Vehicle control method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of vehicle control, and discloses a vehicle control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a plurality of groups of historical driving data combinations of a vehicle; wherein each group of historical driving data combination comprises external data and vehicle control data of one historical driving process; processing the plurality of groups of historical driving data combinations to establish or update a preset corresponding relationship between the external data and the vehicle control data; and obtaining current external data in the current driving process of the vehicle, and determining current vehicle control data based on the current external data and a preset corresponding relation, so as to control the vehicle based on the current vehicle control data. Therefore, the preset corresponding relation between the external data and the vehicle control data is established through the historical data of the vehicle, and the vehicle control data conforming to the driving habit of the user can be determined subsequently according to the current external data and the preset corresponding relation, so that the driving convenience and comfort are improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle control method, device, electronic device and storage medium. Background Art

[0002] With the continuous development of automobile technology, users' demand for intelligent and personalized automobiles is increasing. However, related automobile control systems often only have preset fixed control modes and cannot be adaptively adjusted according to users' actual usage habits and external environmental conditions.

[0003] Based on the fixed control mode, users will need to frequently perform manual operations to achieve control during driving, which not only reduces the convenience and comfort of driving, but also increases driving risks. Summary of the invention

[0004] In view of the above problems, the present application provides a vehicle control method, device, electronic device and storage medium, which establishes a preset correspondence between external data and vehicle control data through the vehicle's historical data, and can subsequently determine the vehicle control data that meets the user's driving habits based on the current external data and the preset correspondence, thereby improving the convenience and comfort of driving.

[0005] The first aspect of the present application provides a vehicle control method, comprising: obtaining multiple groups of historical driving data combinations of the vehicle; wherein each group of historical driving data combinations includes external data and vehicle control data of a historical driving process; processing the multiple groups of historical driving data combinations to establish or update a preset correspondence between the external data and the vehicle control data; obtaining current external data during the current driving process of the vehicle, and determining current vehicle control data based on the current external data and the preset correspondence, so as to control the vehicle based on the current vehicle control data.

[0006] In some specific embodiments, the step of processing multiple groups of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data includes: extracting a first characteristic parameter corresponding to the external data and a second characteristic parameter corresponding to the vehicle control data in each group of historical driving data combinations to form multiple groups of characteristic parameter combinations; screening out a target characteristic parameter combination from the multiple groups of characteristic parameter combinations according to a preset screening rule, and establishing a correspondence between the characteristic parameters in the target characteristic parameter combination as the preset correspondence between the external data and the vehicle control data.

[0007] In some specific embodiments, the step of screening out a target feature parameter combination from a plurality of feature parameter combinations according to preset screening rules includes: comparing the first feature parameter and the second feature parameter in the plurality of feature parameter combinations, and determining the feature parameter combination having the same correspondence between the first feature parameter and the second feature parameter and the largest number of identical features in the plurality of feature parameter combinations as the target feature parameter combination; or, comparing the first feature parameters in the plurality of feature parameter combinations, and determining the feature parameter combination having the second feature parameter closest to the mean feature parameter in the plurality of feature parameter combinations having the same first feature parameter as the target feature parameter combination; wherein the mean feature parameter is the mean parameter of the second feature parameter in the plurality of feature parameter combinations having the same first feature parameter.

[0008] In some specific embodiments, the first characteristic parameter in the characteristic parameter combination includes a preset quantitative characteristic parameter and a preset variable characteristic parameter; the step of screening out a target characteristic parameter combination from multiple groups of characteristic parameter combinations according to preset screening rules includes: determining, among the multiple groups of characteristic parameter combinations, a first characteristic parameter combination having the same preset quantitative characteristic parameter and different preset variable characteristic parameters; determining, among the first characteristic parameter combination, a second characteristic parameter combination corresponding to different preset variable characteristic parameters; and screening out the target characteristic parameter combination from the second characteristic parameter combination according to the preset screening rules.

[0009] In some specific embodiments, the steps of obtaining current external data during the current driving process of the vehicle and determining current vehicle control data based on the current external data and a preset correspondence include: obtaining a first characteristic parameter in the current external data during the current driving process of the vehicle; if the first characteristic parameter in the current external data is the same as the first characteristic parameter in the preset correspondence, then determining the second characteristic parameter corresponding to the first characteristic parameter in the current external data through the preset correspondence as the current vehicle control data.

[0010] In some specific embodiments, the step of processing multiple sets of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data includes: establishing a target prediction model; inputting the external data and vehicle control data in the multiple sets of historical driving data combinations into the target prediction model to obtain a preset correspondence between the external data and the vehicle control data through the target prediction model; wherein the external data includes preset quantitative feature parameters and preset variable feature parameters, and the preset correspondence includes preset relationships in which different preset variable feature parameters correspond to each other when the preset quantitative feature parameters are the same.

[0011] In some specific embodiments, the first characteristic parameter is an ambient temperature parameter, and the second characteristic parameter is an air conditioning parameter; or, the first characteristic parameter is a route parameter, and the second characteristic parameter is a suspension setting parameter.

[0012] The second aspect of the present application provides a vehicle control device, including: an acquisition module, used to acquire multiple groups of historical driving data combinations of the vehicle; wherein each group of historical driving data combinations includes external data and vehicle control data of a historical driving process; a processing module, used to process the multiple groups of historical driving data combinations to establish or update a preset correspondence between the external data and the vehicle control data; a control module, used to acquire current external data in the current driving process of the vehicle, and determine current vehicle control data based on the current external data and the preset correspondence, so as to control the vehicle based on the current vehicle control data.

[0013] A third aspect of the present application provides an electronic device, characterized in that it includes: a processor; and a memory for storing a computer program, which implements any of the above-mentioned vehicle control methods when the computer program is executed by the processor.

[0014] A fourth aspect of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, a vehicle control method as described above is implemented.

[0015] The present application has at least the following beneficial technical effects: Based on the vehicle control method, device, electronic device and storage medium provided by the present application, the method includes: obtaining multiple groups of historical driving data combinations of the vehicle; wherein each group of historical driving data combinations includes external data and vehicle control data of a historical driving process; processing multiple groups of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data; obtaining current external data during the current driving process of the vehicle, and determining current vehicle control data based on the current external data and the preset correspondence, so as to control the vehicle based on the current vehicle control data. Therefore, by establishing a preset correspondence between external data and vehicle control data through the historical data of the vehicle, the vehicle control data that meets the user's driving habits can be determined based on the current external data and the preset correspondence, thereby improving the convenience and comfort of driving.

[0016] The above description is only an overview of the technical solution of the embodiment of the present application. In order to more clearly understand the technical means of the embodiment of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present application. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0018] Figure 1 It is a flow chart of an embodiment of a vehicle control method provided by the present application;

[0019] Figure 2 is a flow chart of another embodiment of the vehicle control method provided by the present application;

[0020] Figure 3 is a flow chart of another embodiment of the vehicle control method provided by the present application;

[0021] Figure 4 is a flow chart of another embodiment of the vehicle control method provided by the present application;

[0022] Figure 5 is a flow chart of another embodiment of the vehicle control method provided by the present application;

[0023] Figure 6 is a flow chart of another embodiment of the vehicle control method provided by the present application;

[0024] Figure 7 is a structural block diagram of an embodiment of a vehicle control device provided by the present application;

[0025] Figure 8 It is a schematic diagram of the structural framework of an embodiment of the electronic device provided by the present application;

[0026] Fig. 9 It is a schematic diagram of the structural framework of an embodiment of the computer-readable storage medium provided by the present application. DETAILED DESCRIPTION

[0027] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0028] If there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features limited to "first" and "second" may explicitly or implicitly include at least one of the features. In addition, if the meaning of "and / or" appearing in the full text is to include three parallel schemes, taking "A and / or B" as an example, it includes scheme A, or scheme B, or a scheme that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0029] The first aspect of the present application provides a vehicle control method, Figure 1 1 is a flow chart of an embodiment of the vehicle control method provided by the present application. Figure 1 , the method comprises the following steps:

[0030] S101: Acquire multiple groups of historical driving data combinations of the vehicle; wherein each group of historical driving data combinations includes external data and vehicle control data of a historical driving process.

[0031] It should be understood that a vehicle generally has multiple historical driving processes within a historical period, and each historical driving process will correspond to external data and vehicle control data, so that each historical driving process will correspond to a historical driving data combination consisting of external data and historical vehicle control data.

[0032] Among them, external data and vehicle control data from multiple historical driving processes in a specific historical period can be obtained to form multiple groups of historical driving data combinations. Among them, the length of the historical period can be greater than a certain length to ensure the richness of the data. For example, it is set to one month. In addition, the end time of the historical period can be the current time to ensure that the data is relatively new.

[0033] Among them, the vehicle control data of the driving process is the control data of the vehicle components during the driving process, which determines the working status of the vehicle components, such as suspension control data, air conditioning control data, etc. The external data of the driving process is data other than the vehicle control data. The external data can reflect the time, route, environmental information, etc. of the driving process, and reflects the driving scene of the driving process.

[0034] S102: Processing multiple groups of historical driving data combinations to establish or update a preset corresponding relationship between external data and vehicle control data.

[0035] The plurality of historical driving data sets are processed, that is, the external data and the vehicle control data in the plurality of historical driving data sets are processed. The processing method can be preset, and this embodiment does not impose any specific limitation.

[0036] The purpose of processing the external data and the vehicle control data is to establish a correspondence between the external data and the vehicle control data as a preset correspondence. It should be understood that in the process of processing a large number of historical driving data combinations, some specific rules between the external data and the vehicle control data can generally be obtained, and these specific rules can generally reflect the user's driving habits. Among them, the preset correspondence in this step can be established based on these specific rules.

[0037] For example, when processing a large amount of historical driving data, it is found that when a certain type of external data appears, a certain type of vehicle control data generally appears. This is a specific rule between external data and vehicle control data. Then, according to this rule, a corresponding relationship can be preset, and the preset corresponding relationship includes the corresponding relationship between a certain type of external data and a certain type of vehicle control data.

[0038] S103: Acquire current external data during the current driving process of the vehicle, and determine current vehicle control data based on the current external data and a preset corresponding relationship, so as to control the vehicle based on the current vehicle control data.

[0039] It should be understood that the preset correspondence between external data and vehicle control data reflects the user's habitual setting of vehicle control data under specific external data during historical driving, and this habitual setting will often continue to subsequent driving processes.

[0040] Therefore, after obtaining the current external data during the current driving process of the vehicle, based on the trust in the continuation of the user's historical driving habits, the current vehicle control data is determined based on the current external data and the preset correspondence, that is, the vehicle control data corresponding to the external data that is the same as the current external data in the preset correspondence is used as the current vehicle control data.

[0041] At this time, the determined current vehicle control data is consistent with the user's driving habits, so the vehicle can be controlled based on the current vehicle control data to improve driving convenience and comfort.

[0042] Figure 2 It is a flow chart of another embodiment of the vehicle control method provided by the present application.

[0043] Combination Figure 2 In some specific embodiments, the step of processing a plurality of sets of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data, i.e., the above-mentioned step S102, includes:

[0044] S201: extracting a first characteristic parameter corresponding to external data and a second characteristic parameter corresponding to vehicle control data in each group of historical driving data combinations to form a plurality of groups of characteristic parameter combinations.

[0045] The external data may include multiple characteristic parameters, and the first characteristic parameter is a collection of multiple characteristic parameters. For example, the external data may include four characteristic parameters: driving time, driving route, environmental conditions, and the number of passengers in the vehicle. In this case, the first characteristic parameter may be any one or more of the four characteristic parameters.

[0046] Similarly, the vehicle control data may also include multiple characteristic parameters, and the second characteristic parameter is a collection of multiple characteristic parameters. For example, the vehicle control data may include air conditioning control parameters, vehicle speed control parameters, suspension control parameters, seat control parameters, power mode control parameters, energy recovery control parameters, etc. At this time, the second characteristic parameter may be any one of these characteristic parameters.

[0047] In this embodiment, we can select one or more characteristic parameters from the external data as the first characteristic parameter, and select one or more characteristic parameters from the vehicle control data as the second characteristic parameter, thereby forming multiple groups of characteristic parameter combinations consisting of the two characteristic parameters. It should be understood that due to the large number of historical driving data combinations, there may be a large number of characteristic parameter combinations.

[0048] S202: Filter out a target feature parameter combination from multiple sets of feature parameter combinations according to a preset filtering rule, and establish a correspondence between feature parameters in the target feature parameter combination as a preset correspondence between external data and vehicle control data.

[0049] The preset screening rules are pre-set, and this embodiment does not limit the preset screening rules. The target feature parameter combination is screened out from all feature parameter combinations according to the preset screening rules, that is, the feature parameter combination that meets the requirements is screened out as the target feature parameter combination through the preset screening rules.

[0050] It should be understood that the correspondence between the characteristic parameters in the selected target characteristic parameter combination, that is, the correspondence between the first characteristic parameter and the second characteristic parameter, is generally consistent with the user's historical driving habits. Therefore, the correspondence between the characteristic parameters in the target characteristic parameter combination can be used as a preset correspondence between external data and vehicle control data.

[0051] Figure 3 It is a flow chart of another embodiment of the vehicle control method provided by the present application.

[0052] Combination Figure 3In some specific embodiments, the step of selecting a target characteristic parameter combination from a plurality of characteristic parameter combinations according to a preset screening rule includes:

[0053] S301: Compare the first feature parameters and the second feature parameters in the plurality of feature parameter combinations, and determine the feature parameter combination in which the correspondence between the first feature parameters and the second feature parameters is the same and the number of the same features is the largest as the target feature parameter combination.

[0054] It should be understood that among multiple characteristic parameter combinations with the same first characteristic parameter, the second characteristic parameters of some characteristic parameter combinations may be the same, while the second characteristic parameters of some other combinations may be different. In this case, when the second characteristic parameters are the same, the characteristic parameter combinations are the same, and when the characteristic parameter combinations are the same, the corresponding relationship between the first characteristic parameter and the second characteristic parameter in the characteristic parameter combination is the same. Therefore, if the corresponding relationship between two sets of characteristic parameter combinations is the same, then the first characteristic parameters of the two sets of characteristic parameters are the same, and the second characteristic parameters are the same.

[0055] Among them, the correspondence between the first characteristic parameter and the second characteristic parameter in multiple sets of characteristic parameter combinations is the same, and the correspondence between the first characteristic parameter and the second characteristic parameter of the characteristic parameter combination with the largest number of identical ones reflects the user's driving habits under a specific external environment.

[0056] Therefore, when the correspondence between the first characteristic parameter and the second characteristic parameter in multiple sets of characteristic parameter combinations is the same and the characteristic parameter combination with the largest number of identical ones is determined as the target characteristic parameter combination, the correspondence obtained through the target characteristic parameter combination is consistent with the user's historical driving habits.

[0057] S302: Compare the first feature parameters in the multiple sets of feature parameter combinations, and determine the feature parameter combination whose second feature parameter is closest to the mean feature parameter in the multiple sets of feature parameter combinations with the same first feature parameter as the target feature parameter combination; wherein the mean feature parameter is the mean parameter of the second feature parameter in the multiple sets of feature parameter combinations with the same first feature parameter.

[0058] It should be understood that the sequence number of the steps in this embodiment does not limit the execution order of the steps, and the implementation methods provided by the two steps in this embodiment are two parallel implementation methods. Different from the above steps, the method for determining the target feature combination provided in this step only compares the first feature parameters of all feature parameter combinations.

[0059] In this step, multiple groups of characteristic parameter combinations with the same first characteristic parameter are first determined. Then, the mean parameter of the second characteristic parameter in the multiple groups of characteristic parameter combinations with the same first characteristic parameter is determined. Wherein, when the second characteristic parameter includes multiple characteristic parameters, the multiple characteristic parameters correspond to multiple mean parameters. It should be understood that this mean parameter reflects the user's historical average driving needs. Therefore, among the multiple groups of characteristic parameter combinations with the same first characteristic parameter, the characteristic parameter combination in which the second characteristic parameter is closest to the mean characteristic parameter is the characteristic parameter combination that is more in line with the user's historical average driving needs.

[0060] Therefore, when the feature parameter combination whose second feature parameter is closest to the mean feature parameter among multiple sets of feature parameter combinations with the same first feature parameter is determined as the target feature parameter combination, the corresponding relationship determined by the target feature parameter combination is more in line with the user's historical average driving needs.

[0061] Figure 4 It is a flow chart of another embodiment of the vehicle control method provided by the present application.

[0062] Combination Figure 4 The step of selecting a target feature parameter combination from multiple sets of feature parameter combinations according to a preset screening rule includes:

[0063] S401: Determine, from among a plurality of sets of feature parameter combinations, a first feature parameter combination having the same preset quantitative feature parameters and different preset variable feature parameters.

[0064] Among them, the first characteristic parameter in the characteristic parameter combination includes a preset quantitative characteristic parameter and a preset variable characteristic parameter, the preset quantitative characteristic parameter and the preset variable characteristic parameter are characteristic parameters of different categories respectively, and the preset quantitative characteristic parameter and the preset variable characteristic parameter can be set according to actual needs, and no specific restrictions are made here.

[0065] As described above, among all the feature parameter combinations, the first feature parameters in some feature parameter combinations may be the same. In this embodiment, the focus is not on the user's driving habits under the feature parameter combinations with the same first feature, but on the changes in the user's driving habits caused by the different preset variable parameters in the first feature parameters in the feature parameter combinations.

[0066] Among them, the characteristic parameter combination with the same preset quantitative characteristic parameters and different preset variable characteristic parameters will be used as the first characteristic parameter combination. Therefore, the first characteristic parameter combination actually reflects the change of the second characteristic parameter brought about by different preset variable characteristic parameters under the same preset quantitative characteristic parameters, that is, reflects the change of the user's driving habits brought about by different preset variable parameters.

[0067] S402: Determine, from the first characteristic parameter combinations, second characteristic parameter combinations corresponding to different preset variable characteristic parameters.

[0068] In combination with the above content, in the first characteristic parameter combination, only the preset variable characteristic parameters are different. At this time, different preset variable characteristic parameters may correspond to different second characteristic parameters, or may correspond to the same second characteristic parameters.

[0069] In this step, the first characteristic parameter combinations are grouped according to different preset variable characteristic parameters, and then divided into multiple groups of second characteristic parameter combinations, and different second characteristic parameter combinations correspond to different preset variable characteristic parameters.

[0070] S403: Filter out a target characteristic parameter combination from the second characteristic parameter combination according to a preset filtering rule.

[0071] Based on the above steps, different second characteristic parameter combinations corresponding to different preset variable characteristic parameters can be obtained. Among them, the preset screening rule is pre-set and is specifically used to screen out the target characteristic parameter combination from the second characteristic parameter combination. For example, the preset screening rule can be that if the second characteristic parameter combination under the same preset variable characteristic parameter is greater than a preset number, then the second characteristic parameter combination is used as the target characteristic parameter combination.

[0072] When the target characteristic parameter combination is screened out from the second characteristic parameter combination according to the preset screening rule, the screened out second characteristic parameter can represent the user's historical driving habits under a certain preset variable characteristic parameter.

[0073] Figure 5 It is a flow chart of another embodiment of the vehicle control method provided by the present application.

[0074] Combination Figure 4 In some specific embodiments, the step of determining the feature parameter combination with the second feature parameter closest to the mean feature parameter among the multiple feature parameter combinations having the same first feature parameter as the target feature parameter combination includes:

[0075] S501: Acquire a first characteristic parameter in current external data during the current driving process of the vehicle.

[0076] The description of the external data can refer to the description of the above embodiment, which will not be repeated here. The difference from the above embodiment is that the external data in the above embodiment is historical external data, while the external data in this embodiment is current external data.

[0077] Corresponding to establishing the correspondence between the first characteristic parameter and the second characteristic parameter in the target characteristic parameter combination as a preset correspondence between the external data and the vehicle control data, this embodiment obtains the first characteristic parameter in the current external data.

[0078] S502: If the first characteristic parameter in the current external data is the same as the first characteristic parameter in the preset corresponding relationship, determine the second characteristic parameter corresponding to the first characteristic parameter in the current external data according to the preset corresponding relationship as the current vehicle control data.

[0079] After obtaining the first characteristic parameter in the current external data, the first characteristic parameter is compared with the first characteristic parameter in the preset correspondence. If they are the same, the second characteristic parameter corresponding to the first characteristic parameter in the preset correspondence that is the same as the first characteristic parameter in the current external data is used as the vehicle control data.

[0080] Specifically, if the preset correspondence contains multiple sets of correspondences between first characteristic parameters and second characteristic parameters, the first characteristic parameters in the current external data are compared with the first characteristic parameters in the multiple sets of correspondences respectively, and the second characteristic parameters of the preset correspondence with the same first characteristic parameters are used as vehicle control data.

[0081] In some application scenarios, the first characteristic parameter is an ambient temperature parameter, and the second characteristic parameter is an air conditioning parameter. In this case, both the first characteristic parameter and the second characteristic parameter only include one type of characteristic parameter, that is, the first characteristic parameter only includes the ambient temperature parameter, and the second characteristic parameter only includes the air conditioning parameter.

[0082] It should be understood that there is a large correlation between the ambient temperature and the air conditioning parameters. For example, when the ambient temperature is low or high, the air conditioning is generally turned on, and the air conditioning parameters may be set differently based on the ambient temperature. Therefore, the first characteristic parameter and the second characteristic parameter are respectively determined as the ambient temperature data and the air conditioning parameter data, and the preset corresponding relationship finally obtained is more in line with the needs of the actual application scenario.

[0083] In some application scenarios, the first characteristic parameter is a route parameter, and the second characteristic parameter is a suspension setting parameter. Similarly, both the first characteristic parameter and the second characteristic parameter only include one type of characteristic parameter.

[0084] It should be understood that the setting parameters of the suspension are related to the driving comfort of the vehicle and are important setting parameters to ensure the driving comfort and safety of the vehicle. Different suspension setting parameters may be required for different routes due to different road conditions, so there is a high correlation between the route parameters and the suspension setting parameters. The first characteristic parameter is the route parameter, and the second characteristic parameter is the suspension setting parameter. The preset corresponding relationship finally obtained can significantly improve the driving comfort and safety of the vehicle when used.

[0085] Figure 6 It is a flow chart of another embodiment of the vehicle control method provided by the present application.

[0086] Combination Figure 6 In some specific embodiments, the step of processing a plurality of sets of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data includes:

[0087] S601: Establish a target prediction model.

[0088] The target prediction model can process big data to obtain a model of the correlation between the big data. The target prediction model can be a variety of models, which are set according to actual needs and are not specifically limited here.

[0089] S602: Inputting external data and vehicle control data in a combination of multiple groups of historical driving data into a target prediction model to obtain a preset corresponding relationship between the external data and the vehicle control data through the target prediction model; wherein the external data includes preset quantitative feature parameters and preset variable feature parameters, and the preset corresponding relationship includes preset relationships corresponding to different preset variable feature parameters when the preset quantitative feature parameters are the same.

[0090] After obtaining multiple sets of historical driving data combinations and establishing the target prediction model, all historical driving data combinations are input into the target prediction model, that is, the external data and vehicle control data of all historical driving data combinations are input into the target prediction model. Then, the target prediction model can obtain the preset corresponding relationship.

[0091] After the target prediction model obtains the preset corresponding relationship, the preset corresponding relationship can be retained in the target prediction model. In the subsequent process, the current external data can be input into the target prediction model, and then the current vehicle control data can be output through the target prediction model to control the vehicle driving.

[0092] In combination with the above content, for the specific form of the preset corresponding relationship, the preset corresponding relationship output by the model also includes the preset relationships corresponding to different preset variable characteristic parameters when the preset quantitative characteristic parameters are the same. Therefore, the preset corresponding relationship output by the model will also focus on the change characteristics of the vehicle control data when different preset variable characteristic parameters are different.

[0093] A second aspect of the present application provides a vehicle control device 20, Figure 7 It is a structural block diagram of an embodiment of the vehicle control device 20 provided in the present application.

[0094] Combination Figure 7The vehicle control device 20 includes an acquisition module 21, a processing module 22 and a control module 23. The acquisition module 21 is used to acquire multiple groups of historical driving data combinations of the vehicle; wherein each group of historical driving data combinations includes external data and vehicle control data of a historical driving process. The processing module 22 is used to process multiple groups of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data. The control module 23 is used to acquire the current external data in the current driving process of the vehicle, and determine the current vehicle control data based on the current external data and the preset correspondence, so as to control the vehicle based on the current vehicle control data. For the specific execution methods of the acquisition module 21, the processing module 22 and the control module 23 for the above steps, please refer to the relevant content of the above embodiment, and no further description will be given.

[0095] A third aspect of the present application provides an electronic device, comprising: a processor; and a memory for storing a computer program, wherein when the computer program is executed by the processor, the vehicle control method in any of the above embodiments is implemented.

[0096] Figure 8 It is a schematic diagram of the structural framework of an embodiment of the electronic device 500 provided in the present application.

[0097] In some specific embodiments, the electronic device 500 includes a central processing unit (CPU) 501 and a read-only memory (ROM) 502, wherein the CPU 501 is a processor and the ROM 502 is a memory. The CPU 501 can perform various appropriate actions and processes according to the program stored in the ROM 502 or the program loaded from the storage part 508 to the random access memory (RAM) 503, such as executing the method in the above embodiment. In the RAM 503, various programs and data required for system operation are also stored. The CPU 501, the ROM 502 and the RAM 503 are connected to each other through the bus 504. The input / output (I / O) interface 505 is also connected to the bus 504.

[0098] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed so that a computer program read therefrom is installed into the storage section 508 as needed.

[0099] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 509, and / or installed from a removable medium 511. When the computer program is executed by a central processing unit (CPU) 501, various functions defined in the system of the present application are executed.

[0100] A fourth aspect of the present application provides a computer-readable storage medium 40, Fig. 9 It is a schematic diagram of the structural framework of an embodiment of the computer-readable storage medium 40 provided in the present application.

[0101] Combination Fig. 9 A computer program 41 is stored on the computer-readable storage medium 40. When the computer program 41 is executed by the processor, the vehicle control method in any of the above embodiments is implemented.

[0102] It should be noted that the computer-readable medium 40 shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (Erasable Programmable Read On ly Memory, EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as a part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0103] In summary, based on the vehicle control method, device, electronic device and storage medium provided by the present application, the method includes: obtaining historical external data and historical vehicle control data during multiple historical driving processes of the vehicle; wherein the historical external data and historical vehicle control data of a historical driving process constitute a historical data combination; processing the historical external data and historical vehicle control data to establish a preset correspondence between the external data and the vehicle control data; obtaining the current external data during the current driving process of the vehicle, and determining the current vehicle control data based on the current external data and the preset correspondence, so as to control the vehicle based on the current vehicle control data. Therefore, by establishing a preset correspondence between external data and vehicle control data through the historical data of the vehicle, the vehicle control data that meets the user's driving habits can be determined based on the current external data and the preset correspondence, thereby improving the convenience and comfort of driving.

[0104] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. A person skilled in the art can easily make corresponding changes or modifications based on the main concept and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. A vehicle control method, characterized in that: include: Acquire multiple groups of historical driving data combinations of the vehicle; wherein each group of historical driving data combinations includes external data and vehicle control data of a historical driving process; Processing the plurality of sets of historical driving data combinations to establish or update a preset corresponding relationship between external data and vehicle control data; The current external data during the current driving process of the vehicle is acquired, and the current vehicle control data is determined based on the current external data and the preset corresponding relationship, so as to control the vehicle based on the current vehicle control data.

2. The vehicle control method according to claim 1, characterized in that: The step of processing the plurality of groups of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data includes: Extracting a first characteristic parameter corresponding to the external data and a second characteristic parameter corresponding to the vehicle control data in each group of historical driving data combinations to form a plurality of groups of characteristic parameter combinations; A target characteristic parameter combination is screened out from the plurality of characteristic parameter combinations according to a preset screening rule, and a corresponding relationship among characteristic parameters in the target characteristic parameter combination is established as a preset corresponding relationship between external data and vehicle control data.

3. The vehicle control method according to claim 2, characterized in that: The step of selecting a target characteristic parameter combination from the plurality of characteristic parameter combinations according to a preset screening rule comprises: Compare the first characteristic parameters and the second characteristic parameters in the plurality of characteristic parameter combinations, and determine the characteristic parameter combination with the same correspondence between the first characteristic parameters and the second characteristic parameters and the largest number of the same correspondences in the plurality of characteristic parameter combinations as the target characteristic parameter combination; or, Comparing the first characteristic parameters in the plurality of characteristic parameter combinations, determining the characteristic parameter combination whose second characteristic parameter is closest to the mean characteristic parameter among the plurality of characteristic parameter combinations having the same first characteristic parameter as the target characteristic parameter combination; The mean characteristic parameter is a mean parameter of the second characteristic parameter in a plurality of sets of characteristic parameter combinations having the same first characteristic parameter.

4. The vehicle control method according to claim 2, characterized in that: The first characteristic parameter in the characteristic parameter combination includes a preset quantitative characteristic parameter and a preset variable characteristic parameter; The step of selecting a target characteristic parameter combination from the plurality of characteristic parameter combinations according to a preset screening rule comprises: Determining, from among the plurality of sets of characteristic parameter combinations, a first characteristic parameter combination having the same preset quantitative characteristic parameter and different preset variable characteristic parameters; Determine, in the first characteristic parameter combination, a second characteristic parameter combination corresponding to different preset variable characteristic parameters; A target characteristic parameter combination is screened out from the second characteristic parameter combination according to a preset screening rule.

5. The vehicle control method according to claim 2, characterized in that: The step of obtaining current external data during the current driving process of the vehicle, and determining current vehicle control data based on the current external data and the preset corresponding relationship includes: Acquiring a first characteristic parameter in current external data during a current driving process of the vehicle; If the first characteristic parameter in the current external data is the same as the first characteristic parameter in the preset corresponding relationship, the second characteristic parameter corresponding to the first characteristic parameter in the current external data is determined according to the preset corresponding relationship as the current vehicle control data.

6. The vehicle control method according to claim 1, characterized in that: The step of processing the plurality of groups of historical driving data combinations to establish or update a preset correspondence between external data and vehicle control data includes: Establish target prediction model; Inputting the external data and the vehicle control data in the plurality of sets of historical driving data into the target prediction model, so as to obtain a preset corresponding relationship between the external data and the vehicle control data through the target prediction model; The external data includes preset quantitative characteristic parameters and preset variable characteristic parameters, and the preset corresponding relationship includes preset relationships corresponding to different preset variable characteristic parameters when the preset quantitative characteristic parameters are the same.

7. The vehicle control method according to claim 2, characterized in that: The first characteristic parameter is an ambient temperature parameter, and the second characteristic parameter is an air conditioning parameter; or, the first characteristic parameter is a route parameter, and the second characteristic parameter is a suspension setting parameter.

8. A vehicle control device, characterized in that: include: An acquisition module is used to acquire multiple groups of historical driving data combinations of the vehicle; wherein each group of historical driving data combinations includes external data and vehicle control data of a historical driving process; A processing module, used for processing the plurality of sets of historical driving data combinations to establish or update a preset corresponding relationship between external data and vehicle control data; The control module is used to obtain current external data during the current driving process of the vehicle, and determine current vehicle control data based on the current external data and the preset corresponding relationship, so as to control the vehicle based on the current vehicle control data.

9. An electronic device, characterized in that: include: processor; A memory for storing a computer program, wherein the computer program, when executed by the processor, implements the vehicle control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the vehicle control method according to any one of claims 1 to 7 is implemented.

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