Driving Behavior Analysis Oriented To Big Data Of Internet Of Vehicles

With the continuous development of social economy,motor vehicle ownership continues to increase.Road traffic safety issues are getting worse,Research shows,Traffic accidents are becoming an important cause of human casualties.The driver as the operator of the vehicle,Its daily driving behavior is the most important factor affecting road safety.Studying driving behavior is important to prevent traffic accidents,promote intelligent transportation,and UBI.This article uses data mining to mine and analyze driving data.Perform clustering judgment of driving tendency and construct driving behavior scoring model after abnormal driving behavior recognition,and visually display driving trajectory,daily driving situation,weekly driving situation,monthly driving situation.The main research work of this article is as follows:(1)Data sources and data preprocessing,The format and meaning of the OBD data used in this paper are explained,and preprocessing methods such as washing,coordinate conversion,and distance calculation are introduced in detail.(2)Through the study of driving behavior evaluation indicators,driving safety impact factors are divided into four categories: driving speed,travel conditions,fatigue driving,and fouremergency behavior.And design algorithms to identify specific indicators of abnormal driving behavior such as speeding,fatigue driving times,rapid acceleration,rapid deceleration,sudden braking,and sharp turns.(3)The K-means++ algorithm is used to classify abnormal driving behavior indicators,and the driving behavior is classified into robust,general,and aggressive.Combined with the Entropy Method and the Analytic Hierarchy Process to construct a driving behavior scoring model.(4)Design a driving behavior analysis system,And through Jeeplus,Html,Css,Ajax,MYSQL,Echarts and other development technologies,using day,week,and month as time nodes to show the vehicle’s driving trajectory,driving time,driving mileage,four emergency behavior,daily comprehensive score and Fatigue driving times.