基于FCM聚类法对行驶工况的构建  

Building of Vehicle Driving Cycle Based on FCM Clustering Method

作　　者：杜勇[1] 相臣 马洪龙[1] 

机构地区：[1]合肥工业大学交通运输工程学院,安徽省合肥市230009 [2]合肥工业大学机械与汽车工程学院,安徽省合肥市230009

出　　处：《农业装备与车辆工程》2014年第9期42-45,共4页Agricultural Equipment & Vehicle Engineering

摘　　要：主要研究FCM聚类法在车辆行驶工况中的应用。通过对合肥市典型道路的试验,获取大量的实验数据,划分为多个运动学片段,并运用多元统计理论方法及Matlab对数据进行分析和处理,引入11个表征汽车行驶特性的特征参数进行研究。运用主成分分析这种数理统计理论,同时通过FCM聚类方法,对合肥市道路行驶工况进行分析与仿真,拟合出能够代表合肥市的代表性工况。通过对实验数据的分析表明,拟合的行驶工况有利地反映了合肥的汽车保有量、城市结构、交通流分布、驾驶行为习惯及道路特征等的情况。The application of FCM clustering method in vehicle driving cycle is mainly studied. By typical road test in Hefei City, a lot of experimental data is got and divided into multiple fragments kinematics. Multivariate statistical theory and Matlab are used for data analysis and processing, 11 characteristic parameters are introduced for study. Principal component analysis theory and mathematical statistics are used to Hefei road conditions for analysis and simulation, fitting representative to represent Hefei conditions. The analysis of experimental data shows that fitting driving conditions reflect car parc, urban construction, traffic flow distribution, driving habits and road characteristics in Hefei City.

关 键 词：数据采集 行驶工况 主成分分析 聚类分析 

分 类 号：U491.2[交通运输工程—交通运输规划与管理]