交通流预测方法综述

A Summary of Traffic Flow Forecasting Methods

实时交通流预测是智能运输系统研究的一个重要问题。为此,建立了许多预测模型,有历史平均模型、时间序列模型、卡尔曼滤波模型、非参数回归模型、神经网络模型和组合模型等。总结评述现存的各类模型,提出交通流预测研究领域今后可能的发展趋势。

Real-time traffic flow forecasting is one of important issues of ITS research.Some forecasting models including history average,time-series,Kalman filtering,non-parametric regression,neural networks and synthetic model,etc,have been established.Review of these existing forecasting models,and probable frequency of traffic flow forecasting research field is presented..