A vehicle disconnection warning method, device, equipment and storage medium

Abstract

The present application discloses a vehicle disconnection warning method, device, equipment and storage medium, which periodically collects the vehicle TBOX voltage; determines the change trend of the vehicle TBOX voltage through a preset linear regression model to judge whether the vehicle has a disconnection risk. It is realized that only the vehicle TBOX voltage can be used to effectively judge whether the vehicle has a disconnection risk, effectively ensuring the driving safety of the vehicle, and the judgment is based on the vehicle TBOX voltage data, with high versatility. The vehicle TBOX voltage data is processed through a linear regression model, with small calculation amount and high data processing efficiency, which can effectively improve the efficiency of vehicle disconnection risk judgment.

Description

Technical Field

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

[0002] With the development of society, cars have become an indispensable means of transportation in people's lives. The on-board telematics terminal TBOX (Telematics-BOX) is an important device on the vehicle. It is used to monitor the vehicle's real-time fuel consumption, engine water temperature, engine speed, vehicle mileage, GPS vehicle location and other data in real time, and can obtain vehicle fault diagnosis information based on this information, and transmit this information to the user to remind the user to deal with these problems in a timely manner. It greatly improves the user's driving safety. TBOX can also be connected to the mobile terminal through the APP to realize the control of the vehicle through the mobile terminal, such as: remote opening of the car door, remote opening of the car window, remote opening of the trunk, remote opening of the air conditioner, etc., which greatly improves the riding experience of the driver and passengers.

[0003] However, in case of battery aging or circuit failure, the on-board TBOX voltage may be lower than the normal operating voltage of 16V, which may cause the TBOX to be disconnected and unable to work, resulting in vehicle disconnection, posing a serious safety hazard to vehicle driving.

[0004] Therefore, how to provide early warning for vehicle disconnection caused by TBOX disconnection is a technical problem that needs to be solved. Summary of the invention

[0005] The main purpose of the present application is to provide a vehicle disconnection warning method, device, equipment and storage medium, aiming to solve the technical problem of how to provide a disconnection warning before the vehicle is disconnected to avoid dangerous driving of the vehicle.

[0006] In a first aspect, the present application provides a vehicle disconnection warning method, the method comprising the following steps:

[0007] Periodically collect the on-board TBOX voltage;

[0008] The preset linear regression model is used to determine the change trend of the on-board TBOX voltage to judge whether the vehicle is at risk of disconnection.

[0009] In some embodiments, after periodically collecting the on-board TBOX voltage, before determining the change trend of the on-board TBOX voltage by a preset linear regression model to determine whether the vehicle has a disconnection risk, the following steps are also included:

[0010] Divide every M adjacent periods into a time segment;

[0011] And according to the collection order of the on-board TBOX voltage, the on-board TBOX voltage in the time segment is marked with a collection sequence number.

[0012] In some embodiments, a preset linear regression model is used to determine the change trend of the vehicle-mounted TBOX voltage to determine whether the vehicle has a disconnection risk, specifically including the following steps:

[0013] Input the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage into the linear regression model, and obtain the disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the change trend of the vehicle-mounted TBOX voltage;

[0014] Determine whether the vehicle has a disconnection risk according to the disconnection risk coefficient.

[0015] In some embodiments, the on-board TBOX voltage collected in a time segment and the collection sequence number corresponding to the on-board TBOX voltage are input into the linear regression model to obtain the disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the on-board TBOX voltage change trend, specifically including the following steps:

[0016] A linear regression curve is fitted based on the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage:

[0017] y=ax+b

[0018] Among them, x is the collection sequence number corresponding to the on-board TBOX voltage in the time segment, y is the on-board TBOX voltage collected in the time segment, a is the disconnection risk coefficient corresponding to the time segment, and b is a constant. When the change trend of the on-board TBOX voltage is increasing, a is larger, and when the change trend of the on-board TBOX voltage is decreasing, a is smaller.

[0019] In some embodiments, determining whether the vehicle has a disconnection risk according to the disconnection risk coefficient specifically includes the following steps:

[0020] If the disconnection risk coefficient is greater than 0, it is determined that there is no disconnection risk for the vehicle in the corresponding time segment;

[0021] If the disconnection risk coefficient is less than 0, it is determined that there is a disconnection risk for the vehicle within the corresponding time segment.

[0022] In some embodiments, the following steps are also included:

[0023] If it is determined that the vehicle is at risk of disconnection within N consecutive time segments, a vehicle disconnection warning is sent.

[0024] In a second aspect, the present application further provides a vehicle disconnection warning device, the device comprising:

[0025] A collection module, which is used to periodically collect the on-board TBOX voltage;

[0026] The determination module is used to determine the change trend of the vehicle-mounted TBOX voltage through a preset linear regression model to determine whether the vehicle has a disconnection risk.

[0027] In some embodiments, the device is also used to:

[0028] Divide every M adjacent periods into a time segment;

[0029] And according to the collection order of the on-board TBOX voltage, the on-board TBOX voltage in the time segment is marked with a collection sequence number.

[0030] In some embodiments, the determining module is further configured to:

[0031] Input the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage into the linear regression model, and obtain the disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the change trend of the vehicle-mounted TBOX voltage;

[0032] Determine whether the vehicle has a disconnection risk according to the disconnection risk coefficient.

[0033] In some embodiments, the determining module is further configured to:

[0034] A linear regression curve is fitted based on the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage:

[0035] y=ax+b

[0036] Among them, x is the collection sequence number corresponding to the on-board TBOX voltage in the time segment, y is the on-board TBOX voltage collected in the time segment, and a is the disconnection risk coefficient corresponding to the time segment. When the change trend of the on-board TBOX voltage is increasing, a is larger, and when the change trend of the on-board TBOX voltage is decreasing, a is smaller.

[0037] In some embodiments, the determining module is further configured to:

[0038] If the disconnection risk coefficient is greater than 0, it is determined that there is no disconnection risk for the vehicle in the corresponding time segment;

[0039] If the disconnection risk coefficient is less than 0, it is determined that there is a disconnection risk for the vehicle within the corresponding time segment.

[0040] In some embodiments, the vehicle disconnection warning device is also used to:

[0041] If it is determined that the vehicle is at risk of disconnection within N consecutive time segments, a vehicle disconnection warning is sent.

[0042] In a third aspect, the present application also provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the vehicle disconnection warning method as described above are implemented.

[0043] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the vehicle disconnection warning method as described above are implemented.

[0044] The present application provides a vehicle disconnection warning method, device, equipment and storage medium, which periodically collects the vehicle TBOX voltage; determines the change trend of the vehicle TBOX voltage through a preset linear regression model to judge whether the vehicle has a disconnection risk. It is realized that only the vehicle TBOX voltage can be used to effectively judge whether the vehicle has a disconnection risk, effectively ensuring the driving safety of the vehicle, and the judgment is based on the vehicle TBOX voltage data, with high versatility. The vehicle TBOX voltage data is processed through a linear regression model, with small calculation amount and high data processing efficiency, which can effectively improve the efficiency of vehicle disconnection risk judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 A schematic diagram of a process flow of a vehicle disconnection warning method provided in an embodiment of the present application;

[0047] Figure 2 This is a schematic diagram of the on-board TBOX voltage storage process;

[0048] Figure 3 It is a schematic diagram of the vehicle-mounted TBOX voltage collected in a time segment;

[0049] Figure 4 It is a schematic diagram of the linear regression curve;

[0050] Figure 5A schematic block diagram of a vehicle disconnection warning device provided in an embodiment of the present application;

[0051] Figure 6 The present invention is a block diagram showing the structure of a computer device according to an embodiment of the present application.

[0052] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. 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 this application.

[0054] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0055] The embodiment of the present application provides a vehicle disconnection warning method, device, equipment and storage medium. The vehicle disconnection warning method can be applied to a computer device, and the computer can be an electronic device such as a vehicle-mounted computer.

[0056] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0057] Please refer to Figure 1 , Figure 1 A flowchart of a vehicle disconnection warning method provided in an embodiment of the present application.

[0058] like Figure 1 As shown, the method includes steps S1 to S2.

[0059] Step S1: periodically collect the vehicle-mounted TBOX voltage.

[0060] As a preferred implementation, in this embodiment, the cycle of collecting the vehicle-mounted TBOX voltage is 1 second, that is, the vehicle-mounted TBOX voltage is collected once every second. And when collecting the vehicle-mounted TBOX voltage, since the vehicle-mounted TBOX voltage states are different when the vehicle is in motion and when it is parked, the vehicle-mounted TBOX voltage can be collected in one of the states of the vehicle in motion or in the parked state.

[0061] Furthermore, after collecting the on-board TBOX voltage, every M adjacent cycles are divided into a time segment; and the on-board TBOX voltage in the time segment is marked with a collection sequence number according to the collection order of the on-board TBOX voltage. After a large amount of data analysis, the possible vehicle disconnection stage caused by the on-board TBOX disconnection is concentrated in the 10 minutes before the disconnection. Therefore, in this embodiment, every 10 adjacent cycles are divided into a time segment, that is, a time segment is ten minutes, and each time segment includes 10 on-board TBOX voltage data. And when it is the on-board TBOX voltage, the first collected on-board TBOX voltage in the time segment is marked as sequence number 1, and the second collected on-board TBOX voltage in the time segment is marked as sequence number 2, and so on.

[0062] In some embodiments, Figure 2 As shown, after the vehicle-mounted TBOX voltage is collected, the collected data is uploaded to the general wireless packet service GPRS network, and then uploaded to the set data storage center through the Internet network. The vehicle-mounted TBOX voltage data is stored by the data storage center, wherein the data storage center can be the Internet of Vehicles information service background.

[0063] Step S2: Determine the change trend of the vehicle-mounted TBOX voltage through a preset linear regression model to determine whether the vehicle has a disconnection risk.

[0064] Specifically, the on-board TBOX voltage collected within a time segment and the collection sequence number corresponding to the on-board TBOX voltage are input into the linear regression model to obtain a disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the on-board TBOX voltage change trend; and whether the vehicle has a disconnection risk is determined based on the disconnection risk coefficient.

[0065] Exemplarily, the data input into the linear regression model includes two parts, the first part is the vehicle TBOX voltage y=(27.6, 27.8, 27.10, 27.14, 26.18, 26.1, 25.4, 25.3, 25.2, 25.1) collected in the time segment, and the second part is the collection sequence number of the vehicle TBOX voltage x=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10). The points corresponding to the vehicle TBOX voltage collected in the time segment and the collection sequence number of the vehicle TBOX voltage are represented in the graph as follows: Figure 3 shown.

[0066] Furthermore, a linear regression curve is fitted according to the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage:

[0067] y=ax+b

[0068] Among them, x is the collection sequence number corresponding to the on-board TBOX voltage in the time segment, y is the on-board TBOX voltage collected in the time segment, a is the disconnection risk coefficient corresponding to the time segment, and b is a constant. When the change trend of the on-board TBOX voltage is increasing, a is larger, and when the change trend of the on-board TBOX voltage is decreasing, a is smaller.

[0069] Exemplarily, the linear regression model in the embodiment of the present application can adopt the linear regression model Model=LinerRegression() of the Sklearn module. The on-board TBOX voltage collected in the time segment and the collection number of the on-board TBOX voltage are input into the linear regression model for training Model.fit(x,y), and finally the linear regression model is obtained to fit the linear regression curve y=ax+b. In the curve, y is the on-board TBOX voltage, and x is the collection number corresponding to the on-board TBOX voltage. a is the focus of attention. According to the linear regression curve y=ax+b, it can be seen that a is related to the changing trend of the on-board TBOX voltage. The greater the increase in the on-board TBOX voltage, the larger a is, and the greater the decrease in the on-board TBOX voltage, the smaller a is, and it is a negative value.

[0070] Furthermore, determining whether the vehicle has a disconnection risk based on the disconnection risk coefficient specifically includes the following steps: if the disconnection risk coefficient is greater than 0, determining that the vehicle has no disconnection risk within the corresponding time segment; if the disconnection risk coefficient is less than 0, determining that the vehicle has a disconnection risk within the corresponding time segment.

[0071] It is worth noting that according to the linear regression curve y=ax+b, it can be seen that a is related to the change trend of the on-board TBOX voltage. When the change trend of the on-board TBOX voltage is increasing, a is a positive value, and the greater the increase, the greater a is. When the change trend of the on-board TBOX voltage is decreasing, a is a negative value, and the greater the decrease, the smaller a is. If the change trend of the on-board TBOX voltage is decreasing, there is a situation where the on-board TBOX voltage decreases to a voltage lower than 16V that cannot work, resulting in a disconnection. Therefore, it can be judged whether the vehicle is at risk of disconnection based on whether a in the linear regression curve is greater than 0. When a is greater than 0, the on-board TBOX voltage is increasing or stable, so there is no risk of disconnection. When a is less than 0, the on-board TBOX voltage is decreasing, so there is a risk of disconnection.

[0072] In this embodiment, after the on-board TBOX voltage and the collection sequence number of the on-board TBOX voltage collected in the above-mentioned time segment are input into the linear regression model for training, the obtained linear regression curve is y=-1 / 3*X+28.125. It can be seen that the disconnection risk coefficient a is -1 / 3, and a is less than 0. Therefore, it can be determined that there is a disconnection risk for the vehicle in the current time segment.

[0073] Further, if it is determined that the vehicle has a disconnection risk in N consecutive time segments, a vehicle disconnection warning is sent. In this embodiment, it is determined that the vehicle has a disconnection risk in 6 consecutive time segments, and a vehicle disconnection warning is sent.

[0074] It is worth mentioning that after judging whether there is a risk of disconnection in each time segment based on the on-board TBOX voltage, the judgment result will also be stored in the data storage center. After judging whether there is a risk in each time segment, the results of the last 6 time segments stored in the database are scanned once. Once it is detected that the results of the judgments in the last 6 time segments are all that there is a risk of disconnection, a vehicle disconnection warning is sent to inform the owner of the risk of disconnection, so that the owner can repair the vehicle in time.

[0075] In some embodiments, when the vehicle sends a vehicle disconnection warning, if the vehicle is parked, the owner can be informed of the possible disconnection risk by text message or phone call. If the vehicle is in driving, in addition to informing the owner of the possible disconnection risk by text message or phone call, the driver can also be reminded of the vehicle disconnection risk by lighting up the indicator light and sounding the alarm in the car, so that the driver can take measures as soon as possible to eliminate the risk, thereby ensuring driving safety.

[0076] The present application provides a vehicle disconnection warning method, device, equipment and storage medium, which periodically collects the vehicle-mounted TBOX voltage; determines the change trend of the vehicle-mounted TBOX voltage through a preset linear regression model to judge whether the vehicle has a disconnection risk. It is realized that only the vehicle-mounted TBOX voltage can be used to effectively judge whether the vehicle has a disconnection risk, effectively ensuring the driving safety of the vehicle, and the judgment is based on the vehicle-mounted TBOX voltage data, with high versatility. The vehicle-mounted TBOX voltage data is processed through a linear regression model, with small calculation amount and high data processing efficiency, which can effectively improve the efficiency of vehicle disconnection risk judgment. And the judgment is made by dividing the vehicle-mounted TBOX voltage within the time segment, so that the judgment result is more accurate and effective.

[0077] Please refer to Figure 5 , Figure 5 A schematic block diagram of a vehicle disconnection warning device provided in an embodiment of the present application.

[0078] like Figure 5 As shown, the device includes a collection module and a determination module.

[0079] The acquisition module is used to periodically collect the on-board TBOX voltage.

[0080] As a preferred implementation, the acquisition module is used to acquire the vehicle-mounted TBOX voltage in a cycle of 1 second, that is, the vehicle-mounted TBOX voltage is acquired once every second. And when acquiring the vehicle-mounted TBOX voltage, since the vehicle-mounted TBOX voltage states are different when the vehicle is in motion and when it is parked, one of the vehicle-mounted states or the parked state can be selected to acquire the vehicle-mounted TBOX voltage.

[0081] The device is also used for: dividing every M adjacent cycles into a time segment; and marking a collection sequence number for the on-board TBOX voltage in the time segment according to the collection sequence of the on-board TBOX voltage.

[0082] Specifically, after collecting the on-board TBOX voltage, every M adjacent cycles are divided into a time segment; and the on-board TBOX voltage in the time segment is marked with a collection sequence number according to the collection order of the on-board TBOX voltage. After a large amount of data analysis, the possible vehicle disconnection caused by the on-board TBOX disconnection is concentrated in the 10 minutes before the disconnection. Therefore, in this embodiment, every 10 adjacent cycles are divided into a time segment, that is, a time segment is ten minutes, and each time segment includes 10 on-board TBOX voltage data. And when it is the on-board TBOX voltage, the first collected on-board TBOX voltage in the time segment is marked as sequence number 1, and the second collected on-board TBOX voltage in the time segment is marked as sequence number 2, and so on.

[0083] The determination module is used to determine the change trend of the on-board TBOX voltage through a preset linear regression model to determine whether the vehicle has a disconnection risk.

[0084] In some embodiments, the determination module is also used to: input the on-board TBOX voltage collected within a time segment and the collection sequence number corresponding to the on-board TBOX voltage into the linear regression model, and obtain the disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the on-board TBOX voltage change trend; determine whether the vehicle has a disconnection risk based on the disconnection risk coefficient.

[0085] Exemplarily, the data input into the linear regression model includes two parts, the first part is the vehicle TBOX voltage y=(27.6, 27.8, 27.10, 27.14, 26.18, 26.1, 25.4, 25.3, 25.2, 25.1) collected in the time segment, and the second part is the collection sequence number of the vehicle TBOX voltage x=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10). The points corresponding to the vehicle TBOX voltage collected in the time segment and the collection sequence number of the vehicle TBOX voltage are represented in the graph as follows: Figure 3 shown.

[0086] In some embodiments, the determination module is further used to fit a linear regression curve according to the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage:

[0087] y=ax+b

[0088] Among them, x is the collection sequence number corresponding to the on-board TBOX voltage in the time segment, y is the on-board TBOX voltage collected in the time segment, a is the disconnection risk coefficient corresponding to the time segment, and b is a constant. When the change trend of the on-board TBOX voltage is increasing, a is larger, and when the change trend of the on-board TBOX voltage is decreasing, a is smaller.

[0089] Exemplarily, the linear regression model in the embodiment of the present application can adopt the linear regression model Model=LinerRegression() of the Sklearn module. The on-board TBOX voltage collected in the time segment and the collection number of the on-board TBOX voltage are input into the linear regression model for training Model.fit(x,y), and finally the linear regression model is obtained to fit the linear regression curve y=ax+b. In the curve, y is the on-board TBOX voltage, and x is the collection number corresponding to the on-board TBOX voltage. a is the focus of attention. According to the linear regression curve y=ax+b, it can be seen that a is related to the changing trend of the on-board TBOX voltage. The greater the increase in the on-board TBOX voltage, the larger a is, and the greater the decrease in the on-board TBOX voltage, the smaller a is, and it is a negative value.

[0090] Furthermore, determining whether the vehicle has a disconnection risk based on the disconnection risk coefficient specifically includes the following steps: if the disconnection risk coefficient is greater than 0, determining that the vehicle has no disconnection risk within the corresponding time segment; if the disconnection risk coefficient is less than 0, determining that the vehicle has a disconnection risk within the corresponding time segment.

[0091] In some embodiments, the determination module is also used to: if the disconnection risk coefficient is greater than 0, determine that there is no disconnection risk for the vehicle within the corresponding time segment; if the disconnection risk coefficient is less than 0, determine that there is a disconnection risk for the vehicle within the corresponding time segment.

[0092] It is worth noting that according to the linear regression curve y=ax+b, it can be seen that a is related to the change trend of the on-board TBOX voltage. When the change trend of the on-board TBOX voltage is increasing, a is a positive value, and the greater the increase, the greater a is. When the change trend of the on-board TBOX voltage is decreasing, a is a negative value, and the greater the decrease, the smaller a is. If the change trend of the on-board TBOX voltage is decreasing, there is a situation where the on-board TBOX voltage decreases to a voltage lower than 116V that cannot work, resulting in a disconnection. Therefore, it can be judged whether the vehicle is at risk of disconnection based on whether a in the linear regression curve is greater than 0. When a is greater than 0, the on-board TBOX voltage is increasing or stable, so there is no risk of disconnection. When a is less than 0, the on-board TBOX voltage is decreasing, so there is a risk of disconnection.

[0093] In some embodiments, the vehicle disconnection warning device is further used to send a vehicle disconnection warning if it is determined that the vehicle is at risk of disconnection in N consecutive time segments.

[0094] In this embodiment, it is determined that the vehicle is at risk of disconnection within six consecutive time segments, and a vehicle disconnection warning is sent.

[0095] It is worth mentioning that after judging whether there is a risk of disconnection in each time segment based on the on-board TBOX voltage, the judgment result will also be stored in the data storage center. After judging whether there is a risk in each time segment, the results of the last 6 time segments stored in the database are scanned once. Once it is detected that the results of the judgments in the last 6 time segments are all that there is a risk of disconnection, a vehicle disconnection warning is sent to inform the owner of the risk of disconnection, so that the owner can repair the vehicle in time.

[0096] When the vehicle sends a disconnection warning, if the vehicle is parked, the owner can be informed of the possible disconnection risk by SMS or phone call. If the vehicle is in driving, in addition to informing the owner of the possible disconnection risk by SMS or phone call, the driver can also be reminded of the disconnection risk by lighting up the indicator light and sounding the alarm in the car, so that the driver can take measures as soon as possible to eliminate the risk and ensure driving safety.

[0097] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules and units can refer to the corresponding processes in the aforementioned embodiments and will not be repeated here.

[0098] The apparatus provided in the above embodiment may be implemented in the form of a computer program. The computer program may be Figure 6 Runs on the computer device shown.

[0099] See also Figure 6 , Figure 6 The present invention provides a schematic block diagram of a computer device provided in an embodiment of the present invention. The computer device may be a vehicle-mounted computer.

[0100] like Figure 6 As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0101] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any vehicle disconnection warning method.

[0102] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0103] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any vehicle disconnection warning method.

[0104] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0105] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0106] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. The computer program includes program instructions. The method implemented when the program instructions are executed can refer to the various embodiments of the present application.

[0107] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc., equipped on the computer device.

[0108] In the description of the present application, it should be noted that the terms "upper", "lower", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0109] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0110] The serial numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments. The above description is only a specific implementation mode of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A vehicle disconnection warning method, characterized in that: The following steps are involved: Periodically collect the on-board TBOX voltage; The preset linear regression model is used to determine the change trend of the vehicle TBOX voltage to determine whether the vehicle is at risk of disconnection; Among them, after periodically collecting the on-board TBOX voltage, before determining the change trend of the on-board TBOX voltage through a preset linear regression model to determine whether the vehicle has a disconnection risk, the following steps are also included: Divide every M adjacent periods into a time segment; And according to the collection order of the on-board TBOX voltage, a collection sequence number is marked for the on-board TBOX voltage in the time segment; The change trend of the on-board TBOX voltage is determined by a preset linear regression model to determine whether the vehicle has a disconnection risk, which specifically includes the following steps: Input the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage into the linear regression model, and obtain the disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the change trend of the vehicle-mounted TBOX voltage; Determine whether the vehicle has a disconnection risk according to the disconnection risk coefficient.

2. The vehicle disconnection warning method according to claim 1, characterized in that: The on-board TBOX voltage collected in the time segment and the collection sequence number corresponding to the on-board TBOX voltage are input into the linear regression model to obtain the disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the on-board TBOX voltage change trend, specifically including the following steps: A linear regression curve is fitted based on the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage: y=ax+b Among them, x is the collection sequence number corresponding to the on-board TBOX voltage in the time segment, y is the on-board TBOX voltage collected in the time segment, a is the disconnection risk coefficient corresponding to the time segment, and b is a constant. When the change trend of the on-board TBOX voltage is increasing, a is larger, and when the change trend of the on-board TBOX voltage is decreasing, a is smaller.

3. The vehicle disconnection warning method according to claim 2, characterized in that: Determining whether the vehicle has a disconnection risk according to the disconnection risk coefficient specifically includes the following steps: If the disconnection risk coefficient is greater than 0, it is determined that there is no disconnection risk for the vehicle in the corresponding time segment; If the disconnection risk coefficient is less than 0, it is determined that there is a disconnection risk for the vehicle within the corresponding time segment.

4. The vehicle disconnection warning method according to claim 3, characterized in that: The following steps are also included: If it is determined that the vehicle is at risk of disconnection within N consecutive time segments, a vehicle disconnection warning is sent.

5. A vehicle disconnection warning device, characterized in that: include: A collection module, which is used to periodically collect the on-board TBOX voltage; A determination module is used to determine the change trend of the vehicle-mounted TBOX voltage through a preset linear regression model to determine whether the vehicle has a disconnection risk; The device is also used for: Divide every M adjacent periods into a time segment; And according to the collection order of the on-board TBOX voltage, a collection sequence number is marked for the on-board TBOX voltage in the time segment; Wherein, the determining module is also used for: Input the vehicle-mounted TBOX voltage collected in the time segment and the collection sequence number corresponding to the vehicle-mounted TBOX voltage into the linear regression model, and obtain the disconnection risk coefficient corresponding to the time segment output by the linear regression model according to the change trend of the vehicle-mounted TBOX voltage; Determine whether the vehicle has a disconnection risk according to the disconnection risk coefficient.

6. A computer device, characterized in that: The computer device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the vehicle disconnection warning method as described in any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the vehicle disconnection warning method according to any one of claims 1 to 4 are implemented.

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