Automatic generation method for driving test subject two teaching and related equipment

Abstract

The application discloses a kind of driving test subject two teaching automation generation method and related equipment.The method comprises the following steps: constructing the virtual three-dimensional site model of subject two driving test training site;Collecting real training data of real training vehicle in the teaching process of subject two driving test training site;The real training data is sent to the mobile terminal to match the virtual three-dimensional site model, to carry out teaching simulation synchronization in the mobile terminal.Can solve the problem that real driving training ability level is not easy to assess, and the requirement of coach is higher, and driving training efficiency is low.

Description

Technical Field

[0001] This application relates to the field of computers, and more specifically, to a method and related equipment for automating the generation of driving test subject 2 teaching materials. Background Technology

[0002] Driving training is the core of driver learning, allowing students to gain valuable driving experience through hands-on vehicle operation. Each student learns at a different pace and with different needs, making it difficult for instructors to provide completely personalized training plans, potentially impacting training effectiveness. Instructors can only focus on one student at a time, resulting in limited training time for each student and lower overall training efficiency. When there are many students, training schedules may need to be lengthy to meet the needs of all students. Instructors need to maintain high concentration for extended periods, monitoring every action of the students, which places high demands on their physical and mental stamina. Summary of the Invention

[0003] The summary section introduces a series of simplified concepts, which will be further explained in detail in the detailed description section. This summary section is not intended to limit the key features and essential technical features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0004] To address the problems of difficulty in assessing actual driving skills, high demands on instructors, and low efficiency in driving training, this invention proposes, firstly, an automated method for generating driving test subject two instruction materials. The method includes: Construct a virtual three-dimensional training ground model for the driving test (subject 2); Collect real training data of actual training vehicles at the driving test training site during the teaching process of Subject 2; The real training data is sent to the mobile device to match the virtual 3D site model, so as to conduct synchronous teaching simulation on the mobile device.

[0005] Specifically, the data collected during the teaching process at the driving test training ground for Subject 2 includes real training data from actual training vehicles at the Subject 2 driving test training ground. The data collected during the teaching process at the driving test training site for Subject 2 included the positional data of the actual training vehicles at the training site.

[0006] Specifically, the data collected during the teaching process at the driving test training ground for Subject 2 includes real training data from actual training vehicles at the Subject 2 driving test training ground. During the teaching process at the driving test training site for Subject 2, the engine parameters of the actual training vehicle at the training site for Subject 2 are collected. The engine parameters include real-time data corresponding to the three hardware components: clutch, brake, and accelerator, which together affect the vehicle's RPM, speed, power, etc.

[0007] Specifically, it also includes: Based on vehicle models, real training data, and virtual 3D site models, the virtual scene images of the rearview mirror are simulated and recorded.

[0008] Specifically, it also includes: Training scores are generated based on simulation results of real training data in a virtual 3D field model and the scoring rules of the Subject 2 exam. The training score is displayed on the mobile device.

[0009] Specifically, it also includes: Analyze real training data with scores below the passing score to determine critical error locations, including the location of the vehicle when making an incorrect turn.

[0010] Specifically, it also includes: Based on the standard training data, vehicle model and virtual three-dimensional site model, obtain the standard steering position and standard virtual scene image of the rearview mirror corresponding to each steering action during the driving test training process. The standard virtual scene image of the rearview mirror is located at the standard steering position, and the virtual scene image that the rearview mirror of the vehicle in the virtual three-dimensional site model should display. The virtual scene of the rearview mirror corresponding to the critical location of the error and the associated standard virtual scene of the rearview mirror are sent to the mobile phone.

[0011] Secondly, the present invention also proposes an automated teaching generation device for driving test subject two, comprising: The building unit is used to construct a virtual three-dimensional site model of the driving test training ground for Subject 2; The data collection unit is used to collect real training data of actual training vehicles at the driving test training site during the teaching process of Subject 2. The simulation unit is used to send the real training data to the mobile terminal to match the virtual three-dimensional site model, so as to conduct synchronous teaching simulation on the mobile terminal.

[0012] Thirdly, an electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program stored in the memory to implement the steps of the automated generation method for driving test subject two instruction as described in any of the first aspects above.

[0013] Fourthly, the present invention also proposes a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the automated generation method for driving test subject two teaching as described in any of the above-mentioned aspects of the first aspect.

[0014] In summary, the automated generation method for driving test subject two teaching proposed in this application constructs a virtual three-dimensional site model of the subject two driving test training ground; collects real training data of actual training vehicles at the subject two driving test training ground during the teaching process; and sends the real training data to a mobile terminal to match the virtual three-dimensional site model for synchronous teaching simulation on the mobile terminal. Instructors can simultaneously monitor and guide the training process of multiple students, no longer limited to real-time teaching of a single student. This significantly improves teaching efficiency, reduces student waiting time, and increases training coverage. Instructors can observe each student's operation in real time through the virtual platform and provide immediate feedback and correction. This real-time guidance helps students quickly correct mistakes and master correct driving skills. Students can reproduce their training process on their mobile phones or other devices, including driving paths and operational details. By replaying training videos, students can more intuitively see their mistakes and improve in the next training session. The system can generate personalized training plans and suggestions based on student performance, helping students improve their driving skills in a targeted manner. Through data analysis, it identifies students' weaknesses and provides specialized training content. Instructors can guide multiple trainees simultaneously, optimizing the utilization of instructor resources. This not only improves the operational efficiency of training institutions but also reduces the workload of instructors. Through virtualized training, some training can be completed in virtual scenarios, reducing the need for actual vehicles. This lowers the frequency of vehicle use and maintenance costs. All training data is recorded and analyzed in detail. Through data analysis, potential safety hazards are identified, and trainees' erroneous driving behaviors are corrected in a timely manner to prevent accidents. The system automatically generates detailed training reports, including scores for each training session, operational details, and error analysis. Trainees can view their progress at any time and understand their learning curve. Intuitive visualizations and feedback are provided to help trainees better understand their training performance. For example, information such as driving trajectories, operation frequency, and error distribution are displayed through charts. By collecting and analyzing a large amount of trainee training data, the system can identify common problems and patterns, helping instructors improve teaching methods and content. Big data analysis can also be used to optimize the design and management of training grounds. Based on machine learning and AI technology, the system can continuously optimize scoring algorithms and feedback mechanisms, making them increasingly accurate and effective. Instructors can also continuously improve their teaching strategies based on the data and suggestions provided by the system.

[0015] The method for automatically generating driving test subject 2 teaching materials of the present invention, other advantages, objectives and features of the present invention will be partly apparent from the following description, and partly understood by those skilled in the art through study and practice of the present invention. Attached Figure Description

[0016] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit this specification. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 This application provides a schematic diagram of a method for automating the generation of driving test subject 2 teaching materials, which is an embodiment of the present application. Figure 2 A schematic diagram of a driver's license test subject 2 teaching automation generation device provided in this application embodiment; Figure 3 This is a schematic diagram of an electronic device for automatically generating teaching materials for driving test subject 2, provided as an embodiment of this application. Detailed Implementation

[0017] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. 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 comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. The technical solutions of the embodiments of this application will now be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0018] To address the challenges of accurately assessing actual driving skills, the high demands on instructor attention, and the low efficiency of driving training, please refer to [the relevant documentation / reference]. Figure 1 This is a schematic diagram of a method for automatically generating teaching materials for driving test subject 2 provided in this application embodiment, which may specifically include steps S110 to S130.

[0019] S110, construct a virtual three-dimensional site model of the driving test training ground for Subject 2.

[0020] For example, a laser scanner or photogrammetry technique can be used to perform a high-precision scan of the driving test training ground for Subject 2, obtaining 3D data of the ground. Professional modeling software (such as Blender or 3ds Max) can then be used to convert the scanned data into a detailed 3D model of the ground, including roads, signs, and obstacles. The 3D model can be optimized to ensure smooth operation on mobile devices and other devices. Interactive elements of the virtual training ground, such as lane lines and parking spaces, can be added to make it more closely resemble a real training environment.

[0021] S120 collects real training data of actual training vehicles at the driving test training site during the teaching process of Subject 2.

[0022] S130, the real training data is sent to the mobile terminal to match the virtual three-dimensional site model, so as to conduct teaching simulation synchronization on the mobile terminal.

[0023] For example, the collected real training data can be transmitted to mobile devices and coaching devices via wireless networks (such as Wi-Fi, 4G / 5G). Data encryption technology can be used to ensure data security during transmission.

[0024] For example, received real training data can be matched with a virtual 3D training field model. Real-time rendering technology can be used to synchronously display the motion state and operation process of the real training vehicle in the virtual 3D training field model. A multi-window interface can be developed on the instructor's device, capable of displaying virtual training scenarios and data for multiple trainees simultaneously. The system automatically generates real-time feedback and prompts based on the trainees' operation data, helping them correct errors promptly. Instructors can send personalized guidance to trainees via voice or text. Data from each training session is stored in a cloud database for easy analysis and review. Data analysis algorithms are used to score trainees' operations and generate detailed training reports. Trainees can view their training records and scores through a mobile application to understand their progress and shortcomings. The system provides a replay function, allowing trainees to review their training process and make improvements based on the instructor's feedback.

[0025] Each window corresponds to a student's training data, which coaches can observe and provide guidance in real time.

[0026] In summary, the automated teaching generation method for driving test subject two provided in this application constructs a virtual three-dimensional training ground model for subject two driving test training; collects real training data of actual training vehicles at the subject two driving test training ground during the teaching process; and sends the real training data to a mobile terminal to match the virtual three-dimensional training ground model for synchronous teaching simulation on the mobile terminal. Instructors can simultaneously monitor and guide the training process of multiple students, no longer limited to real-time teaching of a single student. This significantly improves teaching efficiency, reduces student waiting time, and increases training coverage. Instructors can observe each student's operation in real time through the virtualization platform and provide immediate feedback and correction. This real-time guidance helps students quickly correct mistakes and master correct driving skills. Students can reproduce their training process on mobile terminals or other devices, including driving paths and operational details. By replaying training videos, students can more intuitively see their mistakes and improve in the next training session. The system can generate personalized training plans and suggestions based on student performance, helping students improve their driving skills in a targeted manner. Through data analysis, it identifies students' weaknesses and provides specialized training content. Instructors can guide multiple trainees simultaneously, optimizing the utilization of instructor resources. This not only improves the operational efficiency of training institutions but also reduces the workload of instructors. Through virtualized training, some training can be completed in virtual scenarios, reducing the need for actual vehicles. This lowers the frequency of vehicle use and maintenance costs. All training data is recorded and analyzed in detail. Through data analysis, potential safety hazards are identified, and trainees' erroneous driving behaviors are corrected in a timely manner to prevent accidents. The system automatically generates detailed training reports, including scores for each training session, operational details, and error analysis. Trainees can view their progress at any time and understand their learning curve. Intuitive visualizations and feedback are provided to help trainees better understand their training performance. For example, information such as driving trajectories, operation frequency, and error distribution are displayed through charts. By collecting and analyzing a large amount of trainee training data, the system can identify common problems and patterns, helping instructors improve teaching methods and content. Big data analysis can also be used to optimize the design and management of training grounds. Based on machine learning and AI technology, the system can continuously optimize scoring algorithms and feedback mechanisms, making them increasingly accurate and effective. Instructors can also continuously improve their teaching strategies based on the data and suggestions provided by the system.

[0027] According to some embodiments, the collection of real training data from actual training vehicles at the driving test training site during the teaching process of Subject 2 includes: The data collected during the teaching process at the driving test training site for Subject 2 included the positional data of the actual training vehicles at the training site.

[0028] For advanced training, high-precision GPS or RTK-GPS systems can be used to collect vehicle location information in real time, ensuring accurate positioning for every training movement. Combined with an IMU (Inertial Measurement Unit), data such as vehicle acceleration and angular velocity can be obtained to further improve the accuracy of pose data. Attitude sensors (such as gyroscopes and accelerometers) can be used to acquire vehicle attitude data in real time, including pitch, roll, and yaw angles. This data helps to accurately describe the vehicle's attitude changes within the training area.

[0029] In some examples, it also includes: Based on vehicle models, real training data, and virtual 3D site models, the virtual scene images of the rearview mirror are simulated and recorded.

[0030] In some examples, it also includes: Training scores are generated based on simulation results of real training data in a virtual 3D field model and the scoring rules of the Subject 2 exam. The training score is displayed on the mobile device.

[0031] In some examples, it also includes: Analyze real training data with scores below the passing score to determine critical error locations, including the location of the vehicle when making an incorrect turn.

[0032] Understandably, in order to help students quickly master driving skills, instructors usually teach students the key points of steering wheel rotation at specific positions. Judging these specific positions usually requires using the rearview mirror. However, instructors typically explain the principles of judging from the rearview mirror verbally, which is somewhat abstract and not easy for students to judge, confirm, and master. Therefore, the aforementioned teaching simulation and synchronous method using a mobile device can be used to display the standard image that should be displayed in the rearview mirror at a specific position, combined with the training ground.

[0033] In some examples, it also includes: Based on the standard training data, vehicle model and virtual three-dimensional site model, obtain the standard steering position and standard virtual scene image of the rearview mirror corresponding to each steering action during the driving test training process. The standard virtual scene image of the rearview mirror is located at the standard steering position, and the virtual scene image that the rearview mirror of the vehicle in the virtual three-dimensional site model should display. The virtual scene of the rearview mirror corresponding to the critical location of the error and the associated standard virtual scene of the rearview mirror are sent to the mobile phone.

[0034] For example, based on a vehicle model, real training data, and a virtual 3D course model, the perspective of a rearview mirror is simulated. The rearview mirror image is rendered in a virtual environment, and the scene seen by the learner through the rearview mirror during driving is recorded simultaneously. This provides training in rearview mirror perspective, helping learners become familiar with the use and operation of the rearview mirror. The recorded and replayed rearview mirror images facilitate analysis of the correctness of rearview mirror operations by learners and instructors. Training scores are automatically generated based on the simulation results of real training data in the virtual 3D course model and the scoring rules of the driving test (Part 2). Training scores are displayed on mobile devices, allowing learners to understand their performance. Objective scoring standards are provided to help learners understand their training effectiveness. Real-time score display facilitates timely improvement by learners. Analysis of training data with scores below the passing mark identifies key error locations, such as the vehicle's position during incorrect steering. These key locations are recorded and marked, facilitating targeted training by learners and instructors. This helps learners identify and understand their errors, improving the effectiveness of targeted training. Detailed error analysis is provided to help instructors develop personalized improvement plans. Based on standard training data, vehicle models, and virtual 3D course models, this system acquires the standard steering positions and standard virtual rearview mirror images corresponding to each steering action during driving test training. In the virtual 3D course model, the virtual rearview mirror images corresponding to key error points are compared with the standard virtual rearview mirror images. This provides standard steering positions and rearview mirror perspectives to help trainees understand the correct operating methods. By comparing the trainee's actual operation with the standard operation, the system visually demonstrates the differences and areas for improvement. The virtual rearview mirror images corresponding to key error points and the associated standard virtual rearview mirror images are sent to the trainee's mobile device. Trainees can view these images on their mobile devices and compare and analyze the differences between their operation and the standard operation. This provides intuitive visual feedback to help trainees understand and improve their driving skills, enhancing learning effectiveness and enabling trainees to master correct driving operations more quickly.

[0035] Please see Figure 2 One embodiment of the automated teaching generation device for driving test subject two in this application may include: Construction unit 21 is used to construct a virtual three-dimensional site model of the driving test training ground for subject 2; The data collection unit 22 is used to collect real training data of the actual training vehicles at the driving test training site during the teaching process of the driving test training site for subject two. The simulation unit 23 is used to send the real training data to the mobile terminal to match the virtual three-dimensional site model, so as to conduct teaching simulation synchronization on the mobile terminal.

[0036] In summary, the automated teaching generation device for driving test subject two provided in this application constructs a virtual three-dimensional site model of the subject two driving test training ground; collects real training data of actual training vehicles in the subject two driving test training ground during the teaching process; and sends the real training data to a mobile terminal to match the virtual three-dimensional site model for synchronous teaching simulation on the mobile terminal. Instructors can simultaneously monitor and guide the training process of multiple students, no longer limited to real-time teaching of a single student. This significantly improves teaching efficiency, reduces student waiting time, and increases training coverage. Instructors can observe each student's operation in real time through the virtualization platform and provide immediate feedback and correction. This real-time guidance helps students quickly correct mistakes and master correct driving skills. Students can reproduce their training process on a mobile terminal or other devices, including driving paths and operational details. By replaying training videos, students can more intuitively see their mistakes and improve in the next training session. The system can generate personalized training plans and suggestions based on student performance, helping students improve their driving skills in a targeted manner. Through data analysis, it identifies students' weaknesses and provides specialized training content. Instructors can guide multiple trainees simultaneously, optimizing the utilization of instructor resources. This not only improves the operational efficiency of training institutions but also reduces the workload of instructors. Through virtualized training, some training can be completed in virtual scenarios, reducing the need for actual vehicles. This lowers the frequency of vehicle use and maintenance costs. All training data is recorded and analyzed in detail. Through data analysis, potential safety hazards are identified, and trainees' erroneous driving behaviors are corrected in a timely manner to prevent accidents. The system automatically generates detailed training reports, including scores for each training session, operational details, and error analysis. Trainees can view their progress at any time and understand their learning curve. Intuitive visualizations and feedback are provided to help trainees better understand their training performance. For example, information such as driving trajectories, operation frequency, and error distribution are displayed through charts. By collecting and analyzing a large amount of trainee training data, the system can identify common problems and patterns, helping instructors improve teaching methods and content. Big data analysis can also be used to optimize the design and management of training grounds. Based on machine learning and AI technology, the system can continuously optimize scoring algorithms and feedback mechanisms, making them increasingly accurate and effective. Instructors can also continuously improve their teaching strategies based on the data and suggestions provided by the system.

[0037] like Figure 3 As shown, this application embodiment also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 320 and executable on the processor. When the processor 320 executes the computer program 311, it implements the steps of any of the above-mentioned methods for automating the generation of driving test subject two teaching materials: Construct a virtual three-dimensional training ground model for the driving test (subject 2); Collect real training data of actual training vehicles at the driving test training site during the teaching process of Subject 2; The real training data is sent to the mobile device to match the virtual 3D site model, so as to conduct synchronous teaching simulation on the mobile device.

[0038] Specifically, the data collected during the teaching process at the driving test training ground for Subject 2 includes real training data from actual training vehicles at the Subject 2 driving test training ground. The data collected during the teaching process at the driving test training site for Subject 2 included the positional data of the actual training vehicles at the training site.

[0039] Specifically, the data collected during the teaching process at the driving test training ground for Subject 2 includes real training data from actual training vehicles at the Subject 2 driving test training ground. During the teaching process at the driving test training site for Subject 2, the engine parameters of the actual training vehicle at the training site for Subject 2 are collected. The engine parameters include real-time data corresponding to the three hardware components: clutch, brake, and accelerator, which together affect the vehicle's RPM, speed, power, etc.

[0040] Specifically, it also includes: Based on vehicle models, real training data, and virtual 3D site models, the virtual scene images of the rearview mirror are simulated and recorded.

[0041] Specifically, it also includes: Training scores are generated based on simulation results of real training data in a virtual 3D field model and the scoring rules of the Subject 2 exam. The training score is displayed on the mobile device.

[0042] Specifically, it also includes: Analyze real training data with scores below the passing score to determine critical error locations, including the location of the vehicle when making an incorrect turn.

[0043] Specifically, it also includes: Based on the standard training data, vehicle model and virtual three-dimensional site model, obtain the standard steering position and standard virtual scene image of the rearview mirror corresponding to each steering action during the driving test training process. The standard virtual scene image of the rearview mirror is located at the standard steering position, and the virtual scene image that the rearview mirror of the vehicle in the virtual three-dimensional site model should display. The virtual scene of the rearview mirror corresponding to the critical location of the error and the associated standard virtual scene of the rearview mirror are sent to the mobile phone.

[0044] Since the electronic device described in this embodiment is the device used to implement the automated generation device for driving test subject 2 teaching in the embodiments of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiments of this application is within the scope of protection of this application.

[0045] In practical implementation, when the computer program 311 is executed by the processor, it can achieve the following: Figure 1 Any of the implementation methods in the corresponding embodiments: Construct a virtual three-dimensional training ground model for the driving test (subject 2); Collect real training data of actual training vehicles at the driving test training site during the teaching process of Subject 2; The real training data is sent to the mobile device to match the virtual 3D site model, so as to conduct synchronous teaching simulation on the mobile device.

[0046] Specifically, the data collected during the teaching process at the driving test training ground for Subject 2 includes real training data from actual training vehicles at the Subject 2 driving test training ground. The data collected during the teaching process at the driving test training site for Subject 2 included the positional data of the actual training vehicles at the training site.

[0047] Specifically, the data collected during the teaching process at the driving test training ground for Subject 2 includes real training data from actual training vehicles at the Subject 2 driving test training ground. During the teaching process at the driving test training site for Subject 2, the engine parameters of the actual training vehicle at the training site for Subject 2 are collected. The engine parameters include real-time data corresponding to the three hardware components: clutch, brake, and accelerator, which together affect the vehicle's RPM, speed, power, etc.

[0048] Specifically, it also includes: Based on vehicle models, real training data, and virtual 3D site models, the virtual scene images of the rearview mirror are simulated and recorded.

[0049] Specifically, it also includes: Training scores are generated based on simulation results of real training data in a virtual 3D field model and the scoring rules of the Subject 2 exam. The training score is displayed on the mobile device.

[0050] Specifically, it also includes: Analyze real training data with scores below the passing score to determine critical error locations, including the location of the vehicle when making an incorrect turn.

[0051] Specifically, it also includes: Based on the standard training data, vehicle model and virtual three-dimensional site model, obtain the standard steering position and standard virtual scene image of the rearview mirror corresponding to each steering action during the driving test training process. The standard virtual scene image of the rearview mirror is located at the standard steering position, and the virtual scene image that the rearview mirror of the vehicle in the virtual three-dimensional site model should display. The virtual scene of the rearview mirror corresponding to the critical location of the error and the associated standard virtual scene of the rearview mirror are sent to the mobile phone.

[0052] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0053] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0054] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0055] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1The function specified in one or more boxes.

[0056] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0057] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to perform actions such as... Figure 1 The process of automating the generation of driving test subject 2 teaching materials in the corresponding embodiment.

[0058] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center 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 may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0059] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0060] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units 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, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0061] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0062] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0063] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0064] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for automatically generating driving test subject 2 teaching materials, characterized in that, include: Construct a virtual three-dimensional training ground model for the driving test (subject 2); Collect real training data of actual training vehicles at the driving test training site during the teaching process of Subject 2; The real training data is sent to the mobile device to match the virtual three-dimensional site model, so as to conduct synchronous teaching simulation on the mobile device; Based on vehicle models, real training data, and virtual 3D site models, simulate and record virtual scene images of rearview mirrors; A training score is generated based on the simulation results in the virtual three-dimensional field model and the scoring rules of the Subject 2 test, and the training score is displayed on the mobile device. Analyze real training data with scores below the passing score to determine critical error locations, including the vehicle's location during incorrect steering; Based on standard training data, vehicle models, and virtual 3D track models, the standard steering positions and standard virtual scene images of the rearview mirrors corresponding to each steering action during driving test training are obtained. The standard virtual scene image of the rearview mirror is located at the standard steering position, and the virtual scene image that the rearview mirror of the vehicle in the virtual 3D track model should display. The virtual scene of the rearview mirror corresponding to the critical location of the error and the associated standard virtual scene of the rearview mirror are sent to the mobile phone.

2. The method as described in claim 1, characterized in that, The data collected during the teaching process at the driving test training site for Subject 2 includes real training data from actual training vehicles at the training site for Subject 2 driving test. The data collected during the teaching process at the driving test training site for Subject 2 included the positional data of the actual training vehicles at the training site.

3. The method as described in claim 1, characterized in that, The data collected during the teaching process at the driving test training site for Subject 2 includes real training data from actual training vehicles at the training site for Subject 2, including: During the teaching process at the driving test training site for Subject 2, the engine parameters of the actual training vehicle at the Subject 2 driving test training site are collected. The engine parameters include real-time data corresponding to the three hardware components: clutch, brake, and accelerator.

4. An automated teaching generation device for driving test subject two, characterized in that, The apparatus comprising, using the method as described in any one of claims 1 to 3, includes: The building unit is used to construct a virtual three-dimensional site model of the driving test training ground for Subject 2; The data collection unit is used to collect real training data of actual training vehicles at the driving test training site during the teaching process of Subject 2. The simulation unit is used to send the real training data to the mobile terminal to match the virtual three-dimensional site model, so as to conduct synchronous teaching simulation on the mobile terminal.

5. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program stored in the memory to implement the steps of the automated generation method for driving test subject two teaching as described in any one of claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the automated generation method for driving test subject two teaching as described in any one of claims 1-3.

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