摘要
依托分布式数据库,实时采集GPS浮动车数据,通过聚类分析等算法实现数据优化及异常筛选,从而降低数据传输、存储和计算消耗。结合GIS系统及实例,探索动态特征交通流等优化交通构造的新模型,并仿真实现基于改进平均速度加权算法的交通流状态判定,以及基于改进图论路径选择算法的实时城市道路通行分析,最终通过信息反馈指引车辆在路网中的分布以减轻交通压力。
Based on distributed database, GPS floating car data are collected in real-time. Data optimization and the abnormal screening are achieved with cluster analysis algorithm, to reduce the consumption of data trans- mission, storage and calculation. Combined with GIS systems and real examples, the dynamic traffic flow and models to optimize the traffic structure are explored. The determination of the traffic flow state is achieved with simulations, which is based on the improved weighted average speed algorithm, and the real-time analysis of the urban road traffic is also achieved with simulations, which is based on the improved path selection algorithms of the graph theol7. Consequently, the feedback is obtained to adjust the distribution of vehicles in the road net- work, for easing the traffic pressure.
出处
《测控技术》
CSCD
北大核心
2014年第1期148-152,共5页
Measurement & Control Technology
基金
北京市教委科技计划面上项目(KM201000002002)
关键词
初始聚类中心
交通流
全球定位系统
路径优化
交通调度
initial cluster centers
traffic flow
GPS（ global positioning system）
route optimization
transporta- tion scheduling
