Access control system, method and storage medium for a transport vehicle

Abstract

The application discloses a kind of access control management system, method and storage medium of transport vehicle, the system includes: first monitoring module, second monitoring module, card reading module, control module, access control module, wherein: first monitoring module is used to collect the first image dataset of target transport vehicle;Second monitoring module is used to collect first license plate image dataset;Card reading module is used to read vehicle tag dataset;Control module is used to determine target vehicle identification data according to first image dataset, first license plate image dataset and vehicle tag dataset;Obtain the target transport order data corresponding to target transport vehicle;According to target vehicle identification data and target transport order data determine target access control instruction;Access control module is used to execute corresponding access control action according to target access control instruction, to realize the access control management of transport vehicle.Using the present application, the management and control precision of access control management system is improved.

Description

Technical Field

[0001] This application relates to the field of access control technology, and in particular to an access control management system, method and storage medium for transport vehicles. Background Technology

[0002] The core purpose of access control for freight transportation is to regulate and manage freight vehicles entering and leaving the area, ensure the safety and order of freight transportation, and provide support for vehicle dispatching and safety management.

[0003] Currently, the access control system has a single identification mode function, cannot link vehicle information and transportation order data, lacks on-site passage video recording, has insufficient data traceability, makes it difficult to achieve full-process automated vehicle verification, and has insufficient control precision.

[0004] Therefore, improving the control accuracy of access control systems has become an urgent problem to be solved. Summary of the Invention

[0005] This application provides an access control management system, method, and storage medium for transport vehicles, which improves the control accuracy of the access control management system.

[0006] In a first aspect, embodiments of this application provide an access control management system for a transport vehicle, comprising: a first monitoring module, a second monitoring module, a card reader module, a control module, and an access control module, wherein: The first monitoring module is used to collect image data of the target transport vehicle to obtain a first image dataset; The second monitoring module is used to collect license plate image data of the target transport vehicle to obtain a first license plate image dataset; The card reader module is used to read the radio frequency identification tag data of the target transport vehicle to obtain a vehicle tag dataset; The control module is configured to: determine target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset; obtain target transportation order data corresponding to the target transportation vehicle; and determine target access control instructions based on the target vehicle identification data and the target transportation order data; the target access control instructions include any one of the following: allow access or disallow access. The access control module is used to execute corresponding access control actions according to the target access control command, so as to realize access control management of transport vehicles.

[0007] Secondly, embodiments of this application provide an access control method for transport vehicles, applied to the system described in the first aspect, the method comprising: The first image dataset is obtained by collecting image data of the target transport vehicle through the first monitoring module; The second monitoring module collects license plate image data of the target transport vehicle to obtain a first license plate image dataset; The vehicle tag dataset is obtained by reading the radio frequency identification tag data of the target transport vehicle through the card reader module; The control module determines target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset; obtains target transportation order data corresponding to the target transportation vehicle; and determines target access control instructions based on the target vehicle identification data and the target transportation order data. The target access control instructions include any one of the following: allow access or disallow access. The access control module executes corresponding access control actions according to the target access control command to realize access control management of transport vehicles.

[0008] Thirdly, embodiments of this application provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data interchange, wherein the computer program causes a computer to perform some or all of the steps described in the second aspect of embodiments of this application.

[0009] Fourthly, embodiments of this application provide an electronic device, including: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for performing the steps in the second aspect of embodiments of this application.

[0010] Fifthly, embodiments of this application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps described in the second aspect of embodiments of this application. The computer program product may be a software installation package.

[0011] Implementing this application will have the following beneficial effects: As can be seen, the access control system, method, and storage medium for transport vehicles described in this application simultaneously collect panoramic images of the vehicle, license plate images, and RFID tag data through a first monitoring module, a second monitoring module, and a card reading module, forming multi-dimensional data. The control module integrates these three types of data to comprehensively determine the target vehicle identification data, compensating for the shortcomings of single identification, which is susceptible to obstruction, environmental interference, and license plate fraud, thereby improving the accuracy of vehicle identification. Simultaneously, the system combines target transport order data for linked verification, matching vehicle identity with transport order information to achieve integrated verification of vehicle, tag, and order, preventing unauthorized passage and other violations. The entire process relies on automated data comparison and instruction judgment, reducing errors and management loopholes caused by manual registration and human judgment, and standardizing control standards, thus improving the control accuracy of the access control system. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments or background art of this application, the accompanying drawings used in the embodiments or background art of this application will be described below.

[0013] Figure 1 This is a scenario application diagram of an access control system for a transport vehicle provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of an access control system for a transport vehicle provided in an embodiment of this application; Figure 3 This is a flowchart of a method for determining target vehicle identification data provided in an embodiment of this application; Figure 4 This is a flowchart of a method for determining first vehicle identification data provided in an embodiment of this application; Figure 5 This is a system topology diagram of an access control system for a transport vehicle provided in an embodiment of this application; Figure 6 This is a schematic diagram of another access control management system for transport vehicles provided in an embodiment of this application; Figure 7 This is a flowchart of an access control management method for a transport vehicle provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0015] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0016] It should be understood that the term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document indicates that the preceding and following related objects are in an "or" relationship. In the embodiments of this application, "multiple" refers to two or more.

[0017] In the embodiments of this application, "at least one item" or its similar expression refers to any combination of these items, including any combination of a single item or a plurality of items. "One or more" means one or more, while "multiple" means two or more. For example, "at least one item" of a, b, or c can represent the following seven cases: a, b, c; a and b; a and c; b and c; a, b, and c. Each of a, b, and c can be an element or a set containing one or more elements.

[0018] In this application, the term "connection" refers to various connection methods, such as direct connection or indirect connection, to achieve communication between devices. This application does not impose any limitations on this.

[0019] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0020] The electronic devices described in this application embodiment may include smartphones (such as Android phones, iOS phones, Windows Phones, etc.), tablet computers, PDAs, laptops, video matrices, monitoring platforms, mobile internet devices (MIDs), or wearable devices, etc. The above are merely examples and not exhaustive, and include but are not limited to the above devices.

[0021] Of course, the aforementioned electronic devices may also include access control systems for transport vehicles, or control modules for access control systems for transport vehicles.

[0022] The following describes the relevant content, concepts, meanings, technical issues, technical solutions, and beneficial effects involved in the embodiments of this application.

[0023] First, let me explain some of the technical terms or phrases used in this application: Access control for transport vehicles: For freight and transport vehicles entering and leaving restricted areas such as factory areas and industrial parks, a comprehensive management process is implemented to achieve orderly vehicle passage and safe control of materials through identity verification, order matching, and access control start and stop.

[0024] Radio Frequency Identification (RFID): A non-contact automatic identification technology that uses radio frequency signals to complete data interaction between tags and identification devices, quickly reading the unique identifier and binding information of the target carrier, unaffected by environmental factors such as light and obstruction.

[0025] Radio Frequency Identification (RFID) tag data refers to the collection of information stored inside the RFID tag chip. RFID tags are usually attached to items (e.g., items transported on a transport vehicle). The data content varies depending on the tag type and usage scenario, and typically includes a unique identifier, user-defined data, control parameters, and security verification data.

[0026] Please see Figure 1 , Figure 1 This is a scenario application diagram of a transportation vehicle access control system provided in an embodiment of this application; wherein, the transportation vehicle access control system (hereinafter referred to as the system) includes: a first monitoring module, a second monitoring module, a card reading module, a control module, and an access control module; the first monitoring module, the second monitoring module, and the card reading module can all be installed on a pole; when the target transportation vehicle drives to the access control area, the multiple modules installed on the pole simultaneously start collecting data: The first monitoring module at the top of the pole collects panoramic image data of the target transport vehicle to form the first image dataset, which is used for subsequent extraction of vehicle appearance features. The card reader module in the middle of the pole reads the RFID tag data set on the target transport vehicle to obtain the vehicle tag dataset. The second monitoring module at the bottom of the pole collects license plate image data of the target transport vehicle to form the first license plate image dataset, which is used for subsequent license plate information recognition.

[0027] All of the aforementioned collected data are transmitted to the on-site control module. The control module, based on the received first image dataset, first license plate image dataset, and vehicle tag dataset, fuses and determines the target vehicle identification data; simultaneously, it retrieves the target transport order data corresponding to the target transport vehicle, matches and verifies the target vehicle identification data with the order data, and generates a target access control command.

[0028] The access control module is installed inside the access control channel. Based on the target access control command issued by the control module, it executes the opening or closing action to realize the passage control of the target transport vehicle.

[0029] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a transportation vehicle access control management system provided in an embodiment of this application; it can be seen that the system includes: a first monitoring module, a second monitoring module, a card reading module, a control module, and an access control module, wherein: The first monitoring module is used to collect image data of the target transport vehicle to obtain a first image dataset.

[0030] In this embodiment, the first monitoring module or the second monitoring module may include any of the following: a monitoring camera, a high-definition camera, an industrial camera, a license plate recognition camera, etc., which are not limited here.

[0031] In a specific embodiment, when the target transport vehicle enters the access control area and enters the first preset shooting range, a collection command is triggered, and the first monitoring module is started to continuously collect panoramic images of the target transport vehicle at the first preset shooting frame rate. Simultaneously, multiple images containing the overall appearance and body features of the vehicle are collected to form a multi-frame image sequence. The collected image sequence is format converted and preliminarily filtered to remove invalid images that are overexposed, underexposed, or severely distorted. The filtered valid images are summarized into a first image dataset, which is then transmitted to the control module for subsequent vehicle appearance feature recognition. The first preset shooting range and the first preset shooting frame rate can both be preset in advance or defaulted.

[0032] For example, the first preset shooting range can be: based on the center position of the access control module, within the range of 1.5m to 8m in the direction of vehicle entry, a rectangular area with a length of 10m and a width of 6m is defined as the shooting trigger range (i.e., the first preset shooting range); the first preset shooting frame rate can be 5 frames / second, and the single acquisition time is 2 seconds, that is, 10 panoramic images of the vehicle are continuously acquired; this frame rate can ensure that clear images without motion blur are acquired when the vehicle is traveling at a speed of less than 15km / h, and can also form a multi-frame image sequence, which is convenient for subsequent selection of the optimal frame and improvement of the stability of appearance recognition.

[0033] The second monitoring module is used to collect license plate image data of the target transport vehicle to obtain a first license plate image dataset.

[0034] In this embodiment, when the target transport vehicle enters the second preset shooting range, the second monitoring module is activated to continuously acquire images of the license plate area of ​​the target transport vehicle at the second preset shooting frame rate, thereby obtaining a first license plate image dataset. Both the second preset shooting range and the second preset shooting frame rate can be preset in advance or set by default.

[0035] It should be explained that the second preset shooting range can be the same as or different from the first preset shooting range; similarly, the second preset shooting frame rate can also be the same as or different from the first preset shooting frame rate.

[0036] The card reader module is used to read the radio frequency identification tag data of the target transport vehicle to obtain a vehicle tag dataset.

[0037] In this embodiment, when the target transport vehicle enters the preset radio frequency identification area, the card reader module automatically wakes up the radio frequency identification tag inside the vehicle via radio frequency, establishes wireless communication with the radio frequency identification tag through radio frequency signal, and stably reads the original data stored inside the radio frequency identification tag; the read original data is verified, deduplicated, and formatted, and invalid, interference, and abnormal identification data are filtered out; the processed valid tag data is integrated and summarized to generate a vehicle tag dataset, which is sent to the control module in real time to provide data support for subsequent comprehensive vehicle identity verification.

[0038] For example, the preset radio frequency induction identification area can be set to a range of 0.5m to 5m in front of the access control module; the card reader module adopts directional radio frequency identification to reduce signal interference from surrounding vehicles; the identification response time is controlled at the millisecond level, which can adapt to the passing speed of 15km / h and below, ensuring stable and accurate reading of radio frequency identification tag data during vehicle passage.

[0039] In some embodiments, the radio frequency identification (RFID) tag inside the vehicle may be mounted on the target transport vehicle itself or affixed to the surface of the transported goods.

[0040] The control module is configured to determine target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset; obtain target transportation order data corresponding to the target transportation vehicle; and determine target access control instructions based on the target vehicle identification data and the target transportation order data. The target access control instructions include any one of the following: allow access or disallow access.

[0041] In this embodiment, the control module can integrate and extract the first image dataset, the first license plate image dataset, and the vehicle tag dataset to obtain target vehicle identification data; then, it can obtain target transportation order data corresponding to the target transportation vehicle. Specifically, it can extract the license plate data of the target transportation vehicle from the target vehicle identification data, and query the transportation order data of the target transportation vehicle from a preset server based on the license plate data to obtain the target transportation order data; finally, it can determine the target access control instruction based on the target vehicle identification data and the target transportation order data.

[0042] The preset server can be preset in advance or defaulted. Specifically, the preset server is a backend server that stores transportation order data and is used to provide order query services.

[0043] Optional, please refer to Figure 3 , Figure 3 This is a flowchart illustrating a method for determining target vehicle identification data according to an embodiment of this application; it can be seen that, in determining the target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset, the control module is specifically used to perform the following... Figure 3 The steps shown are as follows: S11. Determine the first vehicle recognition data based on the first image dataset; S12. Determine the second vehicle recognition data based on the first license plate image dataset; S13. Determine the third vehicle identification data based on the vehicle tag dataset; S14. Determine the target vehicle identification data based on the first vehicle identification data, the second vehicle identification data, and the third vehicle identification data.

[0044] In this embodiment of the application, feature parsing and information extraction can be performed on the first image dataset, the first license plate image dataset, and the vehicle tag dataset respectively to obtain the corresponding vehicle recognition data, namely the first vehicle recognition data, the second vehicle recognition data, and the third vehicle recognition data. Finally, these data can be fused and summarized to obtain the target vehicle recognition data.

[0045] Thus, by independently generating corresponding vehicle identification data based on three different dimensions of data—vehicle panoramic image, license plate image, and RFID tag—differentiated vehicle identification can be achieved from multiple dimensions, including appearance features, license plate information, and RFID tags, breaking the limitations of single identification methods. Multi-dimensional independent identification followed by fusion and judgment effectively compensates for identification errors caused by factors such as lighting, occlusion, and equipment interference, which can affect single data. By leveraging the mutual verification and corroboration of multi-source information, problems such as license plate tampering, information alteration, and identification failure are avoided, significantly improving the comprehensiveness, accuracy, and reliability of vehicle identification.

[0046] Optional, please refer to Figure 4 , Figure 4 This is a flowchart illustrating a method for determining first vehicle identification data according to an embodiment of this application. It shows that the first image dataset includes *a* images, where *a* is a positive integer. Regarding the determination of the first vehicle identification data based on the first image dataset, the control module is specifically used to perform the following... Figure 4 The steps shown are as follows: S21. Preprocess each of the a images to obtain a first images; S22. Perform image segmentation on each of the a first images to obtain a segmented images containing the target transport vehicle; S23. Based on the a segmented images, extract features from the target transport vehicle to obtain a vehicle feature dataset; S24. Determine the first vehicle identification data based on the vehicle feature dataset.

[0047] In the embodiments of this application, preprocessing may include at least one of the following: image noise reduction, brightness and contrast adjustment, distortion correction, color balance, etc., which are not limited here.

[0048] In a specific embodiment, each of the *a* images can be preprocessed to obtain *a* first images. Specifically, the preprocessing can include image denoising and distortion correction, as follows: For each image, image denoising is first performed by removing invalid noise such as salt-and-pepper noise, lighting noise, and environmental interference noise from the image using a preset filtering algorithm, and weakening the image interference caused by complex scenes such as rainy days, foggy days, and low light at night; at the same time, distortion correction is performed on lens distortion and perspective shift problems caused by surveillance shooting, correcting abnormal problems such as image stretching and deformation, and restoring the true imaging shape of the vehicle. Through the above preprocessing, the image imaging quality and image standard are unified, the adverse effects of the environment and shooting equipment are eliminated, and the image detail is optimized, thereby obtaining *a* first images with clear image quality and standard shape. The preset filtering algorithm can be preset in advance or defaulted. For example, the preset filtering algorithm can include any of the following: mean filtering algorithm, median filtering algorithm, Gaussian filtering algorithm, bilateral filtering algorithm, etc., without limitation.

[0049] Next, each of the a first images can be segmented to obtain a segmented images containing the target transport vehicle. Specifically, for each first image, an image segmentation algorithm can be used to divide the image into regions, accurately distinguish the vehicle body from the background environment, remove irrelevant background areas such as roads, guardrails, and surrounding debris, select and retain the effective area where the target transport vehicle is located, and generate a segmented image that focuses only on the vehicle body, reducing the interference of background information on feature extraction; in this way, a segmented images can be obtained.

[0050] Furthermore, features can be extracted from the target transport vehicle based on a segmented images to obtain a vehicle feature dataset. Specifically, for each segmented image, key appearance features of the target transport vehicle are extracted, covering stable feature information such as vehicle outline, vehicle structure, vehicle color, vehicle markings, and cargo box shape. Then, the extraction results of these a segmented images can be integrated to form a complete and multi-dimensional vehicle feature dataset.

[0051] Finally, the first vehicle identification data can be determined based on the vehicle feature dataset. Specifically, the vehicle feature dataset can be used directly as the first vehicle identification data, or the vehicle feature dataset can be filtered to remove invalid and redundant feature data, and core vehicle appearance features with high recognizability and strong stability can be selected. Then, the first vehicle identification data can be generated based on these core vehicle appearance features.

[0052] For example, suppose the vehicle feature dataset contains various vehicle feature data such as vehicle body outline, local stains, instantaneous light and shadow color difference, vehicle body color, vehicle body structure, and vehicle logo. Among them, instantaneous light and shadow color difference and temporary stains are invalid features that are easily affected by the environment, and the same type of outline parameters collected repeatedly in multiple frames are redundant features, so these types of features are directly removed. Only the core vehicle appearance features that are not easily affected by lighting and shooting angle and have high distinguishability, such as the main color of the vehicle body, the overall outline size, the type of vehicle body, and fixed logos, can be retained. Based on the selected core vehicle appearance features, the corresponding first vehicle recognition data is generated by integrating and encoding.

[0053] Thus, through a step-by-step processing flow of image preprocessing, image segmentation, feature extraction, and recognition data generation, image noise and distortion interference can be eliminated, irrelevant background areas can be removed, the target vehicle can be accurately located and effective appearance features can be extracted, the adverse effects of complex scenes and shooting conditions can be reduced, the accuracy of feature extraction and recognition stability can be improved, and reliable appearance data support can be provided for subsequent identity verification.

[0054] Optionally, the first license plate image dataset includes b license plate images; b is a positive integer; in determining the second vehicle recognition data based on the first license plate image dataset, the control module is specifically used for: S31. Perform license plate recognition on each of the b license plate images to obtain b license plate recognition results; S32. Perform data verification on the b license plate recognition results to obtain c license plate recognition results that pass the verification; c is an integer less than or equal to b; S33. Determine a reference license plate recognition result based on the c license plate recognition results; S34. Perform compliance verification on the reference license plate recognition result according to the preset license plate rule library to obtain a first verification result; the first verification result includes any of the following: verification successful, verification failed; S35. When the first verification result includes verification success, determine the second vehicle identification data based on the reference license plate recognition result.

[0055] In this embodiment, the preset license plate rule library can be preset in advance or defaulted to. The preset license plate rule library is a set of standardized license plate specifications stored in the system in advance, which integrates the unified format constraints and verification standards of various compliant license plates.

[0056] In a specific embodiment, license plate recognition can be performed on each of the b license plate images to obtain b license plate recognition results. Specifically, for each license plate image, a license plate character recognition algorithm is used to identify the Chinese characters, letters, numbers, and license plate type in the image, and output the corresponding character sequence, license plate format, and other recognition content, i.e., the license plate recognition result; thus, b license plate recognition results can be obtained. Then, data verification can be performed on the b license plate recognition results to obtain c license plate recognition results that pass the verification. Specifically, for each license plate recognition result, a basic compliance verification can be performed first to remove abnormal recognition results with incomplete characters, garbled characters, missing characters, or serious misalignment, and to filter out invalid recognition content caused by image blurring, excessively strong or weak lighting, retaining valid results with complete recognition and preliminary compliance with the format, thereby selecting c qualified license plate recognition results.

[0057] Then, a reference license plate recognition result can be determined based on c license plate recognition results. Specifically, these c license plate recognition results can be compared and analyzed, and the recognition result with the highest repetition and best character consistency can be selected as the unified reference license plate recognition result by using frequency optimization (or similarity fusion) to avoid random errors caused by single image recognition deviations. Furthermore, the reference license plate recognition result can be verified for compliance based on a preset license plate rule library to obtain the first verification result. Specifically, the reference license plate recognition result can be compared with the rules in the preset license plate rule library item by item to verify whether the license plate character combination, number structure, and format specifications meet the standard requirements. Based on this, it can be determined whether the verification is successful or unsuccessful, and the corresponding first verification result can be generated.

[0058] When the first verification result is successful, the second vehicle identification data is determined based on the reference license plate recognition result. Specifically, the reference license plate recognition result can be directly used as the second vehicle identification data.

[0059] When the first verification result includes a verification failure, the second monitoring module can be controlled to collect new license plate image data and re-identify the new license plate image data until a successfully verified license plate recognition result is obtained, which is the second vehicle recognition data.

[0060] Thus, through a multi-layered control mechanism of parallel recognition of multiple license plate images, preliminary data screening, result fusion, and secondary rule verification, abnormal results caused by blurry single-frame recognition and character errors can be effectively eliminated. The reference license plate recognition result is determined by comprehensively considering multiple sets of valid recognition results, and compliance verification is completed by combining a standardized license plate rule library. This significantly reduces the probability of misidentification and omission of license plates, avoids recognition deviations caused by environmental interference, and ensures the accuracy and compliance of license plate dimension recognition data.

[0061] Optionally, the vehicle tag dataset includes d vehicle tag data; d is a positive integer; in determining the third vehicle identification data based on the vehicle tag dataset, the control module is specifically used for: S41. Parse the d vehicle tag data to obtain d tag parsing results; S42. Perform validity verification on the d tag parsing results to obtain d verification results; each verification result includes any of the following: verification successful, verification failed; S43. Based on the d verification results, remove the tag parsing results that failed verification from the d tag parsing results to obtain e tag parsing results; e is an integer less than or equal to d; S44. Determine the third vehicle identification data based on the parsing results of the e tags.

[0062] In this embodiment, d vehicle tag data can be decoded and parsed according to a preset data encoding format to extract core binding information such as vehicle number, transport identifier, and unique identifier stored within the tags, and output the corresponding content one by one to obtain d tag parsing results. Then, the validity of the d tag parsing results can be verified to obtain d verification results. Specifically, for each tag parsing result, a validity verification is performed, mainly checking data integrity, encoding format legality, data field integrity, and tag signal validity. It determines whether there are any anomalies such as garbled characters, missing fields, or data tampering in the parsed content. If none of these anomalies exist, the verification is considered successful; if any anomaly exists, the verification is considered unsuccessful. In this way, d verification results can be obtained. The preset data encoding format can be preset in advance or defaulted.

[0063] Furthermore, based on the d verification results, the label parsing results that failed verification can be removed from the d label parsing results to obtain e label parsing results. Specifically, f verification results that failed verification can be identified from the d verification results, and the f label parsing results corresponding to the f verification results can be removed from the d label parsing results to obtain e label parsing results; where f is an integer less than or equal to d, and f + e = d. Finally, the third vehicle identification data can be determined based on the e label parsing results. Specifically, the e label parsing results can be directly used as the third vehicle identification data.

[0064] In this way, by parsing vehicle tag data, verifying its validity, and removing abnormal parsing results, invalid tag data caused by signal interference, data tampering, and abnormal transmission can be effectively filtered out, while retaining complete and compliant valid tag parsing content, reducing the interference of abnormal data on the recognition results, and improving the authenticity and accuracy of tag information.

[0065] Optionally, the first vehicle identification data includes vehicle appearance data; the second vehicle identification data includes license plate data; and the third vehicle identification data includes RFID tag data. In determining the target vehicle identification data based on the first vehicle identification data, the second vehicle identification data, and the third vehicle identification data, the control module is specifically used for: S51. Based on the license plate data, determine the vehicle registration data corresponding to the target transport vehicle; S52. Determine the first matching result based on the vehicle appearance data and the vehicle registration data; S53. Determine the permitted transportation information corresponding to the target transport vehicle based on the vehicle registration data; S54. Determine the goods transported by the vehicle based on the RFID tag data; S55. Determine the second matching result based on the goods transported by the vehicle and the permitted transportation information; S56. When the first matching result and the second matching result meet the preset conditions, determine the target vehicle identification data based on the vehicle appearance data, the license plate data and the radio frequency tag data.

[0066] In this embodiment of the application, the preset conditions can be preset in advance or defaulted. Specifically, the preset conditions can be: both the first matching result and the second matching result are successful matches.

[0067] In a specific embodiment, vehicle registration data corresponding to the target transport vehicle can be determined based on license plate data. Specifically, the license plate data is used as a retrieval index to query the registration data of the target transport vehicle in a preset vehicle registration database to obtain the vehicle registration data. The preset vehicle registration database can be pre-set or defaulted. Then, a first matching result can be determined based on vehicle appearance data and vehicle registration data. Specifically, the vehicle registration data may include registered appearance data. A preset similarity algorithm is used to calculate the similarity between the vehicle appearance data and the registered appearance data to obtain a first similarity. If the first similarity is greater than a preset similarity threshold, the first matching result is determined to be a successful match; if the first similarity is not greater than the preset similarity threshold, the first matching result is determined to be a failed match. The preset similarity algorithm can be preset or defaulted. For example, the preset similarity algorithm may include any of the following: structural similarity algorithm, feature point matching algorithm, cosine similarity algorithm, etc., which are not limited here.

[0068] Next, the permitted transportation information corresponding to the target transport vehicle can be determined based on the vehicle registration data. Specifically, the vehicle registration data may also include vehicle transport qualification information. Based on this vehicle transport qualification information, compliance information such as the approved transport scope, traffic permissions, and permitted categories of goods to be transported can be obtained, i.e., permitted transportation information. Then, the transported goods can be determined based on the RFID tag data. Specifically, the RFID tag data may include item codes. Based on the item code, a preset item code database can be queried to obtain the transported goods. The preset item code database can be preset in advance or defaulted to.

[0069] Furthermore, a second matching result can be determined based on the goods transported by the vehicle and the permitted transportation information. Specifically, the permitted transportation category can be determined based on the permitted transportation information, and the goods transported by the vehicle can be compared and verified to determine whether the goods transported by the vehicle are within the scope of compliant transportation. If they are, the second matching result is a successful match; otherwise, the second matching result is a failed match.

[0070] When the first and second matching results meet the preset conditions, the vehicle appearance data, license plate data, and RFID tag data can be directly identified as the target vehicle identification data.

[0071] If the first matching result and the second matching result do not meet the preset conditions, the target vehicle identification data is determined to be empty, and the target access control instruction is set to not allow passage through the access control.

[0072] In this way, by combining multiple types of data such as license plate, appearance, and RFID tags for cross-verification, and by making dual judgments based on vehicle appearance matching and compliance of transported goods, the limitations of a single identification method are made up for, identification errors are reduced, vehicle identity and transportation qualifications are comprehensively verified, and the accuracy and reliability of vehicle identification results are effectively improved.

[0073] Optionally, the target transportation order data includes: order vehicle information, order access permissions, and order transported goods; regarding the determination of the target access control command based on the target vehicle identification data and the target transportation order data, the control module is specifically used for: S61. Verify the target vehicle identification data based on the order vehicle information to obtain a second verification result; S62. When the second verification result includes verification success, obtain the vehicle transportation time period of the target transport vehicle; perform permission verification based on the order access permission and the vehicle transportation time period to obtain a third verification result; when the third verification result includes verification success, determine whether the vehicle transported items are consistent with the order transported items; if consistent, determine that the target access control instruction includes allowing access through the access control; if inconsistent, determine that the target access control instruction includes disallowing access through the access control.

[0074] In this embodiment, the target vehicle identification data can be verified based on the order vehicle information to obtain a second verification result. Specifically, the license plate data, vehicle appearance data, and transported goods of the target transport vehicle can be extracted from the target vehicle identification data. Then, the license plate data and vehicle appearance data are compared with the order vehicle information one by one to verify whether the target transport vehicle is the transport vehicle bound to the order. If so, the second verification result is determined to be successful; otherwise, the second verification result is determined to be unsuccessful.

[0075] If the second verification result includes a verification failure, the target access control instruction is determined to include not allowing access through the access control.

[0076] When the second verification result includes a successful verification, the vehicle transportation period of the target transport vehicle is obtained. Specifically, the earliest acquisition time of the image in the first image dataset can be obtained. Based on this earliest acquisition time, a transportation time interval, i.e., the vehicle transportation period, is defined in combination with a preset duration. For example, assuming the earliest acquisition time is 8:10 and the preset duration is 30 minutes, the defined transportation time interval (i.e., the vehicle transportation period) can be 8:00~8:30. Then, permission verification can be performed based on the order access permission and the vehicle transportation period to obtain the third verification result. Specifically, the allowed passage time period limited in the order access permission can be determined, and the vehicle transportation period is compared with the allowed passage time period to determine whether the vehicle transportation period is within the time range permitted by the order. If it is, the third verification result is determined to be a successful verification; if it is not, the third verification result is determined to be a failed verification.

[0077] If the third verification result includes a verification failure, it is determined that the target access control instruction includes not allowing access through the access control.

[0078] If the third verification result includes a successful verification, it can be determined whether the goods transported by the vehicle are consistent with the goods transported in the order. If they are consistent, the target access control instruction is determined to include allowing passage through the access control. If they are inconsistent, the target access control instruction is determined to include disallowing passage through the access control.

[0079] In this way, by sequentially verifying vehicle identity, time of passage, and transported goods, the access conditions are controlled at each level, avoiding misjudgments caused by single verification, effectively standardizing the management of transport vehicle passage, improving the accuracy and security of access control, and ensuring that the transportation order within the site is compliant and controllable.

[0080] The access control module is used to execute corresponding access control actions according to the target access control command, so as to realize access control management of transport vehicles.

[0081] In this application embodiment, the access control module may include any of the following: barrier gate equipment, access control gate machine, access control controller, access control identification terminal, vehicle stop, lifting barrier, etc., without limitation.

[0082] In a specific embodiment, the access control module is used to receive the target access control command issued by the control module, and execute the corresponding access control action according to the target access control command to realize access control management of transport vehicles. For example, if the target access control command is to allow passage through the access control, the module will execute actions such as opening the door and raising the barrier to allow the target transport vehicle to pass; if the target access control command is to disallow passage through the access control, the module will keep the access control closed and prohibit passage. In this way, access control management of transport vehicles can be automatically realized.

[0083] Optional, please refer to Figure 5 , Figure 5 This is a system topology diagram of a transportation vehicle access control system provided in an embodiment of this application. The system topology diagram includes: a data analysis module, a data management module, a server, a mobile terminal, a switch, and the transportation vehicle access control system. The transportation vehicle access control system may include: a license plate recognition camera (i.e., a second monitoring module), a card reader (i.e., a card reading module), a barrier gate (i.e., an access control module), and a high-definition camera (i.e., a first monitoring module); details are as follows: Core Hub: With the server as the data and control core, it connects upwards to the data analysis module, data management module, and mobile terminals to realize data statistics, business management, and mobile terminal appointment / query functions; downwards, it connects to the field equipment network through a switch.

[0084] On-site execution layer: The switch connects to the access control system for transport vehicles. This system consists of four types of devices working collaboratively: License plate recognition camera: Automatically recognizes vehicle license plates as the first line of evidence for identity verification; Card reader: Reads vehicle RFID tags (or access cards) to complete dual verification of vehicle identity and transportation information; High-definition camera: captures real-time images of the scene for vehicle appearance comparison and traffic record keeping; Barrier gate: As an access control device, it receives instructions from the server to complete the release / interception action.

[0085] In this way, the compliance, safety and efficiency of transport vehicle passage are ensured through the collaboration of multiple devices.

[0086] It should be noted that the data analysis module and the data management module can be components of the control module.

[0087] Optional, please refer to Figure 6 , Figure 6This is a schematic diagram of another access control management system for transport vehicles provided in this application embodiment; it can be seen that, in addition to the first monitoring module, second monitoring module, card reading module, control module, and access control module, the system also includes: a reservation module; the reservation module is specifically used for: S71. Receive target reservation information from a target user for the target transport vehicle; the target user is the user of the target transport vehicle; S72. Review the target reservation information to obtain a target review result; the target review result includes any one of the following: review passed, review failed; S73. When the target review result includes "review failed", generate target prompt information; the target prompt information is used to inform the target user of the reason for the review failure.

[0088] In this embodiment, the target user can submit target reservation information to the reservation module using a preset submission method. The reservation module receives the target reservation information in real time and completes the entry and temporary storage of the reservation information. Then, the target reservation information can be reviewed to obtain the target review result. Specifically, preset reservation review rules can be retrieved to verify the completeness, compliance, and validity of the target reservation information one by one, and to check whether key contents such as vehicle information, travel time, and transported goods meet the control requirements. If they meet the requirements, the target review result is "approved"; if they do not meet the requirements, the target review result is "not approved".

[0089] It should be explained that both the preset submission method and the preset appointment review rules can be preset or defaulted in advance; the preset submission method can include any of the following: web page submission, mini program submission, client software submission, offline terminal submission, etc., without any limitation.

[0090] When the target review result includes a failure to pass the review, a target prompt message is generated. Specifically, the appointment module can automatically match the corresponding reason for the exception and generate a target prompt message for the reason for the exception, clearly informing the target user of the specific problem of the rejection, so that the target user can modify and improve the appointment content and resubmit.

[0091] When the target review result includes "Review passed", the appointment module can display "Review passed" to notify the target user that the review has been approved.

[0092] In this way, by collecting the reservation information submitted by users and conducting compliance reviews, non-compliant reservation applications can be screened in advance, and vehicle access management can be standardized from the source. For cases that fail the review, the reason prompts can be automatically generated, which makes it easier for users to correct and supplement information in a timely manner, improve the efficiency of reservation processing, reduce invalid access applications, and ensure the orderly implementation of access control for transport vehicles.

[0093] In summary, the access control system for transport vehicles described in this application simultaneously collects panoramic images of the vehicle, license plate images, and RFID tag data through a first monitoring module, a second monitoring module, and a card reading module, forming multi-dimensional data. The control module integrates these three types of data to comprehensively determine the target vehicle identification data, overcoming the shortcomings of single-identification systems which are susceptible to obstruction, environmental interference, and license plate fraud, thus improving the accuracy of vehicle identification. Simultaneously, the system combines target transport order data for verification, matching vehicle identity with transport order information to achieve integrated verification of vehicle, tag, and order, preventing unauthorized passage and other violations. The entire process relies on automated data comparison and command judgment, reducing errors and management loopholes caused by manual registration and human judgment, and ensuring unified and standardized control standards, thereby improving the control accuracy of the access control system.

[0094] Please see Figure 7 , Figure 7 This is a flowchart of an access control management method for transport vehicles provided in an embodiment of this application; applied to the access control management system for transport vehicles described in the above embodiment, the method includes the following steps: S1. Collect image data of the target transport vehicle through the first monitoring module to obtain the first image dataset; S2. Collect the license plate image data of the target transport vehicle through the second monitoring module to obtain the first license plate image dataset; S3. Read the radio frequency identification tag data of the target transport vehicle through the card reading module to obtain the vehicle tag dataset; S4. The control module determines the target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset; obtains the target transportation order data corresponding to the target transportation vehicle; and determines the target access control instruction based on the target vehicle identification data and the target transportation order data; the target access control instruction includes any one of the following: allow access or disallow access. S5. The access control module executes corresponding access control actions according to the target access control command to realize access control management of transport vehicles.

[0095] In specific implementations, the access control management method for transport vehicles described in the embodiments of the present invention can also execute other implementation methods described in the access control management system for transport vehicles provided in the embodiments of the present invention, which will not be repeated here.

[0096] Please see Figure 8 , Figure 8This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, applied to the access control management system for transport vehicles described in the above embodiment. The electronic device may include a processor, a memory, a communication interface, and one or more programs. The processor, memory, and communication interface can be interconnected via a bus. The one or more programs are stored in the memory and configured to be executed by the processor. In this embodiment, the programs include instructions for performing the following steps: The first image dataset is obtained by collecting image data of the target transport vehicle through the first monitoring module; The second monitoring module collects license plate image data of the target transport vehicle to obtain a first license plate image dataset; The vehicle tag dataset is obtained by reading the radio frequency identification tag data of the target transport vehicle through the card reader module; The control module determines target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset; obtains target transportation order data corresponding to the target transportation vehicle; and determines target access control instructions based on the target vehicle identification data and the target transportation order data. The target access control instructions include any one of the following: allow access or disallow access. The access control module executes corresponding access control actions according to the target access control command to realize access control management of transport vehicles.

[0097] In specific implementations, the electronic devices described in the embodiments of the present invention can also execute other implementation methods described in the access control management method for transport vehicles provided in the embodiments of the present invention, which will not be repeated here.

[0098] The processor can be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, cells, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. The communication unit can be a communication interface, transceiver, transceiver circuit, etc., and the storage unit can be a memory.

[0099] The memory can be volatile or non-volatile, or a combination of both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0100] It is understood that electronic devices may include more or fewer structural elements than those shown in the above block diagram, such as power modules, physical buttons, Wi-Fi modules, speakers, Bluetooth modules, sensors, display modules, etc., without limitation.

[0101] This application also provides a computer-readable storage medium storing a computer program for electronic data interchange, which causes a computer to perform some or all of the steps of any of the methods described in the above method embodiments, wherein the computer includes an electronic device.

[0102] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include an electronic device.

[0103] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0104] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0105] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0106] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0107] The steps of the methods or algorithms described in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (EEPROM), registers, hard disk, portable hard disk, read-only optical disk (CD-ROM), or any other form of storage medium well known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Furthermore, the ASIC can reside in a terminal device or management device. Alternatively, the processor and storage medium can exist as discrete components in the terminal device or management device.

[0108] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in the embodiments of this application can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated.

[0109] The aforementioned computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media.

[0110] The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital video discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0111] The modules / units included in the various devices and products described in the above embodiments can be software modules / units, hardware modules / units, or a combination of both. For example, for devices and products applied to or integrated into a chip, all modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits. For devices and products applied to or integrated into a chip module, all modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The implementation is achieved through a software program that runs on the processor integrated within the chip module. The remaining modules / units (if any) can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into terminal equipment, each of their modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components within the terminal equipment. Alternatively, at least some modules / units can be implemented through a software program that runs on the processor integrated within the terminal equipment, while the remaining modules / units (if any) can be implemented using hardware methods such as circuits.

[0112] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the embodiments of this application. It should be understood that the above descriptions are merely specific embodiments of the embodiments of this application and are not intended to limit the protection scope of the embodiments of this application. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solutions of the embodiments of this application should be included within the protection scope of the embodiments of this application.

Claims

1. An access control management system for transport vehicles, characterized in that, include: The system comprises a first monitoring module, a second monitoring module, a card reader module, a control module, and an access control module, among which: The first monitoring module is used to collect image data of the target transport vehicle to obtain a first image dataset; The second monitoring module is used to collect license plate image data of the target transport vehicle to obtain a first license plate image dataset; The card reader module is used to read the radio frequency identification tag data of the target transport vehicle to obtain a vehicle tag dataset; The control module is configured to: determine target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset; obtain target transportation order data corresponding to the target transportation vehicle; and determine target access control instructions based on the target vehicle identification data and the target transportation order data; the target access control instructions include any one of the following: allow access or disallow access. The access control module is used to execute corresponding access control actions according to the target access control command, so as to realize access control management of transport vehicles; Specifically, in determining the target vehicle recognition data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset, the control module is used for: First vehicle recognition data is determined based on the first image dataset; Determine the second vehicle recognition data based on the first license plate image dataset; The third vehicle identification data is determined based on the vehicle tag dataset; The target vehicle identification data is determined based on the first vehicle identification data, the second vehicle identification data, and the third vehicle identification data; The first vehicle identification data includes vehicle appearance data; the second vehicle identification data includes license plate data; and the third vehicle identification data includes radio frequency tag data. In determining the target vehicle identification data based on the first vehicle identification data, the second vehicle identification data, and the third vehicle identification data, the control module is specifically used for: Based on the license plate data, determine the vehicle registration data corresponding to the target transport vehicle; Based on the vehicle appearance data and the vehicle registration data, a first matching result is determined. Specifically, the vehicle registration data includes registered appearance data. A preset similarity algorithm is used to calculate the similarity between the vehicle appearance data and the registered appearance data to obtain a first similarity. If the first similarity is greater than a preset similarity threshold, the first matching result is determined to be a successful match. If the first similarity is not greater than the preset similarity threshold, the first matching result is determined to be a failed match. The permitted transportation information corresponding to the target transport vehicle is determined based on the vehicle registration data. The goods transported by the vehicle are determined based on the RFID tag data; Based on the goods transported by the vehicle and the permitted transportation information, a second matching result is determined; When the first matching result and the second matching result meet the preset conditions, the target vehicle identification data is determined based on the vehicle appearance data, the license plate data and the radio frequency tag data.

2. The system as described in claim 1, characterized in that, The first image dataset includes a images; a is a positive integer; In determining the first vehicle recognition data based on the first image dataset, the control module is specifically configured to: Each of the a images is preprocessed to obtain a first images; Each of the a first images is segmented to obtain a segmented images containing the target transport vehicle; Based on the a segmented images, feature extraction is performed on the target transport vehicle to obtain a vehicle feature dataset; The first vehicle identification data is determined based on the vehicle feature dataset.

3. The system as described in claim 1 or 2, characterized in that, The first license plate image dataset includes b license plate images; b is a positive integer; In determining the second vehicle recognition data based on the first license plate image dataset, the control module is specifically configured to: Perform license plate recognition on each of the b license plate images to obtain b license plate recognition results; The b license plate recognition results are verified to obtain c license plate recognition results that pass the verification. c is an integer less than or equal to b; A reference license plate recognition result is determined based on the c license plate recognition results; The reference license plate recognition result is verified for compliance based on a preset license plate rule library to obtain a first verification result. The first verification result includes any of the following: verification successful, verification failed; If the first verification result includes verification success, the second vehicle identification data is determined based on the reference license plate recognition result.

4. The system as described in claim 1 or 2, characterized in that, The vehicle tag dataset includes d vehicle tag data; d is a positive integer; In determining the third vehicle identification data based on the vehicle tag dataset, the control module is specifically configured to: The d vehicle tag data are parsed to obtain d tag parsing results; The validity of the d tag parsing results is validated to obtain d validation results; each validation result includes any of the following: validation successful, validation failed; Based on the d verification results, the tag parsing results that failed verification are removed from the d tag parsing results to obtain e tag parsing results; e is an integer less than or equal to d; The third vehicle identification data is determined based on the parsing results of the e tags.

5. The system as described in claim 1, characterized in that, The target transportation order data includes: order vehicle information, order access permissions, and order transported items; In determining the target access control command based on the target vehicle identification data and the target transportation order data, the control module is specifically used for: The target vehicle identification data is verified based on the order vehicle information to obtain a second verification result; If the second verification result includes verification success, the vehicle transportation time period of the target transport vehicle is obtained; permission verification is performed based on the order access permission and the vehicle transportation time period to obtain a third verification result; if the third verification result includes verification success, it is determined whether the vehicle transported items are consistent with the order transported items; if they are consistent, it is determined that the target access control instruction includes allowing access through the access control; if they are inconsistent, it is determined that the target access control instruction includes disallowing access through the access control.

6. The system as described in claim 1 or 2, characterized in that, The system further includes a reservation module; the reservation module is specifically used for: Receive target reservation information from a target user for the target transport vehicle; the target user is the user of the target transport vehicle; The target reservation information is reviewed to obtain a target review result; the target review result includes any one of the following: review passed, review failed; When the target review result includes "review failed", a target prompt message is generated; the target prompt message is used to inform the target user of the reason for the review failure.

7. A method for access control management of transport vehicles, characterized in that, Applied to the system as described in any one of claims 1-6, the method comprises: The first image dataset is obtained by collecting image data of the target transport vehicle through the first monitoring module; The second monitoring module collects license plate image data of the target transport vehicle to obtain a first license plate image dataset; The vehicle tag dataset is obtained by reading the radio frequency identification tag data of the target transport vehicle through the card reader module; The control module determines target vehicle identification data based on the first image dataset, the first license plate image dataset, and the vehicle tag dataset; obtains target transportation order data corresponding to the target transportation vehicle; and determines target access control instructions based on the target vehicle identification data and the target transportation order data. The target access control instructions include any one of the following: allow access or disallow access. The access control module executes corresponding access control actions according to the target access control command to realize access control management of transport vehicles.

8. A computer-readable storage medium, characterized in that, A computer program for electronic data interchange is stored, wherein the computer program causes a computer to perform the method as described in claim 7.

Images