摘要
基于视频检测技术采集得到的北京城市快速路交通特征参数,对城市快速路交通状态进行分析研究。选择车辆行驶速度和速度方差作为城市快速路交通状态分析的决策变量,根据城市快速路交通流特征将交通状态分为自由流、谐动流、同步流和拥堵,利用模糊C均值聚类算法建立交通状态辨识算法,算法经验证表明其有效可行。
Traffic states analysis for urban expressway in Beijing was studied by using data obtained from video detectors. Speed and speed variance were served as input variables for urban traffic states analysis. Traffic states were divided into free flow, coherent-moving flow, synchronized flow, and jam based on traffic flow characters in Beijing urban expressway. An algorithm of traffic states classification was developed by using fuzzy C-means clustering algorithm. The results show that it is efficient and feasible to characterize traffic states.
出处
《交通与计算机》
2008年第4期1-3,共3页
Computer and Communications
基金
国家863计划项目(批准号:2006AA11Z212)
国家“十五”科技攻关专题项目(批准号:2005BA414B16)
教育部科学技术研究重点项目(批准号:106031)
高等学校博士学科点专项科研基金项目(批准号:20070004020)资助
关键词
交通工程
交通状态分析
模糊C均值聚类
城市快速路
traffic engineering
traffic states analysis
fuzzy C-means clustering
urban expressway
