Virtual-real fusion environment driving behavior evaluation method and device and vehicle-mounted edge equipment

Abstract

The embodiment of the invention provides a virtual-real fusion environment driving behavior evaluation method and device and vehicle-mounted edge equipment. The method comprises the steps of collecting driving related data corresponding to a driving behavior of a user based on a driving simulation virtual scene displayed by a display device, the driving related data comprises at least one of the following data: user operation data based on the driving simulator, man-machine interaction data of a user and the driving simulator, driving simulator related data, and user physiological data acquired by the data acquisition equipment during driving; performing data processing on the driving related data according to a set evaluation index to generate analysis data, wherein the analysis data is used for representing the driving performance of the user in the driving simulation virtual scene; and evaluating the driving behavior of the user based on the analysis data.

Description

[Technical field]

[0001] The present invention relates to the field of driving simulation and human-computer interaction technology, and in particular to a method and device for evaluating driving behavior in a virtual-reality fusion environment and an on-vehicle edge device. [Background technology]

[0002] Traditional driving simulators use computer screens and physical control devices. Although traditional driving simulators can simulate driving environments and vehicle dynamics, they lack effective technical means to evaluate user driving behavior. [Summary of the invention]

[0003] In view of this, embodiments of the present invention provide a method, apparatus, and vehicle-mounted edge device for evaluating driving behavior in a virtual-reality fusion environment.

[0004] On the one hand, an embodiment of the present invention provides a method for evaluating driving behavior in a virtual-reality fusion environment, comprising:

[0005] Collecting driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device, the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data collection device during driving;

[0006] Processing the driving-related data according to the set evaluation index to generate analysis data, wherein the analysis data is used to characterize the driving performance of the user in the driving simulation virtual scene;

[0007] The user's driving behavior is evaluated based on the analysis data.

[0008] Optionally, the driving simulation virtual scene includes a set driving scene and / or driving task; and / or,

[0009] After collecting the driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed on the display device, it includes: performing data cleaning, data synchronization and normalization processing on the driving-related data to generate processed driving-related data, and continuing to execute the step of performing data processing on the driving-related data according to the set evaluation indicators to generate analysis data.

[0010] Optionally, the evaluating the user's driving behavior based on the analysis data includes:

[0011] Evaluating the user's driving behavior based on analysis data generated from driving-related data corresponding to the user's driving behavior of a set driving task displayed on a display device; or,

[0012] Evaluate the user's driving behavior based on the analysis data generated from the driving-related data corresponding to the user's driving behavior based on the driving scene displayed by the display device and the acquired user's subjective data; or

[0013] The user's driving behavior is evaluated based on the analysis data generated from the driving-related data corresponding to the user's driving behavior of the set driving task displayed on the display device and the acquired user's subjective data.

[0014] Optionally, the step of evaluating the user's driving behavior based on the analysis data generated from the driving-related data corresponding to the user's driving behavior based on the set driving task displayed on the display device includes:

[0015] When the driving related data includes a steering wheel angle, the analysis data includes a mean square error of a steering wheel angle deviation; and / or, when the driving related data includes a pedal force, the analysis data includes a mean value and a standard deviation of the pedal force; and / or, when the driving related data includes a vehicle speed, the analysis data includes a speed deviation and a fluctuation range of the vehicle speed; and / or, when the driving related data includes a driving trajectory, the analysis data includes a lane deviation distance and a frequency of the driving trajectory; and / or, when the driving related data includes a user's heart rate, the analysis data includes a heart rate variability of the user's heart rate;

[0016] According to the set analysis threshold corresponding to each analysis data corresponding to the stored driving task, the mean square error of the steering wheel angle deviation, the mean value and standard deviation of the pedal force, the speed deviation and fluctuation range of the vehicle speed, the lane deviation distance and frequency of the driving trajectory and / or the heart rate variability of the user's heart rate are compared to evaluate the user's driving behavior.

[0017] Optionally, the user subjective data is generated based on the user's experience rating of the driving simulator, the user's age and the user's driving experience.

[0018] Optionally, when the data acquisition device is a head and eye tracking device, the user physiological data includes user gaze tracking data; and / or,

[0019] When the data acquisition device is a heart rate monitoring device, the user physiological data includes user heart rate data; and / or,

[0020] When the data acquisition device is a skin electrode measurement device, the user physiological data includes the user's skin electrode activity data.

[0021] On the other hand, an embodiment of the present invention provides a driving behavior evaluation device in a virtual-reality fusion environment, comprising:

[0022] A collection module, used to collect driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device, wherein the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data collection device during driving;

[0023] A data processing module, used for processing the driving-related data according to the set evaluation index to generate analysis data, wherein the analysis data is used to characterize the driving performance of the user in the driving simulation virtual scene;

[0024] The evaluation module is used to evaluate the user's driving behavior based on the analysis data.

[0025] On the other hand, an embodiment of the present invention provides a driving simulator, including a simulated cockpit, a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the steps of the above-mentioned virtual-reality fusion environment driving behavior evaluation method are implemented.

[0026] On the other hand, an embodiment of the present invention provides a vehicle-mounted edge device, including a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the steps of the above-mentioned virtual-reality fusion environment driving behavior evaluation method are implemented.

[0027] On the other hand, an embodiment of the present invention provides a storage medium, which includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the above-mentioned virtual-reality fusion environment driving behavior evaluation method.

[0028] In the technical solution of the method for evaluating driving behavior in a virtual-reality fusion environment provided by the embodiment of the present invention, driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device is collected, and the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data acquisition device during driving; the driving-related data is processed according to the set evaluation indicators to generate analysis data, and the analysis data is used to characterize the user's driving performance in the driving simulation virtual scene; the user's driving behavior is evaluated based on the analysis data. In the technical solution provided by the embodiment of the present invention, based on the user operation data of the driving simulator, the human-computer interaction data between the user and the driving simulator, the driving simulator-related data, and the user physiological data collected by the data acquisition device during driving, the user's driving behavior is evaluated in real time, thereby improving the accuracy, comprehensiveness and consistency of the driving behavior evaluation.

Brief Description of the Drawings

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 A flowchart of a method for evaluating driving behavior in a virtual-reality fusion environment provided by an embodiment of the present invention;

[0031] Figure 2 A schematic diagram of the structure of a driving behavior evaluation device in a virtual-reality fusion environment provided by an embodiment of the present invention;

[0032] Figure 3 A schematic diagram of a driving simulator provided by an embodiment of the present invention;

[0033] Figure 4 A schematic diagram of a vehicle-mounted edge device provided in an embodiment of the present invention. [Specific implementation method]

[0034] In order to better understand the technical solution of the present invention, the embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0035] It should be clear that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0037] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0038] A driving simulator is a system that uses computer technology and simulation technology to simulate vehicle driving. It is widely used in driving training, vehicle development, traffic safety research and other fields. Traditional driving simulators usually include a physical cockpit, steering wheel, pedals, display screen and simulation software. In recent years, with the development of virtual reality (VR) and augmented reality (AR) technology, mixed reality (MR) technology has gradually been applied to driving simulators to provide a more realistic and immersive driving experience.

[0039] MR technology combines the advantages of VR and AR technologies, seamlessly integrating virtual objects with the real world. The application of MR technology in driving simulators can not only enhance the immersion of the driving experience, but also improve the effectiveness of driving training and testing through interaction with the real environment. For example, drivers can experience different driving scenarios in the MR environment, such as urban roads, highways, bad weather, etc., to improve their ability to cope with complex traffic environments.

[0040] MR technology is a technology that merges the real world with the virtual world, allowing physical and digital objects to interact in the same space. MR technology does not just overlay virtual elements on the real world, but enables interaction and integration between the two.

[0041] Human-Computer Interaction (HCI) refers to the process of information exchange between people and computers using a certain dialogue language and a certain interactive method to complete a certain task. In the field of HCI, driving simulators require highly accurate user input and feedback systems to ensure that drivers can get a realistic driving experience. Human-computer interaction in traditional driving simulators mainly relies on physical input devices (such as steering wheels, pedals, etc.) and visual and auditory feedback. With the application of MR technology, the dimension and complexity of human-computer interaction have further increased, and new evaluation schemes are needed to evaluate and optimize the performance and user experience of such interactive systems.

[0042] VR or AR technology has begun to be used in some driving simulators, improving the visual and interactive experience. However, VR technology may cause the driver to be disconnected from the real physical environment because of the complete immersion in the virtual environment. Although AR technology can overlay virtual information on the real environment, its interactive ability and immersion still need to be improved.

[0043] There have been some studies and applications in related technologies that have attempted to introduce MR technology into driving simulators, aiming to improve the simulation effect by integrating virtuality and reality. However, driving simulators in related technologies are still imperfect in terms of specific driving evaluation methods and lack systematic evaluation standards and methods.

[0044] In order to solve the technical problems in the related art, the embodiment of the present invention provides a method for evaluating driving behavior in a virtual-reality fusion environment. Figure 1 A flowchart of a method for evaluating driving behavior in a virtual-reality fusion environment provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method includes:

[0045] Step 102: Collect driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device, where the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by a data acquisition device during driving.

[0046] In an embodiment of the present invention, each step can be executed by a vehicle-mounted edge device, which is an intelligent vehicle-mounted device with edge computing capabilities.

[0047] In an embodiment of the present invention, each step can also be executed by a driving simulator. The user wears a data acquisition device and sits in the driving simulator to drive according to the driving simulation virtual scene displayed by the display device, so as to collect driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device.

[0048] The driving simulator may include a simulated cockpit (also referred to as a cockpit system). Optionally, according to the needs of simulated driving, the driving simulator may also be configured with at least one of the following: a motion platform, a display device, and a sensory feedback system.

[0049] The simulated cockpit uses an ergonomically designed seat and is equipped with simulated equipment such as a steering wheel, pedals (accelerator, brake, clutch) and a gear lever. The seat and controls of the simulated cockpit are adjustable to suit the height and body shape of different users.

[0050] The motion platform can be a six-degree-of-freedom motion platform that can simulate the dynamic behavior of a vehicle on different road surfaces and driving conditions, and provide users with real physical feedback.

[0051] The display device can be a high-resolution head-mounted display (such as Microsoft HoloLens) or a multi-screen display system to provide an immersive visual experience.

[0052] The sensory feedback system is equipped with a surround sound system that can simulate sound effects in different environments (such as engine sound, wind noise, road noise) to simulate the environmental sound effects corresponding to the stored driving scenes and / or driving tasks. The tactile feedback devices of the sensory feedback system are installed on the steering wheel, seats and pedals to simulate the real-time vibration feedback corresponding to the stored driving scenes and / or driving tasks.

[0053] In an embodiment of the present invention, the data acquisition device worn by the user may include a head and eye tracking device, a heart rate monitoring device and / or a skin conductance measuring device. Among them, the head and eye tracking device is used to capture the user's line of sight and attention distribution. For example, the head and eye tracking device includes a head-mounted display (Helmet Mounted Display, referred to as HMD), the heart rate monitoring device may include a wearable device or an electrocardiogram monitor, etc., and the skin conductance measuring device may include a variety of skin conductance measuring devices such as an electrodermal activity meter or a wearable biosensor.

[0054] In an embodiment of the present invention, the user starts the driving simulator, which automatically loads the above hardware and software configurations. The user can enter personal information (such as height, weight, and driving experience) for personalized calibration. The seat position, steering wheel angle, and pedal position are adjusted to ensure that the user is in a comfortable driving posture. When the user wears the HMD, the viewing angle can be adjusted according to the user's head movement, and eye tracking calibration can be performed to ensure that the system can accurately track the user's gaze point.

[0055] In the embodiment of the present invention, the driving simulation virtual scene includes a set driving scene and / or driving task. The driving scene is a virtual driving environment including roads, weather, cars, pedestrians and other traffic participants, and the driving task is a task that the user needs to perform in the driving scene, for example, the driving task can be a 100-meter straight driving task, a 50-meter curve driving task, an emergency braking task 2 meters away from an obstacle, etc.

[0056] In an embodiment of the present invention, a user can select a driving task to be performed on a system interface of a driving simulator. At this time, the task objectives, operation requirements and precautions of the driving task can be displayed on the system interface. The user starts driving according to the task objectives, operation requirements and precautions of the selected driving task, and the driving simulator can collect driving-related data corresponding to the driving behavior under the driving task in real time.

[0057] In the embodiment of the present invention, different driving scenarios and / or driving tasks can be used to evaluate the user interaction performance in different situations. The following steps can analyze the accuracy, reaction speed and operation stability of the user operation based on different driving scenarios and / or driving tasks.

[0058] In the embodiment of the present invention, the driving simulator is equipped with a simulation engine that can generate and manage a virtual driving environment, including multiple elements such as roads, traffic, and weather. The driving simulator integrates a high-precision physics engine that can simulate the dynamic characteristics and driving behavior of the vehicle. The driving simulator uses MR technology to seamlessly integrate virtual objects with the real environment, providing a realistic mixed reality driving experience, and can handle the display, position tracking, and interactive response of virtual objects.

[0059] In an embodiment of the present invention, user operation data may include steering wheel angle, pedal force and / or gear lever position. When the data acquisition device is a head and eye tracking device, the user physiological data includes user line of sight tracking data; and / or, when the data acquisition device is a heart rate monitoring device, the user physiological data includes user heart rate data; and / or, when the data acquisition device is a skin electrode measurement device, the user physiological data includes user skin electrode activity data. User skin electrode activity data is skin electrode activity (Electrodermal Activity, EDA) or skin electrode response (Skin Conductance Response, SCR) data, which is usually collected and recorded using special physiological measurement equipment. In an embodiment of the present invention, driving-related data may also include user behavior data, such as driving habits, reaction time, etc.

[0060] Step 104: Perform data cleaning, data synchronization, and normalization processing on the driving related data to generate processed driving related data.

[0061] In the embodiment of the present invention, driving related data can be stored in a database in real time for subsequent analysis.

[0062] In the embodiment of the present invention, data fusion technology can be used to integrate driving-related data from multiple sources and then perform data processing.

[0063] Specifically, based on the application of statistical analysis and machine learning technology, driving-related data is processed to generate analytical data to identify users' interaction patterns and behavioral characteristics. Through real-time data processing, users' driving performance can be dynamically evaluated and instant feedback can be provided.

[0064] In the embodiment of the present invention, the driving-related data is cleaned to remove noise and outliers to ensure the accuracy and consistency of the driving-related data. The driving-related data is synchronized to align the driving-related data from multiple sources to a unified time axis. The driving-related data is normalized to process data of different dimensions to facilitate subsequent analysis and processing.

[0065] Step 106: Process the processed driving-related data according to the set evaluation index to generate analysis data, where the analysis data is used to characterize the user's driving performance in the driving simulation virtual scene.

[0066] In an embodiment of the present invention, the evaluation indicators may include measuring the user's operating accuracy of the steering wheel, pedals and gear lever to evaluate their ability to control the vehicle; recording the user's reaction time in different driving tasks to analyze their response speed to emergencies; using eye tracking data to analyze the user's attention distribution during driving and evaluate their ability to perceive environmental information; monitoring the user's physiological data to evaluate their tension and fatigue in different driving scenarios; collecting the user's subjective evaluation, and comprehensively considering the user's visual, auditory, tactile and other aspects of experience.

[0067] Among them, the steering wheel angle deviation can record the deviation between the user's steering wheel angle and the ideal angle, and evaluate the user's direction control ability. The pedal force change can record the force change of the accelerator and brake pedals, and evaluate the user's acceleration and deceleration control ability. The reaction time of event triggering can measure the time interval from the user's perception of the event (such as the appearance of an obstacle) to the start of the operation (such as braking). The operation response time can evaluate the time from the start of the operation to the expected effect (such as complete stop). The lane departure distance can record the deviation distance of the user's vehicle from the center line of the lane and evaluate the lane keeping ability. Among them, the deviation distance of the vehicle from the center line of the lane can be recorded, and the average deviation distance and the maximum deviation distance can be calculated. The lane departure frequency can be used by cluster analysis or other statistical methods to count the frequency of the user's vehicle deviating from the lane and evaluate the lane keeping stability. The target speed deviation can record the difference between the actual driving speed and the target speed, calculate the average speed deviation, evaluate the speed keeping ability, and use the speed deviation distribution chart to show the user's speed keeping ability. The speed fluctuation range can evaluate the smoothness of the user's speed control and count the range and frequency of speed fluctuations. Heart Rate Variability (HRV) can analyze the changes in the user's heart rate during different tasks and assess stress levels and tension. Galvanic skin response (GSR) can record the galvanic skin response and assess the user's physiological stress response during operation.

[0068] In the embodiment of the present invention, a reaction time distribution graph and a box-and-whisker graph may be used to represent the user's reaction time to an event trigger, so as to demonstrate the user's reaction speed.

[0069] Step 108: Evaluate the user's driving behavior based on the analysis data.

[0070] In an embodiment of the present invention, the user's driving behavior can be evaluated based on the analysis data generated by the driving-related data corresponding to the driving behavior of the set driving task displayed by the user on the display device; or, the user's driving behavior can be evaluated based on the analysis data generated by the driving-related data corresponding to the driving behavior of the driving scene displayed by the user on the display device and the obtained user subjective data; or, the user's driving behavior can be evaluated based on the analysis data generated by the driving-related data corresponding to the driving behavior of the set driving task displayed by the user on the display device and the obtained user subjective data. Among them, the subjective feelings of the driving experience can be collected through the user's self-report and questionnaire survey. The user's subjective data is generated based on the user's experience score of the driving simulator, the user's age and the user's driving experience. This part of the evaluation helps understand the user's subjective experience and acceptance of the simulator. For example, the user's driving behavior can be evaluated based on the user's subjective feelings through the Driving Experience Questionnaire (DEQ). After completing each driving task, the user fills in questions about task difficulty, operating comfort, attention requirements, etc. The System Usability Scale (SUS) can also be used to evaluate the overall usability of the simulator for users, including interface friendliness, ease of operation, etc. Semi-structured interviews with users can also be used to gain an in-depth understanding of users' experience in different driving tasks, the problems they encounter, and their suggestions for improving the system. Statistical analysis of questionnaire data, calculation of average scores and standard deviations, and content analysis of interview data can be performed to extract common problems and user suggestions. User experience (including task difficulty, operational comfort, visual and auditory effects, etc.) can be scored, and system usability (including interface friendliness, ease of operation, timeliness of feedback, etc.) can be scored.

[0071] In one implementation of the embodiment of the present invention, when the user's subjective data includes the score of task difficulty, the score of operation comfort and the score of interface friendliness filled in by the user after completing each driving task, the user's subjective data can be calculated according to the user's age and the user's driving experience. For example, after completing each driving task, participant A fills in a score of 4 for task difficulty, a score of 3 for operation comfort, a score of 5 for interface friendliness, a user age of 30, and a user's driving experience of 10. After completing each driving task, participant B fills in a score of 2 for task difficulty, a score of 2 for operation comfort, a score of 3 for interface friendliness, a user age of 45, and a user's driving experience of 20. After completing each driving task, participant C fills in a score of 5 for task difficulty, a score of 4 for operation comfort, a score of 4 for interface friendliness, a user age of 25, and a user's driving experience of 5. The weight coefficient of the user's driving experience can be set to c1=0.6, and the weight coefficient of the user's age is c2=0.4.

[0072] The weighted score of participant A is calculated as follows: weighted score = (4*(0.6*30+0.4*10)+3*(0.6*30+0.4*10)+5*(0.6*30+0.4*10)) / (0.6*30+0.4*10)=4.

[0073] The weighted score of participant B is calculated as follows: weighted score = (2*(0.6*45+0.4*20)+2*(0.6*45+0.4*20)+3*(0.6*45+0.4*20)) / (0.6*45+0.4*20) = 2.33.

[0074] The weighted score of participant C is calculated as follows: weighted score = (5*(0.6*25+0.4*5)+4*(0.6*25+0.4*5)+4*(0.6*25+0.4*5)) / (0.6*25+0.4*5) = 4.33.

[0075] The overall weighted average score of participants A, B, and C = (4*22+2.33*34+4.33*17) / (22+34+17)≈3.3

[0076] The weighted standard deviations were calculated as follows: Participant A: (4-3.3)^2=0.49, Participant B: (2.33-3.3)^2=0.9409, Participant C: (4.33-3.3)^2=1.081.

[0077] Weighted square error average = (0.49*22+0.9409*34+1.081*17) / (22+34+17)≈0.841, weighted standard deviation = √0.841≈0.917, user subjective data can be weighted standard deviation. Weighted standard deviation is a statistical indicator used to measure the volatility or variability of a set of data. The weighted standard deviation takes into account the weights of different data during the calculation process. This difference allows the weighted standard deviation to more accurately reflect the degree of dispersion of the data, especially when dealing with uneven distribution of sample data and the overall distribution. A larger weighted standard deviation indicates a greater degree of dispersion of the data, and vice versa.

[0078] In an embodiment of the present invention, the user's driving performance can also be quantified through objective analysis data. This part can ensure an objective and accurate assessment of the user's skills. The analysis data may include analysis data generated based on driving-related data corresponding to the user's driving behavior based on a set driving task displayed by a display device; or analysis data generated based on driving-related data corresponding to the user's driving behavior based on a driving scene displayed by a display device.

[0079] For example, when the driving-related data includes a steering wheel angle, the analysis data includes a mean square error of the steering wheel angle deviation; and / or, when the driving-related data includes pedal force, the analysis data includes a mean value and standard deviation of the pedal force; and / or, when the driving-related data includes vehicle speed, the analysis data includes a speed deviation and a fluctuation range of the vehicle speed; and / or, when the driving-related data includes a driving trajectory, the analysis data includes a lane deviation distance and frequency of the driving trajectory; and / or, when the driving-related data includes a user's heart rate, the analysis data includes the heart rate variability of the user's heart rate. The mean square error of the steering wheel angle deviation, the mean value and standard deviation of the pedal force, the speed deviation and fluctuation range of the vehicle speed, the lane deviation distance and frequency of the driving trajectory, and / or the heart rate variability of the user's heart rate can be compared according to a set analysis threshold corresponding to each analysis data corresponding to the stored driving scene and / or driving task, so as to evaluate the user's driving behavior.

[0080] In the embodiment of the present invention, the user's operating accuracy, reaction speed, attention allocation, etc. in different driving scenarios and / or driving tasks can be evaluated according to preset evaluation indicators.

[0081] In an embodiment of the present invention, a clear driving task can be set to comprehensively evaluate the user's operating ability and reaction ability in different driving situations. This part of the evaluation covers a variety of driving scenarios and simulates the complex situations in a real driving environment. For example, the driving task and the task objectives corresponding to the driving task may include:

[0082] Straight-line driving task: The user needs to keep the vehicle moving in a straight line on a straight road, with the speed stable within a specified range.

[0083] Curve driving task: The user needs to control the direction and speed through a series of curves to keep the vehicle in the lane.

[0084] Emergency braking task: The system randomly triggers obstacles, and the user needs to quickly judge and brake to avoid collision. The emergency braking task can be evaluated based on the time it takes for users of different ages to brake. For example, the braking time for users under 30 years old does not exceed 0.6s, and the braking time for users aged 30-60 does not exceed 0.8s.

[0085] Lane changing and overtaking tasks: Users perform lane changing and overtaking operations on multi-lane roads to ensure safety and complete the task as quickly as possible.

[0086] Night driving task: Users drive in low light conditions, facing different light conditions and visual obstacles to ensure safe driving. The night driving task is mainly evaluated based on the user's gaze tracking data collected by the head and eye tracking devices worn by the user.

[0087] Highway driving task: The user drives on the highway, maintains the prescribed speed, and adjusts the speed according to traffic signs.

[0088] Parking tasks: Users complete parking maneuvers in different parking scenarios, such as parallel parking, perpendicular parking, and diagonal parking.

[0089] In the embodiment of the present invention, the user completes each driving task one by one according to the above task objectives. The driving simulator can record the user's operation data and user physiological data in real time. The driving simulator can record the time required for the user to complete each task, calculate the user's operation deviation and standard deviation in the task, record the user's reaction time to emergencies, analyze the user's gaze point and gaze time in the task, and conduct evaluation according to the user's operation data threshold and user physiological data threshold set for different occupations and ages.

[0090] In the embodiment of the present invention, the driving simulator can also be set with driving scenes such as fire and car accident scenes to evaluate the user's obstacle avoidance ability.

[0091] Through the above-mentioned driving behavior evaluation method in a virtual-reality fusion environment, the driving simulator can comprehensively and accurately evaluate the user's driving skills and interactive performance. It can not only help users improve their driving skills, but also provide valuable data and experience for driving training and the development of autonomous driving technology.

[0092] In the embodiment of the present invention, after step 108, the following may also be included: generating a voice reminder notification based on the analysis data, and playing the voice reminder notification; and / or generating a visual reminder notification based on the analysis data, and displaying the visual reminder notification through a display device. For example, the voice reminder notification can be used to remind the user that the steering wheel is improperly operated or the speed is too fast.

[0093] In an embodiment of the present invention, during the driving process, the driving simulator can provide instant voice and / or visual feedback based on real-time data analysis results to help users adjust operations in a timely manner. After the driving task is completed, the driving simulator can generate a detailed evaluation report, including analysis results and improvement suggestions for various indicators (operation accuracy, reaction time, attention distribution, physiological feedback, etc.), and the evaluation report may include charts and statistical data to intuitively display the user's driving performance. Based on the user's evaluation data and subjective feedback, a personalized driving training plan and optimization suggestions can be provided, such as focusing on practicing weak links and adjusting system parameters (such as feedback intensity) to help users gradually improve their driving skills.

[0094] In the embodiment of the present invention, a visualization tool can be used to display the evaluation results to help users understand their driving performance and room for improvement.

[0095] In the technical solution provided by the embodiment of the present invention, driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device is collected, and the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data acquisition device during driving; the driving-related data is processed according to the set evaluation indicators to generate analysis data, and the analysis data is used to characterize the user's driving performance in the driving simulation virtual scene; the user's driving behavior is evaluated based on the analysis data. In the technical solution provided by the embodiment of the present invention, the user's driving behavior is evaluated in real time based on the user operation data of the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data acquisition device during driving, thereby improving the accuracy, comprehensiveness and consistency of the driving behavior evaluation.

[0096] The technical solution provided by the embodiment of the present invention provides users with a comprehensive driving behavior evaluation solution in a virtual-real fusion environment through advanced hardware design, multi-sensory interaction, real-time data collection and analysis, standardized evaluation indicators, and a complete user feedback mechanism. This solution is of great significance in improving the effectiveness of driving training, accelerating the development of autonomous driving technology, and promoting the progress of human-computer interaction research, and provides reference and support for industry technical standardization.

[0097] Traditional driving simulators and existing MR systems often focus on the interactive evaluation of a single or a few senses, such as vision or hearing. The virtual-reality fusion environment driving behavior evaluation method proposed in the embodiment of the present invention covers multiple sensory feedbacks such as vision, hearing, and touch. This multi-dimensional virtual-reality fusion environment driving behavior evaluation method can more comprehensively evaluate the user's interactive experience in the MR environment, thereby more accurately identifying and optimizing each interactive link of the system.

[0098] The technical solution provided by the embodiment of the present invention includes a real-time feedback mechanism, which can dynamically collect and analyze various driving-related data during the user's simulated driving. This real-time virtual-real fusion environment driving behavior evaluation method is different from the traditional post-analysis, and can find problems more promptly and immediately adjust and optimize the interactive system of the driving simulator when necessary.

[0099] The technical solution provided by the embodiment of the present invention can perform personalized interaction optimization according to the behaviors and reactions of different users. For example, by analyzing the user's driving habits, reaction time, operation accuracy and other data, the system can automatically adjust the interactive feedback mechanism to provide the most suitable experience for the user. This personalized adaptability not only improves user satisfaction, but also enhances the training and testing effects of the simulator.

[0100] The technical solution provided in the embodiment of the present invention proposes a set of standardized evaluation frameworks, including specific evaluation indicators, driving behavior evaluation methods and processes in a virtual-reality fusion environment, which will help establish industry standards and improve the technical level of the entire MR driving simulator field.

[0101] Traditional driving simulators may be based on computer screens and physical controls without using mixed reality technology. Although this approach may not provide the same immersion and realism as MR mixed reality, it can still be used to train and evaluate driving skills.

[0102] Virtual reality (VR) driving simulators are another alternative that use VR headsets and controllers to provide an immersive driving experience. Compared to MR, VR simulators may lack the perception of the real environment, but can still effectively simulate driving scenarios and operations.

[0103] Some driving simulators may be implemented entirely in software without the need for specialized hardware. This approach may be suitable for some simple driving training and evaluation tasks, but may not provide the same experience as interacting with physical hardware.

[0104] In addition to MR technology, there are other forms of mixed reality technology, such as AR technology or Deep Learning Augmented Reality (DLAR) technology. These technologies can also be used in driving simulators to provide similar immersive experiences and interactive functions. Although the above alternatives exist, they may not reach the level of MR mixed reality driving simulators in some aspects, such as realism, interactive performance or user experience. Therefore, despite the existence of alternatives, MR mixed reality technology is still a valuable innovation direction with significant advantages and potential market demand.

[0105] In the technical solution provided by the embodiment of the present invention, multiple sensory feedback such as vision, hearing, and touch can be integrated to achieve a more realistic and immersive driving experience. Develop a driving simulator system that monitors and records the driver's operations in real time, evaluates interactive performance and provides instant feedback. Use MR technology to seamlessly integrate virtual objects with the real environment to enhance the realism and interactivity of the driving simulator. Propose a set of standardized evaluation frameworks, including evaluation indicators, driving scenarios, data collection and analysis methods, etc., to ensure the comprehensiveness and consistency of the evaluation process. Design a user experience optimization feedback mechanism, comprehensively consider the user's subjective evaluation and objective evaluation data, and continuously optimize the user experience and interactive effects of the driving simulator.

[0106] An embodiment of the present invention provides a driving behavior evaluation device in a virtual-reality fusion environment. Figure 2 A schematic diagram of a driving behavior evaluation device for a virtual-reality fusion environment provided by an embodiment of the present invention is applied to a driving simulator, which includes a cockpit system and a data acquisition device, such as Figure 2 As shown, the device includes: a collection module 11, a data processing module 12 and an evaluation module 13.

[0107] The acquisition module 11 is used to collect driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device. The driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data acquisition device during driving.

[0108] The data processing module 12 is used to process the driving-related data according to the set evaluation index to generate analysis data, and the analysis data is used to characterize the user's driving performance in the driving simulation virtual scene.

[0109] The evaluation module 13 is used to evaluate the user's driving behavior based on the analysis data.

[0110] In an embodiment of the present invention, the driving simulation virtual scene includes a set driving scene and / or driving task; and / or, the data processing module 12 is specifically used to perform data cleaning, data synchronization and normalization processing on the driving-related data to generate processed driving-related data; the processed driving-related data is processed according to the set evaluation indicators to generate analysis data, and the analysis data is used to characterize the user's driving performance in different driving scenes and / or driving tasks.

[0111] In an embodiment of the present invention, the evaluation module 13 is specifically used to evaluate the user's driving behavior based on analysis data generated from driving-related data corresponding to the user's driving behavior based on a set driving task displayed on a display device; or, to evaluate the user's driving behavior based on analysis data generated from driving-related data corresponding to the user's driving behavior based on a driving scene displayed on a display device and obtained user subjective data; or, to evaluate the user's driving behavior based on analysis data generated from driving-related data corresponding to the user's driving behavior based on a set driving task displayed on a display device and obtained user subjective data.

[0112] In an embodiment of the present invention, the evaluation module 13 is specifically used for analyzing data including the mean square error of the steering wheel angle deviation when the driving-related data includes the steering wheel angle; and / or, when the driving-related data includes the pedal force, the analysis data includes the mean value and standard deviation of the pedal force; and / or, when the driving-related data includes the vehicle speed, the analysis data includes the speed deviation and fluctuation range of the vehicle speed; and / or, when the driving-related data includes the driving trajectory, the analysis data includes the lane deviation distance and frequency of the driving trajectory; and / or, when the driving-related data includes the user's heart rate, the analysis data includes the heart rate variability of the user's heart rate; and comparing the mean square error of the steering wheel angle deviation, the mean value and standard deviation of the pedal force, the speed deviation and fluctuation range of the vehicle speed, the lane deviation distance and frequency of the driving trajectory, and / or the heart rate variability of the user's heart rate according to the set analysis threshold corresponding to each analysis data corresponding to the stored driving scene and / or driving task, so as to evaluate the user's driving behavior.

[0113] In the embodiment of the present invention, the user subjective data is generated based on the user's experience rating of the driving simulator, the user's age and the user's driving experience.

[0114] In an embodiment of the present invention, when the data acquisition device is a head and eye tracking device, the user physiological data includes user gaze tracking data; and / or, when the data acquisition device is a heart rate monitoring device, the user physiological data includes user heart rate data; and / or, when the data acquisition device is an electrical skin measurement device, the user physiological data includes user electrical skin activity data.

[0115] In the technical solution provided by the embodiment of the present invention, driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device is collected, and the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data acquisition device during driving; the driving-related data is processed according to the set evaluation indicators to generate analysis data, and the analysis data is used to characterize the user's driving performance in the driving simulation virtual scene; the user's driving behavior is evaluated based on the analysis data. In the technical solution provided by the embodiment of the present invention, the user's driving behavior is evaluated in real time based on the user operation data of the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data acquisition device during driving, thereby improving the accuracy, comprehensiveness and consistency of the driving behavior evaluation.

[0116] The driving behavior evaluation device in the virtual-reality fusion environment provided in this embodiment can be used to achieve the above Figure 1 For the detailed description of the driving behavior evaluation method in the virtual-reality fusion environment, please refer to the embodiment of the driving behavior evaluation method in the virtual-reality fusion environment, which will not be repeated here.

[0117] An embodiment of the present invention provides a storage medium, which includes a stored program. When the program is running, the device where the storage medium is located is controlled to execute the steps of the embodiment of the above-mentioned virtual-reality fusion environment driving behavior evaluation method. For a specific description, please refer to the embodiment of the above-mentioned virtual-reality fusion environment driving behavior evaluation method.

[0118] An embodiment of the present invention provides a driving simulator, including a simulated cockpit, a memory and a processor, the memory being used to store information including program instructions, the processor being used to control the execution of the program instructions, and the program instructions, when loaded and executed by the processor, implementing the steps of the embodiment of the above-mentioned method for evaluating driving behavior in a virtual-reality fusion environment. For a specific description, please refer to the embodiment of the above-mentioned method for evaluating driving behavior in a virtual-reality fusion environment.

[0119] Figure 3 Schematic diagram of a driving simulator provided by an embodiment of the present invention. Figure 3 As shown, the driving simulator 20 of this embodiment includes: a processor 21, a memory 22, and a computer program 23 stored in the memory 22 and executable on the processor 21. When the computer program 23 is executed by the processor 21, the driving behavior evaluation method applied to the virtual-reality fusion environment in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program is executed by the processor 21, the functions of each model / unit in the driving behavior evaluation device applied to the virtual-reality fusion environment in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0120] The driving simulator 20 includes, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will appreciate that Figure 3 It is only an example of the driving simulator 20 and does not constitute a limitation of the driving simulator 20. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the driving simulator may also include input and output devices, network access devices, buses, etc.

[0121] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0122] The memory 22 may be an internal storage unit of the driving simulator 20, such as a hard disk or memory of the driving simulator 20. The memory 22 may also be an external storage device of the driving simulator 20, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the driving simulator 20. Further, the memory 22 may also include both an internal storage unit of the driving simulator 20 and an external storage device. The memory 22 is used to store computer programs and other programs and data required by the driving simulator. The memory 22 may also be used to temporarily store data that has been output or is to be output.

[0123] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0124] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0126] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0127] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (Processor) to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0128] An embodiment of the present invention provides a vehicle-mounted edge device, including a memory and a processor, the memory is used to store information including program instructions, the processor is used to control the execution of the program instructions, and when the program instructions are loaded and executed by the processor, the steps of the embodiment of the above-mentioned virtual-reality fusion environment driving behavior evaluation method are implemented. For a specific description, please refer to the embodiment of the above-mentioned virtual-reality fusion environment driving behavior evaluation method.

[0129] Figure 4 A schematic diagram of a vehicle-mounted edge device provided by an embodiment of the present invention. Figure 4As shown, the vehicle-mounted edge device 30 of this embodiment includes: a processor 31, a memory 32, and a computer program 33 stored in the memory 32 and executable on the processor 31. When the computer program 33 is executed by the processor 31, the method for evaluating driving behavior in a virtual-reality fusion environment in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program is executed by the processor 31, the functions of each model / unit in the device for evaluating driving behavior in a virtual-reality fusion environment in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0130] The vehicle-mounted edge device 30 includes, but is not limited to, a processor 31 and a memory 32. Those skilled in the art will appreciate that Figure 4 It is only an example of the vehicle-mounted edge device 30 and does not constitute a limitation of the vehicle-mounted edge device 30. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, a driving simulator may also include input and output devices, network access devices, buses, etc.

[0131] The processor 31 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0132] The memory 32 may be an internal storage unit of the vehicle edge device 30, such as a hard disk or memory of the vehicle edge device 30. The memory 32 may also be an external storage device of the vehicle edge device 30, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the vehicle edge device 30. Furthermore, the memory 32 may also include both an internal storage unit of the vehicle edge device 30 and an external storage device. The memory 32 is used to store computer programs and other programs and data required for the driving simulator. The memory 32 may also be used to temporarily store data that has been output or is to be output.

[0133] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0134] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0135] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0136] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0137] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (Processor) to perform some steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating driving behavior in a virtual-reality fusion environment, characterized in that: include: Collecting driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device, the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data collection device during driving; Processing the driving-related data according to the set evaluation index to generate analysis data, wherein the analysis data is used to characterize the driving performance of the user in the driving simulation virtual scene; The user's driving behavior is evaluated based on the analysis data.

2. The method according to claim 1, characterized in that The driving simulation virtual scene includes a set driving scene and / or driving task; and / or, After collecting the driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed on the display device, it includes: performing data cleaning, data synchronization and normalization processing on the driving-related data to generate processed driving-related data, and continuing to execute the step of performing data processing on the driving-related data according to the set evaluation indicators to generate analysis data.

3. The method according to claim 1, characterized in that The evaluating the user's driving behavior based on the analysis data includes: Evaluating the user's driving behavior based on analysis data generated from driving-related data corresponding to the user's driving behavior of a set driving task displayed on a display device; or, Evaluate the user's driving behavior based on the analysis data generated from the driving-related data corresponding to the user's driving behavior based on the driving scene displayed by the display device and the acquired user's subjective data; or The user's driving behavior is evaluated based on the analysis data generated from the driving-related data corresponding to the user's driving behavior of the set driving task displayed on the display device and the acquired user's subjective data.

4. The method according to claim 3, characterized in that: The step of evaluating the user's driving behavior based on the analysis data generated from the driving-related data corresponding to the user's driving behavior of the set driving task displayed on the display device includes: When the driving related data includes a steering wheel angle, the analysis data includes a mean square error of a steering wheel angle deviation; and / or, when the driving related data includes a pedal force, the analysis data includes a mean value and a standard deviation of the pedal force; and / or, when the driving related data includes a vehicle speed, the analysis data includes a speed deviation and a fluctuation range of the vehicle speed; and / or, when the driving related data includes a driving trajectory, the analysis data includes a lane deviation distance and a frequency of the driving trajectory; and / or, when the driving related data includes a user's heart rate, the analysis data includes a heart rate variability of the user's heart rate; According to the set analysis threshold corresponding to each analysis data corresponding to the stored driving task, the mean square error of the steering wheel angle deviation, the mean value and standard deviation of the pedal force, the speed deviation and fluctuation range of the vehicle speed, the lane deviation distance and frequency of the driving trajectory and / or the heart rate variability of the user's heart rate are compared to evaluate the user's driving behavior.

5. The method according to claim 3, characterized in that: The user subjective data is generated based on the user's experience rating of the driving simulator, the user's age and the user's driving experience.

6. The method according to any one of claims 1 to 5, characterized in that: When the data collection device is a head and eye tracking device, the user physiological data includes user gaze tracking data; and / or, When the data acquisition device is a heart rate monitoring device, the user physiological data includes user heart rate data; and / or, When the data acquisition device is a skin electrode measurement device, the user physiological data includes the user's skin electrode activity data.

7. A driving behavior evaluation device in a virtual-reality fusion environment, characterized in that: include: A collection module, used to collect driving-related data corresponding to the user's driving behavior based on the driving simulation virtual scene displayed by the display device, wherein the driving-related data includes at least one of the following: user operation data based on the driving simulator, human-computer interaction data between the user and the driving simulator, driving simulator-related data, and user physiological data collected by the data collection device during driving; A data processing module, used for processing the driving-related data according to the set evaluation index to generate analysis data, wherein the analysis data is used to characterize the driving performance of the user in the driving simulation virtual scene; The evaluation module is used to evaluate the user's driving behavior based on the analysis data.

8. A driving simulator, characterized in that: It includes a simulated cockpit, a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the steps of the method for evaluating driving behavior in a virtual-reality fusion environment described in any one of claims 1 to 6 are implemented.

9. A vehicle-mounted edge device, characterized in that: It includes a memory and a processor, the memory is used to store information including program instructions, the processor is used to control the execution of the program instructions, and the program instructions, when loaded and executed by the processor, implement the steps of the method for evaluating driving behavior in a virtual-reality fusion environment as described in any one of claims 1 to 6.

10. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the driving behavior evaluation method in a virtual-reality fusion environment as described in any one of claims 1 to 6.

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