A method and system for analyzing vehicle speed and throttle data

Abstract

The application provides an automobile speed and throttle data analysis method and system, which comprises the following steps: obtaining speed data of three preset vehicle states from GPS track, vehicle enterprise background monitoring data or vehicle record video with speed display; determining a coefficient k according to the obtained reference speed V and the proportion value of the screened SV; recording the value of the coefficient k and the position of the corresponding field in the data block; screening the field meeting the characteristics in the self-defined binary data block through the range of the three vehicle states and the throttle value, and confirming the position of the throttle in the self-defined data block. The easily obtained, small amount of plaintext speed data is used as reference data, combined with the acceleration, deceleration and static state of the vehicle to reversely determine the storage position of the speed and throttle in the self-defined data block, so that the speed and throttle data can be quickly analyzed, the efficiency of electronic data evidence collection in accident investigation is improved, and the effectiveness of the electronic data evidence is ensured.

Description

Technical Field

[0001] This invention belongs to the field of data processing technology, specifically relating to a method and system for analyzing vehicle speed and throttle data. Background Technology

[0002] Vehicle speed and throttle data are frequently used in traffic accident investigations, analysis, and liability determination. For example, they are used to determine if a vehicle was speeding or if the driver accidentally pressed the accelerator. The recording methods for vehicle speed and throttle data vary depending on the vehicle brand and electronic module, but generally fall into two categories: plaintext recording with explicit Chinese or English labels indicating the meaning of the data, such as "Speed: **km / h" or "Throttle: **%"; and custom binary format without plaintext labels. In this latter format, data is typically recorded in blocks at fixed time intervals, with different fields within the data block representing different values.

[0003] In new energy vehicles, data such as vehicle speed and throttle input are frequently recorded and used by electronic modules, and the amount of data is enormous, with some modules recording data on a millisecond-level basis. Plain text format takes up a lot of storage space. Compared to plain text recording, binary custom format is more space-efficient, recording more data in the same amount of storage. Therefore, this type of binary custom format data is frequently encountered in traffic accident investigations and analyses. Analyzing this type of data requires assistance from the vehicle manufacturer, which is a cumbersome and inefficient process. In some accidents caused by vehicle defects, where the determination of the manufacturer's liability is involved, relying on the manufacturer's own protocol to analyze the data as electronic evidence renders it ineffective.

[0004] Therefore, it is of great significance to propose a method and system for analyzing vehicle speed and throttle data. Summary of the Invention

[0005] To address the problem of frequently encountering custom-format binary data in traffic accident investigations and analyses, which requires assistance from vehicle manufacturers and is cumbersome and inefficient, and in cases where vehicle defects lead to liability determinations, requiring manufacturers to provide protocols for data analysis as electronic evidence, the present invention provides a method and system for analyzing vehicle speed and throttle data to resolve these technical deficiencies.

[0006] In a first aspect, the present invention proposes a method for analyzing vehicle speed and throttle data, the method comprising the following steps:

[0007] S1. Responding to the speed data of three preset vehicle states obtained from GPS trajectory, vehicle manufacturer back-end monitoring data or dashcam video with speed display;

[0008] S2. Select fields that meet preset characteristics from a custom binary data block based on three vehicle states, and then determine the coefficient k based on the obtained reference speed V and the ratio of the selected SV.

[0009] S3. Record the value of coefficient k and the position of the corresponding field in the data block to complete the analysis of vehicle speed data;

[0010] S4. Then, by using the three vehicle states and the unique range of throttle values, select fields that match the characteristics from the custom binary data block, confirm the position of the throttle in the custom data block, and complete the analysis of the car throttle data.

[0011] Preferably, the analysis of vehicle speed data specifically includes:

[0012] S11. Obtain a segment of vehicle speed data when the vehicle is stationary, filter out fields with values ​​of 00 00 from the custom data block of the corresponding time period, and mark the positions of these fields in the data block;

[0013] S12. Obtain a segment of vehicle speed data during start-up acceleration, find the custom data block corresponding to the time period, and filter out fields with gradually increasing values ​​in the data block fields marked in S11, removing fields that do not meet the characteristics.

[0014] S13. Obtain speed data when the vehicle decelerates and stops, find the custom data block corresponding to the time period, and filter out the fields whose values ​​gradually decrease to 0000 from the remaining marked data block fields in S12, and remove the fields that do not meet the characteristics.

[0015] S14. Ratio the reference speed selected in S12 and S13 with the remaining marker field values ​​in the corresponding time period to obtain the coefficient K value.

[0016] Further preferred options include:

[0017] S14. Determine if a constant coefficient K value can be obtained; if a constant coefficient K value cannot be obtained, change to a different time period and return to S11 to reselect the reference speed; if a constant coefficient K value can be obtained, continue to S3.

[0018] Further preferred methods for analyzing vehicle throttle data include:

[0019] S41. Based on vehicle speed, select a segment of data when the vehicle is stationary, filter out fields with a value of 00 in a custom data block, and mark the positions of these fields.

[0020] S42. Select another segment of data when the vehicle starts and accelerates. In the fields marked in S41, filter out the fields whose values ​​gradually increase and whose maximum value does not exceed 0x64, and remove the fields that do not meet the characteristics.

[0021] S43. Select another segment of data when the vehicle decelerates and stops. In the remaining labeled fields in S42, filter out fields whose values ​​gradually decrease or are 00, and remove fields that do not meet the characteristics.

[0022] Further preferred options include:

[0023] S44. Determine whether S43 has filtered out exactly one throttle data field; if there are multiple fields, change to a different time period and return to S41 to reselect data; if there is only one field, record the position of the throttle in the custom data block.

[0024] A further preferred formula for calculating the actual vehicle speed V is:

[0025] V = SV * k

[0026] Where K is the resolution coefficient, which is usually 0.1 or 0.01, and SV represents the number of bytes typically used when recording vehicle speed.

[0027] Secondly, embodiments of the present invention provide a system for analyzing vehicle speed and throttle data, comprising:

[0028] The data acquisition module is configured to acquire speed data for three preset vehicle states from GPS tracks, vehicle manufacturer back-end monitoring data, or dashcam videos with speed displays.

[0029] The coefficient determination module is configured to filter fields that meet preset characteristics from a custom binary data block based on three vehicle states, and then determine the coefficient k based on the obtained reference speed V and the ratio of the filtered SV.

[0030] The recording module is configured to record the value of coefficient k and the position of the corresponding field in the data block, thereby completing the analysis of vehicle speed data.

[0031] The confirmation module is configured to filter fields that meet certain characteristics from a custom binary data block based on three vehicle states and the range of throttle values, confirm the position of the throttle in the custom data block, and complete the analysis of the vehicle's throttle data.

[0032] Thirdly, embodiments of the present invention provide an electronic device, including: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect.

[0033] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the implementations of the first aspect.

[0034] Compared with the prior art, the beneficial results of the present invention are as follows:

[0035] (1) The technical solution of the present invention provides a vehicle speed and throttle data analysis technology. By using easily obtainable and small amounts of plaintext speed data as reference data, combined with the vehicle's acceleration, deceleration, stationary state, as well as the changes and range of the data itself, the storage location of the vehicle speed and throttle in a custom data block can be determined in reverse. The vehicle speed and throttle data can be analyzed quickly, bypassing the car manufacturer, improving the efficiency of electronic data evidence collection in accident investigations and ensuring the validity of electronic data evidence.

[0036] (2) The technical solution of the present invention uses relatively easy-to-obtain and analyze data: GPS trajectory or dashcam video with speed display as reference data. It uses a point-to-surface approach to quickly analyze the vehicle speed and throttle data stored in a custom format, and analyzes their position and related ratio coefficients in the custom data block. It is perfectly compatible with the custom format data of different brands of vehicles, without the need to seek data analysis services from the manufacturer. Attached Figure Description

[0037] The accompanying drawings are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments and, together with the description, serve to explain the principles of the invention. Other embodiments and many anticipated advantages of the embodiments will be readily recognized as they become better understood through reference to the following detailed description. Elements in the drawings are not necessarily to scale. The same reference numerals refer to corresponding similar parts.

[0038] Figure 1 This is an exemplary device architecture diagram in which an embodiment of the present invention can be applied;

[0039] Figure 2 This is a flowchart illustrating the method for analyzing vehicle speed and throttle data according to an embodiment of the present invention.

[0040] Figure 3This is a schematic diagram of the overall process of the vehicle speed and throttle data analysis method according to an embodiment of the present invention.

[0041] Figure 4 This is a schematic diagram of a vehicle speed and throttle data analysis system according to an embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram of the structure of a computer device suitable for implementing electronic devices according to embodiments of the present invention. Detailed Implementation

[0043] Figure 1 An exemplary system architecture 100 is shown, which can be applied to the analysis method or system for analyzing vehicle speed and throttle data according to embodiments of the present invention.

[0044] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as the medium for providing communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0045] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0046] Terminal devices 101, 102, and 103 can be various electronic devices with communication functions, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0047] Server 105 can be a server that provides various services, such as a background information processing server that processes verification request information sent by terminal devices 101, 102, and 103. The background information processing server can analyze and process the received verification request information and obtain the processing results.

[0048] It should be noted that the vehicle speed and throttle data analysis method provided in this embodiment of the invention is generally executed by server 105, and correspondingly, the vehicle speed and throttle data analysis system is generally set in server 105. Additionally, the vehicle speed and throttle data analysis method provided in this embodiment of the invention is generally executed by terminal devices 101, 102, and 103, and correspondingly, the vehicle speed and throttle data analysis system is generally set in terminal devices 101, 102, and 103.

[0049] It should be noted that a server can be either hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When the server is software, it can be implemented as multiple software programs or software modules (for example, used to provide distributed services), or as a single software program or multiple software modules; no specific limitations are made here.

[0050] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Any number of terminal devices, networks, and servers can be included depending on implementation needs. If the data being processed does not need to be retrieved remotely, the above architecture may not include a network, requiring only servers or terminal devices.

[0051] In new energy vehicles, data such as vehicle speed and throttle input are frequently recorded and used by electronic modules, and the amount of data is enormous, with some modules recording data on a millisecond-level basis. Plain text format takes up a lot of storage space. Compared to plain text recording, binary custom format is more space-efficient, recording more data in the same amount of storage. Therefore, this type of binary custom format data is frequently encountered in traffic accident investigations and analyses. Analyzing this type of data requires assistance from the vehicle manufacturer, which is a cumbersome and inefficient process. In some accidents caused by vehicle defects, where the determination of the manufacturer's liability is involved, relying on the manufacturer's own protocol to analyze the data as electronic evidence renders it ineffective.

[0052] This invention provides a vehicle speed and throttle data analysis technology. By using readily available, limited plaintext speed data as reference data, combined with vehicle acceleration, deceleration, and stationary states, as well as the changes and range of the data itself, the storage location of vehicle speed and throttle in a custom data block can be determined. This allows for rapid analysis of vehicle speed and throttle data, bypassing vehicle manufacturers, improving the efficiency of electronic data evidence collection in accident investigations, and ensuring the validity of electronic data evidence.

[0053] In a first aspect, embodiments of the present invention disclose a method for analyzing vehicle speed and throttle data, such as... Figure 2 As shown, the method includes the following steps:

[0054] S1. Responding to the speed data of three preset vehicle states obtained from GPS trajectory, vehicle manufacturer back-end monitoring data or dashcam video with speed display;

[0055] S2. Select fields that meet preset characteristics from a custom binary data block based on three vehicle states, and then determine the coefficient k based on the obtained reference speed V and the ratio of the selected SV.

[0056] S3. Record the value of coefficient k and the position of the corresponding field in the data block to complete the analysis of vehicle speed data;

[0057] S4. Then, by using the three vehicle states and the unique range of throttle values, select fields that match the characteristics from the custom binary data block, confirm the position of the throttle in the custom data block, and complete the analysis of the car throttle data.

[0058] Specifically, the basic principles of the embodiments of the present invention will be explained in detail below:

[0059] Custom data blocks contain driving data such as time, speed, and throttle. First, the time format needs to be confirmed. There are two common time formats: one occupies 6 bytes of storage, with each byte representing the year, month, day, hour, minute, and second. For example, 17 07 0B 16 08 3B represents the time: July 11, 2023, 22:08:59. The other format is a 4-byte timestamp, which represents the total number of seconds since January 1, 1970, 00:00:00. It can be converted to a standard time format using corresponding functions or tools. For example, 64AD 62 7B corresponds to the converted time: July 11, 2023, 22:08:59.

[0060] Common vehicle speed ranges are generally 0–200 km / h. Vehicle speed records typically occupy 2 bytes, which we represent using the SV symbol. The formula for calculating the actual speed is:

[0061] V = SV * k

[0062] K is the resolution coefficient, which is usually 0.1 or 0.01. It needs to be determined by back-calculation based on reference data.

[0063] For example, 125.5 km / h has a coefficient of 0.1. In binary form, this is 125.5 / 0.1 = 1255, and its hexadecimal value is 0x04E7. In byte order, this is "04E7".

[0064] By acquiring readily available GPS tracks or dashcam videos with speed displays, we obtain speed data for three periods: when the vehicle is stationary, during acceleration, and during deceleration. The speed data for the stationary period is stored as "0000"; the speed data for acceleration gradually increases, becoming larger; and the speed data for deceleration gradually decreases, becoming smaller until it reaches 0. Based on these three vehicle states, we filter out fields that match specific characteristics from a custom binary data block. Then, based on the ratio of the obtained reference speed V to the filtered SV, we determine the coefficient k.

[0065] Once the location of the velocity field in the data block and the value of the coefficient k are determined, we can perform a complete velocity analysis.

[0066] The throttle range is 0-100%. When recording, the throttle value typically occupies only one byte, requiring no multiplication by a coefficient for conversion, and this byte ranges from 0 to 0x64. Combining the speed data analyzed above, when stationary, the throttle value is 0; during acceleration, the throttle value gradually increases, with the maximum value not exceeding 0x64; and during deceleration, the throttle value gradually decreases, sometimes remaining at 0. By utilizing these three vehicle states and the unique range of throttle values, fields matching the characteristics are filtered from a custom binary data block, ultimately confirming the throttle's position within the custom data block, thus revealing the throttle data.

[0067] Furthermore, in this embodiment, as Figure 3 As shown, the data extraction process is as follows:

[0068] 1. Obtain speed data for a period of time when the vehicle is stationary by means of GPS trajectory or dashcam video with speed display;

[0069] 2. Filter out fields with values ​​of 00 00 from the custom data block for the corresponding time period, and mark the positions of these fields in the data block;

[0070] 3. Acquire speed data during a segment of the vehicle's acceleration from a standstill;

[0071] 4. Locate the custom data block corresponding to the time period, and then filter out the fields with gradually increasing values ​​from the data block fields marked in step 2, removing fields that do not meet the characteristics;

[0072] 5. Acquire speed data during the vehicle's deceleration and stop.

[0073] 6. Locate the custom data block corresponding to the time period. In the remaining marked data block fields from step 4, filter out the fields whose values ​​gradually decrease to 00 00 and remove the fields that do not meet the characteristics.

[0074] 7. Ratio the reference speed selected in steps 3 and 5 with the remaining marker field values ​​in the corresponding time period to obtain the coefficient K value;

[0075] 8. Determine if a constant coefficient K value can be obtained; if a constant coefficient K value cannot be obtained, change to a different time period, return to step 1, and reselect the reference speed; if a constant coefficient K value can be obtained, continue to step 9.

[0076] 9. Record the proportional coefficient K value and the position of the corresponding field in the custom data block. The speed analysis is now complete.

[0077] 10. Based on vehicle speed, select a segment of data when the vehicle is stationary, filter out fields with a value of 00 in a custom data block, and mark the positions of these fields;

[0078] 11. Select another segment of data during vehicle start-up and acceleration. In the fields marked in step 10, filter out fields whose values ​​gradually increase and whose maximum value does not exceed 0x64, and remove fields that do not meet the characteristics.

[0079] 12. Select another segment of data when the vehicle decelerates and stops. Filter out the fields with gradually decreasing values ​​or values ​​of 00 from the remaining labeled fields in step 11, and remove the fields that do not meet the characteristics.

[0080] 13. Determine whether step 12 has filtered out exactly one throttle data field; if there are multiple fields, change to a different time period and return to step 10 to reselect data; if there is only one field, continue to step 14.

[0081] 14. Record the position of the throttle in the custom data block. At this point, the data format analysis of vehicle speed and throttle in the custom data block is complete.

[0082] The technical solution of this invention uses readily available and analyzable data, such as GPS tracks or dashcam videos with speed displays, as reference data. This allows for the rapid analysis of vehicle speed and throttle data stored in a custom format, revealing their position and relative proportions within a custom data block. This method is perfectly compatible with custom format data from different car brands, eliminating the need to seek data analysis services from the manufacturer.

[0083] Secondly, embodiments of the present invention also disclose a system for analyzing vehicle speed and throttle data, such as... Figure 4As shown, it includes: a data acquisition module 41, a coefficient determination module 42, a recording module 43, and a confirmation module 44.

[0084] In one specific embodiment, the data acquisition module 41 is configured to acquire speed data for three preset vehicle states respectively from GPS trajectory, vehicle manufacturer back-end monitoring data, or dashcam video with speed display; the coefficient determination module 42 is configured to filter out fields that meet preset characteristics from a custom binary data block based on the three vehicle states, and then determine the coefficient k based on the ratio of the acquired reference speed V and the filtered SV; the recording module 43 is configured to record the value of coefficient k and the position of the corresponding field in the data block to complete the analysis of vehicle speed data; the confirmation module 44 is configured to filter out fields that meet the characteristics from the custom binary data block based on the three vehicle states and the range unique to the throttle value, confirm the position of the throttle in the custom data block, and complete the analysis of vehicle throttle data.

[0085] The following is for reference. Figure 5 It illustrates an electronic device suitable for implementing embodiments of the present invention (e.g., Figure 1 The diagram shows the structure of a computer device 600 (a server or terminal device). Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0086] like Figure 5 As shown, the computer device 600 includes a central processing unit (CPU) 601 and a graphics processing unit (GPU) 602, which can perform various appropriate actions and processes according to programs stored in read-only memory (ROM) 603 or programs loaded from storage section 609 into random access memory (RAM) 604. The RAM 604 also stores various programs and data required for the operation of the device 600. The CPU 601, GPU 602, ROM 603, and RAM 604 are interconnected via a bus 605. An input / output (I / O) interface 606 is also connected to the bus 605.

[0087] The following components are connected to I / O interface 606: an input section 607 including a keyboard, mouse, etc.; an output section 608 including an LCD, speakers, etc.; a storage section 609 including a hard disk, etc.; and a communication section 610 including a network interface card, such as a LAN card or modem. The communication section 610 performs communication processing via a network such as the Internet. A drive 611 may also be connected to I / O interface 606 as needed. A removable medium 612, such as a hard disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 611 as needed so that computer programs read from it can be installed into storage section 609 as needed.

[0088] In particular, according to embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 610, and / or installed from removable medium 612. When the computer program is executed by central processing unit (CPU) 601 and graphics processing unit (GPU) 602, the functions defined in the methods of this invention are performed.

[0089] It should be noted that the computer-readable medium described in this invention can be a computer-readable signal medium, a computer-readable medium, or any combination thereof. A computer-readable medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor device, apparatus, or any combination thereof. More specific examples of a computer-readable medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution apparatus, device, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than a computer-readable medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution device, apparatus, or apparatus. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0090] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0091] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using dedicated hardware-based devices that perform the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0092] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be located in a processor.

[0093] In another aspect, the present invention also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquire speed data for three preset vehicle states respectively from GPS tracks, vehicle manufacturer backend monitoring data, or dashcam video with speed display; filter fields conforming to preset characteristics in a custom binary data block based on the three vehicle states; determine a coefficient k based on the ratio of the acquired reference speed V to the filtered SV; record the value of coefficient k and the position of the corresponding field in the data block to complete the analysis of the vehicle speed data; and further filter fields conforming to characteristics in the custom binary data block based on the range specific to the three vehicle states and throttle values, confirm the position of the throttle in the custom data block to complete the analysis of the vehicle throttle data.

[0094] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention is not limited to the specific combination of the above-described technical features, but also includes other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in this invention.

Claims

1. A method for analyzing vehicle speed and throttle data, characterized in that, The method includes the following steps: S1. Responding to GPS trajectory, vehicle manufacturer back-end monitoring data, or dashcam video with speed display, the vehicle speed data is obtained for three vehicle states: stationary, starting and accelerating, and decelerating and stopping. S2. Select fields that meet preset characteristics from a custom binary data block based on three vehicle states. The preset characteristics include: the speed field value is 0000 when stationary, the speed field value gradually increases when accelerating from a standstill, and the speed field value gradually decreases to 0000 when decelerating to a stop. Then, determine the coefficient k based on the ratio of the obtained reference speed V to the selected original speed record byte value SV. S3. Record the value of coefficient k and the position of the corresponding field in the data block to complete the analysis of vehicle speed data; S4. Then, by using the three vehicle states and the unique range of throttle values, select fields that match the characteristics from the custom binary data block, confirm the position of the throttle in the custom data block, and complete the analysis of the car throttle data.

2. The method for analyzing vehicle speed and throttle data according to claim 1, characterized in that, The analysis of vehicle speed data specifically includes: S11. Obtain a segment of vehicle speed data when the vehicle is stationary, filter out fields with values ​​of 00 00 from the binary data block of the corresponding time segment, and mark the positions of these fields in the data block; S12. Obtain a segment of vehicle speed data during start-up acceleration, find the corresponding binary data block for the time period, and filter out fields with gradually increasing values ​​from the data block fields marked in S11, removing fields that do not meet the characteristics. S13. Obtain the speed data of the vehicle when it decelerates and stops, find the binary data block corresponding to the time period, and filter out the fields whose values ​​gradually decrease to 00 00 from the remaining marked data block fields in S12, and remove the fields that do not meet the characteristics. S14. Ratio the reference speed selected in S12 and S13 with the remaining marker field values ​​in the corresponding time period to obtain the coefficient K value.

3. The method for analyzing vehicle speed and throttle data according to claim 2, characterized in that, Also includes: S15. Determine whether a constant coefficient K value within a preset error range can be obtained; If the reference speed cannot be obtained, change to a different time period and return to S11 to select a new reference speed; if the reference speed can be obtained, continue to S3.

4. The method for analyzing vehicle speed and throttle data according to claim 3, characterized in that, The analysis of car throttle data specifically includes: S41. Based on the vehicle speed, select a segment of data when the vehicle is stationary, filter out the fields with a value of 00 in the binary data block, and mark the positions of these fields. S42. Select another segment of data when the vehicle starts and accelerates. In the fields marked in S41, filter out the fields whose values ​​gradually increase and whose maximum value does not exceed 0x64, and remove the fields that do not meet the characteristics. S43. Select another segment of data when the vehicle decelerates and stops. In the remaining labeled fields in S42, filter out fields whose values ​​gradually decrease or are 00, and remove fields that do not meet the characteristics.

5. The method for analyzing vehicle speed and throttle data according to claim 4, characterized in that, Also includes: S44. Determine whether S43 has filtered out exactly one throttle data field; If there are multiple fields, change to a different time period and return to S41 to select data again; if there is only one field, record the position of the throttle in the binary data block.

6. The method for analyzing vehicle speed and throttle data according to claim 5, characterized in that, The formula for calculating the actual speed V of a vehicle is: Where K is the resolution coefficient, which is 0.1 or 0.01, and SV is the raw recorded byte value of the vehicle speed.

7. A system for analyzing vehicle speed and throttle data, characterized in that, include: The data acquisition module is configured to acquire speed data for three vehicle states—stationary, accelerating, and decelerating—from GPS tracks, vehicle manufacturer backend monitoring data, or dashcam videos with speed displays. The coefficient determination module is configured to filter fields that meet preset characteristics from a custom binary data block based on three vehicle states, and then determine the coefficient k based on the ratio of the obtained reference speed V to the filtered original speed record byte value SV. The recording module is configured to record the value of coefficient k and the position of the corresponding field in the data block, thereby completing the analysis of vehicle speed data. The confirmation module is configured to filter fields that meet certain characteristics from a custom binary data block based on three vehicle states and the range of throttle values, confirm the position of the throttle in the custom data block, and complete the analysis of the vehicle's throttle data.

8. An electronic device, comprising: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

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