摘要
为了有效提高驾驶人道路安全教育效果,文中建立适用于检测驾驶人事故倾向性的调查问卷及量表,分析了驾驶人在驾驶中的被教育倾向和心理倾向,在无序多分类Logistic回归模型基础上,结合人格倾向测试量表与k-means聚类算法建立了驾驶人的驾驶学习人格划分模型,提出针对不同的驾驶学习人格特点和教育刺激倾向分别设计了适用于教条型、情绪型和冷静型驾驶学习人格的安全驾驶教育方案.
In order to effectively improve the effect of road safety education for drivers,questionnaires and scales suitable for detecting drivers’accident tendency were established.By analyzing the educated tendency and psychological tendency of drivers in driving,based on the unordered multi-classification logistic regression model,the personality classification model of drivers’driving learning was established by combining the personality tendency test scale and K-means clustering algorithm.According to different characteristics of driving learning personality and educational stimulation tendency,the safe driving education schemes suitable for dogmatic,emotional type and calm driving learning personality were designed respectively.
作者
冯思鹤
程国柱
FENG Sihe;CHENG Guozhu(School of Traffic and Transportation,Northeast Forestry University,Harbin 150040,China)
出处
《武汉理工大学学报（交通科学与工程版）》
2022年第2期213-218,共6页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
教育部人文社会科学研究规划基金项目(18YJAZH009)
黑龙江省自然科学基金项目(LH2020G002)。
