关联交叉口短时交通流可预测性分析及组合预测算法

文中首先根据交叉口交通流参数时间序列的相关性对关联交叉口进行定义,给出关联交叉口短时交通流可预测分析的几个定量指标,以及交通流时间序列最大Lya-punov指数的计算方法;然后提出在短时交通流时间序列的可预测分析基础上,选取一组预测模型并建立基于RBF网络的非线性组合预测模型,提出了关联交叉口短时交通流的组合预测算法;最后对实测短时交通流进行仿真试验,结果表明组合预测方法相对于单项预测方法具有更好的预测性能.

Forecastability Analysis and Combination Forecast Algorithm for Short-Term Traffic Flow of Related Intersections

In this paper,first,the related intersection is defined according to the relationship between traffic flow time series.Then,several forecastability indexes for the short-term traffic flow of related intersections are proposed for the quantitative analysis,and the computation method of the first Lyapunov index to traffic flow time series is described.Moreover,a nonlinear combination forecast model using RBF neural network is set up based on a set of forecast models after the forecastability analysis.Thus,a combination forecast algorithm for the short-term traffic flow of related intersections comes into being.The results of simulation indicate that the proposed method is more efficient than the single forecast method.