Front vehicle information identification method and system, storage medium and vehicle-mounted terminal

Abstract

The invention provides a front vehicle information identification method and system, a storage medium and a vehicle-mounted terminal. The front vehicle information identification method comprises the steps of obtaining license plate information of a front vehicle, uploading the license plate information to a cloud server for license plate matching, and obtaining target vehicle information corresponding to the front vehicle; and then real-time vehicle information of a front vehicle is obtained, and the real-time vehicle information and the target vehicle information are compared and fused to obtain recognized vehicle information and carry out automatic driving. According to the method, the detailed information of the front vehicle can be accurately obtained from the cloud server, and whether the front vehicle is the special-shaped vehicle can be judged, so that the special-shaped vehicle can be accurately identified, a collision accident caused by the fact that the special-shaped vehicle is not identified is prevented, and the automatic driving safety is improved.

Description

Technical Field

[0001] The present application relates to the field of assisted driving technology, and in particular to a method, system, storage medium and vehicle-mounted terminal for identifying information of a vehicle ahead. Background Art

[0002] The perception system of autonomous vehicles mainly relies on sensors such as cameras, ultrasonic detectors, and millimeter-wave radars. Through the data collected by these sensors, the vehicle recognizes the surrounding environment. However, it may be difficult to recognize some special-shaped vehicles, which may lead to collision accidents with special-shaped vehicles during autonomous driving, resulting in poor driving safety of current vehicles. Summary of the invention

[0003] In order to solve the above technical problems, the present application provides a method, system, storage medium and vehicle-mounted terminal for identifying vehicle information ahead, which can accurately determine whether the vehicle information ahead is an irregular vehicle.

[0004] Specifically, the present application provides a method for identifying information of a vehicle ahead, comprising the following steps: S100: Acquire the license plate information of the vehicle in front in real time, and upload the license plate information to the cloud server to perform license plate matching to obtain the target vehicle information corresponding to the vehicle in front.

[0005] S200: Acquire real-time vehicle information of the vehicle ahead, compare and fuse the real-time vehicle information with the target vehicle information to obtain identified vehicle information; wherein the identified vehicle information includes at least license plate information, vehicle type, vehicle size, vehicle color and special-shaped vehicle judgment results.

[0006] And S300: performing automatic driving according to the identified vehicle information.

[0007] In the above technical solution, by acquiring and uploading the license plate information to the cloud server in real time for license plate matching, the detailed information of the vehicle in front can be obtained more accurately in the cloud server; by acquiring the real-time vehicle information of the vehicle in front and comparing it with the target vehicle information, it can be determined whether the vehicle in front is an irregular vehicle, thereby accurately identifying irregular vehicles, preventing collision accidents due to unidentified irregular vehicles, and improving the safety of autonomous driving.

[0008] In addition, traditional perception systems may not be able to identify special-shaped vehicles. However, by combining license plate information with data in the cloud server, these vehicles can be effectively identified and processed, improving the overall adaptability of the vehicle terminal.

[0009] Furthermore, in step S100, uploading the license plate information to a cloud server includes: A vehicle image of a front vehicle is acquired, and license plate information is acquired based on the vehicle image.

[0010] The license plate information is verified to determine whether the format of the acquired license plate information is correct. If it is correct, the license plate information is uploaded to the cloud server; otherwise, an exception is handled.

[0011] In the above technical solution, by acquiring the image of the vehicle in front and extracting the license plate information from it, the accuracy of license plate recognition can be improved, and the format of the license plate information can be verified to ensure that only data that meets the standards is uploaded. This reduces the transmission of erroneous information, improves data quality, reduces the burden of cloud data processing, avoids the storage and processing of invalid data, indirectly improves system efficiency, and provides consistent data input for the cloud server, which helps to efficiently perform subsequent data analysis and processing, thereby optimizing system performance and application effects.

[0012] Furthermore, the step S100 further includes: Based on the vehicle image record acquisition timestamp and acquisition location, the acquisition timestamp, acquisition location and vehicle image are synchronously uploaded to the cloud server.

[0013] In the above technical solution, by synchronously uploading the acquisition timestamp and acquisition location, the cloud server can accurately know the specific acquisition time and location of each vehicle image, provide important time and space background for subsequent abnormal records, and make the data more traceable. When it is necessary to trace back specific events or behaviors, the relevant vehicle images and data can be quickly located through timestamps or location information, thereby improving the efficiency of information retrieval.

[0014] Furthermore, the cloud server at least includes a vehicle database, and obtaining target vehicle information in step S100 includes: Based on the license plate information and the vehicle image, a query is performed in a vehicle database to match the vehicle record corresponding to the license plate information, and based on the vehicle record, the target vehicle information is extracted and sent to the current vehicle.

[0015] In the above technical solution, by querying the vehicle database based on the license plate information and the vehicle image, the vehicle record corresponding to the license plate information can be accurately matched. This matching method helps to ensure that the target vehicle information obtained is accurate, thereby improving the system's recognition accuracy of the vehicle in front; the vehicle database usually contains rich vehicle information, such as vehicle brand, vehicle type, color, size, license plate information, etc. By querying and extracting the target vehicle information, more comprehensive vehicle data can be obtained and provided to the current vehicle to help the driver or the autonomous driving system make more informed decisions; in addition, the vehicle database is usually updated regularly to reflect more comprehensive vehicle information.

[0016] Furthermore, the step S200 of obtaining the identified vehicle information includes: The target vehicle information is compared with the real-time vehicle information to determine whether the vehicle ahead is an irregular vehicle. If so, the target vehicle information and the real-time vehicle information are fused to obtain vehicle fusion information as the identification vehicle information; otherwise, the target vehicle information is used as the identification vehicle information.

[0017] In the above technical solution, by comparing the target vehicle information and the real-time vehicle information, it is possible to effectively identify whether the vehicle in front is an irregular vehicle. For these vehicles, the traditional perception system may find it difficult to identify their features, and this method can make up for this deficiency and improve the accuracy of vehicle identification; for irregular vehicles, the system generates vehicle fusion information by fusing the target vehicle information and the real-time vehicle information to accurately reflect the information of the vehicle in front, thereby providing more reliable information and prompts for the current vehicle, and ensuring that the information obtained by the current vehicle is useful and relevant, reducing false alarms and interference from irrelevant information; for non-irregular vehicles, directly using the target vehicle information as the identification vehicle information can ensure the consistency and accuracy of the information; by providing detailed and accurate identification vehicle information, the driver's confidence and sense of security can be enhanced, allowing them to be more calm when dealing with various road and traffic conditions, and improving the personalization and accuracy of the user experience.

[0018] Furthermore, the cloud server also includes an exception database, and the exception handling includes: The vehicle-side device prompts that the license plate information format is incorrect, and re-acquires the vehicle image, or pops up an input box for the user to manually enter or voice input the license plate information.

[0019] And recording the acquisition timestamp, acquisition location and vehicle image into an abnormality database.

[0020] In the above technical solution, the vehicle-side device prompts that the license plate information format is wrong, so that the user can immediately know the problem, which helps to correct the error in time. A pop-up input box supports manual or voice input of license plate information, which provides users with a convenient error correction method and improves the reliability of the vehicle-mounted terminal; and it can also automatically re-acquire the vehicle image to ensure that the final uploaded data is accurate, reduce the occurrence of erroneous information, and improve the reliability of displayed information.

[0021] In addition, recording the acquisition timestamp, acquisition location, and vehicle image to the anomaly database facilitates subsequent tracing and analysis of abnormal situations, which can help identify potential problems or improvement points in the system, thereby optimizing overall system performance.

[0022] Furthermore, the step S300 further includes: The identified vehicle information is displayed in real time through the vehicle-side device, and a driving safety prompt is output based on the identified vehicle information.

[0023] In the above technical solution, comprehensive and detailed vehicle identification information is provided to the vehicle-side device in real time, which can help the driver make more reasonable driving decisions, especially when dealing with complex traffic conditions or interacting with unusual vehicles. It can enhance driving confidence and sense of security, and can also help the driving assistance process make further decisions and enhance the user's driving experience.

[0024] In addition, through driving safety prompts based on the output of recognized vehicle information, the system can remind the driver in real time of potential safety risks or abnormal situations, such as unusual vehicles or emergencies ahead, thereby enhancing the driver's alertness and preventing potential traffic accidents.

[0025] Based on the same concept, the present application also provides a front vehicle information recognition system, including: The matching module is used to obtain the license plate information of the vehicle in front in real time, and upload the license plate information to the cloud server for license plate matching to obtain the target vehicle information of the vehicle in front.

[0026] The acquisition module is used to acquire the real-time vehicle information of the vehicle in front, and compare and fuse the real-time vehicle information with the target vehicle information to obtain the identified vehicle information.

[0027] and an identification control module for performing automatic driving according to the identified vehicle information.

[0028] In the above technical solution, the matching module can obtain the license plate information of the vehicle in front in real time and upload it to the cloud server for matching. In this way, the target vehicle information of the vehicle in front can be accurately obtained; the acquisition module obtains the real-time vehicle information of the vehicle in front and compares and fuses it with the target vehicle information. This information fusion can improve the system's accurate recognition of vehicle characteristics, provide more comprehensive and detailed identification vehicle information, and then accurately identify special-shaped vehicles and improve driving safety; the identification control module performs automatic driving according to the identified vehicle information to further improve driving safety.

[0029] In addition, the real-time data update capability of the acquisition module enables the system to adapt to the dynamic traffic environment and continuously adjust and optimize the identification of vehicle information to cope with different environmental changes.

[0030] Based on the same concept, the present application also provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the method for identifying the front vehicle information when running.

[0031] Based on the same concept, the present application also provides a vehicle-mounted terminal, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the method for identifying the forward vehicle information.

[0032] Compared with the prior art, the beneficial effects of this application are: This application first obtains the license plate information of the vehicle in front, and uploads the license plate information to the cloud server to perform license plate matching and obtain the target vehicle information corresponding to the vehicle in front; then obtains the real-time vehicle information of the vehicle in front, compares and merges the real-time vehicle information with the target vehicle information to obtain the identification vehicle information and perform automatic driving. This application can accurately obtain the detailed information of the vehicle in front in the cloud server, and can determine whether the vehicle in front is a special-shaped vehicle, thereby accurately identifying special-shaped vehicles, preventing collision accidents due to unidentified special-shaped vehicles, and improving the safety of automatic driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flow chart of the method for identifying the forward vehicle information described in this application.

[0034] Figure 2 A schematic diagram showing a vehicle-side device for identifying vehicle information.

[0035] Figure 3 This is a framework diagram of the forward vehicle information recognition system described in this application. DETAILED DESCRIPTION

[0036] The following is a further detailed description of a forward vehicle information recognition method, system, storage medium and vehicle-mounted terminal of the present application in conjunction with specific embodiments and drawings.

[0037] See also Figure 1 The present application provides a method for identifying information of a vehicle ahead, comprising the following steps: S100: Acquire the license plate information of the vehicle in front in real time, and upload the license plate information to the cloud server to perform license plate matching to obtain the target vehicle information corresponding to the vehicle in front.

[0038] In some embodiments, in step S100, uploading the license plate information to a cloud server includes: A vehicle image of a front vehicle is acquired, and license plate information is acquired based on the vehicle image.

[0039] The license plate information is verified to determine whether the format of the acquired license plate information is correct. If it is correct, the license plate information is uploaded to the cloud server; otherwise, an exception is handled.

[0040] In some embodiments, a camera is used to capture an image of a vehicle in front, and then the captured vehicle image is recognized through image processing technology (such as an optical character recognition method) to extract a license plate area from the vehicle image and recognize character information on the license plate, thereby obtaining the license plate information.

[0041] Further, the identified license plate information is compared with a preset license plate format rule; optionally, the license plate format rule includes, for example, the length of the license plate number, the character type (letters and numbers), the arrangement order, etc.

[0042] Specifically: check whether the extracted license plate information conforms to the license plate format rules. If the license plate format is correct, upload the license plate information to the cloud server; otherwise, enter exception processing.

[0043] Furthermore, it should be noted that the verification of the license plate information is performed on the vehicle side of the current vehicle, and only when the correct license plate information is obtained will it be uploaded to the cloud server.

[0044] In other embodiments, the valid license plate information is organized into a formatted data format (such as JSON or XML), and the license plate information is uploaded to a cloud server via an encrypted network connection to ensure the security and privacy of data transmission.

[0045] It should be noted that whether the license plate information needs to be encrypted and uploaded is a choice that can be made by those skilled in the art according to the actual application scenario.

[0046] In the above technical solution, by acquiring the image of the vehicle in front and extracting the license plate information from it, the accuracy of license plate recognition can be improved, and the format of the license plate information can be verified to ensure that only data that meets the standards is uploaded. This reduces the transmission of erroneous information, improves data quality, reduces the burden of cloud data processing, avoids the storage and processing of invalid data, indirectly improves system efficiency, and provides consistent data input for the cloud server, which helps to efficiently perform subsequent data analysis and processing, thereby optimizing system performance and application effects.

[0047] Furthermore, in some embodiments, step S100 further includes: Based on the vehicle image record acquisition timestamp and acquisition location, the acquisition timestamp, acquisition location and vehicle image are synchronously uploaded to the cloud server.

[0048] In some embodiments, while uploading the license plate information, the acquisition timestamp and acquisition location corresponding to the vehicle image and the vehicle image are also synchronously uploaded to the cloud server.

[0049] In other embodiments, if the data uploaded to the cloud server is uploaded in an encrypted manner, when the cloud server receives the data, it will first perform a decryption process and then perform subsequent comparison and query work.

[0050] In the above technical solution, by synchronously uploading the acquisition timestamp and acquisition location, the cloud server can accurately know the specific acquisition time and location of each vehicle image, provide important time and space background for subsequent abnormal records, and make the data more traceable. When it is necessary to trace back specific events or behaviors, the relevant vehicle images and data can be quickly located through timestamps or location information, thereby improving the efficiency of information retrieval.

[0051] Furthermore, the cloud server at least includes a vehicle database, and obtaining target vehicle information in step S100 includes: Based on the license plate information and the vehicle image, a query is performed in a vehicle database to match the vehicle record corresponding to the license plate information, and based on the vehicle record, the target vehicle information is extracted and sent to the current vehicle.

[0052] In some embodiments, the cloud server queries the uploaded license plate information in the vehicle database to obtain the corresponding vehicle records, such as vehicle brand, vehicle type, color, size, license plate information, vehicle mileage, etc.; then extracts the required information based on the preset display requirements and sends it to the vehicle as the target vehicle information.

[0053] Optionally, the target vehicle information includes vehicle type, vehicle size, vehicle color and license plate information.

[0054] It should be noted that the vehicle records stored in the cloud server are the initial registration information of each vehicle.

[0055] In the above technical solution, by querying the vehicle database based on the license plate information and the vehicle image, the vehicle record corresponding to the license plate information can be accurately matched. This matching method helps to ensure that the target vehicle information obtained is accurate, thereby improving the system's recognition accuracy of the vehicle ahead; the vehicle database usually contains rich vehicle information. By querying and extracting the target vehicle information, more comprehensive vehicle data can be obtained and provided to the current vehicle to help the driver or the autonomous driving system make more informed decisions; in addition, the vehicle database is usually updated regularly to reflect more comprehensive vehicle information.

[0056] Furthermore, after the target vehicle information is acquired, step S200 may be executed.

[0057] S200: Acquire real-time vehicle information of the vehicle ahead, compare and fuse the real-time vehicle information with the target vehicle information to obtain identified vehicle information; wherein the identified vehicle information includes at least license plate information, vehicle type, vehicle size, vehicle color and special-shaped vehicle judgment results.

[0058] In some embodiments, the step S200 of obtaining the identified vehicle information includes: The target vehicle information is compared with the real-time vehicle information to determine whether the vehicle ahead is an irregular vehicle. If so, the target vehicle information and the real-time vehicle information are fused to obtain vehicle fusion information as the identification vehicle information; otherwise, the target vehicle information is used as the identification vehicle information.

[0059] In some embodiments, after obtaining the target vehicle information from the cloud server, the current visual information of the vehicle in front (i.e., the real-time vehicle information) is detected through the on-board camera and sensor, including the actual color, size, and appearance features (such as body shape, tire size, etc.) of the vehicle in front.

[0060] Furthermore, the real-time vehicle information and the target vehicle information are compared, including vehicle size comparison and color comparison, to determine whether the actual vehicle parameter information is consistent with the registered vehicle information stored in the cloud server.

[0061] For example, if the registered size of the vehicle ahead received does not match the actual size detected visually, it suggests that the vehicle ahead may be a modified vehicle (i.e., the special-shaped vehicle); for example, if the registered color of the vehicle ahead does not match the actual color, it can also suggest that the vehicle ahead is a modified vehicle.

[0062] Furthermore, based on the size and color comparison results combined with other visual features, a judgment is made as to whether the vehicle ahead is an irregular vehicle. The fused information is organized into a structured format and output as vehicle identification information.

[0063] For example, the target vehicle information obtained by the cloud server is as follows: License plate information: XYZ1234; vehicle type: sedan (brand A); registered dimensions: length 4800mm, width 1800mm, height 1450mm; registered color: red.

[0064] The real-time vehicle information currently obtained by the vehicle terminal is as follows: Actual color: blue; Actual size: length 4900mm, width 1850mm, height 1500mm; Appearance features: vehicle front face modified and large wheels installed.

[0065] At this time, after comparison, it can be obtained that the vehicle in front is a special-shaped vehicle, and the output identification vehicle information is as follows: License plate information: XYZ1234; Vehicle type: Sedan (Brand A); Actual color: Blue; Actual dimensions: Length 4900mm, width 1850mm, height 1500mm; Is it an irregular vehicle: Yes.

[0066] In other embodiments, if the target vehicle information and the real-time vehicle information are consistent, the identified vehicle information output at this time is as follows: License plate information: XYZ1234; Vehicle type: Sedan (Brand A); Registration color: Red; Registration dimensions: Length 4800mm, width 1800mm, height 1450mm; Is it an irregular vehicle: No.

[0067] In the above technical solution, by comparing the target vehicle information and the real-time vehicle information, it is possible to effectively identify whether the vehicle in front is an irregular vehicle. For these vehicles, the traditional perception system may find it difficult to identify their features, and this method can make up for this deficiency and improve the accuracy of vehicle identification; for irregular vehicles, the system generates vehicle fusion information by fusing the target vehicle information and the real-time vehicle information to accurately reflect the information of the vehicle in front, thereby providing more reliable information and prompts for the current vehicle, and ensuring that the information obtained by the current vehicle is useful and relevant, reducing false alarms and interference from irrelevant information; for non-irregular vehicles, directly using the target vehicle information as the identification vehicle information can ensure the consistency and accuracy of the information; by providing detailed and accurate identification vehicle information, the driver's confidence and sense of security can be enhanced, allowing them to be more calm when dealing with various road and traffic conditions, and improving the personalization and accuracy of the user experience.

[0068] In some embodiments, the exception handling includes: The vehicle-side device prompts that the license plate information format is incorrect, and re-acquires the vehicle image, or pops up an input box for the user to manually enter or voice input the license plate information.

[0069] And recording the acquisition timestamp, acquisition location and vehicle image into an abnormality database.

[0070] In some embodiments, “The license plate information format is incorrect, please enter the correct information” can be displayed on the vehicle-side device (such as the vehicle screen). In addition to being displayed on the vehicle screen, it can also be further combined with voice broadcast.

[0071] In other embodiments, only the vehicle screen may prompt "license plate information format error", then automatically re-acquire the vehicle image, and return to step S100 to re-execute the front vehicle information recognition method; in addition to the vehicle screen prompt, voice broadcast can also be performed.

[0072] In addition, while giving the prompt, the current vehicle will also record the vehicle image, acquisition timestamp and acquisition location corresponding to the erroneous license plate information into the exception database for further optimization processing; the exception database also belongs to the cloud server, which is convenient for technical personnel to obtain more comprehensive exception data to achieve comprehensive optimization.

[0073] In the above technical solution, the vehicle-side device prompts that the license plate information format is wrong, so that the user can immediately know the problem, which helps to correct the error in time. A pop-up input box supports manual or voice input of license plate information, which provides users with a convenient error correction method and improves the reliability of the vehicle-mounted terminal; and it can also automatically re-acquire the vehicle image to ensure that the final uploaded data is accurate, reduce the occurrence of erroneous information, and improve the reliability of displayed information.

[0074] In addition, recording the acquisition timestamp, acquisition location, and vehicle image into the anomaly database facilitates subsequent tracing and analysis of abnormal situations, which can help identify potential problems or improvement points in the system, thereby optimizing overall system performance.

[0075] Further, after obtaining the identified vehicle information, step S300 may be executed.

[0076] S300: Performing automatic driving according to the identified vehicle information.

[0077] Furthermore, in some embodiments, step S300 further includes: The identified vehicle information is displayed in real time through the vehicle-side device, and a driving safety prompt is output based on the identified vehicle information.

[0078] In some embodiments, Figure 2 As shown, vehicle identification information and driving safety tips displayed on a vehicle-side device (such as a car screen) are shown. While reminders are displayed on the car screen, voice broadcasts can also be combined; technical personnel in this field can choose other display forms and display information according to actual application requirements, and are not limited to this.

[0079] In the above technical solution, by outputting driving safety prompts based on the identification of vehicle information, the system can remind the driver in real time of potential safety risks or abnormal situations, such as an unusual vehicle or emergency situation ahead, thereby enhancing the driver's alertness and preventing potential traffic accidents.

[0080] Furthermore, automatic driving is performed based on the identified vehicle information, that is, the vehicle's driving state is controlled. The function of controlling the vehicle's driving state can adjust the vehicle's driving strategy based on the identified vehicle information, such as automatically adjusting the vehicle speed, adjusting the lane position, etc., to help the driver make safer driving decisions and cope with complex traffic environments; the system can intelligently respond to different driving scenarios based on real-time identification of vehicle information, provide personalized driving assistance, and enhance the system's intelligence level and adaptability to the environment; in addition, the adjustment of the vehicle's driving state is based on real-time identification of vehicle information. This data-driven control method can ensure the accuracy and effectiveness of the vehicle state adjustment and provide more precise driving assistance.

[0081] Further, if Figure 3 As shown, the present application also provides a front vehicle information recognition system, comprising: The matching module is used to obtain the license plate information of the vehicle in front in real time, and upload the license plate information to the cloud server for license plate matching to obtain the target vehicle information of the vehicle in front.

[0082] In some embodiments, the matching module obtains the vehicle image of the vehicle in front through the camera to extract the license plate information, and the license plate information needs to be verified to determine whether the format of the license plate information is correct. If it is correct, it will be uploaded to the cloud server; if it is wrong, exception processing will be performed.

[0083] In the cloud server, the received license plate information will be matched with the vehicle database to obtain the corresponding vehicle record, and then the target vehicle information (i.e. the registration information of the vehicle in front) will be further extracted.

[0084] The acquisition module is used to acquire the real-time vehicle information of the vehicle in front, and compare and fuse the real-time vehicle information with the target vehicle information to obtain the identified vehicle information.

[0085] In some embodiments, the camera of the current vehicle recognizes the vehicle in front again to obtain the corresponding real-time vehicle information (i.e., the actual information of the vehicle in front); then the registered information is compared with the actual information to determine whether the vehicle in front is an irregular vehicle. If so, it is necessary to further fuse the registered information and the actual information to obtain the final identified vehicle information; if not, the target vehicle information can be directly used as the identified vehicle information.

[0086] and an identification control module for performing automatic driving according to the identified vehicle information.

[0087] In some embodiments, corresponding driving status control is performed based on the identified vehicle information, such as deceleration, lane change, etc.

[0088] In the above technical solution, the matching module can obtain the license plate information of the vehicle in front in real time and upload it to the cloud server for matching. In this way, the target vehicle information of the vehicle in front can be accurately obtained; the acquisition module obtains the real-time vehicle information of the vehicle in front and compares and fuses it with the target vehicle information. This information fusion can improve the system's accurate recognition of vehicle characteristics, provide more comprehensive and detailed identification vehicle information, and then accurately identify special-shaped vehicles and improve driving safety; the identification control module performs automatic driving according to the identified vehicle information to further improve driving safety.

[0089] In addition, the real-time data update capability of the acquisition module enables the system to adapt to the dynamic traffic environment and continuously adjust and optimize the display content to cope with different environmental changes.

[0090] Furthermore, the present application also provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the method for identifying the forward vehicle information when running.

[0091] In some embodiments, the storage medium stores several computer programs for enabling the vehicle-mounted terminal to execute all or part of the steps of the method described in each embodiment of the present application.

[0092] The medium may include a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk, and other media that can store program codes.

[0093] Furthermore, the present application also provides a vehicle-mounted terminal, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the method for identifying the forward vehicle information.

[0094] In some embodiments, the memory and processor are interconnected via a bus; the processor may be one or more CPUs. When the processor is a CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor is used to control various functional modules of the vehicle terminal and process signals.

[0095] The memory includes but is not limited to RAM (Random Access Memory), ROM (Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), and CD-ROM (Compact Disc Read-Only Memory). The memory is used to store computer programs, operating systems, various applications and data, such as storing a computer program for implementing the method for identifying the forward vehicle information.

[0096] In summary, the present application provides a method, system, storage medium and vehicle-mounted terminal for identifying the information of the vehicle ahead; first, the license plate information of the vehicle ahead is obtained, and the license plate information is uploaded to the cloud server for license plate matching to obtain the target vehicle information corresponding to the vehicle ahead; then, the real-time vehicle information of the vehicle ahead is obtained, and the real-time vehicle information is compared and integrated with the target vehicle information to obtain the identified vehicle information and perform automatic driving. The present application can accurately obtain the detailed information of the vehicle ahead in the cloud server, and can determine whether the vehicle ahead is a special-shaped vehicle, thereby accurately identifying special-shaped vehicles, preventing collision accidents due to unidentified special-shaped vehicles, and improving the safety of automatic driving.

[0097] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely exemplary and are not intended to limit the scope of the present application to this. Those of ordinary skill in the art may make various changes and modifications therein without departing from the scope and spirit of the present application. All these changes and modifications are intended to be included within the scope of the present application as required by the appended claims.

[0098] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0100] The various component embodiments of the present application can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some modules according to the embodiments of the present application. The application can also be implemented as a device program (e.g., computer program and computer program product) for executing a part or all of the methods described herein. Such a program implementing the present application can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0101] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device 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 device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0102] Although the description of the present application is carried out in conjunction with the above specific embodiments, it is obvious that those skilled in the art can make many substitutions, modifications and changes based on the above content. Therefore, all such substitutions, improvements and changes are included in the spirit and scope of the appended claims.

Claims

1. A method for identifying vehicle information ahead, characterized in that: The following steps are involved: S100: Acquire the license plate information of the vehicle in front in real time, and upload the license plate information to the cloud server to perform license plate matching to obtain target vehicle information corresponding to the vehicle in front; S200: acquiring real-time vehicle information of the vehicle ahead, comparing and fusing the real-time vehicle information with the target vehicle information to obtain identification vehicle information; wherein the identification vehicle information at least includes license plate information, vehicle type, vehicle size, vehicle color and a judgment result of a special-shaped vehicle; and S300: Performing automatic driving according to the identified vehicle information.

2. The method for identifying the front vehicle information according to claim 1, characterized in that: In step S100, uploading the license plate information to a cloud server includes: Acquire a vehicle image of a front vehicle, and acquire license plate information based on the vehicle image; The license plate information is verified to determine whether the format of the acquired license plate information is correct. If it is correct, the license plate information is uploaded to the cloud server; otherwise, an exception is handled.

3. The method for identifying the front vehicle information according to claim 2, characterized in that: The step S100 further includes: Based on the vehicle image record acquisition timestamp and acquisition location, the acquisition timestamp, acquisition location and vehicle image are synchronously uploaded to the cloud server.

4. The method for identifying the front vehicle information according to claim 3, characterized in that: The cloud server at least includes a vehicle database, and the step S100 of obtaining target vehicle information includes: Based on the license plate information and the vehicle image, a query is performed in a vehicle database to match the vehicle record corresponding to the license plate information, and based on the vehicle record, the target vehicle information is extracted and sent to the current vehicle.

5. The method for identifying the front vehicle information according to claim 4, characterized in that: The step S200 of obtaining the identified vehicle information includes: The target vehicle information is compared with the real-time vehicle information to determine whether the vehicle ahead is an irregular vehicle. If so, the target vehicle information and the real-time vehicle information are fused to obtain vehicle fusion information as the identification vehicle information; otherwise, the target vehicle information is used as the identification vehicle information.

6. The method for identifying the front vehicle information according to claim 2, characterized in that: The cloud server also includes an exception database, and the exception handling includes: The vehicle-side device prompts that the license plate information format is incorrect, and re-acquires the vehicle image, or pops up an input box for the user to manually input or voice input the license plate information; And recording the acquisition timestamp, acquisition location and vehicle image into an abnormality database.

7. The method for identifying the front vehicle information according to claim 1, characterized in that: The step S300 further includes: The identified vehicle information is displayed in real time through the vehicle-side device, and a driving safety prompt is output based on the identified vehicle information.

8. A system using the method for identifying the front vehicle information according to any one of claims 1 to 7, characterized in that: include: A matching module is used to obtain the license plate information of the vehicle in front in real time and upload the license plate information to the cloud server for license plate matching to obtain the target vehicle information of the vehicle in front; An acquisition module is used to acquire real-time vehicle information of a vehicle ahead, and compare and fuse the real-time vehicle information with the target vehicle information to obtain identification vehicle information; as well as An identification control module is used to perform automatic driving based on the identified vehicle information.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method for identifying the forward vehicle information according to any one of claims 1 to 7 when running.

10. A vehicle-mounted terminal, characterized in that: The vehicle-mounted terminal includes a processor and a memory, and the memory stores at least one instruction, at least one program, a code set or an instruction set. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method for identifying the forward vehicle information as described in any one of claims 1 to 7.

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