Method Of Drivers’ Education Recommendation Based On Driving Portrait

As the first line of defense to curb road traffic accidents,driver’s traffic safety education is related to people’s life and property safety and happy life.At present,China’s road traffic safety education system for motor vehicle drivers is thin,the education mode is relatively single,the education content does not consider the driver’s individual differences,the lack of pertinence,resulting in the role of traffic safety education is not well played.At the same time,with the rapid growth of the number of drivers,there are also big data generated by the public security traffic management department in business.How to analyze,manage and use these data intelligently becomes more and more important.This paper selects the latest open source big data framework,applies the big data of public security traffic management,and constructs a data warehouse focusing on the driver’s driving behavior portrait.Combining the driver’s driving behavior portrait with the content-based recommendation algorithm,this paper abstracts the driver’s education recommendation method with the driver’s driving behavior portrait technology as the core.The main contents of this paper are as follows:(1)construct the driver’s driving behavior portrait model: mine the driver’s driving behavior data,and then complete the establishment of the driving behavior data set;based on the driving behavior data set,select the seven dimensions of the driver’s driving behavior labels,and divide the labels of each dimension to determine the driver’s driving behavior standard Finally,the label system is presented in a visual way to get the driver’s driving behavior model.(2)The evaluation model of driver’s driving behavior is established:Based on the driver’s driving behavior portrait model,the evaluation index system of driver’s driving behavior is established;the weight of the evaluation index is determined by the improved entropy weight method AHP algorithm,and the evaluation model of driver’s driving behavior is obtained and verified;based on the evaluation model,the driving behavior is evaluated The safety of human driving behavior is classified.(3)Using content-based recommendation algorithm to recommend driver’s education content: analyzing the characteristics of content-based recommendation algorithm,clarifying the application steps of the algorithm;explaining the source of driver’s education recommendation content;combining the driver’s driving behavior portrait and driver’s safety level,following the steps of contentbased recommendation algorithm,using quantitative quantitative After the plot tests that the driver’s safety level follows the normal distribution,the similarity between the educational recommendation content and the driver’s safety risk tendency is measured by the identity link.The educational recommendation content with the smallest loss function is selected as the optimal recommendation result of driver’s education,and the recommendation result is analyzed and evaluated.In view of the problems existing in the driver education at this stage and the difficulty for learners to grasp the key points in the face of massive educational resources,this paper introduces the user portrait technology into the field of traffic safety education,explores the new application mode of public security big data,and probes into the personalized recommendation technology of the driver’s network education learning resources,so as to further improve the vehicle driver’s traffic safety education system in China In addition,it can provide valuable reference information to improve the driver’s awareness of traffic safety and ensure traffic safety.