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针对动态O-D矩阵在全路网中难以直接获得的问题,提出了一种改进的反推模型。首先提出了以最小化观测值与反推值偏差的绝对值之和作为目标函数的路口参数优化模型,并采用遗传算法求解,设计了编解码方案。将反推得到的路口转向流量和流量检测系统中得到的路段流量共同作为已知量,建立了其与全路网动态O-D矩阵的动态关系,增强了系统的静定性。以反推值与最优历史值的偏差作为状态变量,建立了基于Kalman滤波的状态空间模型,并采用扩展Kalman滤波求解。仿真结果表明,模型和算法具有较好的精度、效率和鲁棒性。
Aiming at the problem that the dynamic O-D matrix can not be directly obtained in the whole network, an improved inverse model is proposed. Firstly, the intersection parameter optimization model with the sum of the absolute value of the deviation between the observed value and the estimated value as the objective function is proposed. The genetic algorithm is used to solve the problem and the code scheme is designed. Based on the known traffic volume, the dynamic relation between the inverse traffic flow and the traffic in the flow detection system is established and its dynamic network relationship with the dynamic O-D matrix of the whole road network is established, which enhances the static stability of the system. The state space model based on Kalman filtering is established with the deviation of the inverse value and the optimal historical value as the state variables, and the extended Kalman filter is used to solve the model. The simulation results show that the model and the algorithm have better accuracy, efficiency and robustness.