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Evaluation of Factors Affecting Driver’s Behaviors Using Association Rule
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作者 Jingdian Yang 《现代交通(中英文版)》 2020年第1期1-9,共9页
In this paper,association rule mining algorithm is utilized to analyze the correlations of various factors of causing traffic accidents,from which the relationship model of dangerous driving behaviors is established.I... In this paper,association rule mining algorithm is utilized to analyze the correlations of various factors of causing traffic accidents,from which the relationship model of dangerous driving behaviors is established.In this model,the factors and their correlations include:ability of risk control,ability of driving self-confidence,individual characteristics,and incorrect driving operations.By selecting the drivers in the city of Chengdu to be the objects of investigation,a group of valid sample data is obtained.Based on these data,the Support and Confidence for association rules are analyzed.In the analysis,the two stage computing of Apriori algorithm programming is simulated,and from which some important rules are obtained.With these rules,departments of traffic administration can focus on these key factors in their processing of traffic transactions.By the training of drivers’skills and their physical and mental behaviors,the incorrect driving operations can be greatly reduced and the traffic safety can be effectively guaranteed. 展开更多
关键词 driving technique Traffic Safety Big Data Association Rules Apriori Algorithm
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