基于改进Sage滤波器的车辆行程时间预测模型

BRT Vehicles Travel Time Prediction Model Based on Improved Sage Filter

在现代ITS环境中,公交车辆行程时间预测是实现公共交通智能化调度子系统、电子站牌显示子系统及公交信息服务子系统的必要条件。针对Sage滤波器自身的优缺点,提出了一种基于车辆行程时间历史数据流信息的Sage滤波器,并在此基础建立了BRT(Bus Rapid Transit)车辆行程时间预测模型。最后针对2007年6月7日北京市南中轴路大容量快速公交(BRT)线的实际数据进行了对比实验,结果表明,改进的Sage滤波器有效降低了原算法的误差。

In modem ITS environment, vehicles travel time prediction is a necessary condition for the realization of the intelligent public transport scheduling subsystems, station electronic display subsystem and bus information service subsystem. First analyzed Sage filter＇ s advantages and disadvantages, and presented an improved Sage filter based on the historical data samples of vehicle travel time. Then, on the basis of such algorithm, it built BRT vehicle travel time prediction model. Finally used actual data collected from BRT Transport of South Axis Street in Beijing on June 7, 2007 for experiment. The result shows that the improved Sage filter effectively reduce the error of the original algorithm.