CN110956867B - Training system and training method based on big data driver behavior analysis - Google Patents
Training system and training method based on big data driver behavior analysis Download PDFInfo
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- CN110956867B CN110956867B CN201910401078.7A CN201910401078A CN110956867B CN 110956867 B CN110956867 B CN 110956867B CN 201910401078 A CN201910401078 A CN 201910401078A CN 110956867 B CN110956867 B CN 110956867B
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- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
- G09B9/02—Simulators for teaching or training purposes for teaching control of vehicles or other craft
- G09B9/04—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles
- G09B9/052—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles characterised by provision for recording or measuring trainee's performance
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- G—PHYSICS
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- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
- G09B9/02—Simulators for teaching or training purposes for teaching control of vehicles or other craft
- G09B9/04—Simulators for teaching or training purposes for teaching control of vehicles or other craft for teaching control of land vehicles
Abstract
The invention discloses a training system and a training method based on big data driver behavior analysis, wherein the training system based on big data driver behavior analysis comprises a driver big data acquisition module, a big data preprocessing module, a big data analysis processing module and a driving school training management module; the training method based on big data driver behavior analysis comprises the steps of driver big data acquisition, big data preprocessing, big data analysis processing and driving school training management guidance. The invention is beneficial to improving and perfecting the formulation of the traffic policy and the design of the driving test subjects, improving the training quality of drivers and bringing higher guarantee to the road traffic safety.
Description
Technical Field
The invention relates to a training system and a training method, in particular to an intelligent training system and a training method based on big data driver behavior analysis.
Background
Based on the basic national conditions of China, more than 95% of driving skill training of new drivers of motor vehicles is finished in driving schools, and the key point for improving the driving skill of the new drivers and improving safe driving consciousness is to improve the training quality of the driving schools. The current road driving training of drivers in China is short in school time, a C-syndrome of a small automobile is taken as an example (C1 and C2), and the road driving training is only 24 school times; taking the german minibus B certificate as an example (B, BE) with high training quality, the road driving training needs 42 hours of learning, including 30 hours of urban road base training and 12 hours of learning special condition driving training, wherein the special condition driving training includes at least 5 suburban road hours of learning, 4 highway hours of learning, and 3 night road hours of learning. Therefore, the training of road driving skills of beginners should have more practical training requirements, and the purpose of teaching by trial cannot be achieved. At the present stage, the motor vehicle driving training period is short, the phenomenon of teaching for test is common, the road driving training period is properly prolonged, and the phenomenon of teaching for test is avoided. At the present stage, the phenomenon of trial teaching of driving training in China is common, and the teaching training and the actual driving are disjointed.
Disclosure of Invention
The purpose of the invention is as follows: the training system and the training method based on big data driver behavior analysis are provided, so that the training quality of a driving school is improved, and the driving skill of a driver is improved; the formulation of a traffic policy and the design of driving test subjects are improved and perfected, the road traffic safety level is improved, and higher guarantee is brought to national road traffic safety.
In order to achieve the purpose, the invention adopts the technical scheme that: the training system based on big data driver behavior analysis comprises a driver big data acquisition module, a big data preprocessing module, a big data analysis processing module and a driving school training management module. The big data acquisition module mainly comprises the steps of acquiring big data of road traffic of a driver and acquiring big data of training of the driver. The driver road traffic big data come from various traffic flow check out test set, and traffic check out test set mainly includes video detector, earth magnetism detector, microwave detector, bayonet socket, semaphore, crossing signal equipment etc. and the traffic flow data of equipment collection passes through communication link and transmits to policeman's traffic control center, and policeman's traffic control center carries out the classification statistics to the interior motor vehicle illegal activities of district in the jurisdiction, for example: running red light, speeding, driving after drinking, driving in a solid line, and the like. And simultaneously, driving image information corresponding to a motor vehicle driver is collected to form driver road traffic big data when the motor vehicle is illegal. The driver training big data come from training vehicle-mounted detection equipment, and the vehicle-mounted detection equipment comprises a satellite positioning detection device, a video detection device, a radar detection device, a vehicle operation sensing detection device and the like. The vehicle-mounted detection equipment mainly collects driver training big data of a driver in a course of road driving training of subjects.
The big data preprocessing module is mainly used for preprocessing big data for driver training. The big driver training data comprises data collected by various detection devices, and the denoising and deduplication preprocessing is needed firstly, and the denoising and deduplication preprocessing method disclosed by the invention adopts a data filtering method based on mode mining: various illegal deduction driving behaviors in the driver training big data are classified as different deduction interestingness, pruning is directly carried out according to illegal deduction interestingness index conditions, an interest mode is dug in place in one step, noise data filtering can be effectively achieved, high-quality data are obtained, correctness and consistency of the data are improved, and the purpose of denoising is achieved; the method comprises the steps of establishing a driving training data de-duplication analysis extraction model algorithm, utilizing a data mapping relation among unstructured data, amplifying a data sequence generated by mapping to a comparison range of data similarity, and carrying out data coding on obtained data analysis factors to generate an initial population so as to improve individual similarity and individual quality among data objects and achieve the purpose of de-duplication. Furthermore, after the driver training big data denoising and de-duplication processing, the obtained data individuals are subjected to multi-dimensional cluster analysis again, and fine-grained local analysis and disturbance are achieved, so that the multi-dimensional analysis speed of the data population is accelerated.
The big data analysis and processing module is mainly used for analyzing and processing the preprocessed data, mining and analyzing the big road traffic data of the driver and the big training data of the driver through technologies such as correlation analysis, regression analysis and the like, finding out the relation between the big road traffic data and the big training data of the driver, obtaining a valuable correlation rule, analyzing the linear relation between traffic illegal behaviors and the training driving behaviors of the driver, establishing a prediction model according to the analysis result, carrying out analysis and prediction on the data acquired in real time based on the prediction model, predicting the conditions of the traffic illegal behaviors possibly occurring to the drivers with different driving behaviors, and transmitting the prediction result to a training management platform of a driving school.
The driving school training management module guides the driving behavior of the driver in a targeted manner according to the analysis and prediction result obtained by the big data analysis and processing module, so that the driving skill of the learner is improved, and the examination passing rate of the subject three-step is improved.
The invention also discloses a training method based on big data driver behavior analysis, which comprises the following steps: s1 acquiring driver big data; s2 preprocessing big data; s3, analyzing and processing big data; s4 driving school training management guide.
S1 driver big data collection mainly collects driver road traffic big data and driver training big data. The driver road traffic big data come from various traffic flow detection devices, and the traffic detection devices mainly comprise video detectors, geomagnetic detectors, microwave detectors, bayonets, signal machines, intersection signal devices and the like. The device collects traffic flow data and transmits the traffic flow data to a traffic management data center of a police department through a communication link, the traffic management center of the police department classifies and counts illegal behaviors of motor vehicles in a district, and meanwhile, driving image information corresponding to a motor vehicle driver is collected to form driver road traffic big data when the illegal behaviors of the motor vehicles are collected each time. The driver training big data come from training vehicle-mounted detection equipment, and the vehicle-mounted detection equipment comprises a satellite positioning detection device, a video detection device, a radar detection device, a vehicle operation sensing detection device and the like. The vehicle-mounted detection equipment is mainly used for collecting driver training data of a driver in a course of road driving training of subjects. And importing the road traffic big data and the training big data of the driver into a big data platform hive database through an sqoop tool.
The S2 big data preprocessing is mainly used for preprocessing big data of driver training. The big driver training data comprises data collected by various detection devices, and the denoising and deduplication preprocessing is needed firstly, and the denoising and deduplication preprocessing method disclosed by the invention adopts a data filtering method based on mode mining: various illegal deduction driving behaviors in the driving training process are classified into different deduction interestingness, illegal deduction interestingness index conditions are directly pruned, an interest mode is dug in place by one step, noise data filtering can be effectively achieved, high-quality data are obtained, the correctness and the consistency of the data are improved, and the purpose of denoising is achieved; the method comprises the steps of establishing a driving training data de-duplication analysis extraction model algorithm, utilizing a data mapping relation among unstructured data, amplifying a data sequence generated by mapping to a comparison range of data similarity, and carrying out data coding on obtained data analysis factors to generate an initial population so as to improve individual similarity and individual quality among data objects and achieve the purpose of de-duplication. After the driver trains big data to perform denoising and de-duplication processing, multidimensional clustering analysis is performed on the obtained data individuals again, fine-grained local analysis and disturbance are achieved, and the multidimensional analysis speed of the data population is accelerated.
The S3 big data analysis process is to analyze and process the big data of the driver road traffic and the preprocessed driver training data. Aiming at the road traffic big data of a driver and the preprocessed driver training big data, python and tenserflow are connected with a hive database to obtain data, mining analysis is carried out through technologies such as association analysis, regression analysis and the like, the relation between the python and tenserflow is found out, a valuable association rule is obtained, the linear relation between traffic illegal behaviors and the driver training driving behaviors is analyzed, a prediction model is built according to the result, the data obtained in real time is analyzed and predicted through strom based on the prediction model, the conditions of the traffic illegal behaviors possibly occurring to the drivers with different driving behaviors are predicted, the prediction result is transmitted to a driving school management platform database through sqoop, and the driving school is convenient to carry out targeted guidance training on the specific driving behaviors.
The S4 driving school training management guidance is that the driving school management platform carries out targeted guidance on the driving behavior of the driver according to the analysis and prediction result obtained by the big data analysis and processing module, improves the passing rate of the subject three-test and improves the driving skill of the trainee.
Has the advantages that: the invention provides a training system and a training method based on big data driver behavior analysis, thereby improving the driver training quality and bringing higher guarantee to the road traffic safety; the method is beneficial to improving and perfecting the formulation of the traffic policy and the design of the driving test subjects, and the road traffic safety level is improved.
Detailed Description
The present invention will be further described with reference to the following examples.
The training system based on big data driver behavior analysis comprises a driver big data acquisition module, a big data preprocessing module, a big data analysis processing module and a driving school training management module.
The big data acquisition module mainly comprises the steps of acquiring big data of road traffic of a driver and acquiring big data of training of the driver. The traffic detection equipment mainly comprises a video detector, a geomagnetic detector, a microwave detector, a bayonet, a signal machine, intersection signal equipment and the like, wherein traffic flow data collected by the equipment is transmitted to a traffic control data center of a public security department through a communication link, the traffic control center of the public security department classifies and counts illegal behaviors of motor vehicles in a district, and meanwhile, driving image information corresponding to the motor vehicle drivers during each illegal behavior of the motor vehicles is collected to form the road traffic big data of the drivers. The driver training big data come from training vehicle-mounted detection equipment, and the vehicle-mounted detection equipment comprises a satellite positioning detection device, a video detection device, a radar detection device, a vehicle operation sensing detection device and the like. The vehicle-mounted detection equipment mainly collects driver training big data of a driver in a course of road driving training of subjects. And importing the road traffic big data of the driver and the training big data of the driver into a big data platform hive database through an sqoop data migration tool.
The big data preprocessing module is mainly used for preprocessing big data for driver training. The big driver training data comprises data collected by various detection devices, and the denoising and deduplication preprocessing is needed firstly, and the denoising and deduplication preprocessing method disclosed by the invention adopts a data filtering method based on mode mining: various illegal deduction driving behaviors in the driving training process are classified into different deduction interestingness, illegal deduction interestingness index conditions are directly pruned, an interest mode is dug in place by one step, noise data filtering can be effectively achieved, high-quality data are obtained, the correctness and the consistency of the data are improved, and the purpose of denoising is achieved; the method comprises the steps of establishing a driving training data de-duplication analysis extraction model algorithm, utilizing a data mapping relation among unstructured data, amplifying a data sequence generated by mapping to a comparison range of data similarity, and carrying out data coding on obtained data analysis factors to generate an initial population so as to improve individual similarity and individual quality among data objects and achieve the purpose of de-duplication. After the driver trains big data to perform denoising and de-duplication processing, multidimensional clustering analysis is performed on the obtained data individuals again, fine-grained local analysis and disturbance are achieved, and the multidimensional analysis speed of the data population is accelerated.
The big data analysis processing module is mainly used for analyzing and processing the preprocessed data. Aiming at multidimensional data in road traffic big data and driver training big data of a driver, python and tensoflow are used for connecting with a hive database to obtain data, mining analysis is carried out through technologies such as association analysis and regression analysis to find out the relation between the python and tensoflow so as to obtain a valuable association rule, the linear relation between traffic illegal behaviors and driver training driving behaviors is analyzed, a prediction model is established according to the result, the data obtained in real time is analyzed and predicted through strom based on the prediction model, the conditions of the traffic illegal behaviors possibly occurring to the drivers with different driving behaviors are predicted, and the prediction result is transmitted to a driving school training management platform database through sqoop so that driving schools can conveniently conduct targeted guidance and training on specific driving behaviors.
The driving school training management module carries out targeted guidance on the driving behavior of the driver according to the analysis and prediction result obtained by the big data analysis and processing module, improves the passing rate of the subject three-examination and improves the driving skill of the trainees.
The training method based on the big data driver behavior analysis mainly comprises S1 driver big data acquisition; s2 preprocessing big data; s3, analyzing and processing big data; s4 training management of driving school guides four steps, which are described as follows:
s1 driver big data collection mainly collects driver road traffic big data and driver training big data. The driver road traffic big data come from various traffic flow detection devices, and the traffic detection devices mainly comprise video detectors, geomagnetic detectors, microwave detectors, bayonets, signal machines, intersection signal devices and the like. The device collects traffic flow data and transmits the traffic flow data to a traffic management data center of a police department through a communication link, the traffic management center of the police department classifies and counts illegal behaviors of motor vehicles in a district, and meanwhile, driving image information corresponding to a motor vehicle driver is collected to form driver road traffic big data when the illegal behaviors of the motor vehicles are collected each time. The driver training big data come from training vehicle-mounted detection equipment, and the vehicle-mounted detection equipment comprises a satellite positioning detection device, a video detection device, a radar detection device, a vehicle operation sensing detection device and the like. The vehicle-mounted detection equipment is mainly used for collecting driver training data of a driver in a course of road driving training of subjects. And importing the road traffic big data and the training big data of the driver into a big data platform hive database through an sqoop tool.
The preprocessing of the big data of S2 is mainly to preprocess the big data of driver training, the big data of driver training includes the data collected by various detection devices, firstly, the preprocessing of denoising and deduplication is needed, the preprocessing method of denoising and deduplication disclosed by the invention adopts a data filtering method based on mode mining: various illegal deduction driving behaviors in the driver training big data are classified as different deduction interestingness, pruning is directly carried out according to illegal deduction interestingness index conditions, an interest mode is dug in place in one step, noise data filtering can be effectively achieved, high-quality data are obtained, correctness and consistency of the data are improved, and the purpose of denoising is achieved; the method comprises the steps of establishing a driving training data de-duplication analysis extraction model algorithm, utilizing a data mapping relation among unstructured data, amplifying a data sequence generated by mapping to a comparison range of data similarity, and carrying out data coding on obtained data analysis factors to generate an initial population so as to improve individual similarity and individual quality among data objects and achieve the purpose of de-duplication. After the driver trains big data to perform denoising and de-duplication processing, multidimensional clustering analysis is performed on the obtained data individuals again, fine-grained local analysis and disturbance are achieved, and the multidimensional analysis speed of the data population is accelerated.
The S3 big data analysis processing is to analyze and process the preprocessed data, acquire data by using python and tenserflow connected live databases aiming at the multidimensional data in the big road traffic data of the driver and the big training data of the driver, carry out mining analysis by technologies of association analysis, regression analysis and the like, find out the relation between the two data, obtain valuable association rules, analyze the linear relation between the traffic violation behaviors and the driver training driving behaviors, establish a prediction model according to the result, analyze and predict the data acquired in real time by strom, predict the conditions of the traffic violation behaviors possibly generated by the drivers with different driving behaviors, and transmit the prediction result to the driving school management platform database through sqoop, so that the driving school can carry out targeted guidance and training on the specific driving behaviors.
The S4 driving school training management guidance is that the driving school management platform carries out targeted guidance on the driving behavior of the driver according to the analysis and prediction result obtained by the big data analysis and processing module, improves the passing rate of the subject three-test and improves the driving skill of the trainee.
While embodiments of the present invention have been described above, the present invention is not limited to the specific embodiments and applications described above, which are intended to be illustrative, instructive, and not limiting. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto without departing from the scope of the invention as defined by the appended claims.
Claims (10)
1. A training system based on big data driver behavior analysis is characterized by comprising a driver big data acquisition module, a big data preprocessing module, a big data analysis processing module and a driving school training management module; wherein: the big data acquisition module acquires big data of road traffic of a driver and big data of training of the driver; the big data preprocessing module is used for carrying out denoising and de-duplication preprocessing on the big data of the driver training by adopting a data filtering method based on mode mining; the big data analysis and processing module carries out mining analysis on the big road traffic data of the driver and the preprocessed big training data of the driver through association analysis and regression analysis, finds out the relation between the big road traffic data and the preprocessed big training data of the driver to obtain a valuable association rule, establishes a prediction model according to an analysis result, carries out analysis prediction on the driving behavior data of the training vehicle driver in the driving school obtained in real time based on the prediction model, predicts the possible traffic illegal behaviors of different driving behaviors, and transmits the analysis prediction result to the training management module in the driving school; the driving school training management module carries out targeted guidance on the driving behavior of the driver according to an analysis and prediction result obtained by the big data analysis and processing module; the driver road traffic big data specifically refers to normal road driver road traffic big data, and the driver training big data specifically refers to driving school training vehicle driving student training big data.
2. The training system according to claim 1, wherein the driver road traffic big data come from various traffic flow detection devices, the traffic flow detection devices collect traffic flow data and transmit the traffic flow data to a traffic management center of a police department through a communication link, the traffic management center of the police department carries out classified statistics on illegal motor vehicle behaviors in a district, and meanwhile, the driver road traffic big data are formed by collecting driving image information corresponding to a motor vehicle driver when each illegal motor vehicle behavior is collected; the traffic detection equipment comprises a video detector, a geomagnetic detector, a microwave detector, a bayonet, a signal machine and intersection signal equipment.
3. The training system of claim 1, wherein the driver training big data is from training vehicle on-board detection equipment comprising satellite positioning detection devices, video detection devices, radar detection devices, vehicle operation sensing detection devices.
4. The training system as claimed in claim 1, wherein the de-noising and de-duplication preprocessing specifically comprises: classifying various illegal deduction driving behaviors in the driver training big data as different deduction interestingness, directly carrying out pruning denoising according to illegal deduction interestingness index conditions, and excavating an interest mode; and establishing a driving training data de-clustering analysis extraction model algorithm, amplifying a data sequence generated by mapping to a comparison range of data similarity by using a data mapping relation among unstructured data, and performing data coding on the obtained data analysis factors to generate an initial population.
5. The training system of claim 4, wherein the de-noising and de-duplication pre-processing further comprises: after the driver trains big data to perform denoising and de-duplication processing, multidimensional clustering analysis is performed on the obtained data individuals again, fine-grained local analysis and disturbance are achieved, and the multidimensional analysis speed of the data population is accelerated.
6. A training method based on big data driver behavior analysis is characterized by comprising the following steps: s1, collecting road traffic big data and driver training big data of a driver; s2, performing denoising and de-duplication preprocessing on the big training data of the driver by adopting a data filtering method based on mode mining; s3 mining and analyzing the road traffic big data of the driver and the preprocessed training big data of the driver through association analysis and regression analysis, finding out the relationship between the road traffic big data and the preprocessed training big data of the driver to obtain a valuable association rule, establishing a prediction model according to an analysis result, analyzing and predicting the driving behavior data of the training vehicle driving trainees in the driving school obtained in real time based on the prediction model, predicting the possible traffic illegal behaviors of different driving behaviors, and transmitting the analysis and prediction result to a training management platform in the driving school; s4 the driving school training management guide guides the driving behavior of the driver in a targeted manner according to the analysis and prediction result obtained by the big data analysis and processing module; the driver road traffic big data specifically refers to normal road driver road traffic big data, and the driver training big data specifically refers to driving school training vehicle driving student training big data.
7. The training method according to claim 6, wherein the driver road traffic big data come from various traffic flow detection devices, the traffic flow detection devices collect traffic flow data and transmit the traffic flow data to a traffic management center of a police department through a communication link, the traffic management center of the police department carries out classified statistics on illegal motor vehicle behaviors in a district, and meanwhile, the driver road traffic big data are formed by collecting driving image information corresponding to a motor vehicle driver when each illegal motor vehicle behavior is collected; the traffic detection equipment comprises a video detector, a geomagnetic detector, a microwave detector, a bayonet, a signal machine and intersection signal equipment.
8. The training method as claimed in claim 6, wherein the driver training big data is from training vehicle on-board detection equipment, the on-board detection equipment including satellite positioning detection devices, video detection devices, radar detection devices, vehicle operation sensing detection devices.
9. The training method as claimed in claim 6, wherein the denoising and de-duplication preprocessing specifically comprises: classifying various illegal deduction driving behaviors in the driver training big data as different deduction interestingness, directly carrying out pruning denoising according to illegal deduction interestingness index conditions, and excavating an interest mode; and establishing a driving training data de-clustering analysis extraction model algorithm, amplifying a data sequence generated by mapping to a comparison range of data similarity by using a data mapping relation among unstructured data, and performing data coding on the obtained data analysis factors to generate an initial population.
10. The training method as recited in claim 9, wherein the de-noising and de-duplication preprocessing further comprises: after the driver trains big data to perform denoising and de-duplication processing, multidimensional clustering analysis is performed on the obtained data individuals again, fine-grained local analysis and disturbance are achieved, and the multidimensional analysis speed of the data population is accelerated.
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