高速公路多路段状态联合估计方法
A New Estimation Method for Multi-section Traffic States of Freeway
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摘要: 为了准确估计高速公路多个路段的交通状态,该文通过分析高速公路的路段宏观模型,提出了一种新的多路段误差状态方程。在该模型中,考虑了各路段交通密度、平均速度估计误差的传播。通过该模型,可以采用推广Kalman滤波方法进行多路段的交通状态估计。为了克服多路段状态方程的维数灾、提高计算效率并增强数值稳定性,根据系统矩阵分块的特点,该文采用了平方根滤波方法。仿真计算和实际应用表明,该文方法不仅避免了估计误差的积累效应,而且大大提高了多路段交通状态估计的计算效率。Abstract: To accurately estimate multi-section traffic states of freeway, a new multi-section error state equations are built up. In the new model, error propagations of both the traffic density and the average velocity are considered and the extended Kalman filter is used to estimate all traffic states. To avoid a series of high-dimension problems, a modified weighted Gram-Schmidt orthogonal U-D factorization method is used for the time update and measurement update of the extended Kalman filter to get high numerical stability and computational efficiency. Considered the structure of system matrix, block matrix is used in U-D factorization algorithm. Results of simulation to 100 section states of freeway and actual application show that the new method can be efficiently used to estimate and predict freeway traffic flows.
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