CN114627717A - Virtual reality and big data analysis-based novice driver training system - Google Patents
Virtual reality and big data analysis-based novice driver training system Download PDFInfo
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Abstract
The invention relates to a novice driver training system based on virtual reality and big data analysis, which comprises six modules: the course customization module selects different courses and scenes according to the age, the gender and the driving style of a driver; the scene design module is used for scene selection and scene construction; the driving simulator and hardware access module is used for accessing software of the driving simulation scene library into hardware such as a multi-degree-of-freedom driving simulator, virtual reality equipment and the like for debugging; the data acquisition module is used for acquiring the data of drivers and the parameters of the motion state of the vehicle in each scene; the operation evaluation module is used for evaluating the operation of the driver and providing a scientific and quantitative improvement suggestion; and the effect verification module is used for detecting the qualification of the training content of the driver. By the training method, the safety awareness and the coping ability of the driver in a complex scene can be effectively improved, the land using area is reduced, the training effect is improved, and the service quality is improved.
Description
Technical Field
The invention relates to the driving training industry, in particular to a driving training system aiming at a novice driver in a complex scene based on a virtual reality and big data analysis technology.
Background
In traffic accidents, factors related to drivers are more than 80% in proportion, and all the factors are caused by poor driving behaviors. Although the automatic driving technology is continuously developed at present, a man-machine mixed driving traffic condition for a long time still exists before full automatic driving is realized, namely an unmanned vehicle and a manned vehicle run together, and the traffic environment faced by a driver is more complicated at the moment. The complex traffic environment demands drivers with increased awareness of their driving skills and safety.
The traditional driving training industry at present has the following problems:
1. the number of the used vehicles is short, and the effective training time of the new trainees is short.
2. The driving training subjects are far away from the actual traffic scene, so that the phenomenon of the 'family' is serious.
3. The service awareness of the coach is light and the driving experience of the new student is low.
4. The attention is paid to the training of driving skills, and the propaganda of traffic safety consciousness is lacked.
5. The traditional driving school is lack of land for vehicles, and lacks of test driving vehicles and driving practice sites.
With the maturity of virtual reality technology and big data technology, complex traffic scenes can enable drivers to participate and train through a driving simulator. However, the driving simulation scene of the driving school is only the examination scene of subject two and subject three at present, the image quality is fuzzy, the acquisition and analysis of training data are lacked, and the training effect is very limited.
In view of this, science and technology in this field are dedicated to research and develop a driver training system based on virtual reality and big data analysis technology in a complex scene to improve the training effect and improve the service quality.
Disclosure of Invention
The invention aims to provide a novice driver training system based on virtual reality and big data analysis, which is provided with six modules: course customization module, scene design module, drive simulator and hardware access module, data acquisition module, operation evaluation module, effect verification module, through the operation training under the virtual reality environment, can effectively promote driver's safety consciousness and reply ability under the complicated scene, reduce tradition driving school and use land pressure with the car, improve the training effect, promote quality of service, training subject is single in the training system of having solved from this, lack the problem of the collection and the analysis of training data.
The technical solution of the invention is as follows:
the utility model provides a novice driver training system based on virtual reality and big data analysis which characterized in that: the training system comprises a course customization module, a scene design module, a driving simulator and hardware access module, a data acquisition module, an operation evaluation module and an effect verification module;
the course customization module is used for designing multi-scene courses for novice drivers, re-education drivers, special vehicle drivers and driving styles thereof; the trainees need to fill in the driving style scales twice before and after training to be used as verification of training effect, and the system can select scenes with different parameters as courses according to different driving styles of drivers;
the scene design module is used for scene selection and scene construction, wherein the scene selection part adopts a daily traffic scene, a driving auxiliary function scene, a frequently-occurring accident scene and a complex driving scene as a virtual scene library, and the scene library is updated according to the frequently-occurring accident scene in the violation record data 1-3 after a driver leaves a driving school; the scene building part adopts Unity 3D to build a virtual simulation scene model, and the 3D scene can be displayed in corresponding equipment after being processed by a virtual reality technology;
the driving simulator and hardware access module is used for accessing software of a driving simulation scene library into the driving simulator and virtual reality hardware for debugging; the debugging content comprises the following steps: the display content of a display related to the picture is correct and clear, the force feedback reality of a steering wheel, an accelerator pedal and a brake pedal, and the multi-degree-of-freedom washout algorithm ensure that the three-axis speed and the Euler angle of a vehicle output by a motion platform respond correctly in a simulator, and the virtual reality picture is displayed correctly and clearly;
the data acquisition module is used for acquiring standard data and driver data under multiple scenes, the acquired driver data comprise vehicle coordinates, vehicle three-axis speed, vehicle three-axis acceleration, steering wheel turning angle, opening degree of an accelerator/brake pedal, yaw angle, lane offset and vehicle head distance, and a system of a driver can automatically acquire and store the driving data under the multiple scenes in the scene training process, so that later-stage data query is facilitated; the standard data are coach driving data under multiple scenes, the system can collect the coach data under the multiple scenes firstly, and the standard data under the multiple scenes are formed through data preprocessing, data cleaning and data query analysis methods in a big data analysis technology;
the operation evaluation module is used for scoring the operation of the driver and giving an improvement suggestion; the operation evaluation module comprises an evaluation unit, a judgment unit and a suggestion unit, wherein the evaluation unit is used for evaluating the correctness and proficiency of the operation of the driver, the judgment unit is used for judging the driving style of the driver, the suggestion unit is used for showing the difference value of the data of the driver and the standard data, and an improvement suggestion is proposed to the current operation of the driver according to the difference value; the operation evaluation module is combined with a data visualization and data prediction module in the big data analysis technology;
the operation evaluation module compares the operation data of the driver with the coach data to obtain the difference values of the track, the speed, the acceleration and the distance between the car heads, provides quantitative improvement suggestions for the operation of the driver according to the difference values, and can effectively improve the learning efficiency of the driver;
the effect verification module is used for detecting the qualification of the training content of the driver; the effect verification module comprises a complex scene assessment unit and is used for examining the complex driving scene of the driver and graduating the complex driving scene through the rear.
The effect verification module further comprises a safe driving habit evaluation unit and a violation recording unit, wherein the safe driving habit evaluation unit is used for recording safe driving habits of the driver after leaving school, and the violation recording unit is used for recording violation data of the driver after leaving school for 1-3 years.
The course customization module is used for scenes of novice drivers and adding scenes of common urban traffic and scenes of driving assistance functions.
The course customization module is used for re-educating the driver's scene and increasing the training of the scene with multiple accidents.
The course customization module is used for scenes of drivers of special vehicles and increasing complex scenes of long and large downhill roads and urban road intersections.
The driving style scale result in the course customization module is a four-dimensional driving style graph which comprises an incentive degree, an anxiety degree, a cautious degree and an effect degree.
The improvement suggestions provided by the suggestion unit in the operation evaluation module comprise operation degrees and operation time, wherein the operation degrees refer to the stroke of stepping on an accelerator/brake pedal, the direction of rotating a steering wheel and the degrees of a steering angle; the operation timing refers to an operation time point and an end time point of turning the steering wheel by stepping on the accelerator/brake pedal.
The novice driver training system based on virtual reality and big data analysis is provided with six modules: course customization module, scene design module, driving simulator and hardware access module, data acquisition module, operation evaluation module, effect verification module through the operation training under the virtual reality environment, can effectively promote driver's safety consciousness and reply ability under the complicated scene, reduce the tradition and drive school and use land pressure with the car, improve the training effect, promote quality of service.
The system configuration and the working process of the novice driver training system based on the virtual reality and the big data analysis are as follows:
the course customization module in the system customizes different learning courses according to drivers of different types and driving styles, and comprises the following steps: the method aims at urban traffic scenes and driving assistance scenes of novice drivers, scenes with frequent accidents of re-educated drivers and complex scenes of special vehicle drivers. And realizing the scene library containing the four scenes in the Unity 3D software through a scene design module. And then, the data is imported into a driving simulator through a hardware access module for debugging, so that the display content is correct and clear, and the flexibility of a steering wheel and an accelerator/brake pedal is the same as that of a real vehicle. Then, coach data is collected through a data collection module to serve as a standard, and driver data is collected to be analyzed. And comparing the two data through an operation evaluation module to obtain an operation score and an improvement suggestion. And finally, checking the driver through a complex scene unit in the effect verification module before leaving the driving school. The system can continuously record the violation records of 1-3 years after the graduate leaves the school, and can update the scene library aiming at the scene with frequent accidents in the record.
Drawings
FIG. 1 is a technical route flow diagram of a novice driver training system based on virtual reality and big data analysis of the present invention.
FIG. 2 is a schematic diagram of the scene design module in the system of the present invention.
Fig. 3 is a schematic diagram of the data acquisition module in the system of the present invention.
FIG. 4 is a schematic diagram of the operational evaluation module in the system of the present invention.
FIG. 5 is a schematic diagram of the system of the present invention employing big data analytics techniques.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and examples.
Referring to fig. 1 to 5, the invention provides a novice driver training system based on virtual reality and big data analysis, which is provided with a course customization module, a scene design module, a driving simulator and hardware access module, a data acquisition module, an operation evaluation module and an effect verification module.
Wherein: and the course customizing module is used for designing courses of different scenes aiming at different types of drivers (including novice drivers, re-educated drivers and special vehicle drivers) and driving styles thereof.
Common urban traffic scenes and scenes with driving assistance functions are added for novice drivers. The urban traffic scene is the most common scene encountered by modern drivers in daily use, and the advance adaptation to the scene is beneficial to the future skilled operation. The driving support function scene training aims to adapt a novice driver to the driving support function of the vehicle in advance because the driving support function has been popularized.
Aiming at re-educating drivers, training in scenes with multiple accidents is increased. The re-education driver is a driver with 12 points of full driving evidence, and when re-education training is carried out, the test difficulty is increased, more training is carried out in the scene with multiple accidents, and the purpose of avoiding errors is achieved.
Aiming at drivers of special vehicles (school buses, fire trucks, ambulances and the like), complex scenes such as long and large downhill slopes and urban road intersections are added, and the ability of the drivers to cope with the complex scenes is developed. The special vehicle driver has a heavy driving safety task, so that the training scene is more complicated, and comprises complex scenes such as unfavorable linear combination in an expressway, intersections in an urban road and the like.
The trainee needs to fill out a Driving Style scale (MDSI) twice before and after training as verification of the training effect. The driving style scale result is a four-dimensional driving style chart comprising an excitation degree, an anxiety degree, a cautious degree and an effect degree. According to different driving styles of drivers, the system can select scenes with different parameters as courses. For example, different vehicle speeds and different headway distances are set for conservative drivers and aggressive drivers respectively.
By adopting the technical scheme, the driving students are classified according to types and driving styles, and are taught according to the profiles to formulate customized courses, so that the operation skills and safety awareness of the drivers are effectively improved.
The scene design module shown in fig. 2 is used for scene selection and scene construction, wherein the scene selection part adopts a daily traffic scene, a driving assistance function scene, an accident multi-occurrence scene and a complex driving scene as a virtual scene library. And the scene library is also updated according to the accident frequently occurring scene in the violation record data 1-3 after the driver leaves the driving school. The scene building part adopts Unity 3D to build a virtual simulation scene model, and the 3D scene can be displayed in corresponding equipment after being processed by virtual reality technology (including VR, AR and MR). The virtual reality technology can enable a driver to have an immersion feeling during scene training, and scene reality is increased.
The driving simulator and the hardware access module in the training system comprise a driving simulator access module and virtual reality hardware (a head-wearing type, a calibration device and the like), and are used for accessing software of a driving simulation scene library into the driving simulator and the virtual reality hardware for debugging. The debugging content comprises: the display content of the display related to the picture is correct and clear; force feedback authenticity of a steering wheel, an accelerator pedal and a brake pedal; the multi-degree-of-freedom washout algorithm ensures that the three-axis speed and the Euler angle of the vehicle output by the motion platform respond correctly in the simulator; the virtual reality picture is displayed correctly and clearly.
The data acquisition module shown in fig. 3 is used for acquiring standard data and driver data in each scene. The collected driver data comprise vehicle coordinates, vehicle three-axis speed, vehicle three-axis acceleration, steering wheel turning angle, opening degree of an accelerator/brake pedal, yaw angle, lane deviation and vehicle head distance. The system can automatically collect and store the driving data in each scene during the scene training process of the driver, so that the later data query is facilitated. The standard data is coach driving data in each scene, the system collects coach data in each scene, and as shown in fig. 5, the standard data in each scene is formed through methods of data preprocessing, data storage, data cleaning, data query analysis and the like in a big data analysis technology.
An operation evaluation module as shown in fig. 4, which is used for scoring the operation of the driver and giving an improvement suggestion. The operation evaluation module comprises an evaluation unit, a judgment unit and a suggestion unit, wherein the evaluation unit is used for evaluating the correctness and proficiency of the operation of the driver, for example, an operation assessment scoring mechanism is set, the judgment unit is used for judging the driving style of the driver, the suggestion unit is used for showing the difference value of the driver data and the standard data, and an improvement suggestion is proposed for the current operation of the driver according to the difference value. With combined reference to fig. 5, the operation evaluation module combines modules for data visualization, data prediction, etc. in the big data analysis technique.
The operation evaluation module compares the operation data of the driver with the coach data to obtain the difference values of the track, the speed, the acceleration and the distance between the two heads, provides quantitative improvement suggestions for the operation of the driver according to the difference values, and can effectively improve the learning efficiency of the driver.
The improvement suggestions provided by the suggestion unit in the operation evaluation module comprise an operation degree and an operation time, wherein the operation degree refers to the stroke (percentage) of stepping on an accelerator/brake pedal, the direction of turning a steering wheel and the degree of turning angle; the operation timing refers to an operation time point and an end time point of turning the steering wheel by stepping on the accelerator/brake pedal.
The effect verification module in the training system is used for detecting the qualification of the training content of the driver. The effect verification module is provided with a complex scene assessment unit for examining the complex driving scene of the driver and graduating the complex driving scene through the rear. The effect verification module is further provided with a safe driving habit evaluation unit and a violation recording unit, wherein the safe driving habit evaluation unit is used for recording safe driving habits of the driver after leaving school, and the violation recording unit is used for recording violation data of the driver after leaving school for 1-3 years.
The effect verification module simultaneously records the training effect of the driving trainees in the school and the violation record after leaving the school, and has positive significance for the verification of the training effect. The effect verification module also makes the scene with multiple accidents in the violation record into a new scene, and updates the scene library of the training scene design module.
As shown in fig. 1, the operation steps of the virtual reality and big data analysis based novice driver training system of the present invention are as follows:
the method comprises the following steps that (1) a novice driver starts training, information of the driver is input, a course customization module, a scene design module, a driving simulator and hardware access module, a data acquisition module, an operation evaluation module and a complex scene assessment unit in an effect verification module are operated in sequence, and the training is completed after the assessment is qualified; and if the complex scene is unqualified in examination, returning to the data acquisition module for re-operation until the examination is qualified, and finishing the training.
Aiming at the training of the re-educated driver, after the operation steps are completed, the safe driving habit evaluation unit and the violation recording unit in the effect verification module are operated until the examination is qualified, and the training is completed.
Aiming at the training of drivers of special vehicles, after the operation steps are completed, the training of complex scenes such as long and large downhill slopes, unfavorable linear combination in expressways, intersections in urban roads and the like is added.
After the operation training of the driver is completed, the training system updates the scene library aiming at the scene with the frequent accidents in the record.
In summary, the novice driver training system based on virtual reality and big data analysis of the invention is composed of six modules: the course customization module selects different courses and scenes according to the age, the gender and the driving style of a driver; the scene design module is used for scene selection and scene construction; the driving simulator and hardware access module is used for accessing software of the driving simulation scene library into hardware such as a multi-degree-of-freedom driving simulator, virtual reality equipment and the like for debugging; the data acquisition module is used for acquiring the data of drivers and the parameters of the motion state of the vehicle in each scene; the operation evaluation module is used for evaluating the operation of the driver and providing a scientific and quantitative improvement suggestion; and the effect verification module is used for detecting the qualification of the training content of the driver. By training the training system, the safety awareness and the coping ability of a driver in a complex scene can be effectively improved, the land use pressure of a traditional driving school is reduced, the training effect is improved, and the service quality is improved.
Of course, those skilled in the art will recognize that the above-described embodiments are illustrative only and not intended to be limiting, and that changes, modifications, etc. to the above-described embodiments are intended to fall within the scope of the appended claims, provided they fall within the true spirit and scope of the present invention.
Claims (7)
1. The utility model provides a novice driver training system based on virtual reality and big data analysis which characterized in that: the training system comprises a course customization module, a scene design module, a driving simulator and hardware access module, a data acquisition module, an operation evaluation module and an effect verification module;
the course customization module is used for designing multi-scene courses for novice drivers, re-education drivers, special vehicle drivers and driving styles thereof; the trainees need to fill in the driving style scales twice before and after training to be used as verification of training effect, and the system can select scenes with different parameters as courses according to different driving styles of drivers;
the scene design module is used for scene selection and scene construction, wherein the scene selection part adopts a daily traffic scene, a driving auxiliary function scene, a frequently-occurring accident scene and a complex driving scene as a virtual scene library, and the scene library is updated according to the frequently-occurring accident scene in the violation record data 1-3 after a driver leaves a driving school; the scene building part adopts Unity 3D to build a virtual simulation scene model, and the 3D scene can be displayed in corresponding equipment after being processed by a virtual reality technology;
the driving simulator and hardware access module is used for accessing software of a driving simulation scene library into the driving simulator and virtual reality hardware for debugging; the debugging content comprises the following steps: the display content of a display related to the picture is correct and clear, the force feedback authenticity of a steering wheel, an accelerator pedal and a brake pedal, the multi-degree-of-freedom washout algorithm ensures that the vehicle three-axis speed and the Euler angle output by a motion platform respond correctly in a simulator, and the virtual reality picture is displayed correctly and clearly;
the data acquisition module is used for acquiring standard data and driver data under multiple scenes, the acquired driver data comprise vehicle coordinates, vehicle three-axis speed, vehicle three-axis acceleration, steering wheel turning angle, opening degree of an accelerator/brake pedal, yaw angle, lane offset and vehicle head distance, and a system of a driver can automatically acquire and store the driving data under the multiple scenes in the scene training process, so that later-stage data query is facilitated; the standard data are coach driving data under multiple scenes, the system can collect the coach data under the multiple scenes firstly, and the standard data under the multiple scenes are formed through data preprocessing, data cleaning and data query analysis methods in a big data analysis technology;
the operation evaluation module is used for scoring the operation of the driver and giving an improvement suggestion; the operation evaluation module comprises an evaluation unit, a judgment unit and a suggestion unit, wherein the evaluation unit is used for evaluating the correctness and proficiency of the operation of the driver, the judgment unit is used for judging the driving style of the driver, the suggestion unit is used for showing the difference value of the data of the driver and the standard data, and an improvement suggestion is proposed to the current operation of the driver according to the difference value; the operation evaluation module is combined with a data visualization and data prediction module in the big data analysis technology;
the operation evaluation module compares the operation data of the driver with the coach data to obtain the difference values of the track, the speed, the acceleration and the distance between the car heads, provides quantitative improvement suggestions for the operation of the driver according to the difference values, and can effectively improve the learning efficiency of the driver;
the effect verification module is used for detecting the qualification of the training content of the driver; the effect verification module comprises a complex scene assessment unit and is used for examining the complex driving scene of the driver and graduating the complex driving scene through the rear.
2. The virtual reality and big data analysis-based novice driver training system of claim 1, wherein: the effect verification module further comprises a safe driving habit evaluation unit and a violation recording unit, wherein the safe driving habit evaluation unit is used for recording safe driving habits of the driver after leaving school, and the violation recording unit is used for recording violation data of the driver after leaving school for 1-3 years.
3. The virtual reality and big data analysis-based novice driver training system of claim 1, wherein: the course customization module is used for scenes of novice drivers and adding scenes of common urban traffic and scenes of driving assistance functions.
4. The virtual reality and big data analysis-based novice driver training system of claim 1, wherein: the course customization module is used for re-educating the scenes of the driver and increasing the training of scenes with multiple accidents.
5. The virtual reality and big data analysis-based novice driver training system of claim 1, wherein: the course customization module is used for scenes of drivers of special vehicles and increasing complex scenes of long and large downhill slopes and urban road intersections.
6. The virtual reality and big data analysis-based novice driver training system of claim 1, wherein: the driving style scale result in the course customization module is a four-dimensional driving style graph which comprises an incentive degree, an anxiety degree, a cautious degree and an effect degree.
7. The virtual reality and big data analysis-based novice driver training system of claim 1, wherein: the improvement suggestions provided by the suggestion unit in the operation evaluation module comprise operation degrees and operation time, wherein the operation degrees refer to the stroke of stepping on an accelerator/brake pedal, the direction of rotating a steering wheel and the degrees of a steering angle; the operation timing refers to an operation time point and an end time point of stepping on the accelerator/brake pedal and rotating the steering wheel.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115116297A (en) * | 2022-06-14 | 2022-09-27 | 合肥工业大学 | Method suitable for taking over training of man-machine co-driving vehicle drivers |
| CN115440107A (en) * | 2022-10-26 | 2022-12-06 | 北京千种幻影科技有限公司 | VR virtual reality-based intelligent driving training system and method for deaf-mute |
| CN115635979A (en) * | 2022-11-10 | 2023-01-24 | 安徽江淮汽车集团股份有限公司 | New-hand-assisted driving control method based on head-up display terminal |
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