and filtering noise level deviation, the parameters can be prevented from drifting due to noise; by adjusting the parameters in the direction of error reduction through gradient updates, the convergence speed and accuracy of parameter identification can be improved, thereby enhancing the accuracy of the lateral control model.

[0078] In some embodiments, responding to the current steering input angle satisfying the excitation condition includes: determining that the excitation condition is satisfied when the absolute value of the current steering input angle is greater than a preset excitation threshold.

[0079] In the embodiments of this application, the preset excitation threshold is a pre-calibrated positive number in radians (rad), used to determine whether the current steering input angle is large enough to provide sufficient steering excitation. The excitation threshold is typically set based on the characteristics of the vehicle steering system, sensor noise levels, and sensitivity requirements for parameter identification.

[0080] For example, the preset excitation threshold can be set to 0.2 rad. When the absolute value of the steering input angle exceeds this threshold, the vehicle is considered to be in a state of sufficient steering excitation. At this time, the influence of the parameters on the yaw rate is significant enough, and the updated parameters have a high signal-to-noise ratio.

[0081] In the embodiments of this application, the excitation conditions refer to a set of preconditions that allow parameter updates. In this embodiment, the excitation conditions are only related to the current steering input angle, that is, the absolute value of the current steering input angle is greater than a preset excitation threshold. When this condition is met, subsequent parameter update steps (such as calculating the theoretical yaw rate, determining the prediction error, and updating the target parameters) will be executed. If the condition is not met, the update is skipped to avoid introducing noise under low excitation conditions.

[0082] In the embodiments of this application, the excitation condition is determined to be met when the absolute value of the current steering input angle is greater than a preset excitation threshold. Within each control cycle, the current steering input angle is first acquired. Calculate its absolute value Then With the preset excitation threshold Compare. If > If the current steering input angle meets the excitation condition, subsequent parameter update operations are allowed; if ≤ If the excitation conditions are not met, then the parameters will not be updated.

[0083] In the embodiments of this application, when the vehicle is traveling in a straight line or making only minor steering adjustments (such as slight directional corrections), the steering input angle is very small. At this time, the effect of parameter changes on the yaw rate is negligible, while sensor measurement noise is relatively significant. If parameter updates are still performed under these conditions, the update amount will be primarily driven by noise, leading to random parameter drift and contaminating the control model. Therefore, by setting an excitation threshold, updates are only enabled when the steering action is sufficiently significant, which is equivalent to only accepting samples with a high signal-to-noise ratio, thereby ensuring the quality and stability of parameter updates.

[0084] For example, assuming a preset excitation threshold =0.2 rad. The vehicle is traveling straight on a highway, and the driver is making only minor adjustments to the steering wheel; the current steering input angle is 0.05 rad. Calculate the absolute value. = 0.05 rad, less than 0.2 rad, therefore the excitation condition is not met, and no parameter update is performed. This avoids mistaking road bumps or sensor noise as parameter changes. The vehicle is changing lanes, and the driver turns the steering wheel 0.4 rad. Calculate the absolute value. = 0.4 rad, which is greater than 0.2 rad, therefore the excitation condition is met, allowing subsequent steps to calculate the theoretical yaw rate, determine the prediction error, and update the target parameters. At this point, the steering excitation is sufficient, and parameter changes can significantly affect the yaw response, resulting in an update with a high signal-to-noise ratio.

[0085] It should be noted that the stimulus conditions are only a prerequisite for parameter updates. Even if the stimulus conditions are met, subsequent steps can still consider other conditions (such as whether the prediction error exceeds the dead zone threshold) to determine whether to actually perform the update.

[0086] Through the embodiments of this application, by setting an excitation threshold, parameter updates are only enabled when the steering input angle is sufficiently large, effectively filtering noise interference under low excitation conditions, preventing parameters from drifting due to noise, improving the signal-to-noise ratio and stability of parameter updates, and thus improving the accuracy of the lateral control model.

[0087] In some embodiments, the method further includes: when the current vehicle speed is less than or equal to a first threshold vehicle speed, adjusting the understeer coefficient to a preset first nominal value in each control cycle according to a preset regression rate, so that the understeer coefficient gradually approaches the first nominal value.

[0088] In the embodiments of this application, the preset regression rate can be a pre-calibrated positive number with units of 1 / s, used to control how quickly the understeering coefficient regresses to its nominal value. A larger regression rate results in faster parameter regression; a smaller regression rate results in slower parameter regression. For example, it can be set to 1 / s.

[0089] In the embodiments of this application, the control cycle refers to the time interval between each calculation performed by the vehicle control system, measured in seconds (s), for example, 0.01 s. Within each control cycle, a parameter adjustment operation is performed once.

[0090] In the embodiments of this application, the preset first nominal value can be a safe default value for the understeer coefficient, which is the target value to which the parameter regresses when it leaves the identification domain. The first nominal value is usually taken as the nominal value of the vehicle under standard operating conditions, such as 0.005 s² / m². This value can be pre-calibrated according to vehicle model, tire characteristics, etc.

[0091] In the embodiments of this application, when the current vehicle speed is less than or equal to a first threshold speed, the understeer coefficient is adjusted towards a preset first nominal value in each control cycle according to a preset regression rate, so that the understeer coefficient gradually approaches the first nominal value. When the vehicle's current speed is low (less than or equal to the first threshold speed), the understeer coefficient leaves its identifiable high-speed domain, and at this time, it is no longer updated with gradients (because at this speed, the understeer coefficient has almost no effect on the yaw rate, and the update will only absorb noise). Instead, according to a preset regression rate, the understeer coefficient is adjusted towards a safe nominal value in each control cycle, so that it gradually approaches that nominal value. When the parameter leaves the identification domain, the confidence of its estimated value decreases over time. Actively regressing the nominal value is safer than indefinitely maintaining outdated estimates, and can prevent parameters that have become invalid after changes in operating conditions from continuing to contaminate the control model.

[0092] In the embodiments of this application, it is assumed that when a vehicle is traveling on a highway, the understeer coefficient is updated to an accurate estimate (e.g., 0.006 s² / m²). Subsequently, the vehicle enters a low-speed urban area, where the understeer coefficient is no longer observable and cannot be updated. If this value remains unchanged, but the actual tire pressure, load, etc., of the vehicle change, causing the true understeer coefficient to become 0.004 s² / m², then when the vehicle re-enters the highway, the old estimate of 0.006 s² / m² is invalid, introducing a significant model error. By allowing the understeer coefficient to gradually return to its nominal value (e.g., 0.005 s² / m²) in the low-speed domain, the parameters can be placed near a more reasonable initial value when re-entering the high-speed domain, thereby accelerating the re-convergence speed.

[0093] In the embodiments of this application, the adjustment process can be represented by the following first-order dynamic regression formula. ;in, This is the understeering coefficient at the start of the current control cycle; The preset regression rate; The first nominal value is preset; To control the cycle; the arrow indicates an assignment operation, that is, assigning the calculation result on the right to the left. This will be used as the new value for the next control cycle.

[0094] Through the embodiments of this application, the out-of-domain regression mechanism enables the underperformance coefficient leaving the identification domain to decay toward the nominal value at a controllable rate, avoiding the long-term pollution control model of outdated estimates after changes in operating conditions, improving the adaptability and safety of parameters when switching between different operating conditions, and providing a reasonable initial value for the next entry into the identification domain.

[0095] In some embodiments, the method further includes: when the current vehicle speed is greater than or equal to the second threshold speed and less than or equal to the first threshold speed, performing linear interpolation on the equivalent wheelbase correction coefficient based on the relative position of the current vehicle speed between the second threshold speed and the first threshold speed, such that the equivalent wheelbase correction coefficient takes the current value at the second threshold speed, takes the preset second nominal value at the first threshold speed, and is continuous at both ends.

[0096] In the embodiments of this application, in each control cycle, the system determines the vehicle speed based on the current vehicle speed. The relationship between the vehicle speed and a preset threshold speed is used to determine the vehicle's speed range. Specifically, if... The second speed limit (denoted as...) If ), then it is determined to be a low-speed recognition domain; if The first threshold speed (denoted as...) ,in If the width of the transition band is 1, then it is determined to be the high-speed recognition domain; if If the condition is such that the transition zone is defined, then this is considered a transition zone. This embodiment deals with the situation within the transition zone.

[0097] In the embodiments of this application, the transition zone refers to the speed range between the second threshold speed and the first threshold speed. Within this range, the vehicle is neither in a purely low-speed domain nor a purely high-speed domain. The equivalent wheelbase correction coefficient needs to smoothly transition from the identification value in the low-speed domain to the nominal value in the high-speed domain to avoid a jump in the control model during domain switching. The width of the transition zone is the first threshold speed minus the second threshold speed.

[0098] In the embodiments of this application, the relative position of the current vehicle speed between the second threshold speed and the first threshold speed refers to the proportional position of the current vehicle speed within the transition zone, typically represented by a normalized variable. This relative position is used to determine the weight of the linear interpolation. For example, if the second threshold is 8 m / s, the first threshold is 9 m / s, and the current vehicle speed is 8.5 m / s, then the relative position is (8.5-8) / (9-8)=0.5, which means it is located at the midpoint of the transition zone.

[0099] In the embodiments of this application, the current value refers to the current identified value obtained by gradient update of the equivalent wheelbase correction coefficient in the low-speed domain, denoted as... The preset second nominal value refers to the nominal value of the equivalent wheelbase correction coefficient used in the high-speed domain, usually taken as 1.0 (meaning the equivalent wheelbase equals the nominal wheelbase). This value can be pre-calibrated according to the vehicle model. Linear interpolation is a method of calculating intermediate values ​​between two points according to a linear relationship. Within the transition zone, the value of the equivalent wheelbase correction coefficient changes linearly with vehicle speed, continuously transitioning from the current value at the low-speed domain boundary to the nominal value at the high-speed domain boundary. Continuity at both boundaries means that at the second threshold speed, the interpolation result equals the current value in the low-speed domain; at the first threshold speed, the interpolation result equals the nominal value in the high-speed domain. This means that at the two boundary points of the transition zone, the equivalent wheelbase correction coefficient does not jump, ensuring the continuity of the control model.

[0100] In the embodiments of this application, when the current vehicle speed is greater than or equal to the second threshold speed and less than or equal to the first threshold speed, the equivalent wheelbase correction coefficient is linearly interpolated based on the relative position of the current vehicle speed between the second and first threshold speeds. This results in the equivalent wheelbase correction coefficient taking the current value at the second threshold speed and a preset second nominal value at the first threshold speed, and being continuous at both boundaries. When the vehicle's current speed is within the transition zone, the equivalent wheelbase correction coefficient identified in the low-speed domain is no longer directly used, nor is the nominal value of 1.0 in the high-speed domain directly used. Instead, the coefficient is adjusted according to the relative position of the vehicle speed within the transition zone. Linear interpolation with 1.0 yields a smooth-transition equivalent wheelbase correction factor. This is used to control the model. Thus, when the vehicle speed gradually increases from the low-speed domain, crosses the transition zone, and enters the high-speed domain, from The value can be continuously changed to 1.0 without any jump, thus avoiding sudden changes in steering commands caused by parameter mutations in the control model.

[0101] In the embodiments of this application, the equivalent wheelbase correction coefficient actually used by the control model Continuous transition according to vehicle speed, within the low-speed range transition zone High-speed domain =1. This linear mixture guarantees... The control model is continuous at both boundaries and does not jump due to domain switching.

[0102] Through the embodiments of this application, linear interpolation within the transition zone enables the equivalent wheelbase correction coefficient to transition smoothly and continuously between the identified value in the low-speed domain and the nominal value in the high-speed domain, eliminating the jump in model parameters caused by domain switching, thereby avoiding abrupt changes in steering commands and improving the smoothness and stability of vehicle lateral control.

[0103] Figure 4 A flowchart illustrating a vehicle parameter updating method according to yet another embodiment of this application is shown. Figure 4 As shown, the vehicle parameter update method according to the embodiments of this application may further include steps S410 to S430.

[0104] In step S410, the lateral and longitudinal velocities of the target vehicle are obtained. After setting a lower limit for the longitudinal velocities, the sideslip angle is calculated based on the lateral velocities and the longitudinal velocities after setting the lower limit.

[0105] In the embodiments of this application, lateral velocity refers to the speed of the target vehicle in the direction perpendicular to the longitudinal axis of the vehicle body, typically provided by an inertial measurement unit or a vehicle state estimation algorithm, and is measured in meters per second (m / s). Lateral velocity reflects the speed of the vehicle's lateral movement; for example, a vehicle generates lateral velocity when turning.

[0106] In the embodiments of this application, longitudinal speed refers to the speed of the target vehicle in the direction parallel to the longitudinal axis of the vehicle body, that is, the speed at which the vehicle moves forward or backward, and the unit is meters per second (m / s). Longitudinal speed is usually provided by a vehicle speed sensor or a wheel speed sensor.

[0107] In the embodiments of this application, a lower limit is set for the longitudinal velocity to prevent abnormal amplification of the result or division error during division operations due to an excessively low longitudinal velocity. A positive lower limit value is set for the longitudinal velocity. Specifically, the larger of the actual longitudinal velocity and the lower limit value is taken as the longitudinal velocity used for calculation. For example, if the lower limit value is set to 0.5 m / s, and the actual longitudinal velocity is 0.3 m / s, then 0.5 m / s is used for calculation; if the actual longitudinal velocity is 10 m / s, then 10 m / s is used.

[0108] In the embodiments of this application, the sideslip angle refers to the angle between the actual direction of vehicle travel and the longitudinal axis of the vehicle body, measured in radians (rad). The sideslip angle can be approximated by the ratio of lateral velocity to longitudinal velocity, reflecting whether the vehicle has experienced lateral slippage. For example, the sideslip angle may be larger when the vehicle is turning on a wet or slippery surface.

[0109] In the embodiments of this application, the lateral and longitudinal velocities of the target vehicle are obtained. After setting a lower limit for the longitudinal velocities, the sideslip angle is calculated based on the lateral velocities and the longitudinal velocities after setting the lower limit. The current lateral velocity of the vehicle is obtained. and longitudinal velocity To prevent calculation errors caused by excessively low longitudinal velocity, a positive lower limit is set for the longitudinal velocity. (e.g., 0.5 m / s), take The longitudinal velocity is used for calculation. Based on the lateral velocity... and the longitudinal velocity after setting the lower limit Calculate the sideslip angle .

[0110] In step S420, the sideslip angle activation coefficient is determined based on the relative position of the current vehicle speed with respect to the preset vehicle speed range. The sideslip angle activation coefficient represents the degree to which the sideslip angle participates in the heading state correction.

[0111] In embodiments of this application, the preset vehicle speed range can be a pre-calibrated speed range used to control the degree to which sideslip angle correction is enabled. This range is defined by a lower limit and an upper limit, for example, 3.5 m / s to 4.5 m / s. When the vehicle speed is below the lower limit, sideslip angle correction is completely disabled; when the vehicle speed is above the upper limit, sideslip angle correction is fully enabled; when the vehicle speed is within the range, the correction amount changes smoothly with the vehicle speed.

[0112] In the embodiments of this application, the relative position of the current vehicle speed with respect to the preset vehicle speed range refers to the proportional position of the current vehicle speed within the preset vehicle speed range, which is used to determine the magnitude of the sideslip angle activation coefficient. For example, if the preset vehicle speed range is 3.5 m / s to 4.5 m / s, and the current vehicle speed is 4.0 m / s, then the relative position is (4.0-3.5) / (4.5-3.5)=0.5.

[0113] In embodiments of this application, the sideslip enable factor can be a dimensionless coefficient between 0 and 1, used to characterize the degree to which the sideslip angle participates in heading state correction. When the coefficient is 0, sideslip correction is completely prohibited; when the coefficient is 1, sideslip correction is fully allowed; when the coefficient is between 0 and 1, sideslip correction is scaled proportionally.

[0114] In the embodiments of this application, a sideslip angle activation coefficient is determined based on the relative position of the current vehicle speed with respect to a preset speed range. The sideslip angle activation coefficient characterizes the degree to which the sideslip angle participates in heading state correction. This is based on the vehicle's current speed. (or longitudinal velocity after setting a lower limit) Relative to the preset speed range, determine a sideslip angle activation coefficient between 0 and 1. The preset speed range is defined by a center speed. and half transition band width Defined, its lower bound is The upper limit is .

[0115] In step S430, after scaling the sideslip angle using the sideslip angle activation coefficient, the scaled sideslip angle is used to correct the heading state of the target vehicle.

[0116] In the embodiments of this application, the heading state refers to the current orientation angle of the target vehicle, typically expressed in radians or degrees. The heading state is a crucial state variable in vehicle lateral control, used to describe the vehicle's directional deviation relative to a reference trajectory. Correcting the heading state can improve lateral control accuracy.

[0117] In the embodiments of this application, the scaled sideslip angle refers to the value obtained by multiplying the original sideslip angle by the sideslip angle activation factor. For example, if the original sideslip angle is 0.03 rad and the activation factor is 0.6, then the scaled sideslip angle is 0.018 rad.

[0118] In the embodiments of this application, the sideslip angle is scaled using a sideslip angle activation factor, and the scaled sideslip angle is used to correct the heading state of the target vehicle. The calculated sideslip angle... Multiply by the side slip angle activation factor This yields the actual amount of sideslip angle correction used for the correction. Then Used to correct the heading status of the target vehicle. Specifically, The error is subtracted from the initial heading error state of the predictive controller, and also from the initial reference heading used to construct the nominal heading trajectory, so that the optimized initial state and the nominal trajectory on which the model linearization depends are consistent.

[0119] Through the embodiments of this application, noise amplification is suppressed by setting a lower limit for longitudinal speed, and the participation degree is corrected by smoothly controlling the side slip angle activation coefficient with vehicle speed. At low speeds, the disturbance of lateral speed noise on heading correction is effectively suppressed, and at high speeds, complete side slip angle compensation is restored. At the same time, heading state jumps caused by hard switching are avoided, thereby improving the smoothness and robustness of lateral control.

[0120] In some embodiments, determining the sideslip angle activation coefficient based on the relative position of the current vehicle speed with respect to a preset speed range includes: determining the sideslip angle activation coefficient to zero when the current vehicle speed is less than or equal to the lower limit of the preset speed range, so as to prohibit the scaling sideslip angle from correcting the heading state; determining the sideslip angle activation coefficient to one when the current vehicle speed is greater than or equal to the upper limit of the preset speed range, so as to allow the scaling sideslip angle to correct the heading state; and calculating the sideslip angle activation coefficient based on the relative position of the current vehicle speed within the preset speed range using a smoothing function with zero first derivatives at both ends when the current vehicle speed is within the preset speed range, so that the amount of correction of the heading state by the scaling sideslip angle increases continuously and smoothly as the vehicle speed increases.

[0121] In the embodiments of this application, a smoothing function with zero first derivatives at both ends refers to a smoothing function with zero rate of change (first derivative) at the interval boundary, used to ensure a smooth transition of the side deflection angle activation coefficient at the interval boundary, avoiding abrupt changes. A commonly used function is a cubic smoothing function.

[0122] In the embodiments of this application, the normalized variable refers to the variable that maps the current vehicle speed within a preset speed range to the interval [0,1], denoted as z. When z=0, it corresponds to the lower limit of the interval, and when z=1, it corresponds to the upper limit of the interval.

[0123] In the embodiments of this application, while performing the aforementioned sideslip angle smoothing and silencing, this embodiment also updates the understeer coefficient. and the equivalent wheelbase correction factor after transition band smoothing. The internal model is provided to the lateral predictive controller. These parameters are used to calculate the yaw gain and feedforward gain, thereby generating precise steering control commands. Simultaneously, the system records parameter values, gating status, and the update amount for the current cycle for diagnostic and monitoring purposes. Side slip angle activation factor. It does not participate in the gradient calculation for parameter identification, but instead suppresses the influence of low-speed lateral velocity noise on heading correction after the identified parameters are entered into the kinematic prediction model.

[0124] In embodiments of this application, when the current vehicle speed is less than or equal to the lower limit of a preset vehicle speed range, the sideslip angle activation coefficient is determined to be zero to prevent the scaled sideslip angle from correcting the heading state. When the current vehicle speed... At this time, the vehicle is at an extremely low speed. The noise in the lateral velocity measurement is very large compared to the longitudinal velocity, and the calculated sideslip angle contains a significant amount of noise. Directly using this value for heading correction would introduce unnecessary disturbances. Therefore, the sideslip angle activation factor is... Set it to zero, so that the actual sideslip angle correction amount A value of 0 completely prohibits the correction of heading status by the sideslip angle.

[0125] In embodiments of this application, when the current vehicle speed is greater than or equal to the upper limit of a preset speed range, the sideslip angle activation coefficient is determined to be one, allowing the scaled sideslip angle to correct the heading state. When the current vehicle speed... At this time, the vehicle speed is relatively high, the lateral velocity noise is relatively low, and the calculated sideslip angle value has high reliability. Therefore, the sideslip angle coefficient is activated at this time. Let it be 1, so that the actual sideslip angle correction amount This restores the complete sideslip angle correction and makes full use of sideslip angle information to improve heading accuracy.

[0126] In the embodiments of this application, when the current vehicle speed is within a preset speed range, a smoothing function with zero first derivatives at both ends is used to calculate the sideslip angle activation coefficient based on the relative position of the current vehicle speed within the preset speed range. This ensures that the scaling sideslip angle's correction to the heading state increases continuously and smoothly as the vehicle speed increases. When the current vehicle speed... At that time, the side slip angle activation coefficient The value should vary continuously between 0 and 1, and to ensure smoothness, the first derivative should be zero at the interval boundaries to avoid sudden changes in the correction amount. Therefore, a cubic smoothing function is used to calculate... .

[0127] In the embodiments of this application, the sideslip angle is calculated using the following formula. ;in, The measured lateral velocity is provided by the inertial measurement unit; To set the longitudinal velocity after setting the lower limit, , To measure the longitudinal velocity, This is a preset positive lower limit; This represents the maximum permissible amplitude of the sideslip angle. This formula can calculate the actual sideslip angle of a vehicle while avoiding division by zero and noise amplification, and limit it to a physically reasonable range.

[0128] In the embodiments of this application, the normalized variable and the activation coefficient can be calculated using the following formula. ;in, The variable is a normalized variable (dimensionless), with a value range of [0,1], representing the relative position of the current vehicle speed within the interval. The above formula maps the vehicle speed to the [0,1] interval, providing input for the subsequent smoothing function and ensuring a smooth transition of the sideslip angle activation coefficient at the interval boundaries without abrupt changes, thus avoiding sudden changes in the heading correction. The final sideslip angle correction is... .

[0129] Through the embodiments of this application, by using a cubic smoothing function with zero first derivatives at both ends to calculate the sideslip angle activation coefficient, the sideslip angle correction amount increases continuously and smoothly with the vehicle speed within the preset speed range, without any jumps at the boundary. This effectively suppresses the disturbance of lateral speed noise to the heading correction at low speeds, while avoiding sudden changes in heading state caused by hard switching, thus improving the smoothness and robustness of lateral control.

[0130] Based on the above-described vehicle parameter updating method, embodiments of this application also provide a vehicle parameter updating device. The following will be combined with... Figure 5 The device is described in detail.

[0131] Figure 5 A schematic block diagram of a vehicle parameter updating device according to an embodiment of this application is shown.

[0132] like Figure 5 As shown, the vehicle parameter updating device 500 of this embodiment includes an acquisition module 510, a first determination module 520, a second determination module 530, and an update module 540.

[0133] The acquisition module 510 is used to acquire the target vehicle's current speed, current steering input angle, and measured yaw rate. In one embodiment, the acquisition module 510 can be used to execute step S210 described above, which will not be repeated here.

[0134] The first determining module 520 is used to determine the target parameters from the understeer coefficient and the equivalent wheelbase correction coefficient based on the comparison result between the current vehicle speed and the preset threshold vehicle speed. In one embodiment, the first determining module 520 can be used to execute the step S220 described above, which will not be repeated here.

[0135] The second determining module 530 is used to calculate the theoretical yaw rate based on the understeer coefficient and the equivalent wheelbase correction coefficient in response to the current steering input angle satisfying the excitation condition, and to determine the prediction error based on the measured yaw rate and the theoretical yaw rate. In one embodiment, the second determining module 530 can be used to perform step S230 described above, which will not be repeated here.

[0136] The update module 540 is used to update the target parameters based on the prediction error. In one embodiment, the update module 540 can be used to perform step S240 described above, which will not be repeated here.

[0137] According to embodiments of this application, any multiple modules among the acquisition module 510, the first determination module 520, the second determination module 530, and the update module 540 can be merged into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module. According to embodiments of this application, at least one of the acquisition module 510, the first determination module 520, the second determination module 530, and the update module 540 can be at least partially implemented as a hardware circuit, such as a field-programmable gate array, a programmable logic array, a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit, or implemented by any other reasonable means of integrating or packaging the circuit, or implemented in software, hardware, or firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the acquisition module 510, the first determination module 520, the second determination module 530, and the update module 540 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0138] Figure 6 A schematic block diagram of a vehicle parameter update system according to an embodiment of this application is shown.

[0139] like Figure 6 As shown, the vehicle steering control system according to an embodiment of this application includes: an acquisition unit 610, used to acquire the current vehicle speed, current steering input angle, and measured yaw rate of an autonomous driving vehicle 101 (target vehicle); and a controller 102, communicatively connected to the acquisition unit, configured to: determine target parameters from an understeer coefficient and an equivalent wheelbase correction coefficient based on a comparison result between the current vehicle speed and a preset threshold vehicle speed; calculate a theoretical yaw rate based on the understeer coefficient and the equivalent wheelbase correction coefficient in response to the current steering input angle satisfying the excitation condition, and determine a prediction error based on the measured yaw rate and the theoretical yaw rate; and update the target parameters based on the prediction error.

[0140] Based on the above-described vehicle steering control system, this application also provides an autonomous driving vehicle, including: a vehicle parameter update system according to any of the above embodiments.

[0141] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0143] Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application.

Claims

1. A method for updating vehicle parameters, characterized in that, The method includes: Obtain the target vehicle's current speed, current steering input angle, and measured yaw rate; Based on the comparison between the current vehicle speed and the preset threshold vehicle speed, the target parameters are determined from the understeer coefficient and the equivalent wheelbase correction coefficient. In response to the current steering input angle satisfying the excitation condition, the theoretical yaw rate is calculated based on the understeer coefficient and the equivalent wheelbase correction coefficient, and the prediction error is determined based on the measured yaw rate and the theoretical yaw rate. The target parameters are updated based on the prediction error.

2. The method according to claim 1, characterized in that, The preset threshold speed includes a first threshold speed and a second threshold speed, wherein the first threshold speed is greater than the second threshold speed; the step of determining the target parameter from the understeer coefficient and the equivalent wheelbase correction coefficient based on the comparison result between the current vehicle speed and the preset threshold speed includes: When the current vehicle speed is greater than the first threshold vehicle speed, the understeer coefficient is determined as the target parameter; When the current vehicle speed is less than the second threshold vehicle speed, the equivalent wheelbase correction coefficient is determined as the target parameter.

3. The method according to claim 2, characterized in that, Updating the target parameter based on the prediction error includes: When the target parameter is the understeer coefficient and the absolute value of the prediction error is greater than a preset dead zone threshold, the first parameter update amount is calculated based on the influence of the prediction error and the understeer coefficient on the theoretical yaw rate, and the understeer coefficient is updated based on the first parameter update amount. When the target parameter is the equivalent wheelbase correction coefficient and the absolute value of the prediction error is greater than the preset dead zone threshold, the second parameter update amount is calculated based on the influence of the prediction error and the equivalent wheelbase correction coefficient on the theoretical yaw rate, and the equivalent wheelbase correction coefficient is updated based on the second parameter update amount.

4. The method according to claim 1, characterized in that, The response to the current steering input angle satisfying the excitation condition includes: In response to the absolute value of the current steering input angle being greater than a preset excitation threshold, it is determined that the excitation condition is met.

5. The method according to claim 2, characterized in that, The method further includes: When the current vehicle speed is less than or equal to the first threshold vehicle speed, the understeer coefficient is adjusted to a preset first nominal value in each control cycle according to a preset regression rate, so that the understeer coefficient gradually approaches the first nominal value.

6. The method according to claim 2, characterized in that, The method further includes: When the current vehicle speed is greater than or equal to the second threshold speed and less than or equal to the first threshold speed, the equivalent wheelbase correction coefficient is linearly interpolated based on the relative position of the current vehicle speed between the second threshold speed and the first threshold speed, so that the equivalent wheelbase correction coefficient takes the current value at the second threshold speed and takes the preset second nominal value at the first threshold speed, and is continuous at both ends.

7. The method according to claim 1, characterized in that, The method further includes: The lateral and longitudinal velocities of the target vehicle are obtained. After setting a lower limit for the longitudinal velocities, the sideslip angle is calculated based on the lateral velocities and the longitudinal velocities after setting the lower limit. Based on the relative position of the current vehicle speed with respect to the preset vehicle speed range, a sideslip angle activation coefficient is determined, wherein the sideslip angle activation coefficient represents the degree to which the sideslip angle participates in the heading state correction. After scaling the sideslip angle using the sideslip angle activation coefficient, the scaled sideslip angle is used to correct the heading state of the target vehicle.

8. The method according to claim 7, characterized in that, The step of determining the sideslip angle activation coefficient based on the relative position of the current vehicle speed with respect to a preset vehicle speed range includes: If the current vehicle speed is less than or equal to the lower limit of the preset vehicle speed range, the sideslip angle activation coefficient is determined to be zero to prevent the scaled sideslip angle from correcting the heading status. If the current vehicle speed is greater than or equal to the upper limit of the preset vehicle speed range, the sideslip angle activation coefficient is determined to be one, so as to allow the scaled sideslip angle to correct the heading state. When the current vehicle speed is within the preset vehicle speed range, a smoothing function with zero first derivatives at both ends is used to calculate the sideslip angle activation coefficient based on the relative position of the current vehicle speed within the preset vehicle speed range, so that the correction amount of the scaled sideslip angle to the heading state increases continuously and smoothly as the vehicle speed increases.

9. A vehicle parameter update system, characterized in that, include: The acquisition unit is used to acquire the target vehicle's current speed, current steering input angle, and measured yaw rate. The controller is communicatively connected to the acquisition unit, and the controller is configured to: Based on the comparison between the current vehicle speed and the preset threshold vehicle speed, the target parameters are determined from the understeer coefficient and the equivalent wheelbase correction coefficient. In response to the current steering input angle satisfying the excitation condition, the theoretical yaw rate is calculated based on the understeer coefficient and the equivalent wheelbase correction coefficient, and the prediction error is determined based on the measured yaw rate and the theoretical yaw rate. The target parameters are updated based on the prediction error.

10. An autonomous vehicle, characterized in that, include: The vehicle parameter update system according to claim 9.

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