基于多项式趋势模型的动态OD矩阵估计

发布时间：2018-03-16 00:37

本文选题：智能交通　切入点：OD矩阵无偏估计　出处：《交通运输系统工程与信息》2016年06期 　论文类型：期刊论文

【摘要】：为了更加精准地描述动态交通流演变过程,得到状态的最优无偏估计,本文基于多项式趋势模型和卡尔曼滤波理论,提出一种实时动态OD矩阵估计的多项式趋势滤波算法.该算法首先将状态变量定义为实际OD流量相对于其历史值的偏差,并将该偏差表述为一个具有滑动趋势的随机演变过程,然后通过建立一个多项式趋势滤波模型实现对动态OD矩阵的估计与预测.最后以一条接近实际路况的高速路网为研究对象进行仿真.大量仿真试验结果表明,本文提出的算法性能优于传统方法,能获得更准确的OD矩阵估计与预测信息.
[Abstract]:In order to describe the evolution of dynamic traffic flow more accurately and obtain the optimal unbiased estimation of the state, this paper is based on polynomial trend model and Kalman filter theory. A polynomial trend filtering algorithm for real-time dynamic OD matrix estimation is proposed. Firstly, the state variable is defined as the deviation of the actual OD flow relative to its historical value, and the deviation is expressed as a random evolution process with sliding trend. Then a polynomial trend filter model is established to estimate and predict the dynamic OD matrix. Finally, a highway network close to the actual road condition is simulated. A large number of simulation results show that, The proposed algorithm has better performance than the traditional method and can obtain more accurate OD matrix estimation and prediction information.
【作者单位】：西华大学能源与动力工程学院;同济大学铁道与城市轨道交通研究院;山东警察学院治安系;
【基金】：国家自然科学基金(71471104) 流体及动力机械教育部重点实验室开放基金(szjj2014-038,szjj2015-026)~~
【分类号】：U491

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