A parking control method, device, vehicle, storage medium and program product

Abstract

This application discloses a parking control method, device, vehicle, storage medium, and program product, relating to the field of automatic parking technology. The method includes: determining a current target speed based on the current remaining distance to the parking point of the vehicle; the current remaining distance to the parking point is the distance between the current position of the vehicle and the endpoint of its longitudinal movement trajectory; performing closed-loop speed control based on the current target speed and the current actual speed of the vehicle to obtain a current target acceleration; and controlling the longitudinal movement of the vehicle during the parking process based on the current target acceleration. This method provides a way to determine the current target acceleration using a closed-loop speed control method and control the longitudinal movement of the vehicle during the parking process, reducing the complexity, code size, and computational load of the parking control algorithm, making it easier to understand and facilitating the optimization of the parking control algorithm.

Description

Technical Field

[0001] This application relates to the field of automatic parking technology, and more particularly to a parking control method, device, vehicle, storage medium, and program product. Background Technology

[0002] Automatic parking refers to the automatic parking of a car without human intervention. During the parking process, the longitudinal motion control of the vehicle from a standstill until it returns to a standstill is generally achieved through closed-loop acceleration control. By providing a suitable target acceleration value, and controlling the vehicle's actual acceleration to approach the target acceleration, the desired longitudinal motion performance is achieved by adjusting the magnitude of the driving and braking forces.

[0003] However, current parking algorithm methods primarily generate target acceleration values ​​using a fifth-order polynomial to describe the smooth transition of the vehicle from a stationary state to a complete stop during parking. Based on the vehicle's current state information and the state information at the desired parking position, including position, speed, acceleration, and constraints corresponding to speed following or point-acceleration control methods, the coefficients of the fifth-order polynomial are solved to obtain the target acceleration at the current moment. This algorithm for calculating target acceleration by solving the fifth-order polynomial coefficients is extremely complex, not only due to its large code size and computational load, but also because it is difficult to understand and optimize. Summary of the Invention

[0004] This application provides a parking control method, device, vehicle, storage medium, and program product to solve the problems of existing algorithms for determining the target acceleration of a vehicle during its longitudinal movement in the parking control process being complex, having large code size and computational load, and being difficult to understand and optimize.

[0005] In a first aspect, embodiments of this application provide a parking control method, including:

[0006] The current target speed is determined based on the current remaining distance to the destination of the vehicle waiting to park; the current remaining distance to the destination is the distance between the current position of the vehicle waiting to park and the end position of its longitudinal movement trajectory.

[0007] Speed ​​closed-loop control is performed based on the current target speed and the current actual speed of the vehicle waiting to park to obtain the current target acceleration;

[0008] The longitudinal movement of the vehicle to be parked is controlled based on the current target acceleration during the parking process.

[0009] Secondly, embodiments of this application provide a parking control device, including:

[0010] The target speed determination module is used to determine the current target speed based on the current remaining distance to the destination of the vehicle waiting to park; the current remaining distance to the destination is the distance between the current position of the vehicle waiting to park and the end position of the longitudinal movement trajectory.

[0011] The target acceleration determination module is used to perform closed-loop speed control based on the current target speed and the current actual speed of the vehicle waiting to park, and obtain the current target acceleration.

[0012] The parking control module is used to control the longitudinal movement of the vehicle to be parked during the parking process based on the current target acceleration.

[0013] Thirdly, embodiments of this application provide a vehicle, the vehicle comprising:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the parking control method described in any embodiment of this application.

[0017] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the parking control method described in any embodiment of this application.

[0018] Fifthly, embodiments of this application provide a computer program product including a computer program, which, when executed by a processor, implements the parking control method described in any embodiment of this application.

[0019] The technical solution of this application embodiment determines the current target speed based on the current remaining distance to the parking point of the vehicle waiting to park; the current remaining distance to the parking point is the distance between the current position of the vehicle waiting to park and the end position of the longitudinal movement trajectory; speed closed-loop control is performed based on the current target speed and the current actual speed of the vehicle waiting to park to obtain the current target acceleration; and the longitudinal movement of the vehicle waiting to park is controlled based on the current target acceleration during the parking process. This provides a method for determining the current target acceleration using a speed closed-loop control method and controlling the longitudinal movement of the vehicle waiting to park during the parking process. It solves the problems of existing algorithms for determining the target acceleration in the longitudinal movement of a vehicle during parking control being complex, with large code size and computational load, and difficult to understand and optimize. This reduces the complexity of the parking control algorithm, decreases the code size and computational load, is easier to understand, and facilitates the optimization of the parking control algorithm.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart of a parking control method provided in an embodiment of this application;

[0023] Figure 2 A schematic diagram illustrating the principle of a parking control method provided in an embodiment of this application;

[0024] Figure 3 This is a schematic diagram of the structure of a parking control device provided in an embodiment of this application;

[0025] Figure 4 A schematic diagram of the vehicle structure for implementing the parking control method of this application embodiment. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Figure 1 This is a flowchart illustrating a parking control method provided in an embodiment of this application. This embodiment is applicable to situations where the longitudinal movement of a vehicle waiting to be parked is controlled during the parking process. This method can be executed by a parking control device, which can be implemented in hardware and / or software and can be configured in a vehicle. Figure 1 As shown, the method includes:

[0029] S110. Determine the current target speed based on the current remaining distance to the destination of the vehicle waiting to park; the current remaining distance to the destination is the distance between the current position of the vehicle waiting to park and the end position of the longitudinal movement trajectory.

[0030] In this context, the vehicle waiting to park can be considered as the vehicle requiring automatic parking. The current remaining distance to the destination can be understood as the distance between the current position of the vehicle waiting to park and the endpoint of its longitudinal movement trajectory. The longitudinal movement trajectory can be understood as the trajectory used to control the longitudinal movement of the vehicle waiting to park, which can be issued by the intelligent driving control system. It is understandable that during the parking control process of the vehicle waiting to park, one or more longitudinal movements may be executed to successfully bring the vehicle to the desired parking position.

[0031] The current target speed can be understood as the expected speed of the vehicle waiting to park at the current moment. Optionally, if the vehicle mainly moves longitudinally during parking, the current target speed can be the expected longitudinal speed of the vehicle waiting to park at the current moment.

[0032] Specifically, the system obtains the current remaining distance to the parking point for the vehicle at the current moment, and determines the corresponding current target speed based on the current remaining distance. This allows for adjustments to the target speed of the vehicle at the end of the parking trajectory to prevent the vehicle from slowing down too late when approaching the end of the current longitudinal movement trajectory, which could lead to position deviation or sudden braking.

[0033] For example, the remaining distance to the destination of a vehicle waiting to park can be obtained by using an image sensor mounted on the vehicle to collect surrounding environmental information, determining the vehicle's current position and the endpoint of its current longitudinal trajectory, and then calculating the remaining distance. Alternatively, the distance between the vehicle and the endpoint of its current longitudinal trajectory can be measured using a radar sensor or an ultrasonic sensor.

[0034] For example, determining the current target speed based on the remaining distance to the destination can be achieved by using speed planning algorithms such as model prediction, curve planning, objective function optimization, and scenario simulation to establish a mapping table between the remaining distance to the destination and the target speed. The target speed can then be obtained by looking up this mapping table. Alternatively, the speed obtained from looking up the mapping table can be filtered to obtain the target speed. To ensure the safety and comfort of the vehicle during parking, the current speed can be limited to a low range.

[0035] S120. Perform closed-loop speed control based on the current target speed and the current actual speed of the vehicle waiting to park, and obtain the current target acceleration.

[0036] Here, the current actual speed can be understood as the actual speed of the vehicle waiting to park at the current moment. The current target acceleration can be understood as the expected acceleration of the vehicle waiting to park at the current moment. Optionally, the vehicle mainly moves longitudinally during parking, so the actual speed can be the actual longitudinal speed of the vehicle waiting to park at the current moment, and the current target acceleration can be the expected longitudinal acceleration of the vehicle waiting to park at the current moment.

[0037] Specifically, closed-loop speed control is performed based on the current target speed and the current actual speed of the vehicle waiting to park. The closed-loop speed control is based on the feedback principle. For example, the current actual speed is compared with the current target speed to generate a deviation signal to adjust the current actual speed so that the current actual speed approaches the current target speed, thereby determining the current target acceleration.

[0038] For example, the method for speed closed-loop control based on the current target speed and the current actual speed of the vehicle waiting to be parked can be a proportional-integral (PI) control algorithm or controller, or a proportional-integral-derivative (PID) control algorithm or controller. The parameters of the speed closed-loop control algorithm can be set according to the actual parking scenario and requirements, and this application embodiment does not impose any restrictions on this.

[0039] S130. Control the longitudinal movement of the vehicle waiting to be parked during the parking process based on the current target acceleration.

[0040] Specifically, based on the current target acceleration obtained from the speed closed-loop control, the vehicle waiting to be parked is controlled to move along the longitudinal trajectory during the parking process.

[0041] It should be noted that multiple longitudinal movements may be required during parking. For example, the vehicle may shift between forward and reverse gears during parking, adjusting its position by moving longitudinally forward and backward. Each longitudinal movement can be considered an independent speed closed-loop control process. Furthermore, in some parking scenarios, the vehicle needs not only longitudinal movement but also lateral movement. Therefore, the parking control method based on speed closed-loop control for controlling longitudinal movement provided in this embodiment can also be used in conjunction with lateral movement control methods for parking control.

[0042] The technical solution of this application embodiment determines the current target speed based on the current remaining distance to the parking point of the vehicle waiting to park; the current remaining distance to the parking point is the distance between the current position of the vehicle waiting to park and the end position of the longitudinal movement trajectory; speed closed-loop control is performed based on the current target speed and the current actual speed of the vehicle waiting to park to obtain the current target acceleration; and the longitudinal movement of the vehicle waiting to park is controlled based on the current target acceleration during the parking process. This provides a method for determining the current target acceleration using a speed closed-loop control method and controlling the longitudinal movement of the vehicle waiting to park during the parking process, reducing the complexity of the parking control algorithm, reducing code size and computational load, making it easier to understand and facilitating the optimization of the parking control algorithm.

[0043] As an optional embodiment of this application, S120, the step of performing speed closed-loop control based on the current target speed and the current actual speed of the vehicle waiting to park, to obtain the current target acceleration, includes:

[0044] S121. Calculate the current speed error between the current target speed and the current actual speed.

[0045] For example, if the current target speed is set to VTar and the current actual speed is VRef, then the current speed error is error = VTar - VRef.

[0046] S122. Input the current velocity error into the proportional-integral control algorithm to obtain the current target acceleration output by the proportional-integral control algorithm.

[0047] The proportional-integral (PI) control algorithm can be applied using a PI controller. The PI control algorithm combines proportional and integral control methods, including a proportional control term and an integral term. Proportional control directly converts the error into the control output through the proportional control coefficient. This means the output of the control algorithm is proportional to the error; the larger the error, the larger the output of the control algorithm, thus more actively adjusting the vehicle speed. Integral control integrates the error through the integral control coefficient and accumulates the integral result as part of the control output. Integral control can eliminate steady-state errors, allowing the vehicle speed to reach the desired output in steady state. The output of the PI control algorithm is the sum of the proportional and integral control terms.

[0048] The performance of the proportional-integral (PI) control algorithm depends on the selection of the proportional control parameter Kp and the integral control parameter Ki. These two parameters can be optimized according to the characteristics and performance requirements of the parking process, or the appropriate proportional control coefficient and integral control coefficient can be determined through methods such as experimentation, modeling, and simulation. This application does not impose any limitations on these parameters.

[0049] Specifically, the current velocity error is used as the input to the proportional-integral (PI) control algorithm, and the current target acceleration ATar is output through the closed-loop PI control of the PI control algorithm.

[0050] This embodiment is based on a proportional-integral control algorithm. It accurately controls the current target acceleration based on the speed error between the current target speed and the current actual speed of the vehicle waiting to be parked. It uses a simple control method to effectively control the longitudinal speed of the vehicle waiting to be parked during the parking process. Compared with the algorithm that calculates the target acceleration by solving the coefficients of a fifth-order polynomial, it significantly reduces the computational complexity of acceleration while ensuring parking accuracy.

[0051] As an optional embodiment of this application, S122, before inputting the current velocity error into the proportional-integral control algorithm to obtain the current target acceleration output by the proportional-integral control algorithm, the method further includes:

[0052] S210. Optimize the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment.

[0053] The target acceleration generated in the previous moment can be understood as the target acceleration generated by the speed closed-loop control in the longitudinal motion control during parking, based on the previous moment. The control parameters of the proportional-integral (PI) control algorithm can be understood as parameters that affect the control performance of the PI control algorithm, and may include, for example, dead zone, integral term, proportional control coefficient, and integral control coefficient.

[0054] Specifically, considering the potential problems and needs in controlling the current target acceleration based on the proportional-integral (PI) control algorithm, the control parameters of the PI control algorithm are optimized based on at least one of the remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment, thereby improving the accuracy of the PI control algorithm in controlling the current target acceleration.

[0055] In an optional embodiment, S210, optimizing the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment, includes:

[0056] S211. Obtain the dead zone value corresponding to the current remaining distance to the point, and set the dead zone value in the proportional-integral control algorithm to adjust the current speed error.

[0057] The dead zone value can be understood as a threshold set in the speed closed-loop control algorithm. When the absolute value of the speed error is less than this dead zone value, the target acceleration will not be adjusted. This design can reduce frequent control actions caused by small speed errors, thereby avoiding over-control and system oscillation, and improving the stability and response performance of parking control. The size of the dead zone value directly affects the performance of the parking control system. Too small a dead zone value may cause the parking control system to be overly sensitive to small errors, while too large a dead zone value may cause the parking control system to respond slowly, or even fail to eliminate steady-state errors.

[0058] Specifically, the dead zone value corresponding to the remaining distance to the point is obtained, and the dead zone value is set in the proportional-integral control algorithm. The current speed error within the dead zone range is adjusted to zero, and no integral or derivative calculations are performed. This helps to reduce control actions caused by small errors and avoids oscillations of the parking control system near the set point.

[0059] For example, the dead zone value corresponding to the remaining distance to the destination can be obtained by determining a current remaining distance to the destination-dead zone value mapping table according to the dead zone value setting principle, and then finding the dead zone value corresponding to the remaining distance to the destination by looking up the current remaining distance to the destination mapping table. The principle for determining the dead zone value corresponding to the remaining distance to the destination can be that when the vehicle waiting to park is far from the end point of the current longitudinal movement trajectory, the dead zone value can be set to a larger value to make the control less sensitive. Conversely, when the vehicle waiting to park is close to the end point of the current longitudinal movement trajectory, the dead zone value can be set to a smaller value to ensure arrival accuracy.

[0060] In an optional embodiment, S210, optimizing the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment, includes:

[0061] S212. If the absolute value of the current speed error is greater than the error threshold, then the integral term in the proportional-integral control algorithm is turned off.

[0062] The error threshold can be understood as a threshold used to determine the error.

[0063] Specifically, if the absolute value of the current speed error, abs(VTar-VRef), is greater than the error threshold, the integral term in the proportional-integral control algorithm is turned off. This is equivalent to controlling the current speed error based on the proportional control algorithm and outputting the current target acceleration. This can prevent speed control overshoot caused by an excessively large integral term, maintain stable vehicle speed during parking, and improve parking smoothness.

[0064] In an optional embodiment, S210, optimizing the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment, includes:

[0065] S213. If the target acceleration generated by the proportional-integral control algorithm at the previous moment is greater than the upper limit threshold of acceleration, then the integral term of the proportional-integral control algorithm is accumulated with negative values ​​of the current velocity error, and positive values ​​of the current velocity error are not accumulated.

[0066] S214. If the target acceleration generated by the proportional-integral control algorithm at the previous moment is less than the lower limit threshold of acceleration, then the integral term of the proportional-integral control algorithm is accumulated with a positive value of the current velocity error, and the negative value of the current velocity error is not accumulated.

[0067] Specifically, in the process of controlling the target acceleration using the proportional-integral (PI) control algorithm, it is determined whether the target acceleration generated in the previous moment exceeds the acceleration range, which is the numerical range between the upper acceleration threshold AMax and the lower acceleration threshold AMin. If the target acceleration generated by the PI control algorithm in the previous moment ATar(K-1) is greater than the upper acceleration threshold AMax, then the integral term of the PI control algorithm accumulates negative values ​​of the current speed error, but does not accumulate positive values ​​of the current speed error. If the target acceleration generated by the PI control algorithm in the previous moment is less than the lower acceleration threshold, then the integral term of the PI control algorithm accumulates positive values ​​of the current speed error, but does not accumulate negative values ​​of the current speed error. This avoids the target acceleration value from remaining in the saturation region for a long time, thereby preventing the problem of long-term vehicle speed overshoot caused by integral saturation.

[0068] As an optional embodiment of this application, S210, optimizing the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment, includes:

[0069] S215. Obtain the proportional control coefficient corresponding to the current speed error; if the current remaining distance to the point is less than the distance threshold, correct the proportional control coefficient according to the correction coefficient corresponding to the positive or negative result of the current speed error, and update the proportional control parameters of the proportional integral control algorithm according to the proportional control coefficient.

[0070] The proportional control coefficient refers to the proportional gain Kp in proportional control. The role of the proportional control coefficient is to quickly respond to changes in the parking control system, proportionally reflecting changes in the input signal, thereby adjusting the output of the proportional-integral control algorithm to reduce deviation. When the proportional gain is too large, the parking control response is rapid, but overshoot and oscillation are prone to occur; when the proportional gain is too small, the parking control response is slow, the control effect is poor, and it may not be able to eliminate steady-state errors. The correction coefficient can be understood as a coefficient that corrects the proportional control coefficient.

[0071] Specifically, the proportional control coefficient is obtained based on the current speed error to reduce speed fluctuations that may be caused by the proportional control term when the speed error in the speed closed-loop control is small. Furthermore, if the current remaining distance to the destination is less than the distance threshold, the corresponding correction coefficient is obtained based on the sign of the current speed error, and the proportional control coefficient is corrected accordingly. The proportional control parameters of the proportional-integral control algorithm are then updated based on the proportional control coefficient, thereby improving the destination accuracy at the end of the trajectory during parking.

[0072] For example, the proportional control coefficient corresponding to the current speed error can be obtained by establishing a mapping table between the current speed error and the proportional control coefficient, and then querying the mapping table to obtain the proportional control coefficient corresponding to the current speed error. Similarly, the correction coefficient can be obtained based on the sign of the current speed error by establishing a mapping table between the sign of the current speed error and the correction coefficient, and then querying the mapping table to obtain the correction coefficient for the current speed error.

[0073] In this embodiment, the proportional control coefficient of the proportional-integral control algorithm is adjusted according to the current remaining distance to the destination, the current speed difference, and the current actual speed. This can improve the accuracy of the destination at the end of the trajectory during parking and reduce speed fluctuations.

[0074] In addition, the integral coefficient Ki in this embodiment can be directly calibrated.

[0075] As an optional embodiment of this application, it also includes:

[0076] When the vehicle waiting to park is in either the first state or the second state, the current target acceleration is initialized to the current actual acceleration; wherein, the first state is when the current actual speed of the vehicle waiting to park is zero, and the second state is when the current actual speed of the vehicle waiting to park is not zero and the current remaining distance to the destination is zero.

[0077] The first state is when the actual speed of the vehicle waiting to park is zero, which is the state before the speed closed-loop control begins. The second state is when the actual speed of the vehicle waiting to park is not zero and the remaining distance to the destination is zero, which is the state after the speed closed-loop control ends.

[0078] Specifically, before and after the speed closed-loop control of the vehicle waiting to park ends, the current target acceleration is initialized to the current actual acceleration, making the change of the current target acceleration smoother and improving the stability of parking control.

[0079] As an optional embodiment of this application, before S130, controlling the longitudinal movement of the vehicle to be parked during the parking process based on the current target acceleration, the method further includes:

[0080] The current target acceleration is constrained according to acceleration constraints, which include a first acceleration constraint range and a first jerk constraint range.

[0081] Acceleration constraints can be understood as conditions that limit and constrain acceleration. These constraints include the first acceleration constraint range and the first jerk constraint range. Acceleration is a physical quantity describing the rate of change of velocity, and jerk (Jerk) is a physical quantity describing the rate of change of acceleration. Its SI unit is meters per cubic second (m·s⁻³ or m / s²). 3 The first acceleration constraint range and the first jerk constraint range can be set according to actual needs, and the embodiments of this application do not impose any restrictions on them.

[0082] Specifically, the current target acceleration is adjusted according to the first acceleration constraint range and the first jerk constraint range to prevent the target acceleration or the rate of change of acceleration from exceeding the limits of the parking control system.

[0083] For example, if the current target acceleration exceeds the first acceleration constraint range, the current target acceleration is adjusted to the upper limit threshold of the first acceleration constraint range. If the current target acceleration exceeds the first jerk constraint range, the jerk between the current target acceleration and the target acceleration at the previous moment is determined, the jerk is adjusted to the upper limit threshold of the first acceleration constraint range, and the current target acceleration is adjusted according to the constrained jerk.

[0084] As an optional embodiment of this application, S110, determining the current target speed based on the current remaining distance to the parking spot of the vehicle waiting to park, includes:

[0085] S111. Obtain the current calibrated speed corresponding to the current remaining distance to the point.

[0086] The current calibration speed can be understood as the speed at the current moment, calibrated based on the remaining distance to the point under the calibration environment.

[0087] Specifically, the way to obtain the current calibration speed corresponding to the current remaining distance to the point is to use a mapping table between the current remaining distance to the point and the current calibration speed. The current calibration speed corresponding to the current remaining distance to the point can be obtained by looking up the mapping table.

[0088] S112. Obtain the target speed threshold, and constrain the current calibration speed according to the target speed threshold to obtain the current optimized calibration speed.

[0089] The target speed threshold can be understood as the maximum speed at which a vehicle is allowed to move while waiting to park. This threshold can be determined by the intelligent driving control system based on the overall state of the vehicle and its surrounding environment, and then sent to the parking control system. Alternatively, it can be obtained by the parking control system further processing the speed threshold sent by the intelligent driving control system. It's important to note that the target speed threshold is not a fixed value; it's a changing curve during the parking process. Generally, the closer the vehicle is to the end of its current longitudinal trajectory, the smaller the target speed threshold.

[0090] Specifically, the current calibrated speed is determined under calibrated conditions. However, during the parking process, the vehicle's speed needs to be controlled based on vehicle status and surrounding environmental data. Therefore, the intelligent driving control system needs to comprehensively judge the vehicle status and surrounding environmental data to determine the target speed threshold and send the target speed threshold to the parking control system. The parking control system then constrains the current calibrated speed based on the target speed threshold to obtain the current optimized calibrated speed, ensuring that the constrained current calibrated speed is within a safe range.

[0091] In one optional embodiment, obtaining the target velocity threshold includes:

[0092] The target velocity threshold is obtained by constraining the received initial velocity threshold according to the velocity threshold constraint conditions, wherein the velocity threshold constraint conditions include a second acceleration constraint range and a second jerk constraint range.

[0093] The velocity threshold constraint can be understood as a condition that constrains the target velocity threshold. The velocity threshold constraint includes a second acceleration constraint range and a second jerk constraint range. The second acceleration constraint range and the second jerk constraint range can be set according to actual needs; this application embodiment does not impose any restrictions on them.

[0094] Specifically, the target speed threshold is adjusted according to the second acceleration constraint range and the second jerk constraint range to prevent the change trend of the target speed threshold from exceeding the limit of the parking system.

[0095] For example, the target speed threshold change rate at the current moment is calculated based on the target speed threshold at the current moment and the target speed threshold at the previous moment. If the target speed threshold change rate at the current moment exceeds the second acceleration constraint range, the target speed threshold at the current moment will be adjusted. If the difference between the target speed threshold change rate at the current moment and the target speed threshold change rate at the previous moment exceeds the second acceleration constraint range, the target speed threshold at the current moment will be adjusted.

[0096] S113. Filter the current optimized calibration speed to obtain the current target speed.

[0097] Specifically, the current optimized calibration speed is filtered to obtain the current target speed, making the changes in the current target speed at continuous times smoother and improving the stability of parking.

[0098] This embodiment constrains the current calibrated speed corresponding to the current remaining distance to the point by using a target speed threshold and performs filtering processing, thereby improving the smoothness and safety of the parking process.

[0099] As an optional embodiment of this application, it also includes:

[0100] S310. When the vehicle waiting to park is in a first state or a second state, the current target speed is initialized to the target speed threshold; wherein, the first state is when the current actual speed of the vehicle waiting to park is zero, and the second state is when the current actual speed of the vehicle waiting to park is not zero and the current remaining distance to the destination is zero.

[0101] The first state is when the actual speed of the vehicle waiting to park is zero, which is before the speed closed-loop control begins. The second state is when the actual speed of the vehicle waiting to park is not zero and the remaining distance to the destination is zero, which is after the speed closed-loop control ends.

[0102] Specifically, before and after the speed closed-loop control of the vehicle waiting to park ends, the current target speed is initialized to the target speed threshold to prevent the current target speed from exceeding the limit of the parking function system.

[0103] As an optional embodiment of this application, it also includes:

[0104] When the vehicle waiting to park is in a preset operating condition, the target acceleration of the previous moment is controlled in an open loop according to the preset control parameters corresponding to the preset operating condition to obtain the current target acceleration.

[0105] Among them, the preset control parameters can be understood as parameters for controlling the target acceleration; the preset control parameters can be an accumulated control quantity or a slope value;

[0106] Specifically, when the vehicle waiting to park is in preset conditions such as starting, emergency braking, comfort braking, normal stopping, early stopping, or collision avoidance, the target acceleration of the previous moment is controlled in an open loop according to preset control parameters to obtain the current target acceleration, thereby meeting the special requirements of intelligent driving for parking functions.

[0107] In a specific example Figure 2 This is a schematic diagram illustrating the principle of a parking control method provided in an embodiment of this application, as shown below. Figure 2 As shown, within each longitudinal motion control cycle of the parking control method, the longitudinal motion control mainly includes the following steps:

[0108] (1) Determine the current target speed. Obtain the initial speed threshold issued by the intelligent driving system, and constrain the initial speed threshold according to the speed threshold constraint conditions to obtain the target speed threshold; query the corresponding current calibration speed according to the current remaining distance to the parking point of the vehicle waiting to park, and constrain the current calibration speed according to the target speed threshold to obtain the current optimized calibration speed. Filter the current optimized calibration speed to obtain the current target speed. In addition, when the vehicle waiting to park is in the first state or the second state, initialize the current target speed to the target speed threshold; wherein, the first state is when the current actual speed of the vehicle waiting to park is zero, that is, before the speed closed-loop control starts, and the second state is when the current actual speed of the vehicle waiting to park is not zero and the current remaining distance to the parking point is zero, that is, after the speed closed-loop control ends. The initialization operation of the current target speed makes the change of the current target speed smoother and improves the stability of parking control. (2) Determine the current target acceleration. The dead zone value is obtained by querying the remaining distance to the target point. The current speed error is calculated based on the current target speed and the current actual speed. The current speed error is adjusted based on the dead zone value, and the adjusted current speed error is input into the proportional-integral (PI) control algorithm (or PI controller) to obtain the current acceleration. The integral term of the PI control algorithm can be enabled based on the current speed error. Specifically, the proportional control coefficient of the PI control algorithm can be corrected based on the current speed error and the remaining distance to the target point. The final determined current acceleration is constrained according to acceleration constraints to obtain the current target acceleration.

[0109] Furthermore, when the vehicle waiting to park is in either the first or second state, the current target acceleration is initialized to the current actual acceleration. The first state is when the vehicle's current actual speed is zero, i.e., before speed closed-loop control begins. The second state is when the vehicle's current actual speed is not zero and the remaining distance to the parking spot is zero, i.e., after speed closed-loop control ends. This initialization of the current target acceleration makes its changes smoother, improving the stability of parking control.

[0110] (3) Based on the current target acceleration, control the vehicle waiting to be parked to move along the longitudinal trajectory during the parking process.

[0111] Figure 3 This is a schematic diagram of a parking control device provided in an embodiment of this application. Figure 3 As shown, the device includes: a target speed determination module 310, a target acceleration determination module 320, and a parking control module 330; wherein,

[0112] The target speed determination module 310 is used to determine the current target speed based on the current remaining distance to the destination of the vehicle waiting to park; the current remaining distance to the destination is the distance between the current position of the vehicle waiting to park and the end position of the longitudinal movement trajectory.

[0113] The target acceleration determination module 320 is used to perform closed-loop speed control based on the current target speed and the current actual speed of the vehicle waiting to park, and obtain the current target acceleration.

[0114] The parking control module 330 is used to control the longitudinal movement of the vehicle to be parked during the parking process based on the current target acceleration.

[0115] The technical solution of this application embodiment determines the current target speed based on the current remaining distance to the parking point of the vehicle waiting to park; the current remaining distance to the parking point is the distance between the current position of the vehicle waiting to park and the end position of the longitudinal movement trajectory; speed closed-loop control is performed based on the current target speed and the current actual speed of the vehicle waiting to park to obtain the current target acceleration; and the longitudinal movement of the vehicle waiting to park is controlled based on the current target acceleration during the parking process. This provides a method for determining the current target acceleration using a speed closed-loop control method and controlling the longitudinal movement of the vehicle waiting to park during the parking process, reducing the complexity of the parking control algorithm, reducing code size and computational load, making it easier to understand and facilitating the optimization of the parking control algorithm.

[0116] Optionally, the target acceleration determination module 320 includes:

[0117] A speed error calculation unit is used to calculate the current speed error between the current target speed and the current actual speed;

[0118] An acceleration control unit is used to input the current velocity error into a proportional-integral (PI) control algorithm to obtain the current target acceleration output by the PI control algorithm.

[0119] Optional, also includes:

[0120] The control parameter optimization module is used to optimize the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current speed error, and the target acceleration generated at the previous moment, before inputting the current speed error into the proportional-integral control algorithm to obtain the current target acceleration output by the proportional-integral control algorithm.

[0121] Optionally, the control parameter optimization module includes:

[0122] The dead zone setting unit is used to obtain the dead zone value corresponding to the current remaining distance to the point, and set the dead zone value in the proportional-integral control algorithm to adjust the current speed error.

[0123] Optionally, the control parameter optimization module includes:

[0124] The integral term shutdown unit is used to shut down the integral term in the proportional-integral control algorithm if the absolute value of the current speed error is greater than the error threshold.

[0125] Optionally, the control parameter optimization module includes:

[0126] The first integral term optimization unit is used to accumulate negative values ​​of the current velocity error in the integral term of the proportional-integral control algorithm if the target acceleration generated by the proportional-integral control algorithm at the previous moment is greater than the upper limit threshold of acceleration, and not to accumulate positive values ​​of the current velocity error.

[0127] The second integral term optimization unit is used to accumulate positive values ​​of the current velocity error in the integral term of the proportional-integral control algorithm if the target acceleration generated by the proportional-integral control algorithm at the previous moment is less than the lower limit threshold of acceleration, and not to accumulate negative values ​​of the current velocity error.

[0128] Optionally, the control parameter optimization module includes:

[0129] A proportional control coefficient acquisition unit is used to acquire the proportional control coefficient corresponding to the current speed error;

[0130] The proportional control parameter update unit is used to correct the proportional control coefficient according to the correction coefficient corresponding to the positive or negative result of the current speed error if the current remaining distance to the point is less than the distance threshold, and update the proportional control parameter of the proportional integral control algorithm according to the proportional control coefficient.

[0131] Optional, also includes:

[0132] An acceleration initialization module is used to initialize the current target acceleration to the current actual acceleration when the vehicle waiting to park is in a first state or a second state; wherein, the first state is when the current actual speed of the vehicle waiting to park is zero, and the second state is when the current actual speed of the vehicle waiting to park is not zero and the current remaining distance to the destination is zero.

[0133] Optional, also includes:

[0134] An acceleration constraint module is used to constrain the current target acceleration according to acceleration constraint conditions, the acceleration constraint conditions including a first acceleration constraint range and a first jerk constraint range.

[0135] Optionally, the target speed determination module 310 includes:

[0136] A calibration speed acquisition unit is used to acquire the current calibration speed corresponding to the current remaining distance to the point;

[0137] The calibration speed optimization unit is used to obtain a target speed threshold and constrain the current calibration speed according to the target speed threshold to obtain the current optimized calibration speed.

[0138] The filtering unit is used to filter the current optimized calibration speed to obtain the current target speed.

[0139] Optional, also includes:

[0140] A speed initialization module is used to initialize the current target speed to the target speed threshold when the vehicle waiting to park is in a first state or a second state; wherein, the first state is when the current actual speed of the vehicle waiting to park is zero, and the second state is when the current actual speed of the vehicle waiting to park is not zero and the current remaining distance to the destination is zero.

[0141] Optional, also includes:

[0142] The maximum speed constraint module is used to constrain the received initial speed threshold according to the speed threshold constraint conditions before controlling the longitudinal movement of the vehicle to be parked during the parking process according to the current target acceleration, so as to obtain the target speed threshold. The speed threshold constraint conditions include a second acceleration constraint range and a second jerk constraint range.

[0143] Optional, also includes:

[0144] An open-loop control module is used to perform open-loop speed control on the target acceleration of the previous moment according to the preset control parameters corresponding to the preset operating condition when the vehicle waiting to park is in a preset operating condition, so as to obtain the current target acceleration.

[0145] The parking control device provided in this application embodiment can execute the parking control method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the execution method.

[0146] Figure 4 A schematic diagram of the structure of a vehicle 10 that can be used to implement embodiments of this application is shown. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of this application described and / or claimed herein.

[0147] like Figure 4As shown, vehicle 10 includes at least one processor 11 and a memory, such as read-only memory (ROM) 12 and random access memory (RAM) 13, communicatively connected to at least one processor 11. The memory stores computer programs executable by at least one processor. Processor 11 can perform various appropriate actions and processes based on the computer program stored in ROM 12 or loaded from storage unit 18 into RAM 13. RAM 13 can also store various programs and data required for the operation of vehicle 10. Processor 11, ROM 12, and RAM 13 are interconnected via bus 14. Input / output (I / O) interface 15 is also connected to bus 14.

[0148] Multiple components in vehicle 10 are connected to I / O interface 15, including: input units 16, such as a steering wheel, braking device, and sensors; output units 17, such as various types of displays and speakers; storage units 18, such as disks and optical discs; and communication units 19, such as network cards, modems, and wireless transceivers. Communication unit 19 allows vehicle 10 to exchange information / data with other devices via computer networks such as the Internet and / or various telecommunications networks.

[0149] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as parking control methods.

[0150] In some embodiments, the parking control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on vehicle 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the parking control method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the parking control method by any other suitable means (e.g., by means of firmware).

[0151] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0152] In some embodiments, the parking control method may be implemented as a computer program, which is implicitly included in a computer program product. When executed by a processor, the computer program implements the parking control method of this application. The computer program product can be understood as a software product that primarily implements its solution through a computer program. The computer program used to implement the method of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0153] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0154] To provide interaction with the user, the systems and technologies described herein can be implemented in a vehicle having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a sound acquisition device (e.g., a microphone) and a touch display screen through which the user can provide input to the vehicle. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0155] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0156] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0157] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0158] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A parking control method, characterized in that, include: The current target speed is determined based on the remaining distance to the destination of the vehicle waiting to park; The current remaining distance to the destination is the distance between the current position of the vehicle waiting to park and the end position of its longitudinal movement trajectory; Speed ​​closed-loop control is performed based on the current target speed and the current actual speed of the vehicle waiting to park to obtain the current target acceleration; The longitudinal movement of the vehicle to be parked is controlled based on the current target acceleration during the parking process.

2. The method according to claim 1, characterized in that, The step of performing closed-loop speed control based on the current target speed and the current actual speed of the vehicle waiting to park, to obtain the current target acceleration, includes: Calculate the current speed error between the current target speed and the current actual speed; The current velocity error is input into the proportional-integral control algorithm to obtain the current target acceleration output by the proportional-integral control algorithm.

3. The method according to claim 2, characterized in that, Before inputting the current velocity error into the proportional-integral (PI) control algorithm to obtain the current target acceleration output by the PI control algorithm, the method further includes: The control parameters of the proportional-integral control algorithm are optimized based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment.

4. The method according to claim 3, characterized in that, The optimization of the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment includes: Obtain the dead zone value corresponding to the current remaining distance to the point, and set the dead zone value in the proportional-integral control algorithm to adjust the current speed error.

5. The method according to claim 3, characterized in that, The optimization of the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment includes: If the absolute value of the current speed error is greater than the error threshold, then the integral term in the proportional-integral control algorithm is turned off.

6. The method according to claim 3, characterized in that, The optimization of the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment includes: If the target acceleration generated by the proportional-integral control algorithm in the previous moment is greater than the upper limit threshold of acceleration, then the integral term of the proportional-integral control algorithm is accumulated with negative values ​​of the current velocity error, and positive values ​​of the current velocity error are not accumulated. If the target acceleration generated by the proportional-integral control algorithm in the previous moment is less than the lower limit threshold of acceleration, then the integral term of the proportional-integral control algorithm is accumulated with a positive value of the current velocity error, and the negative value of the current velocity error is not accumulated.

7. The method according to claim 3, characterized in that, The optimization of the control parameters of the proportional-integral control algorithm based on at least one of the current remaining distance to the point, the current velocity error, and the target acceleration generated at the previous moment includes: Obtain the proportional control coefficient corresponding to the current speed error; If the current remaining distance to the point is less than the distance threshold, the proportional control coefficient is corrected according to the correction coefficient corresponding to the positive or negative result of the current speed error, and the proportional control parameters of the proportional-integral control algorithm are updated according to the proportional control coefficient.

8. The method according to claim 3, characterized in that, Also includes: When the vehicle waiting to park is in the first state or the second state, the current target acceleration is initialized to the current actual acceleration; The first state is when the current actual speed of the vehicle waiting to park is zero, and the second state is when the current actual speed of the vehicle waiting to park is not zero and the current remaining distance to the destination is zero.

9. The method according to claim 1 or 8, characterized in that, Before controlling the longitudinal movement of the vehicle to be parked during the parking process based on the current target acceleration, the method further includes: The current target acceleration is constrained according to acceleration constraints, which include a first acceleration constraint range and a first jerk constraint range.

10. The method according to claim 1, characterized in that, Determining the current target speed based on the remaining distance to the parking spot includes: Obtain the current calibrated speed corresponding to the current remaining distance to the point; Obtain the target speed threshold, and constrain the current calibration speed according to the target speed threshold to obtain the current optimized calibration speed; The current optimized calibration speed is filtered to obtain the current target speed.

11. The method according to claim 10, characterized in that, Also includes: When the vehicle waiting to park is in the first state or the second state, the current target speed is initialized to the target speed threshold. The first state is when the current actual speed of the vehicle waiting to park is zero, and the second state is when the current actual speed of the vehicle waiting to park is not zero and the current remaining distance to the destination is zero.

12. The method according to claim 10, characterized in that, The acquisition of the target speed threshold includes: The target velocity threshold is obtained by constraining the received initial velocity threshold according to the velocity threshold constraint conditions, wherein the velocity threshold constraint conditions include a second acceleration constraint range and a second jerk constraint range.

13. The method according to claim 1, characterized in that, Also includes: When the vehicle waiting to park is in a preset operating condition, the target acceleration of the previous moment is controlled in an open loop according to the preset control parameters corresponding to the preset operating condition to obtain the current target acceleration.

14. A parking control device, characterized in that, include: The target speed determination module is used to determine the current target speed based on the current remaining distance to the parking spot of the vehicle waiting to park. The current remaining distance to the destination is the distance between the current position of the vehicle waiting to park and the end position of its longitudinal movement trajectory; The target acceleration determination module is used to perform closed-loop speed control based on the current target speed and the current actual speed of the vehicle waiting to park, and obtain the current target acceleration. The parking control module is used to control the longitudinal movement of the vehicle to be parked during the parking process based on the current target acceleration.

15. A vehicle, characterized in that, The vehicles include: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the parking control method according to any one of claims 1-13.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the parking control method according to any one of claims 1-13.

17. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the parking control method according to any one of claims 1-13.

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