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交通拥堵已经成为最严重的城市问题之一,而先进的动态交通分配系统能够用来缓解日益严重的交通拥堵。因此,动态交通分配系统的参数标定问题一直以来都是研究领域内的热点。结合微观交通仿真系统Flow SIM,利用扩展卡尔曼滤波和无迹卡尔曼滤波算法,对动态交通分配系统的离线参数标定问题进行了实例研究。结果表明,两种求解算法都能够很好的实现标定功能,其中无迹卡尔曼滤波优于扩展卡尔曼滤波。研究表明,Flow SIM能够很好的应用于交通系统的参数标定及其相关研究中。
Traffic congestion has become one of the most serious urban problems, and advanced dynamic traffic distribution systems can be used to ease the growing congestion. Therefore, the problem of parameter calibration of dynamic traffic distribution system has always been a hot spot in the research field. Combined with Flow SIM of micro-traffic simulation system, the problem of calibration of off-line parameters of dynamic traffic distribution system is studied by using extended Kalman filter and unscented Kalman filter. The results show that both algorithms can achieve good calibration function, of which the unscented Kalman filter is better than the extended Kalman filter. The research shows that Flow SIM can be well applied to the parameter calibration of traffic system and its related research.