现代信息科技2024，Vol.8Issue(2)：17-20,4.DOI:10.19850/j.cnki.2096-4706.2024.02.005
基于K-means的驾驶行为离散化特征聚类分析与研究
Clustering Analysis and Research on Discretization Characteristics of Driving Behavior Based on K-means
宋月亭 1卢巍1
作者信息
- 1. 昆明文理学院 信息工程学院,云南 昆明 650221
- 折叠
摘要
Abstract
To explore potential feature relationships in continuous driving behavior data,this paper collects continuous driving behavior data of actual transportation vehicles.Firstly,through corresponding preprocessing and feature extraction,obtain continuous driving behavior data of the corresponding vehicle during the corresponding time period;secondly,the K-means clustering method,which has stable performance in both discrete standard datasets and continuous noisy datasets,is used to make discretization clustering processing and analysis on driving behavior data;finally,three representative driving behaviors are obtained:"Steady Driving""Impulsive Driving""Dangerous Driving".In addition,analyzing and studying the various hidden features in driving behavior provides a strong basis for further correlation analysis in data mining based on driving behavior data.关键词
驾驶行为/聚类/离散化/特征分析Key words
driving behavior/clustering/discretization/characteristics analysis分类
信息技术与安全科学引用本文复制引用
宋月亭,卢巍..基于K-means的驾驶行为离散化特征聚类分析与研究[J].现代信息科技,2024,8(2):17-20,4.
