Vehicle taximeter checking method and device, equipment and storage medium
By calculating the verification index of the vehicle meter, the vehicles with suspicious meter in the satellite positioning sparse scenario were screened out, which solved the problem of low verification efficiency and accuracy affected by traditional methods in the case of sparse satellite positioning sparse, and achieved efficient and accurate Vehicle verification.
Patent Information
- Application Number
- CN202310979686.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-08-04
- Publication Date
- 2025-02-18
AI Technical Summary
In the scenario where satellite positioning points are sparse, traditional satellite positioning data is difficult to restore the complete driving trajectory, resulting in low verification efficiency of vehicle meter and affected accuracy, making it difficult to effectively screen out taxis with suspicious meters.
By obtaining the itinerary data and satellite positioning speed collection of the vehicle meter during the verification cycle, calculating the average speed and verification index, and filtering out the target vehicle with the smallest verification index as the verification target, improving vehicle verification efficiency.
When the satellite positioning points are sparse, vehicles with suspicious meters can be accurately screened out to improve vehicle verification efficiency, and are not affected by the accuracy of satellite positioning positioning.
Smart Images
Figure CN119479102A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of vehicle networking technology, and in particular to a vehicle meter verification method, device, equipment and storage medium. Background Art
[0002] Meter tampering is an unhealthy phenomenon in the taxi industry and needs to be checked and corrected in a timely manner to avoid malicious meter tampering that causes the measured distance traveled to exceed the actual distance, resulting in illegal overcharges.
[0003] Traditional meter verification methods usually use the satellite positioning data of taxis to estimate the travel distance, and then compare it with the travel distance recorded by the meter itself to verify vehicles with suspicious meters. However, since the collection of satellite positioning data depends on the deployed positioning points, this leads to a large sampling interval for the satellite positioning data reported through the Internet of Vehicles, generally 30 to 60 seconds. When the distribution of satellite positioning points is sparse, especially in urban areas with many intersections, it is difficult for the above satellite positioning method to restore the complete original driving trajectory, and the accuracy of satellite positioning will also have a great impact on the meter verification effect.
[0004] Therefore, there is an urgent need for a vehicle meter verification method that can be used in scenarios where satellite positioning points are sparse, effectively screen out taxis with suspicious meters, and improve vehicle verification efficiency. Summary of the invention
[0005] The present application provides a vehicle meter verification method, device, equipment and storage medium, which can be used in scenarios where satellite positioning points are sparse, effectively screen out taxis with suspicious meters, and improve vehicle verification efficiency.
[0006] In order to achieve the above objectives, in a first aspect, the present application provides a vehicle meter verification method, the method comprising:
[0007] S1. Obtaining the trip data of at least one revenue trip of a vehicle meter within a verification period, and obtaining a set of satellite positioning speeds corresponding to a plurality of satellite positioning points in the revenue trip, wherein each of the trip data includes the trip duration and metered trip distance of the revenue trip;
[0008] S2. Calculating the average speed measured by the vehicle meter during the revenue trip based on the trip data;
[0009] S3, determining a verification index of the revenue trip based on the difference between a plurality of satellite positioning speeds in the satellite positioning speed set and the average speed, the verification index indicating: a ratio of a speed fluctuation degree of a vehicle higher than the average speed to a speed fluctuation degree of a vehicle lower than the average speed in the plurality of satellite positioning speeds;
[0010] S4. According to the verification indexes of the plurality of vehicles in the verification cycle, the target vehicle with the smallest verification index is determined as the verification target, and the smaller the verification index is, the more suspicious the meter is.
[0011] In a possible implementation manner, step S3 includes:
[0012] For the revenue trip, based on the differences between the multiple satellite positioning speeds in the satellite positioning speed set and the average speed, the fluctuation variance between the multiple differences that are higher than or equal to the average speed and the fluctuation variance between the multiple differences that are lower than or equal to the average speed are determined to obtain a verification index for the revenue trip, and the verification index D is expressed as:
[0013]
[0014] V a is the average speed, V m is the satellite positioning speed higher than or equal to the average speed, V n is a satellite positioning speed that is lower than or equal to the average speed.
[0015] In a possible implementation manner, step S3 includes:
[0016] For an i-th vehicle among the multiple vehicles, averaging the verification indexes of j revenue trips of the i-th vehicle within the verification period to obtain an average verification index of the i-th vehicle;
[0017] According to the sorting of the verification index averages of the plurality of vehicles in the verification cycle, determining the target vehicle with the smallest verification index average as the verification target;
[0018] In the event that there is a problem with the meter of the target vehicle, the vehicle with the second smallest verification index average is determined as the next verification target.
[0019] In one possible implementation, the method further includes:
[0020] According to the verification indexes of the plurality of vehicles in the verification cycle, a plurality of vehicles whose verification indexes are less than a preset verification threshold are determined as verification targets.
[0021] In one possible implementation, the travel data is obtained from a vehicle meter via Internet of Vehicles technology.
[0022] In a second aspect, a verification device for a vehicle meter is provided, the device comprising a plurality of functional modules for executing corresponding steps in the verification method for a vehicle meter provided in the first aspect.
[0023] In a third aspect, a computing device is provided, the computing device comprising a memory and a processor, the memory storing at least one program, the at least one program being executed by the processor to implement the vehicle meter verification method provided in the first aspect.
[0024] In a fourth aspect, a computer-readable storage medium is provided, wherein at least one program is stored in the storage medium, and the at least one program is executed by a processor to implement the vehicle meter verification method provided in the first aspect.
[0025] The technical solution provided by this application includes at least the following technical effects:
[0026] The vehicle meter verification method provided in the present application utilizes the measurement characteristics of the meter after adjustment. It does not use the satellite positioning position information, but instead uses the satellite positioning speed information to verify the measurement of the vehicle meter. When the satellite positioning points and positioning data are sparse, key vehicles that need to be checked can be screened out, and the accuracy of the screening is not affected by the satellite positioning accuracy, thereby effectively improving the vehicle verification efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0027] Figure 1 It is a flow chart of a vehicle meter verification method provided by an embodiment of the present application;
[0028] Figure 2 is a schematic diagram of a vehicle meter verification device provided by an embodiment of the present application;
[0029] Figure 3 It is a schematic diagram of the hardware structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0030] To further illustrate the various embodiments, the present application provides drawings. These drawings are part of the disclosure of the present application, and are mainly used to illustrate the embodiments, and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, a person of ordinary skill in the art should be able to understand other possible implementations and the advantages of the present application. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.
[0031] The present application is now further described in conjunction with the accompanying drawings and specific implementation methods.
[0032] The vehicle involved in this application is a taxi. The taximeter is composed of a host and a sensor. The host includes a microprocessor for calculating travel data and a microprocessor for monitoring data. The taximeter is connected to the moving vehicle through the sensor. The mileage of the taxi is transmitted to the meter through the pulse signal of the sensor, and the meter is converted into a certain metered operating mileage. The meter is modified so that the actual distance of the travel distance recorded by the meter generates illegal overcharges, which becomes a meter adjustment behavior. In order to correct and verify this illegal behavior in a timely manner, it is necessary to promptly verify the vehicles with suspicious meters.
[0033] In view of this, the present application provides a vehicle meter verification method that can be executed by a computing device. The computing device can obtain the vehicle's travel data and data such as the vehicle's satellite positioning, and analyze the data recorded by the vehicle meter through the satellite positioning data to determine whether the vehicle's meter is OK, thereby screening out vehicles with suspicious meters from a large number of vehicles and achieving efficient vehicle verification.
[0034] The computing device can be a server, a server cluster consisting of multiple physical servers, or a distributed file system, or a cloud server cluster that provides basic cloud computing services such as cloud storage and cloud services, cloud databases, cloud computing, cloud functions, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), big data and artificial intelligence platforms, but this application does not limit this.
[0035] Figure 1 A flow chart of a vehicle meter verification method provided in this application, see Figure 1 The method is executed by a computing device and includes the following steps S1 to S4.
[0036] S1. Obtaining travel data of at least one revenue trip of a vehicle meter within a verification period, and obtaining a set of satellite positioning speeds corresponding to multiple satellite positioning points in the revenue trip.
[0037] Among them, a revenue trip refers to a vehicle trip that is fully completed and generates revenue; each trip data includes the trip duration and metered trip distance of the revenue trip.
[0038] Among them, the travel data and the satellite positioning speed set can be obtained separately, and this application does not limit the order of obtaining these two types of data.
[0039] In the embodiment of the present application, for each vehicle, the travel data of j revenue trips within the verification period can be obtained. For example, the vehicle serves as a terminal in the Internet of Vehicles system, and the computing device can access the Internet of Vehicles system to obtain the travel data of multiple vehicles managed by the Internet of Vehicles within the verification period.
[0040] In a specific implementation, for the jth operating trip of vehicle i, the trip data of its meter can be expressed as: T ij =(t ijs ,t ije ,d ij ), t ijs is the trip start time recorded by the taximeter, t ije is the meter trip end time, d ij It is the metered trip distance recorded by the taximeter.
[0041] The verification period can be set according to the verification requirements, for example, one week, one month or three months.
[0042] In the embodiment of the present application, the above-mentioned travel data can be obtained from the vehicle's meter through the Internet of Vehicles technology. For example, the vehicle, as an Internet of Vehicles terminal, can transmit the travel data through the surrounding access points, communication infrastructure, etc. to the computing device responsible for executing the vehicle meter verification method, and the computing device can be a cloud server or a data center, etc.
[0043] In the embodiment of the present application, the vehicle is equipped with a vehicle-mounted global navigation satellite system (GNSS), and the computing device is connected to the GNSS to obtain k satellite positioning speeds of the vehicle within the verification period. The set of these k satellite positioning speeds is recorded as V k Optionally, the GNSS may specifically be a GPS system or a BeiDou system.
[0044] S2. Calculate the average speed measured by the vehicle meter during the revenue trip based on the trip data.
[0045] In the embodiment of the present application, for the jth revenue trip of vehicle i, according to the trip data T ij =(t ijs ,t ije ,d ij ), the average speed of the taximeter is calculated as:
[0046] S3. Determine the verification index of the revenue trip based on the difference between multiple satellite positioning speeds in the satellite positioning speed set and the average speed.
[0047] The verification index indicates: a ratio of a vehicle speed fluctuation degree above the average speed to a vehicle speed fluctuation degree below the average speed.
[0048] According to the characteristics of meter adjustment, the lower the vehicle speed, the smaller the error of the meter in measuring the distance; when the vehicle is stationary, the distance measured by the meter is equal to the actual distance; when the vehicle speed is higher, the error between the distance measured by the meter and the actual distance is greater, and accordingly, the error reflected in the distance speed is also greater. Based on this characteristic, this application uses the relationship between the speed data of the satellite positioning point and the average speed measured by the meter to screen out the vehicles with the most suspicious meters, thereby determining the target vehicles that need to be checked in detail.
[0049] In the embodiment of the present application, for any revenue trip, based on the difference between multiple satellite positioning speeds in the satellite positioning speed set and the average speed, the fluctuation variance between multiple differences higher than or equal to the average speed and the fluctuation variance between multiple differences lower than the average speed are determined to obtain the verification index D of the revenue trip. The calculation principle is expressed as follows:
[0050]
[0051] Among them, V a is the average speed, V m is the satellite positioning speed higher than or equal to the average speed, V n is the satellite positioning speed lower than or equal to the average speed, V m ∈V k ,V n ∈V k . m represents the number of satellite positioning speeds that are higher than or equal to the average speed, and n represents the number of satellite positioning speeds that are lower than or equal to the average speed.
[0052] In the embodiment of the present application, the verification index D represents the ratio of the high-speed fluctuation variance to the low-speed fluctuation variance relative to the average speed. When the meter is adjusted, the average speed measured by the meter is greater than the actual average speed. Therefore, the less satellite positioning speed data in the high-speed range greater than the average speed, the smaller the numerator of D; because the difference between the meter adjustment error and the actual speed is small at low speed, the denominator volatility of D is smaller than the numerator volatility. Based on this, the verification index can reflect the degree of meter adjustment of the vehicle. The more serious the adjustment, the smaller the verification index D.
[0053] S4. According to the inspection indexes of the multiple vehicles in the inspection cycle, the target vehicle with the smallest inspection index is determined as the inspection target.
[0054] The smaller the verification index is, the more suspicious the taximeter is. Therefore, the most suspicious target vehicle can be determined according to the size of the verification index and the target vehicle is used as the verification target.
[0055] In other embodiments, suspicious vehicles can also be screened according to a verification threshold. Specifically, according to the verification indexes of multiple vehicles within the verification cycle, multiple vehicles whose verification indexes are less than the verification threshold are determined as verification targets. Among them, the verification threshold can be predetermined according to the characteristics of the verified area. For example, an urban area with many intersections corresponds to a first verification threshold, and a suburban area with fewer intersections and more highways corresponds to a second verification threshold. Since the vehicle speed changes in urban areas are more frequent than in suburban areas, it is more reasonable for the vehicle speed to fluctuate accordingly. Therefore, the first verification threshold can be less than the second verification threshold. Based on this, the technical solution of the present application can be well applied to different types of areas where vehicles travel, and can be adjusted according to the characteristics of the area to ensure the rationality of the verification method.
[0056] In one possible implementation, for multiple vehicles to be analyzed, the computing device calculates the verification index of each of the j revenue trips of vehicle i within the verification period, and accumulates and averages the verification indexes of the j revenue trips. During the verification period, all vehicles managed by the Internet of Vehicles are sorted according to the average of the verification index. Furthermore, the vehicle with the smallest average of the verification index within the verification period is first checked. If there is a problem with the vehicle, the vehicle with the second smallest average is then subject to pricing verification.
[0057] In a specific implementation, for the i-th vehicle among multiple vehicles, the verification indexes of the j revenue trips of the i-th vehicle within the verification period are averaged to obtain the average verification index of the i-th vehicle; based on the sorting of the verification index averages of the multiple vehicles within the verification period, the target vehicle with the smallest verification index average is determined as the verification target; in the event that there is a problem with the meter of the target vehicle, the vehicle with the second smallest verification index average is determined as the next verification target.
[0058] The vehicle meter verification method provided in the present application utilizes the measurement characteristics of the meter after adjustment. It does not use the satellite positioning position information, but instead uses the satellite positioning speed information to verify the measurement of the vehicle meter. When the satellite positioning points and positioning data are sparse, key vehicles that need to be checked can be screened out, and the accuracy of the screening is not affected by the satellite positioning accuracy, thereby effectively improving the vehicle verification efficiency.
[0059] The present application also provides a schematic diagram of a vehicle meter verification device, referring to Figure 2 , the device comprises:
[0060] The data collection module 21 is used to obtain the trip data of at least one revenue trip of the vehicle meter within the verification period, and obtain the satellite positioning speed set corresponding to multiple satellite positioning points in the revenue trip, each of the trip data includes the trip duration and metered trip distance of the revenue trip;
[0061] The calculation module 22 is used to calculate the average speed measured by the vehicle meter in the revenue trip according to the trip data; determine the verification index of the revenue trip based on the difference between multiple satellite positioning speeds in the satellite positioning speed set and the average speed, and the verification index indicates: the ratio of the fluctuation degree of the vehicle speed higher than the average speed to the fluctuation degree of the vehicle speed lower than the average speed in the multiple satellite positioning speeds;
[0062] The verification screening module 23 determines the target vehicle with the smallest verification index as the verification target according to the verification indexes of multiple vehicles in the verification cycle, and the smaller the verification index, the more suspicious the meter is.
[0063] In one possible implementation, the calculation module 22 is used to
[0064] For the revenue trip, based on the differences between the multiple satellite positioning speeds in the satellite positioning speed set and the average speed, the fluctuation variance between the multiple differences that are higher than or equal to the average speed and the fluctuation variance between the multiple differences that are lower than or equal to the average speed are determined to obtain the verification index D of the revenue trip, and the verification index D is expressed as:
[0065]
[0066] V a is the average speed, V m is the satellite positioning speed higher than or equal to the average speed, V n is a satellite positioning speed that is lower than or equal to the average speed.
[0067] In a possible implementation manner, the verification and screening module 23 is used to:
[0068] For an i-th vehicle among the multiple vehicles, averaging the verification indexes of j revenue trips of the i-th vehicle within the verification period to obtain an average verification index of the i-th vehicle;
[0069] According to the sorting of the verification index averages of the plurality of vehicles in the verification cycle, determining the target vehicle with the smallest verification index average as the verification target;
[0070] In the event that there is a problem with the meter of the target vehicle, the vehicle with the second smallest verification index average is determined as the next verification target.
[0071] In a possible implementation manner, the checking and screening module 23 is further used for:
[0072] According to the verification indexes of the plurality of vehicles in the verification cycle, a plurality of vehicles whose verification indexes are less than a preset verification threshold are determined as verification targets.
[0073] In one possible implementation, the travel data is obtained from a vehicle meter via Internet of Vehicles technology.
[0074] It should be noted that the vehicle verification device provided in the above embodiment only uses the division of the above functional modules as an example when implementing the corresponding steps. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the vehicle verification device provided in the above embodiment and the above-mentioned vehicle meter verification method belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.
[0075] In the present application, the term "at least one" means one or more, and the term "plurality" in the present application means two or more, for example, a plurality of vehicles means two or more vehicles.
[0076] The vehicle meter verification method provided in the present application can be executed by a computing device. Figure 3 is a schematic diagram of the hardware structure of a computing device provided in an embodiment of the present application, such as Figure 3 As shown, the computing device includes a processor 301, a memory 302, a bus 303, and a computer program stored in the memory 302 and executable on the processor 301. The processor 301 includes one or more processing cores. The memory 302 is connected to the processor 301 via the bus 303. The memory 302 is used to store program instructions. When the processor executes the computer program, all or part of the steps in the above method embodiments provided in the present application are implemented.
[0077] Further, as an executable solution, the computing device may be a computer unit, which may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer unit may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the composition structure of the computer unit is merely an example of a computer unit and does not constitute a limitation on the computer unit, and may include more or fewer components than the above, or a combination of certain components, or different components. For example, the computer unit may also include input and output devices, network access devices, buses, etc., which are not limited in the embodiments of the present application.
[0078] Further, as an executable solution, the processor may be a central processing unit (CPU), 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. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the computer unit, and various interfaces and lines are used to connect the various parts of the entire computer unit.
[0079] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the computer unit by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.
[0080] The present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the above method in the embodiment of the present application are implemented.
[0081] If the module / unit integrated in the computer unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory) and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.
[0082] Although the present application has been specifically shown and described in conjunction with the preferred embodiments, those skilled in the art should understand that various changes may be made to the present application in form and details without departing from the spirit and scope of the present application as defined by the appended claims, all of which are within the scope of protection of the present application.
Claims
1. A method for checking a vehicle meter, characterized in that: The method comprises: S1. Obtaining the trip data of at least one revenue trip of a vehicle meter within a verification period, and obtaining a set of satellite positioning speeds corresponding to a plurality of satellite positioning points in the revenue trip, wherein each of the trip data includes the trip duration and metered trip distance of the revenue trip; S2. Calculating the average speed measured by the vehicle meter during the revenue trip based on the trip data; S3, determining a verification index of the revenue trip based on the difference between a plurality of satellite positioning speeds in the satellite positioning speed set and the average speed, the verification index indicating: a ratio of a speed fluctuation degree of a vehicle higher than the average speed to a speed fluctuation degree of a vehicle lower than the average speed in the plurality of satellite positioning speeds; S4. According to the verification indexes of the plurality of vehicles in the verification cycle, the target vehicle with the smallest verification index is determined as the verification target, and the smaller the verification index is, the more suspicious the meter is.
2. The verification method according to claim 1, characterized in that: The step S3 comprises: For the revenue trip, based on the differences between the multiple satellite positioning speeds in the satellite positioning speed set and the average speed, the fluctuation variance between the multiple differences that are higher than or equal to the average speed and the fluctuation variance between the multiple differences that are lower than or equal to the average speed are determined to obtain the verification index D of the revenue trip, and the verification index D is expressed as: V a is the average speed, V m is the satellite positioning speed higher than or equal to the average speed, V n is a satellite positioning speed that is lower than or equal to the average speed.
3. The verification method according to claim 1 or 2, characterized in that: The step S3 comprises: For an i-th vehicle among the multiple vehicles, averaging the verification indexes of j revenue trips of the i-th vehicle within the verification period to obtain an average verification index of the i-th vehicle; According to the sorting of the verification index averages of the plurality of vehicles in the verification cycle, determining the target vehicle with the smallest verification index average as the verification target; In the event that there is a problem with the meter of the target vehicle, the vehicle with the second smallest verification index average is determined as the next verification target.
4. The verification method according to claim 1, characterized in that: The method further comprises: According to the verification indexes of the plurality of vehicles in the verification cycle, a plurality of vehicles whose verification indexes are less than a preset verification threshold are determined as verification targets.
5. The verification method according to claim 1, characterized in that: The travel data is obtained from the vehicle's meter through vehicle networking technology.
6. A vehicle meter verification device, characterized in that: The device comprises: A data collection module, used to obtain the trip data of at least one revenue trip of the vehicle meter within the verification period, and obtain the satellite positioning speed set corresponding to multiple satellite positioning points in the revenue trip, each of the trip data including the trip duration and metered trip distance of the revenue trip; a calculation module, configured to calculate an average speed measured by the vehicle meter within the revenue trip according to the trip data; determine a verification index of the revenue trip based on a difference between a plurality of satellite positioning speeds in the satellite positioning speed set and the average speed, the verification index indicating: a ratio of a speed fluctuation degree of a vehicle higher than the average speed to a speed fluctuation degree of a vehicle lower than the average speed among the plurality of satellite positioning speeds; The verification screening module determines the target vehicle with the smallest verification index as the verification target according to the verification indexes of multiple vehicles in the verification cycle, and the smaller the verification index, the more suspicious the meter is.
7. The verification device according to claim 6, characterized in that: The calculation module is used for: For the revenue trip, based on the differences between the multiple satellite positioning speeds in the satellite positioning speed set and the average speed, the fluctuation variance between the multiple differences that are higher than or equal to the average speed and the fluctuation variance between the multiple differences that are lower than or equal to the average speed are determined to obtain the verification index D of the revenue trip, and the verification index D is expressed as: V a is the average speed, V m is the satellite positioning speed higher than or equal to the average speed, V n is a satellite positioning speed that is lower than or equal to the average speed.
8. A computing device, characterized in that It comprises a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to implement the vehicle meter verification method as claimed in any one of claims 1 to 5.
9. A computer-readable storage medium, characterized in that: The storage medium stores at least one program, and the at least one program is executed by a processor to implement the vehicle meter verification method as described in any one of claims 1 to 5.