基于车联网大数据分析的实时路况检测系统  

Design of Real-time Road Condition Detection System Based on Big Data Analysis of Vehicle Network

作　　者：张长青[1] 杨楠[1] ZHANG Changqing;YANG Nan(School of Information Engineering,Chang’an University,Xi’an 710064,China)

机构地区：[1]长安大学信息工程学院

出　　处：《电子科技》2019年第8期66-69,74,共5页Electronic Science and Technology

基　　金：国家自然科学基金(61572083)~~

摘　　要：为解决城市交通拥堵问题,给人们提供优质的出行体验,文中提出了基于车联网大数据分析的实时路况检测系统。使用GPS技术对行驶的车辆进行数据采集,通过数据清洗和数据修复得到样本集合,利用改进模糊C均值聚类算法对样本数据进行分析,得出各路段的平均车速,进而得到相应路段的交通状态。测试结果表明,该系统能够准确得获取道路上行驶车辆的交通数据,识别出当前路段的交通状态,从而证明了该系统设计的合理性和正确性。In order to solve the problem of urban traffic congestion and provide people with high quality services, this paper proposed a real-time road condition detection system based on the big data analysis of the Internet of Vehicles. In this paper, GPS technology was used to collect the vehicle data. Sample collection was obtained through data cleaning and data repair. The improved fuzzy C-means clustering algorithm was used to analyze the sample data, and the average speed of each road segment was obtained, and then the traffic of the corresponding road segment was obtained.Tests showed that the system could accurately obtained the traffic data of the vehicles on the road and identify the traffic status of the current road section. These illustrated the rationality and correctness of the system design.

关 键 词：车联网 GPS技术 改进模糊C均值聚类算法 实时路况 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]