New energy automobile early warning method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of new energy vehicles, in particular to a new energy vehicle early warning method and device, computer equipment and a storage medium. First historical data of the current driver is called from the first database, then the current driver is detected to obtain first detection data, if the first detection data exceeds the error range of the first historical data, the current driver needs to be reminded whether to enter an early warning mode or not, and if the current driver enters the early warning mode, the current driver is reminded to enter the early warning mode; the driving operation data of the current driver are monitored in real time, if the real-time driving data exceed the error range of the first historical driving data, early warning reminding needs to be sent out, the new energy automobile driven by the current driver is controlled, and the problem that danger is possibly generated due to the driving problem of the driver is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicles, and in particular to a new energy vehicle early warning method, device, computer equipment and storage medium. Background Art

[0002] New energy vehicles in a broad sense, also known as alternative fuel vehicles, include pure electric vehicles, fuel cell electric vehicles, and other vehicles that use all non-petroleum fuels, as well as hybrid electric vehicles, ethanol gasoline vehicles, and other vehicles that partially use non-petroleum fuels. All new energy vehicles currently in existence are included in this concept, which is specifically divided into six categories: hybrid vehicles, pure electric vehicles, fuel cell vehicles, alcohol ether fuel vehicles, natural gas vehicles, etc. However, when driving a new energy vehicle, the driver may accidentally step on the accelerator pedal or the driver may be fatigued or inattentive, which may lead to danger. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention proposes a new energy vehicle early warning method, device, computer equipment and storage medium, aiming to solve the problem that the driver may be in danger due to his own driving problems.

[0004] The technical solution proposed by the present invention is:

[0005] A new energy vehicle early warning method, the method comprising:

[0006] Get the first face information of the current driver;

[0007] Matching the first facial information with a first database to obtain first historical driving data of the current driver;

[0008] Detecting the current driving of the current driver to obtain first detection data;

[0009] determining whether the first detection data is within an error range with respect to the first historical driving data;

[0010] If not, reminding the current driver whether to enter the early warning mode;

[0011] If the early warning mode is entered, the driving operation data of the current driver is monitored in real time to obtain real-time driving data;

[0012] Determining whether the real-time driving data and the first historical driving data are within an error range;

[0013] If not, a warning reminder is issued and the new energy vehicle driven by the current driver is controlled.

[0014] Further, after the step of reminding the current driver whether to enter the early warning mode, the method further comprises:

[0015] If the user chooses not to enter the warning mode, the step of detecting the current driving of the current driver continues, and the number of rejections is recorded;

[0016] Determining whether the number of rejections is greater than a preset number;

[0017] If so, there will be no reminder to enter the warning mode in the current driving record.

[0018] Further, the step of determining whether the first detection data is within the error range of the first historical driving data includes:

[0019] extracting first acceleration data from the first detection data;

[0020] comparing the first acceleration data with acceleration data in first historical driving data;

[0021] If the two are similar, it is considered that the first detection data is within the error range of the first historical driving data;

[0022] If the two are not similar, it is considered that the first detection data is not within the error range of the first historical driving data.

[0023] Further, the step of determining whether the first detection data is within the error range of the first historical driving data includes:

[0024] Extracting first braking data from the first detection data;

[0025] comparing the first braking data with braking data in first historical driving data;

[0026] If the two are similar, it is considered that the first detection data is within the error range of the first historical driving data;

[0027] If the two are not similar, it is considered that the first detection data is not within the error range of the first historical driving data.

[0028] Furthermore, in the step of matching the first facial information with the first database to obtain the first historical driving data of the current driver, the following steps are included:

[0029] Performing facial feature matching on the first facial information in the first database;

[0030] If the match is successful, the corresponding historical driving data is retrieved from the first database to obtain the first historical driving data of the current driver.

[0031] Further, after the step of performing facial feature matching on the first facial information in the first database, the method further includes:

[0032] If the matching fails, a new driving data file is created for the current driver in the first database.

[0033] Furthermore, the step of issuing a warning reminder and controlling the new energy vehicle driven by the current driver includes:

[0034] Broadcasting a voice reminder to the current driver to enter the automatic driving mode;

[0035] The new energy vehicle currently driven by the driver enters the automatic driving mode.

[0036] The present invention also provides a new energy vehicle early warning device, the device comprising:

[0037] A first acquisition module, used to acquire first face information of the current driver;

[0038] A first matching module, used for matching the first facial information with a first database to obtain first historical driving data of the current driver;

[0039] A first detection module, used for detecting the current driving of the current driver to obtain first detection data;

[0040] A first judgment module, used to judge whether the first detection data is within an error range with the first historical driving data;

[0041] A first reminder module, used for reminding the current driver whether to enter the early warning mode if no;

[0042] A first real-time monitoring module is used to monitor the driving operation of the current driver in real time to obtain real-time driving data if the warning mode is entered;

[0043] A second judgment module, used to judge whether the real-time driving data and the first historical driving data are within an error range;

[0044] The first processing module is used to issue a warning reminder if the answer is no, and control the new energy vehicle driven by the current driver.

[0045] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above-mentioned methods when executing the computer program.

[0046] The present invention also provides 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 of the above-mentioned methods are implemented.

[0047] According to the above technical scheme, the beneficial effects of the present invention are as follows: the first historical data of the current driver is retrieved from the first database, and then the current driver is tested to obtain the first test data. If the first test data exceeds the error range of the first historical data, it is necessary to remind the current driver whether to enter the early warning mode. If the early warning mode is entered, the driving operation data of the current driver is monitored in real time. If the real-time driving data exceeds the error range of the first historical driving data, it is necessary to issue an early warning reminder and control the new energy vehicle driven by the current driver to solve the problem that the driver may be in danger due to his own driving problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a flow chart of a new energy vehicle early warning method provided by an embodiment of the present invention;

[0049] Figure 2 This is a functional module diagram of a new energy vehicle early warning device provided by an embodiment of the present invention;

[0050] Figure 3 It is a schematic block diagram of the structure of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0052] like Figure 1 As shown, an embodiment of the present invention provides a new energy vehicle early warning method, the method comprising:

[0053] Step S101, obtaining the first facial information of the current driver.

[0054] The driving seat is photographed by the camera inside the car, thereby photographing the current driver and obtaining the first facial information of the current driver.

[0055] Step S102: Match the first facial information with a first database to obtain first historical driving data of the current driver.

[0056] The vehicle system is connected to the cloud server and the first facial information is sent to the first database for feature matching. If the match is successful, the first historical driving data of the current driver will be obtained.

[0057] Step S103: Detect the current driving of the current driver to obtain first detection data.

[0058] The driving data of the current driver can be obtained through the vehicle computer system, and the current driving of the current driver can be detected to obtain the first detection data.

[0059] Step S104: determine whether the first detection data is within an error range with the first historical driving data.

[0060] First, it is determined whether the first detection data is within the range of the first historical data. If not, it is determined again whether the first detection data is within the error range of the first historical data.

[0061] Step S105: If not, remind the current driver whether to enter the early warning mode.

[0062] If the first detection data is not within the error range of the first historical data, then it is necessary to remind the current driver whether to enter the early warning mode.

[0063] Step S106: If the early warning mode is entered, the driving operation data of the current driver is monitored in real time to obtain real-time driving data.

[0064] The current driver can use voice control to decide whether to enter the warning mode. If the current driver chooses to enter the warning mode, the driving operation data of the current driver will be monitored in real time to obtain real-time driving data.

[0065] Furthermore, after receiving the voice selection of the current driver, the voiceprint features are extracted from the voice information, and then the extracted voiceprint features are compared with the voiceprint features in the first historical driving data. If the similarity is greater than a preset value, the voice selection of the current driver is responded to.

[0066] Step S107: Determine whether the real-time driving data and the first historical driving data are within an error range.

[0067] After entering the early warning mode, it is determined whether the real-time driving data is within an error range with respect to the first historical driving data.

[0068] Step S108: If not, a warning reminder is issued, and the new energy vehicle driven by the current driver is controlled.

[0069] If it is not within the error range, the new energy vehicle needs to be controlled.

[0070] The first historical data of the current driver is retrieved from the first database, and then the current driver is tested to obtain the first test data. If the first test data exceeds the error range of the first historical data, the current driver needs to be reminded whether to enter the early warning mode. If the early warning mode is entered, the driving operation data of the current driver is monitored in real time. If the real-time driving data exceeds the error range of the first historical driving data, a warning reminder needs to be issued and the new energy vehicle driven by the current driver is controlled to solve the possible danger caused by the driver's own driving problems.

[0071] In this embodiment, after step S105, the following steps are included:

[0072] If the user chooses not to enter the warning mode, the step of detecting the current driving of the current driver continues, and the number of rejections is recorded;

[0073] Determining whether the number of rejections is greater than a preset number;

[0074] If so, there will be no reminder to enter the warning mode in the current driving record.

[0075] If the current driver refuses to enter the early warning mode for multiple times, then no reminder will be given in the current driving record. Specifically, the preset number of times is three times, and the current driving record is from start to shutdown.

[0076] In this embodiment, the judgment step S104 includes:

[0077] extracting first acceleration data from the first detection data;

[0078] comparing the first acceleration data with acceleration data in first historical driving data;

[0079] If the two are similar, it is considered that the first detection data is within the error range of the first historical driving data;

[0080] If the two are not similar, it is considered that the first detection data is not within the error range of the first historical driving data.

[0081] By comparing the first acceleration data with the acceleration data of the first historical driving data, if the similarity is greater than a preset value, then the two are considered to be similar, and the first detection data is considered to be within the error range of the first historical driving data. On the contrary, if the similarity is less than or equal to the preset value, then the two are considered to be dissimilar, and the first detection data is considered to be not within the error range of the first historical driving data.

[0082] In this embodiment, the judgment step S104 includes:

[0083] Extracting first braking data from the first detection data;

[0084] comparing the first braking data with braking data in first historical driving data;

[0085] If the two are similar, it is considered that the first detection data is within the error range of the first historical driving data;

[0086] If the two are not similar, it is considered that the first detection data is not within the error range of the first historical driving data.

[0087] By comparing the first braking data with the braking data of the first historical driving data, if the similarity is greater than a preset value, then the two are considered to be similar, and the first detection data is considered to be within the error range of the first historical driving data. On the contrary, if the similarity is less than or equal to the preset value, then the two are considered to be dissimilar, and the first detection data is considered to be not within the error range of the first historical driving data.

[0088] In this embodiment, step S102 includes:

[0089] Performing facial feature matching on the first facial information in the first database;

[0090] If the match is successful, the corresponding historical driving data is retrieved from the first database to obtain the first historical driving data of the current driver.

[0091] The first database stores the facial feature information of each driver.

[0092] In this embodiment, after the step of performing facial feature matching on the first facial information in the first database, the method includes:

[0093] If the matching fails, a new driving data file is created for the current driver in the first database.

[0094] If the first face information is not matched in the first database, a new driving data file is created for the current driver.

[0095] In this embodiment, the step of issuing a warning reminder and controlling the new energy vehicle driven by the current driver includes:

[0096] Broadcasting a voice reminder to the current driver to enter the automatic driving mode;

[0097] The new energy vehicle currently driven by the driver enters the automatic driving mode.

[0098] If an error occurs again, the new energy vehicle will be controlled to enter the automatic driving mode and the information will be broadcast to the current driver.

[0099] like Figure 2 As shown, an embodiment of the present invention proposes a new energy vehicle early warning device 1, which includes a first acquisition module 11, a first matching module 12, a first detection module 13, a first judgment module 14, a first reminder module 15, a first real-time monitoring module 16, a second judgment module 17 and a first processing module 18.

[0100] The first acquisition module 11 is used to acquire the first face information of the current driver.

[0101] The driving seat is photographed by the camera inside the car, thereby photographing the current driver and obtaining the first facial information of the current driver.

[0102] The first matching module 12 is used to match the first facial information with a first database to obtain first historical driving data of the current driver.

[0103] The vehicle system is connected to the cloud server and the first facial information is sent to the first database for feature matching. If the match is successful, the first historical driving data of the current driver will be obtained.

[0104] The first detection module 13 is used to detect the current driving of the current driver to obtain first detection data.

[0105] The driving data of the current driver can be obtained through the vehicle computer system, and the current driving of the current driver can be detected to obtain the first detection data.

[0106] The first judgment module 14 is used to judge whether the first detection data is within an error range with the first historical driving data.

[0107] First, it is determined whether the first detection data is within the range of the first historical data. If not, it is determined again whether the first detection data is within the error range of the first historical data.

[0108] The first reminding module 15 is used for reminding the current driver whether to enter the early warning mode if no.

[0109] If the first detection data is not within the error range of the first historical data, then it is necessary to remind the current driver whether to enter the early warning mode.

[0110] The first real-time monitoring module 16 is used to monitor the driving operation data of the current driver in real time to obtain real-time driving data if the early warning mode is entered.

[0111] The current driver can use voice control to decide whether to enter the warning mode. If the current driver chooses to enter the warning mode, the driving operation data of the current driver will be monitored in real time to obtain real-time driving data.

[0112] Furthermore, after receiving the voice selection of the current driver, the voiceprint features are extracted from the voice information, and then the extracted voiceprint features are compared with the voiceprint features in the first historical driving data. If the similarity is greater than a preset value, the voice selection of the current driver is responded to.

[0113] The second judgment module 17 is used to judge whether the real-time driving data and the first historical driving data are within an error range.

[0114] After entering the early warning mode, it is determined whether the real-time driving data is within an error range with respect to the first historical driving data.

[0115] The first processing module 18 is used to issue a warning reminder if no, and control the new energy vehicle driven by the current driver.

[0116] If it is not within the error range, the new energy vehicle needs to be controlled.

[0117] The first historical data of the current driver is retrieved from the first database, and then the current driver is tested to obtain the first test data. If the first test data exceeds the error range of the first historical data, the current driver needs to be reminded whether to enter the early warning mode. If the early warning mode is entered, the driving operation data of the current driver is monitored in real time. If the real-time driving data exceeds the error range of the first historical driving data, a warning reminder needs to be issued and the new energy vehicle driven by the current driver is controlled to solve the possible danger caused by the driver's own driving problems.

[0118] In this embodiment, the device includes:

[0119] A first sub-processing module, configured to continue to execute the step of detecting the current driving of the current driver and record the number of rejections if the user chooses not to enter the warning mode;

[0120] A first sub-judgment module, used to judge whether the number of rejections is greater than a preset number;

[0121] The second sub-processing module is used to, if yes, not remind the driver to enter the early warning mode in the current driving record.

[0122] If the current driver refuses to enter the early warning mode for multiple times, then no reminder will be given in the current driving record. Specifically, the preset number of times is three times, and the current driving record is from start to shutdown.

[0123] In this embodiment, the first determination module 14 includes:

[0124] A first sub-extraction module, used to extract first acceleration data from the first detection data;

[0125] a first sub-comparison module, configured to compare the first acceleration data with acceleration data in first historical driving data;

[0126] a first sub-determination module, configured to consider that the first detection data is within an error range of the first historical driving data if the two are similar;

[0127] The second sub-determination module is configured to determine that the first detection data is not within an error range of the first historical driving data if the two are not similar.

[0128] By comparing the first acceleration data with the acceleration data of the first historical driving data, if the similarity is greater than a preset value, then the two are considered to be similar, and the first detection data is considered to be within the error range of the first historical driving data. On the contrary, if the similarity is less than or equal to the preset value, then the two are considered to be dissimilar, and the first detection data is considered to be not within the error range of the first historical driving data.

[0129] In this embodiment, the first determination module 14 includes:

[0130] A second sub-extraction module, used for extracting first braking data from the first detection data;

[0131] a second sub-comparison module, configured to compare the first braking data with braking data in first historical driving data;

[0132] a third sub-determination module, configured to consider that the first detection data is within an error range of the first historical driving data if the two are similar;

[0133] The fourth sub-determination module is used to determine that the first detection data is not within the error range of the first historical driving data if the two are not similar.

[0134] By comparing the first braking data with the braking data of the first historical driving data, if the similarity is greater than a preset value, then the two are considered to be similar, and the first detection data is considered to be within the error range of the first historical driving data. On the contrary, if the similarity is less than or equal to the preset value, then the two are considered to be dissimilar, and the first detection data is considered to be not within the error range of the first historical driving data.

[0135] In this embodiment, the first matching module 12 includes:

[0136] A first sub-matching module, used for performing facial feature matching on the first face information in the first database;

[0137] The first sub-retrieval module is used to retrieve the corresponding historical driving data from the first database if the match is successful, so as to obtain the first historical driving data of the current driver.

[0138] The first database stores the facial feature information of each driver.

[0139] In this embodiment, the device 1 comprises:

[0140] The first sub-establishment module is used to establish a new driving data file for the current driver in the first database if the matching fails.

[0141] If the first face information is not matched in the first database, a new driving data file is created for the current driver.

[0142] In this embodiment, the first processing module 18 includes:

[0143] A first sub-reminding module, configured to broadcast a voice reminder to the current driver to enter the automatic driving mode;

[0144] The first sub-control module is used to put the new energy vehicle driven by the current driver into an automatic driving mode.

[0145] If an error occurs again, the new energy vehicle will be controlled to enter the automatic driving mode and the information will be broadcast to the current driver.

[0146] like Figure 3 As shown, in an embodiment of the present invention, a computer device is also provided. The computer device may be a server, and its internal structure may be as shown in FIG. Figure 3 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as a model of a new energy vehicle early warning method. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a new energy vehicle early warning method is implemented.

[0147] The processor executes the steps of the new energy vehicle early warning method: obtaining the first face information of the current driver;

[0148] Matching the first facial information with a first database to obtain first historical driving data of the current driver;

[0149] Detecting the current driving of the current driver to obtain first detection data;

[0150] determining whether the first detection data is within an error range with respect to the first historical driving data;

[0151] If not, reminding the current driver whether to enter the early warning mode;

[0152] If the early warning mode is entered, the driving operation data of the current driver is monitored in real time to obtain real-time driving data;

[0153] Determining whether the real-time driving data and the first historical driving data are within an error range;

[0154] If not, a warning reminder is issued and the new energy vehicle driven by the current driver is controlled.

[0155] Those skilled in the art will understand that Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied.

[0156] The computer device of the embodiment of the present invention retrieves the first historical data of the current driver from the first database, and then detects the current driver to obtain the first detection data. If the first detection data exceeds the error range of the first historical data, it is necessary to remind the current driver whether to enter the early warning mode. If the early warning mode is entered, the driving operation data of the current driver is monitored in real time. If the real-time driving data exceeds the error range of the first historical driving data, it is necessary to issue an early warning reminder and control the new energy vehicle driven by the current driver to solve the problem that the driver may be in danger due to his own driving problems.

[0157] An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, a new energy vehicle early warning method is implemented, specifically: obtaining first face information of the current driver;

[0158] Matching the first facial information with a first database to obtain first historical driving data of the current driver;

[0159] Detecting the current driving of the current driver to obtain first detection data;

[0160] determining whether the first detection data is within an error range with respect to the first historical driving data;

[0161] If not, reminding the current driver whether to enter the early warning mode;

[0162] If the early warning mode is entered, the driving operation data of the current driver is monitored in real time to obtain real-time driving data;

[0163] Determining whether the real-time driving data and the first historical driving data are within an error range;

[0164] If not, a warning reminder is issued and the new energy vehicle driven by the current driver is controlled.

[0165] The storage medium of the embodiment of the present invention retrieves the first historical data of the current driver from the first database, and then detects the current driver to obtain the first detection data. If the first detection data exceeds the error range of the first historical data, it is necessary to remind the current driver whether to enter the early warning mode. If the early warning mode is entered, the driving operation data of the current driver is monitored in real time. If the real-time driving data exceeds the error range of the first historical driving data, it is necessary to issue an early warning reminder and control the new energy vehicle driven by the current driver to solve the problem that the driver may be in danger due to his own driving problems.

[0166] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0167] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A new energy vehicle early warning method, characterized in that: The method comprises: Get the first face information of the current driver; Matching the first facial information with a first database to obtain first historical driving data of the current driver; Detecting the current driving of the current driver to obtain first detection data; determining whether the first detection data is within an error range with respect to the first historical driving data; If not, reminding the current driver whether to enter the early warning mode; If the early warning mode is entered, the driving operation of the current driver is monitored in real time to obtain real-time driving data; Determining whether the real-time driving data and the first historical driving data are within an error range; If not, a warning reminder is issued and the new energy vehicle driven by the current driver is controlled.

2. The new energy vehicle early warning method according to claim 1, characterized in that: After the step of reminding the current driver whether to enter the early warning mode, the method includes: If the user chooses not to enter the warning mode, the step of detecting the current driving of the current driver continues, and the number of rejections is recorded; Determining whether the number of rejections is greater than a preset number; If so, there will be no reminder to enter the warning mode in the current driving record.

3. The new energy vehicle early warning method according to claim 1, characterized in that: The step of determining whether the first detection data is within the error range of the first historical driving data includes: extracting first acceleration data from the first detection data; comparing the first acceleration data with acceleration data in first historical driving data; If the two are similar, it is considered that the first detection data is within the error range of the first historical driving data; If the two are not similar, it is considered that the first detection data is not within the error range of the first historical driving data.

4. The new energy vehicle early warning method according to claim 1, characterized in that: The step of determining whether the first detection data is within the error range of the first historical driving data includes: Extracting first braking data from the first detection data; comparing the first braking data with braking data in first historical driving data; If the two are similar, it is considered that the first detection data is within the error range of the first historical driving data; If the two are not similar, it is considered that the first detection data is not within the error range of the first historical driving data.

5. The new energy vehicle early warning method according to claim 1, characterized in that: The step of matching the first facial information with the first database to obtain the first historical driving data of the current driver includes: Performing facial feature matching on the first facial information in the first database; If the match is successful, the corresponding historical driving data is retrieved from the first database to obtain the first historical driving data of the current driver.

6. The new energy vehicle early warning method according to claim 5, characterized in that: After the step of performing facial feature matching on the first face information in the first database, the method includes: If the matching fails, a new driving data file is created for the current driver in the first database.

7. The new energy vehicle early warning method according to claim 1, characterized in that: The step of issuing a warning reminder and controlling the new energy vehicle driven by the current driver includes: Broadcasting a voice reminder to the current driver to enter the automatic driving mode; The new energy vehicle currently driven by the driver enters the automatic driving mode.

8. A new energy vehicle early warning device, characterized in that: The device comprises: A first acquisition module, used to acquire first face information of the current driver; A first matching module, used for matching the first facial information with a first database to obtain first historical driving data of the current driver; A first detection module, used for detecting the current driving of the current driver to obtain first detection data; A first judgment module, used to judge whether the first detection data is within an error range with the first historical driving data; A first reminder module, used for reminding the current driver whether to enter the early warning mode if no; A first real-time monitoring module is used to monitor the driving operation of the current driver in real time to obtain real-time driving data if the warning mode is entered; A second judgment module, used to judge whether the real-time driving data and the first historical driving data are within an error range; The first processing module is used to issue a warning reminder if the answer is no, and control the new energy vehicle driven by the current driver.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. 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 7 are implemented.

Images