Parking control method, device, vehicle, storage medium and program product

Abstract

The present disclosure relates to a parking control method, device, vehicle, storage medium and program product, which belongs to the field of automatic driving technology. The method can determine the control parameters in the automatic parking mode according to the historical driving data of the vehicle. In this way, the vehicle can be controlled to park automatically according to the automatic parking mode. With the above scheme, the control parameters in the automatic parking mode can be determined according to the historical driving data of the vehicle, so that the automatic parking control strategy can match the historical driving behavior of the vehicle. In this way, it is possible to provide users with personalized automatic parking services that fit the user's driving habits.

Description

Technical Field

[0001] The present disclosure relates to the field of autonomous driving technology, and in particular to a parking control method, device, vehicle, storage medium, and program product. Background Art

[0002] When using the automatic parking function, the vehicle's sensing device can identify the parking space, and the user can select the target parking space in the interactive interface and click to send the parking start command. In this way, the vehicle can plan the parking route and realize automatic parking through the steering system and motion system. In relevant scenarios, the automatic parking speed may be too fast or too slow, causing discomfort to the user. Summary of the invention

[0003] To overcome the problems existing in the related art, the present disclosure provides a parking control method, device, vehicle, storage medium and program product.

[0004] According to a first aspect of an embodiment of the present disclosure, there is provided a parking control method, comprising:

[0005] Determining control parameters in an automatic parking mode based on historical driving data of the vehicle;

[0006] The vehicle is controlled to perform automatic parking according to the automatic parking mode.

[0007] Optionally, determining the control parameters in the automatic parking mode according to the historical driving data of the vehicle includes:

[0008] determining the first type of control parameters in the automatic parking mode according to the first type of data in the historical driving data;

[0009] The first type includes one or more of a velocity type, an acceleration type, and a jerk type.

[0010] Optionally, determining the first type of control parameters in the automatic parking mode according to the first type of data in the historical driving data includes:

[0011] determining an adjustment factor for a control parameter of the first type;

[0012] Determine an upper limit value and a lower limit value of the first type of data according to the first type of data in the historical driving data, and obtain a first upper limit value and a first lower limit value respectively;

[0013] The first type of control parameter in the automatic parking mode is determined according to the adjustment coefficient, the first upper limit value, and the first lower limit value.

[0014] Optionally, determining the adjustment coefficient of the first type of control parameter includes:

[0015] Determining a first adjustment coefficient of the control parameter according to an operation interval duration in the historical driving data, wherein the operation interval duration includes an interval duration between a brake pedal step and an accelerator pedal step that are adjacent in time;

[0016] determining a second adjustment coefficient of the control parameter according to acceleration data of the vehicle during acceleration control in the historical driving data;

[0017] determining a third adjustment coefficient of the control parameter according to acceleration data of the vehicle during deceleration control in the historical driving data;

[0018] The adjustment coefficient of the control parameter includes one or more of the first adjustment coefficient, the second adjustment coefficient, and the third adjustment coefficient.

[0019] Optionally, the adjustment coefficient includes the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient, and the determining the adjustment coefficient of the first type of control parameter includes:

[0020] Determining a weight of the first adjustment coefficient to obtain a first weight;

[0021] Determining a weight of the second adjustment coefficient to obtain a second weight;

[0022] Determining a weight of the third adjustment coefficient to obtain a third weight;

[0023] According to the first weight, the second weight and the third weight, the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient are weighted and summed to obtain the adjustment coefficient of the control parameter.

[0024] Optionally, determining the weight of the first adjustment coefficient to obtain a first weight, determining the weight of the second adjustment coefficient to obtain a second weight, and determining the weight of the third adjustment coefficient to obtain a third weight includes:

[0025] In response to a weight setting operation, a first weight of the first adjustment coefficient, a second weight of the second adjustment coefficient, and a third weight of the third adjustment coefficient are determined, and the sum of the first weight, the second weight, and the third weight is 1.

[0026] Optionally, determining the first adjustment coefficient of the control parameter according to the operation interval duration in the historical driving data includes:

[0027] Determine a first value of operation interval durations according to the historical driving data;

[0028] Determine a reference value of the operation interval duration to obtain a first reference value;

[0029] Determine the number of operation intervals whose duration is less than the first reference value, and obtain a second value;

[0030] determining a ratio of the second value to the first value to obtain a first ratio;

[0031] The first adjustment coefficient is determined according to the first ratio.

[0032] Optionally, determining the first adjustment coefficient according to the first ratio includes:

[0033] Calculate the product of the first ratio and 2;

[0034] The difference between the product and 1 is calculated to obtain the first adjustment coefficient.

[0035] Optionally, determining the second adjustment coefficient of the control parameter according to the acceleration data of the vehicle during acceleration control in the historical driving data includes:

[0036] Determining a third acceleration value according to the acceleration data of the vehicle during acceleration control in the historical driving data;

[0037] Determine a reference value of the third acceleration to obtain a second reference value;

[0038] Determine the number of accelerations of the third value whose acceleration values ​​are greater than the second reference value, to obtain a fourth value;

[0039] determining a ratio of the fourth value to the third value to obtain a second ratio;

[0040] The second adjustment coefficient is determined according to the second ratio.

[0041] Optionally, determining the third adjustment coefficient of the control parameter according to the acceleration data of the vehicle during deceleration control in the historical driving data includes:

[0042] determining a fifth acceleration value according to the acceleration data of the vehicle during deceleration control in the historical driving data;

[0043] Determining a reference value of the fifth acceleration to obtain a third reference value;

[0044] Determine the number of accelerations whose acceleration values ​​are greater than the third reference value among the fifth value accelerations to obtain a sixth value;

[0045] determining a ratio of the sixth value to the fifth value to obtain a third ratio;

[0046] The third adjustment coefficient is determined according to the third ratio.

[0047] Optionally, determining an upper limit value and a lower limit value of the data of the first type in the historical driving data to obtain a first upper limit value and a first lower limit value, respectively, includes:

[0048] Determining, based on the first type of data in the historical driving data, an average value and a standard deviation of the first type of data;

[0049] Determine an upper limit value and a lower limit value corresponding to the first type of data of the vehicle to obtain a second upper limit value and a second lower limit value respectively;

[0050] Determine a sum of the mean value and the standard deviation, and a difference between the mean value and the standard deviation to obtain a first difference;

[0051] determining the smaller one of the sum value and the second upper limit value as the first upper limit value;

[0052] The larger one of the first difference value and the second lower limit value is determined as the first lower limit value.

[0053] Optionally, determining the first type of control parameter in the automatic parking mode according to the adjustment coefficient, the first upper limit value, and the first lower limit value includes:

[0054] Calculate an average of the first upper limit value and the first lower limit value;

[0055] Calculate the difference between the first upper limit and the first lower limit to obtain a second difference;

[0056] Calculating the product of the second difference and the adjustment coefficient;

[0057] A sum of one half of the product and the average value is determined as the first type of control parameter in the automatic parking mode.

[0058] According to a second aspect of an embodiment of the present disclosure, there is provided a parking control device, comprising:

[0059] A first module is configured to determine control parameters in an automatic parking mode based on historical driving data of the vehicle;

[0060] The second module is configured to control the vehicle to perform automatic parking according to the automatic parking mode.

[0061] Optionally, the first module includes:

[0062] A first submodule is configured to determine the first type of control parameters in the automatic parking mode according to the first type of data in the historical driving data;

[0063] The first type includes one or more of a velocity type, an acceleration type, and a jerk type.

[0064] Optionally, the first submodule includes:

[0065] a first subunit, configured to determine an adjustment coefficient of a control parameter of the first type;

[0066] A second subunit is configured to determine an upper limit value and a lower limit value of the first type of data according to the first type of data in the historical driving data, and obtain a first upper limit value and a first lower limit value respectively;

[0067] The third subunit is configured to determine the first type of control parameter in the automatic parking mode according to the adjustment coefficient, the first upper limit value, and the first lower limit value.

[0068] Optionally, the first subunit includes:

[0069] A first processing unit is configured to determine a first adjustment coefficient of the control parameter according to an operation interval duration in the historical driving data, wherein the operation interval duration includes an interval duration between a brake pedal step and an accelerator pedal step that are adjacent in time;

[0070] A second processing unit is configured to determine a second adjustment coefficient of the control parameter according to acceleration data of the vehicle during acceleration control in the historical driving data;

[0071] The third processing unit is configured to determine a third adjustment coefficient of the control parameter based on the acceleration data of the vehicle during deceleration control in the historical driving data, and the adjustment coefficient of the control parameter includes one or more of the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient.

[0072] Optionally, the adjustment coefficient includes the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient, and the first subunit is configured as:

[0073] Determining a weight of the first adjustment coefficient to obtain a first weight;

[0074] Determining a weight of the second adjustment coefficient to obtain a second weight;

[0075] Determining a weight of the third adjustment coefficient to obtain a third weight;

[0076] According to the first weight, the second weight and the third weight, the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient are weighted and summed to obtain the adjustment coefficient of the control parameter.

[0077] Optionally, the first subunit is configured as:

[0078] In response to a weight setting operation, a first weight of the first adjustment coefficient, a second weight of the second adjustment coefficient, and a third weight of the third adjustment coefficient are determined, and the sum of the first weight, the second weight, and the third weight is 1.

[0079] Optionally, the first processing unit includes:

[0080] A first execution unit is configured to determine a first value of operation interval durations according to the historical driving data;

[0081] A second execution unit is configured to determine a reference value of the operation interval duration to obtain a first reference value;

[0082] A third execution unit is configured to determine the number of operation intervals whose duration is less than the first reference value, and obtain a second value;

[0083] a fourth execution unit, configured to determine a ratio of the second value to the first value to obtain a first ratio;

[0084] The fifth execution unit is configured to determine the first adjustment coefficient according to the first ratio.

[0085] Optionally, the fifth execution unit is configured to:

[0086] Calculate the product of the first ratio and 2;

[0087] The difference between the product and 1 is calculated to obtain the first adjustment coefficient.

[0088] Optionally, the second processing unit is configured to:

[0089] Determining a third acceleration value according to the acceleration data of the vehicle during acceleration control in the historical driving data;

[0090] Determine a reference value of the third acceleration to obtain a second reference value;

[0091] Determine the number of accelerations of the third value whose acceleration values ​​are greater than the second reference value, to obtain a fourth value;

[0092] determining a ratio of the fourth value to the third value to obtain a second ratio;

[0093] The second adjustment coefficient is determined according to the second ratio.

[0094] Optionally, the third processing unit is configured to:

[0095] determining a fifth acceleration value according to the acceleration data of the vehicle during deceleration control in the historical driving data;

[0096] Determining a reference value of the fifth acceleration to obtain a third reference value;

[0097] Determine the number of accelerations whose acceleration values ​​are greater than the third reference value among the fifth value accelerations to obtain a sixth value;

[0098] determining a ratio of the sixth value to the fifth value to obtain a third ratio;

[0099] The third adjustment coefficient is determined according to the third ratio.

[0100] Optionally, the second subunit is configured as:

[0101] Determining, based on the first type of data in the historical driving data, an average value and a standard deviation of the first type of data;

[0102] Determine an upper limit value and a lower limit value corresponding to the first type of data of the vehicle to obtain a second upper limit value and a second lower limit value respectively;

[0103] Determine a sum of the mean value and the standard deviation, and a difference between the mean value and the standard deviation to obtain a first difference;

[0104] determining the smaller one of the sum value and the second upper limit value as the first upper limit value;

[0105] The larger one of the first difference value and the second lower limit value is determined as the first lower limit value.

[0106] Optionally, the third subunit is configured as:

[0107] Calculate an average of the first upper limit value and the first lower limit value;

[0108] Calculate the difference between the first upper limit and the first lower limit to obtain a second difference;

[0109] Calculating the product of the second difference and the adjustment coefficient;

[0110] A sum of one half of the product and the average value is determined as the first type of control parameter in the automatic parking mode.

[0111] According to a third aspect of an embodiment of the present disclosure, a vehicle is provided, comprising:

[0112] processor;

[0113] a memory for storing processor-executable instructions;

[0114] The processor is configured to execute the steps of any one of the methods described in the first aspect.

[0115] According to a fourth aspect of an embodiment of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods described in the first aspect are implemented.

[0116] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, including a computer program, which implements the steps of any one of the methods in the first aspect when executed by a processor.

[0117] In the above scheme, the control parameters in the automatic parking mode can be determined according to the historical driving data of the vehicle. In this way, the vehicle can be controlled to automatically park according to the automatic parking mode. With the above scheme, the control parameters in the automatic parking mode can be determined according to the historical driving data of the vehicle, so that the automatic parking control strategy can match the historical driving behavior of the vehicle. In this way, a personalized automatic parking service that fits the user's driving habits can be provided to the user.

[0118] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0119] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0120] Figure 1 The figure is a flow chart of a parking control method according to an exemplary embodiment.

[0121] Figure 2 The figure is a flow chart of determining a control parameter according to an exemplary embodiment.

[0122] Figure 3 is a flowchart of an implementation of step S21 according to an exemplary embodiment.

[0123] Figure 4is a flowchart of an implementation of step S22 according to an exemplary embodiment.

[0124] Figure 5 The figure is a flow chart of a parking control method according to an exemplary embodiment.

[0125] Figure 6 The figure is a block diagram of a parking control device according to an exemplary embodiment.

[0126] Figure 7 is a block diagram of a vehicle according to an exemplary embodiment. DETAILED DESCRIPTION

[0127] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0128] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the device is located and with the authorization given by the owner of the corresponding device.

[0129] Before introducing the parking control method, device, vehicle, storage medium and program product of the present disclosure, the relevant scenarios of the embodiments of the present disclosure are first exemplified.

[0130] When using the automatic parking function, the vehicle's sensing device can identify the parking space, and the user can select the target parking space in the interactive interface and click to send the parking start command. In this way, the vehicle can plan the parking route and realize automatic parking through the steering system and motion system. Sometimes, the automatic parking speed may be too fast or too slow for the user, causing discomfort.

[0131] In some scenarios, multiple automatic parking control strategies can be preset in the vehicle, such as an automatic parking strategy that prioritizes comfort, an automatic parking strategy that prioritizes efficiency, and so on. However, different users may have different driving styles, making it difficult for the preset automatic parking control strategy to meet the driving habits of different users. Therefore, it is still possible that the user perceives that the automatic parking speed is too fast or too slow. In addition, the user's driving habits may change over time, and the relevant automatic parking control strategy is also difficult to be personalized according to the changes in the user's driving habits.

[0132] To this end, the present disclosure provides a parking control method. Figure 1 is a flowchart of a parking control method shown in an exemplary embodiment of the present disclosure, referring to Figure 1 , the method may include:

[0133] In step S11 , control parameters in the automatic parking mode are determined according to historical driving data of the vehicle.

[0134] In a possible implementation, historical driving data of the vehicle may be obtained.

[0135] For example, in one implementation, all historical driving data of the vehicle may be acquired.

[0136] In one embodiment, the time interval length can be set, and the historical driving data within the time interval length starting from the current moment can be obtained. For example, the time interval length can be set to 1 month. In this way, the historical driving data of the vehicle within one month before the current moment can be obtained.

[0137] In one embodiment, the historical driving data may also be associated with the user. For example, for different users, the historical driving data of the user driving the vehicle may be obtained. In implementation, different users may be distinguished by the account logged into the vehicle computer, the vehicle key, biometrics, etc.

[0138] In one embodiment, historical driving data may include vehicle speed , start control data, acceleration control data, deceleration control data, brake control data, etc. The start control data may include the acceleration of the start control and jerk The acceleration control data may include the acceleration of the acceleration control and jerk The deceleration control data may include the acceleration of the deceleration control and jerk The brake control data may include the acceleration of the brake control and jerk Among them, the jerk can be the time derivative of the acceleration, which can describe the rate of change of the acceleration.

[0139] In one embodiment, the control parameters of the automatic parking mode may include comfort type control parameters and safety type control parameters. The comfort type control parameters may include, for example, vehicle speed, starting control data, acceleration control data, deceleration control data, brake control data, etc. The safety type control parameters may be set with reference to production standards and safety standards.

[0140] When the user is driving the vehicle, the user can control the vehicle to perform relevant operations, such as starting, accelerating, decelerating, braking, etc. In this way, historical driving data of the vehicle can be generated.

[0141] Taking starting as an example, starting control can involve the acceleration of starting control. and jerk In this way, multiple accelerations can be generated after multiple start controls. . For example, N accelerations It can be expressed as In addition, multiple jerks can be generated . For example, N jerks It can be expressed as .

[0142] Taking brake control as an example, it can involve the acceleration of brake control. and jerk In this way, multiple accelerations can be generated after multiple braking stops. . For example, N accelerations It can be expressed as In addition, multiple jerks can be generated . For example, N jerks It can be expressed as .

[0143] In a possible implementation manner, the first type of control parameters in the automatic parking mode may be determined according to the first type of data in the historical driving data, wherein the first type includes one or more of a speed type, an acceleration type, and a jerk type.

[0144] For example, the speed control parameter in the automatic parking mode may be determined according to the speed data in the historical driving data. The acceleration control parameter in the automatic parking mode may be determined according to the acceleration data in the historical driving data. The jerk control parameter in the automatic parking mode may be determined according to the jerk data in the historical driving data.

[0145] In addition, the acceleration data may be acceleration data during the acceleration / deceleration / braking control process, and thus the acceleration control parameters during the acceleration / deceleration / braking control process in the automatic parking mode may be determined based on the acceleration data.

[0146] The jerk data may be jerk data during acceleration / deceleration / braking control, and thus a jerk control parameter during acceleration / deceleration / braking control in the automatic parking mode may be determined based on the jerk data.

[0147] Figure 2 is a flow chart showing a control parameter determination process according to an exemplary embodiment of the present disclosure, referring to Figure 2 The determining of the first type of control parameters in the automatic parking mode according to the first type of data in the historical driving data includes:

[0148] In step S21 , an adjustment coefficient of a control parameter of a first type is determined.

[0149] In a possible implementation, the adjustment coefficient may be determined in response to a user operation. As an example, the user may manually input the adjustment coefficient.

[0150] In one embodiment, a control control and a progress bar for adjusting the coefficient may be provided in the vehicle-machine interaction interface. The progress bar may be configured such that the left side indicates that the automatic parking control prioritizes stability, and the right side indicates that the automatic parking control prioritizes parking efficiency. The midpoint of the progress bar is the default parking control mode. In this way, the user can drag the control control to control the position of the control in the progress bar and select the corresponding control mode. The vehicle end may determine the adjustment coefficient corresponding to the position of the control in the progress bar according to the position of the control in the progress bar.

[0151] In a possible implementation manner, the adjustment coefficient may be calculated based on historical driving data. Figure 3 is an implementation flow chart of step S21 shown in an exemplary embodiment of the present disclosure, referring to Figure 3 , the determining of the adjustment coefficient of the first type of control parameter comprises:

[0152] In step S31, a first adjustment coefficient of a control parameter is determined according to the operation interval duration in the historical driving data.

[0153] The operation interval duration includes the interval duration between a time-adjacent stepping of the brake pedal and a time-adjacent stepping of the accelerator pedal. For example, the operation interval duration can be obtained by obtaining the interval duration between the user's continuous stepping of the brake pedal and the stepping of the accelerator pedal when parking in historical driving data.

[0154] In this way, the first adjustment coefficient can be determined according to the operation interval duration.

[0155] For example, in one embodiment, a first value of operation interval durations may be determined based on the historical driving data. The first value may be set based on demand. In some implementation scenarios, each operation interval duration in the historical driving data may also be obtained. In this case, the first value may be the total number of operation interval durations in the historical driving data.

[0156] In some implementations, the time points corresponding to the operation intervals may also be determined, and the first numerical operation intervals that are closer to the current moment may be selected. In this way, the time points corresponding to the operation intervals are closer to the current moment and can better represent the user's current driving habits.

[0157] After determining the first numerical operation interval duration, a reference value of the operation interval duration can be determined to obtain a first reference value. As an example, the median of the first numerical operation duration intervals can be determined and the median can be determined as the first reference value. In a possible implementation, the first reference value can be calibrated and set according to demand.

[0158] In addition, the number of operation intervals whose duration is less than the first reference value can be determined to obtain a second value. In this way, the ratio of the second value to the first value can be determined to obtain a first ratio, and the first adjustment coefficient can be determined based on the first ratio.

[0159] For example, the first value may be N, and the duration of the N operation intervals may be expressed as:

[0160] .

[0161] As an example, the median is used as the first reference value, which is recorded as In this way, we can determine , and obtain the first ratio.

[0162] In one implementation, the first adjustment coefficient may be obtained by calculating the product of the first ratio and 2 and calculating the difference between the product and 1.

[0163] Using the above example, the first adjustment coefficient can be calculated by the following formula: :

[0164] , ,in, is the first ratio.

[0165] In one embodiment, the first adjustment coefficient can also be calculated by the following formula: :

[0166] , n is an odd number.

[0167] In one embodiment, the first adjustment coefficient can also be calculated by the following formula: :

[0168] , Φ is the cumulative distribution function of the standard normal distribution.

[0169] Reference Figure 3 In step S32, a second adjustment coefficient of the control parameter is determined based on the acceleration data of the vehicle during acceleration control in the historical driving data.

[0170] In a possible implementation, the third value of acceleration may be determined based on the acceleration data of the vehicle during acceleration control in the historical driving data. For example, the acceleration of the user during acceleration control in a parking scenario may be obtained.

[0171] In one implementation, a third value of accelerations of the user in the parking scenario may be determined based on the historical driving data. The third value may be set based on demand. In some implementation scenarios, each acceleration during vehicle acceleration control in the historical driving data may also be obtained. In this case, the third value may be the total number of accelerations during vehicle acceleration control in the historical driving data.

[0172] In some implementations, the time point of the acceleration control may also be determined, and the acceleration in the acceleration control closer to the current moment may be selected to obtain the third value of acceleration. In this way, selecting the acceleration in the acceleration control closer to the current moment can better represent the user's current driving habits.

[0173] After the third value of acceleration is determined, a reference value of the third value of acceleration may be determined to obtain a second reference value.

[0174] As an example, the median of the third number of accelerations may be determined, and the median may be determined as the second reference value. In a possible implementation, the second reference value may be calibrated and set according to requirements.

[0175] In addition, the number of accelerations of the third value whose acceleration value is greater than the second reference value can be determined to obtain a fourth value. In this way, the ratio of the fourth value to the third value can be determined to obtain a second ratio, and the second adjustment coefficient can be determined according to the second ratio.

[0176] For example, the third value may be M, and the M accelerations may be expressed as:

[0177] .

[0178] As an example, the median is used as the second reference value, which is recorded as In this way, we can determine , the second ratio is obtained.

[0179] In one implementation, the product of the second ratio and 2 may be calculated, and the difference between the product and 1 may be calculated to obtain the second adjustment coefficient.

[0180] Using the above example, the second adjustment coefficient can be calculated by the following formula: :

[0181] , ,in, is the second ratio.

[0182] In one embodiment, the second adjustment coefficient can also be calculated by the following formula: :

[0183] , n is an odd number.

[0184] In one embodiment, the second adjustment coefficient can also be calculated by the following formula: :

[0185] , Φ is the cumulative distribution function of the standard normal distribution.

[0186] Still refer to Figure 3 In step S33, a third adjustment coefficient of the control parameter is determined based on the acceleration data of the vehicle during deceleration control in the historical driving data.

[0187] In a possible implementation, the fifth value of acceleration may be determined based on the acceleration data of the vehicle during deceleration control in the historical driving data. For example, the acceleration of the user during deceleration control in a parking scenario may be obtained.

[0188] In one implementation, a fifth value of accelerations of the user in the parking scenario may be determined based on the historical driving data. The fifth value may be set based on demand. In some implementation scenarios, each acceleration during vehicle deceleration control in the historical driving data may also be obtained. In this case, the fifth value may be the total number of accelerations during vehicle deceleration control in the historical driving data.

[0189] In some implementations, the time point of the deceleration control may also be determined, and the acceleration in the deceleration control closer to the current time may be selected to obtain the fifth value of acceleration. In this way, selecting the acceleration in the deceleration control closer to the current time may better represent the user's current driving habits.

[0190] After the fifth value of acceleration is determined, a reference value of the fifth value of acceleration may be determined to obtain a third reference value.

[0191] As an example, the median of the fifth number of accelerations may be determined, and the median may be determined as the third reference value. In a possible implementation, the third reference value may be calibrated and set according to requirements.

[0192] In addition, the number of accelerations whose acceleration values ​​are greater than the third reference value among the fifth value accelerations can be determined to obtain a sixth value. In this way, the ratio of the sixth value to the fifth value can be determined to obtain a third ratio, and the third adjustment coefficient can be determined according to the third ratio.

[0193] For example, the fifth value may be Z, and the Z accelerations may be expressed as:

[0194] .

[0195] As an example, the median is used as the third reference value, which is recorded as In this way, we can determine , and obtain the third ratio.

[0196] In one implementation, the third adjustment coefficient may be obtained by calculating the product of the third ratio and 2, and calculating the difference between the product and 1.

[0197] Using the above example, the third adjustment coefficient can be calculated by the following formula: :

[0198] , ,in, is the third ratio.

[0199] In one embodiment, the third adjustment coefficient can also be calculated by the following formula: :

[0200] , n is an odd number.

[0201] In one embodiment, the third adjustment coefficient can also be calculated by the following formula: :

[0202] , Φ is the cumulative distribution function of the standard normal distribution.

[0203] Reference Figure 3 In a possible implementation manner, the adjustment coefficient of the control parameter includes one or more of the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient.

[0204] Exemplarily, the adjustment coefficient may include the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient. Thus, determining the adjustment coefficient of the first type of control parameter in step S21 may include:

[0205] The weight of the first adjustment coefficient is determined to obtain a first weight. The weight of the second adjustment coefficient is determined to obtain a second weight. The weight of the third adjustment coefficient is determined to obtain a third weight.

[0206] In one embodiment, the first weight, the second weight and the third weight may be default values, which may be calibrated and set according to requirements. The sum of the first weight, the second weight and the third weight may be, for example, 1, or other values ​​set according to requirements.

[0207] In one embodiment, in response to a weight setting operation, a first weight of the first adjustment coefficient, a second weight of the second adjustment coefficient, and a third weight of the third adjustment coefficient can be determined, and the sum of the first weight, the second weight, and the third weight is 1.

[0208] Exemplarily, a weight setting portal may be provided in the vehicle, and the user may set the first weight, the second weight, and the third weight by himself through the weight setting portal.

[0209] After determining the first weight, the second weight and the third weight, the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient may be weightedly summed according to the first weight, the second weight and the third weight to obtain the adjustment coefficient of the control parameter.

[0210] Exemplarily, the adjustment coefficient can be calculated by the following formula: :

[0211] ;

[0212] in, is the first weight, is the first adjustment coefficient, is the second weight, is the second adjustment coefficient, is the third weight, is the third adjustment factor, and .

[0213] Reference Figure 2 In step S22, based on the first type of data in the historical driving data, an upper limit value and a lower limit value of the first type of data are determined to obtain a first upper limit value and a first lower limit value, respectively.

[0214] Figure 4 is an implementation flow chart of step S22 shown in an exemplary embodiment of the present disclosure, referring to Figure 4 , determining an upper limit value and a lower limit value of the first type of data according to the first type of data in the historical driving data, and obtaining a first upper limit value and a first lower limit value respectively, including:

[0215] In step S41 , the average value and standard deviation of the first type of data in the historical driving data are determined.

[0216] When the driver drives the vehicle, historical driving data may be generated. The first type of data in the historical driving data may conform to a Gaussian distribution, for example, it may be expressed as , where X is a parameter set, such as a set of data of the first type, is the expected value of the parameter set, In step S41, the mean value and standard deviation of the first type of data can be determined according to the first type of data in the historical driving data.

[0217] In step S42, an upper limit value and a lower limit value corresponding to the first type of data of the vehicle are determined to obtain a second upper limit value and a second lower limit value, respectively.

[0218] It should be understood that, for a vehicle system, the first type of data may have an upper limit and a lower limit. For example, in a brake control scenario, the first type of data may include the acceleration of the brake control. In this case, the upper limit of the braking acceleration of the vehicle system may be determined as the second upper limit. In addition, the minimum acceleration that satisfies the brake condition may be calculated based on information such as the brake distance, the brake duration, and the current speed of the vehicle to obtain the second lower limit.

[0219] In addition, the upper limit value and the lower limit value of the vehicle corresponding to the first type of data may also be determined by calibration, preset, etc., to obtain the second upper limit value and the second lower limit value, respectively.

[0220] In step S43, the sum of the mean value and the standard deviation, and the difference between the mean value and the standard deviation are determined to obtain a first difference.

[0221] In step S44, the smaller one of the sum value and the second upper limit value is determined as the first upper limit value.

[0222] In step S45 , the larger one of the first difference value and the second lower limit value is determined as the first lower limit value.

[0223] Taking the acceleration type data in the braking scene as an example, the average value can be , the standard deviation can be . Thus, the sum of the mean and the standard deviation is , the first difference between the mean and the standard deviation can be The second upper limit value can be expressed as , the second lower limit value can be expressed as .

[0224] Thus, the first lower limit can be expressed as , for and The larger one of the first upper limit can be expressed as , for and The smaller one.

[0225] In step S23 , a first type of control parameter in the automatic parking mode is determined according to the adjustment coefficient, the first upper limit value, and the first lower limit value.

[0226] In a possible implementation manner, determining the first type of control parameter in the automatic parking mode according to the adjustment coefficient, the first upper limit value, and the first lower limit value includes:

[0227] The first upper limit value and the first lower limit value are averaged, and the first upper limit value and the first lower limit value are differenced to obtain a second difference value. The second difference value and the adjustment coefficient are multiplied, and the sum of one half of the product and the average value is determined as the first type of control parameter in the automatic parking mode.

[0228] The first upper limit is as follows: , the first lower limit is , the adjustment factor is The control parameter (denoted as ):

[0229] .

[0230] In addition, in a possible implementation, the control parameter may be determined by other calculation formulas. For example, the control parameter may be calculated by the following calculation formula: :

[0231] . f is an adjustment factor, which can be set by the user, for example.

[0232] In this way, after the control parameters in the automatic parking mode are determined, in step S12, the vehicle is controlled to perform automatic parking according to the automatic parking mode.

[0233] By adopting the above scheme, the control parameters in the automatic parking mode can be determined according to the historical driving data of the vehicle. For example, the speed, acceleration, and jerk in the automatic parking mode can be determined according to the speed, acceleration, and jerk in the historical driving data of the user. In this way, the automatic parking control strategy can be matched with the historical driving behavior of the vehicle. In this way, a personalized automatic parking service that fits the user's driving habits can be provided to the user.

[0234] Figure 5 is a flowchart of a parking control method shown in an exemplary embodiment of the present disclosure, referring to Figure 5 , the method comprising:

[0235] Collecting data. For example, the driving behavior data of the user when using the vehicle can be collected. In one embodiment, the vehicle may include a driver behavior collection and storage module, so the driver's driving behavior data can be collected through the driver behavior collection and storage module.

[0236] Based on the driving behavior data, statistical parameters can be calculated For example, statistical parameters may be calculated for each type of data in the driving behavior data. The data types in the driving behavior data may include vehicle speed, starting control data, acceleration control data, deceleration control data, brake control data, and the like.

[0237] Reference Figure 5 Taking the brake control data as an example, the acceleration boundary data of the vehicle during brake control can be calculated. For example, the upper limit value of acceleration in dynamics can be calculated. , and the lower limit In addition, the optimal value range of the acceleration parameter during brake control can be calculated based on the driving behavior data and the dynamic boundary data. ].

[0238] In addition, the preference function (preference parameter) can be calculated. The calculation formula is:

[0239] ,in, and . , , For example, it may be a preset value.

[0240] The vehicle may also provide a professional mode, and when in the professional mode, the parameters , , In this way, users can set the parameters in the preference function by themselves and obtain , and .

[0241] Determine the preference function And the optimal value interval [ ], the acceleration parameters during brake control can be calculated. Figure 5 , the acceleration parameter can be calculated by the following formula :

[0242] 。

[0243] It should be noted that Figure 5 The method of obtaining the relevant parameters in Figures 1 to 4 For the sake of brevity, this disclosure will not go into detail in the embodiments of the present disclosure.

[0244] By adopting the above scheme, the control parameters in the automatic parking mode can be determined according to the historical driving data of the vehicle, so that the automatic parking control strategy can match the historical driving behavior of the vehicle. In this way, it is possible to provide users with personalized automatic parking services that fit the user's driving habits.

[0245] The disclosed embodiment also provides a parking control device. Figure 6 is a block diagram of a parking control device shown in an exemplary embodiment of the present disclosure, referring to Figure 6 , the parking control device comprises:

[0246] The first module 501 is configured to determine control parameters in the automatic parking mode according to historical driving data of the vehicle;

[0247] The second module 502 is configured to control the vehicle to perform automatic parking according to the automatic parking mode.

[0248] In the above parking control device, the control parameters in the automatic parking mode can be determined according to the historical driving data of the vehicle. In this way, the vehicle can be controlled to automatically park according to the automatic parking mode. With the above parking control device, the control parameters in the automatic parking mode can be determined according to the historical driving data of the vehicle, so that the automatic parking control strategy can match the historical driving behavior of the vehicle. In this way, a personalized automatic parking service that fits the user's driving habits can be provided to the user.

[0249] Optionally, the first module 501 includes:

[0250] A first submodule is configured to determine the first type of control parameters in the automatic parking mode according to the first type of data in the historical driving data;

[0251] The first type includes one or more of a velocity type, an acceleration type, and a jerk type.

[0252] Optionally, the first submodule includes:

[0253] a first subunit, configured to determine an adjustment coefficient of a control parameter of the first type;

[0254] A second subunit is configured to determine an upper limit value and a lower limit value of the first type of data according to the first type of data in the historical driving data, and obtain a first upper limit value and a first lower limit value respectively;

[0255] The third subunit is configured to determine the first type of control parameter in the automatic parking mode according to the adjustment coefficient, the first upper limit value, and the first lower limit value.

[0256] Optionally, the first subunit includes:

[0257] A first processing unit is configured to determine a first adjustment coefficient of the control parameter according to an operation interval duration in the historical driving data, wherein the operation interval duration includes an interval duration between a brake pedal step and an accelerator pedal step that are adjacent in time;

[0258] A second processing unit is configured to determine a second adjustment coefficient of the control parameter according to acceleration data of the vehicle during acceleration control in the historical driving data;

[0259] The third processing unit is configured to determine a third adjustment coefficient of the control parameter based on the acceleration data of the vehicle during deceleration control in the historical driving data, and the adjustment coefficient of the control parameter includes one or more of the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient.

[0260] Optionally, the adjustment coefficient includes the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient, and the first subunit is configured as:

[0261] Determining a weight of the first adjustment coefficient to obtain a first weight;

[0262] Determining a weight of the second adjustment coefficient to obtain a second weight;

[0263] Determining a weight of the third adjustment coefficient to obtain a third weight;

[0264] According to the first weight, the second weight and the third weight, the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient are weighted and summed to obtain the adjustment coefficient of the control parameter.

[0265] Optionally, the first subunit is configured as:

[0266] In response to a weight setting operation, a first weight of the first adjustment coefficient, a second weight of the second adjustment coefficient, and a third weight of the third adjustment coefficient are determined, and the sum of the first weight, the second weight, and the third weight is 1.

[0267] Optionally, the first processing unit includes:

[0268] A first execution unit is configured to determine a first value of operation interval durations according to the historical driving data;

[0269] A second execution unit is configured to determine a reference value of the operation interval duration to obtain a first reference value;

[0270] A third execution unit is configured to determine the number of operation intervals whose duration is less than the first reference value, and obtain a second value;

[0271] a fourth execution unit, configured to determine a ratio of the second value to the first value to obtain a first ratio;

[0272] The fifth execution unit is configured to determine the first adjustment coefficient according to the first ratio.

[0273] Optionally, the fifth execution unit is configured to:

[0274] Calculate the product of the first ratio and 2;

[0275] The difference between the product and 1 is calculated to obtain the first adjustment coefficient.

[0276] Optionally, the second processing unit is configured to:

[0277] Determining a third acceleration value according to the acceleration data of the vehicle during acceleration control in the historical driving data;

[0278] Determine a reference value of the third acceleration to obtain a second reference value;

[0279] Determine the number of accelerations of the third value whose acceleration values ​​are greater than the second reference value, to obtain a fourth value;

[0280] determining a ratio of the fourth value to the third value to obtain a second ratio;

[0281] The second adjustment coefficient is determined according to the second ratio.

[0282] Optionally, the third processing unit is configured to:

[0283] determining a fifth acceleration value according to the acceleration data of the vehicle during deceleration control in the historical driving data;

[0284] Determining a reference value of the fifth acceleration to obtain a third reference value;

[0285] Determine the number of accelerations whose acceleration values ​​are greater than the third reference value among the fifth value accelerations to obtain a sixth value;

[0286] determining a ratio of the sixth value to the fifth value to obtain a third ratio;

[0287] The third adjustment coefficient is determined according to the third ratio.

[0288] Optionally, the second subunit is configured as:

[0289] Determining, based on the first type of data in the historical driving data, an average value and a standard deviation of the first type of data;

[0290] Determine an upper limit value and a lower limit value corresponding to the first type of data of the vehicle to obtain a second upper limit value and a second lower limit value respectively;

[0291] Determine a sum of the mean value and the standard deviation, and a difference between the mean value and the standard deviation to obtain a first difference;

[0292] determining the smaller one of the sum value and the second upper limit value as the first upper limit value;

[0293] The larger one of the first difference value and the second lower limit value is determined as the first lower limit value.

[0294] Optionally, the third subunit is configured as:

[0295] Calculate an average of the first upper limit value and the first lower limit value;

[0296] Calculate the difference between the first upper limit and the first lower limit to obtain a second difference;

[0297] Calculating the product of the second difference and the adjustment coefficient;

[0298] A sum of one half of the product and the average value is determined as the first type of control parameter in the automatic parking mode.

[0299] The present disclosure also provides a vehicle, including:

[0300] processor;

[0301] a memory for storing processor-executable instructions;

[0302] The processor is configured to execute the steps of the parking control method provided in any embodiment of the present disclosure.

[0303] An embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the parking control method provided in any embodiment of the present disclosure are implemented.

[0304] An embodiment of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the parking control method provided in any embodiment of the present disclosure.

[0305] Regarding the parking control device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the parking control method, and will not be elaborated here.

[0306] Figure 7 6 is a block diagram of a vehicle 600 according to an exemplary embodiment. For example, the vehicle 600 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. The vehicle 600 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.

[0307] Reference Figure 7 , the vehicle 600 may include various subsystems, for example, an infotainment system 610, a perception system 620, a decision control system 630, a drive system 640, and a computing platform 650. The vehicle 600 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, each subsystem and each component of the vehicle 600 may be interconnected by wire or wireless means.

[0308] In some embodiments, the infotainment system 610 may include a communication system, an entertainment system, and a navigation system, among others.

[0309] The perception system 620 may include several sensors for sensing information about the environment around the vehicle 600. For example, the perception system 620 may include a global positioning system (the global positioning system may be a GPS system, or a Beidou system or other positioning systems), an inertial measurement unit (IMU), a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera.

[0310] The decision control system 630 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0311] The drive system 640 may include components that provide powered motion for the vehicle 600. In one embodiment, the drive system 640 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of an internal combustion engine, an electric motor, and an air compression engine. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0312] Some or all functions of the vehicle 600 are controlled by a computing platform 650. The computing platform 650 may include at least one processor 651 and a memory 652, and the processor 651 may execute instructions 653 stored in the memory 652.

[0313] The processor 651 may be any conventional processor, such as a commercially available CPU. The processor may also include a graphics processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0314] The memory 652 may be implemented by any type of volatile or nonvolatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0315] In addition to the instructions 653 , the memory 652 may also store data, such as road maps, route information, and data such as the location, direction, and speed of the vehicle. The data stored in the memory 652 may be used by the computing platform 650 .

[0316] In the embodiment of the present disclosure, the processor 651 may execute the instruction 653 to complete all or part of the steps of the above-mentioned parking control method.

[0317] In addition, the word "exemplary" is used herein to indicate serving as an example, instance, or diagram. Any aspect or design described as "exemplary" in this article is not necessarily understood to be advantageous compared to other aspects or designs. On the contrary, the use of the word exemplary is intended to present concepts in a specific way. As used herein, the term "or" is intended to represent an inclusive "or" rather than an exclusive "or". That is, unless otherwise specified or clear from the context, "X applies A or B" is intended to represent any one of the natural inclusive arrangements. That is, if X applies A; X applies B; or X applies both A and B, "X applies A or B" is satisfied under any of the aforementioned examples. In addition, unless otherwise specified or clearly pointed to a singular form from the context, the articles "one" and "an" as used in this application and the appended claims are generally understood to mean "one or more".

[0318] Likewise, although the present disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art after reading and understanding the specification and drawings. The present disclosure includes all such modifications and variations and is limited only by the scope of the claims. In particular, with respect to the various functions performed by the components (e.g., modules) described above, unless otherwise indicated, the terms used to describe such components are intended to correspond to any component (functionally equivalent) that performs the specific functions of the described components, even if the structure is not equivalent to the disclosed structure. In addition, although specific features of the present disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations as may be desired and beneficial to any given or specific application. In addition, with respect to "including", "having", "having", "having", or variations thereof used in a specific embodiment or claim, such terms are intended to be inclusive in a manner similar to the term "comprising".

[0319] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

[0320] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0321] In addition, unless otherwise specified, the features of some embodiments of the present disclosure described herein may be combined with each other. As used herein, the term "and / or" includes any one of the related listed items and any combination of any two or more; similarly, "at least one of . . . " includes any one of the related listed items and any combination of any two or more.

[0322] Although terms such as "first", "second" and "third" may be used herein to describe various modules, these modules are not limited to these terms. On the contrary, these terms are only used to distinguish one module from another. Therefore, without departing from the teachings of the various examples, the first module mentioned in the examples described herein may also be referred to as the second module. In addition, the terms "first" and "second" are used only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description herein, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

Claims

1. A parking control method, characterized in that: include: Determining control parameters in an automatic parking mode based on historical driving data of the vehicle; controlling the vehicle to perform automatic parking according to the automatic parking mode; The step of determining the control parameters in the automatic parking mode according to the historical driving data of the vehicle includes: determining the first type of control parameters in the automatic parking mode according to the first type of data in the historical driving data; The determining, according to the first type of data in the historical driving data, the first type of control parameter in the automatic parking mode comprises: determining an adjustment factor for a control parameter of the first type; Determine an upper limit value and a lower limit value of the first type of data according to the first type of data in the historical driving data, and obtain a first upper limit value and a first lower limit value respectively; determining the first type of control parameter in the automatic parking mode according to the adjustment coefficient, the first upper limit value, and the first lower limit value; The determining the adjustment coefficient of the first type of control parameter includes: determining a first adjustment coefficient of the control parameter according to an operation interval duration in the historical driving data, wherein the operation interval duration includes an interval duration between a time-adjacent stepping of a brake pedal and a time-adjacent stepping of an accelerator pedal, and the adjustment coefficient of the control parameter includes the first adjustment coefficient; The determining, according to the operation interval duration in the historical driving data, a first adjustment coefficient of the control parameter comprises: Determine a first value of operation interval durations according to the historical driving data; Determine a reference value of the operation interval duration to obtain a first reference value; Determine the number of operation intervals whose duration is less than the first reference value to obtain a second value; Determine a ratio of the second value to the first value to obtain a first ratio; The first adjustment coefficient is determined according to the first ratio.

2. The method according to claim 1, characterized in that The first type includes one or more of a velocity type, an acceleration type, and a jerk type.

3. The method according to claim 1, characterized in that The determining the adjustment coefficient of the first type of control parameter further includes: determining a second adjustment coefficient of the control parameter according to acceleration data of the vehicle during acceleration control in the historical driving data; A third adjustment coefficient of the control parameter is determined according to the acceleration data of the vehicle during deceleration control in the historical driving data, and the adjustment coefficient of the control parameter also includes one or more of the second adjustment coefficient and the third adjustment coefficient.

4. The method according to claim 3, characterized in that: The adjustment coefficient includes the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient, and the determining of the adjustment coefficient of the first type of control parameter includes: Determining a weight of the first adjustment coefficient to obtain a first weight; Determining a weight of the second adjustment coefficient to obtain a second weight; Determining a weight of the third adjustment coefficient to obtain a third weight; According to the first weight, the second weight and the third weight, the first adjustment coefficient, the second adjustment coefficient and the third adjustment coefficient are weighted and summed to obtain the adjustment coefficient of the control parameter.

5. The method according to claim 4, characterized in that The determining the weight of the first adjustment coefficient to obtain a first weight, determining the weight of the second adjustment coefficient to obtain a second weight, and determining the weight of the third adjustment coefficient to obtain a third weight includes: In response to a weight setting operation, a first weight of the first adjustment coefficient, a second weight of the second adjustment coefficient, and a third weight of the third adjustment coefficient are determined, and the sum of the first weight, the second weight, and the third weight is 1.

6. The method according to claim 1, characterized in that The determining the first adjustment coefficient according to the first ratio includes: Calculate the product of the first ratio and 2; The difference between the product and 1 is calculated to obtain the first adjustment coefficient.

7. The method according to claim 3, characterized in that The determining the second adjustment coefficient of the control parameter according to the acceleration data of the vehicle during acceleration control in the historical driving data includes: Determining a third acceleration value according to the acceleration data of the vehicle during acceleration control in the historical driving data; Determine a reference value of the third acceleration to obtain a second reference value; Determine the number of accelerations of the third value whose acceleration values ​​are greater than the second reference value, to obtain a fourth value; determining a ratio of the fourth value to the third value to obtain a second ratio; The second adjustment coefficient is determined according to the second ratio.

8. The method according to claim 3, characterized in that The determining the third adjustment coefficient of the control parameter according to the acceleration data of the vehicle during deceleration control in the historical driving data includes: determining a fifth acceleration value according to the acceleration data of the vehicle during deceleration control in the historical driving data; Determining a reference value of the fifth acceleration to obtain a third reference value; Determine the number of accelerations whose acceleration values ​​are greater than the third reference value among the fifth value accelerations to obtain a sixth value; determining a ratio of the sixth value to the fifth value to obtain a third ratio; The third adjustment coefficient is determined according to the third ratio.

9. The method according to any one of claims 1 to 8, characterized in that The step of determining an upper limit value and a lower limit value of the data of the first type according to the data of the first type in the historical driving data, and obtaining a first upper limit value and a first lower limit value respectively, comprises: Determining, based on the first type of data in the historical driving data, an average value and a standard deviation of the first type of data; Determine an upper limit value and a lower limit value corresponding to the first type of data of the vehicle to obtain a second upper limit value and a second lower limit value respectively; Determine a sum of the mean value and the standard deviation, and a difference between the mean value and the standard deviation to obtain a first difference; determining the smaller one of the sum value and the second upper limit value as the first upper limit value; The larger one of the first difference value and the second lower limit value is determined as the first lower limit value.

10. The method according to any one of claims 1 to 8, characterized in that The determining, according to the adjustment coefficient, the first upper limit value, and the first lower limit value, the first type of control parameter in the automatic parking mode includes: Calculate an average of the first upper limit value and the first lower limit value; Calculate the difference between the first upper limit and the first lower limit to obtain a second difference; Calculating the product of the second difference and the adjustment coefficient; A sum of one half of the product and the average value is determined as the first type of control parameter in the automatic parking mode.

11. A parking control device, characterized in that: include: A first module is configured to determine control parameters in an automatic parking mode based on historical driving data of the vehicle; A second module is configured to control the vehicle to perform automatic parking according to the automatic parking mode; The first module comprises: A first submodule is configured to determine the first type of control parameters in the automatic parking mode according to the first type of data in the historical driving data; The first submodule includes: a first subunit, configured to determine an adjustment coefficient of a control parameter of the first type; A second subunit is configured to determine an upper limit value and a lower limit value of the first type of data according to the first type of data in the historical driving data, and obtain a first upper limit value and a first lower limit value respectively; a third subunit, configured to determine the first type of control parameter in the automatic parking mode according to the adjustment coefficient, the first upper limit value, and the first lower limit value; The first subunit comprises: a first processing unit configured to determine a first adjustment coefficient of the control parameter according to an operation interval duration in the historical driving data, wherein the operation interval duration includes an interval duration between a brake pedal step and an accelerator pedal step that are adjacent in time, and the adjustment coefficient of the control parameter includes the first adjustment coefficient; The first processing unit comprises: A first execution unit is configured to determine a first value of operation interval durations according to the historical driving data; A second execution unit is configured to determine a reference value of the operation interval duration to obtain a first reference value; A third execution unit is configured to determine the number of operation intervals whose duration is less than the first reference value, and obtain a second value; a fourth execution unit, configured to determine a ratio of the second value to the first value to obtain a first ratio; The fifth execution unit is configured to determine the first adjustment coefficient according to the first ratio.

12. A vehicle, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute the steps of the method according to any one of claims 1 to 10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

14. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 10.

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