基于Kalman滤波的城市环路交通流短时预测研究

在介绍现有的主要交通流预测方法的基础上，阐述了基于卡尔曼滤波（Kalman）的预测模型及其具体算法。结合城市环路的交通运行特性，构建了基于卡尔曼滤波的交通流短时预测模型，并根据北京市三环路的实际数据对模型进行验证。实证数据表明．所建立的交通流动态实时预测模型的预测效果比较理想，算法的实时性也满足实际预测系统的要求，可应用于交通流预测及交通智能控制。

Short-term Traffic Forecasting of City Ring Road Based on Kalman Filter

In this paper, the main forecasting models for short-term traffic flow are introduced and the Kalman filter forecasting models and its relevant algorithm are clarified in detail. In accordance with the traffic characteristics of urban ring road, a model of dynamic real-time forecasting based on Kalman filter is proposed, and the traffic flow data of Beijing third ring road are explored to test the validity of the model. The experimental results show that the forecasting data obtained by the model coincide with the actual data ideally, and that the algorithm can satisfy the demand of real-time forecasting. Thus, the model can be used in the traffic control as well as in the traffic flow forecasting.