摘要
分析与评估驾驶行为,建立行车安全评估模型,为智能交通系统建设提供参考。基于车联网数据预处理后,提取驾驶人行为的特征指标,采用主成分分析法对驾驶行为评价指标进行降维分析,形成综合信息特征变量;使用多聚类算法建立基于驾驶行为的行车安全评估模型,经过对比分析,确定合适的驾驶行为安全评价模型,实现对驾驶行为进行归类评价;通过建立反射模型,验证驾驶行为安全评价模型的有效性,为相关部门判断运输车辆驾驶行为是否符合安全规范提供量化分析工具。
Through the analysis and evaluation of driving behavior, a driving safety evaluation model is established to provide reference for the construction of intelligent transportation system.After pre-processing the data based on the Internet of vehicles, the characteristic indicators of driver behavior are extracted, and the dimension of the driving behavior evaluation indicators is reduced by using the principal component analysis method to form the comprehensive information characteristic variables;The multi-clustering algorithm is used to establish a driving behaviour-based driving safety evaluation model, and after comparative analysis, a suitable driving behaviour safety evaluation model is identified to realise the categorisation and evaluation of driving behaviour;the validity of the driving behaviour safety evaluation model is verified through the establishment of a reflection model, and a quantitative analysis tool is provided for the relevant departments to judge whether the driving behaviour of transport vehicles complies with safety norms.
作者
郑美容
Zheng Meirong(Fujian Chuanzheng Communications College,Fuzhou City,Fujian Province 350000)
出处
《黄河科技学院学报》
2023年第2期80-87,共8页
Journal of Huanghe S&T College
基金
教育部科技发展中心产学研创新基金项目(2020ITA03033)。
关键词
车联网
道路运输
驾驶行为
主成分分析
聚类
安全评估模型
vehicle networking
road transport
driving behavior
principal component analysis
clustering
safety assessment model
作者简介
郑美容(1982-),女,湖北鄂州人,副教授,硕士,主要研究方向为计算机模糊信息处理。
