相关法自适应滤波在动态行程时间预测中的应用研究

The feasibility analysis of the relevant adaptive filtering in the dynamic travel time prediction

动态行程时间预测是智能交通系统研究的重要内容。为避免卡尔曼滤波中白噪声方差对行程时间预测结果的影响,本文把相关法自适应滤波理论引入到动态行程时间预测中,提出了应用浮动车GPS数据建立相关法自适应滤波模型的方法。预测结果表明,相关法自适应滤波模型的涉动性小,精度满足要求。

Dynamic traffic prediction is important in intelligent transportation system. To avoid the influence of system noise and observation noise, the theory of relevant adaptive filtering was introduced into the dynamic traffic prediction. Therefore the method of building the model was put forward by the float GPS data. The predicting result showed that the fluctuation of relevant adaptive filtering was small and its precision could meet the applied requirement.