基于卡尔曼滤波算法的公交车辆行程时间预测  

Forecasting of Travel Time for Public Transport Vehicles Based on the Kalman Filtering Algorithm

作　　者：周文霞[1] 徐建闽[1] 刘正东[1] 

机构地区：[1]华南理工大学交通学院,广东广州510641

出　　处：《交通标准化》2007年第2期174-177,共4页Communications Standardization

基　　金：国家自然科学基金(60064001);广东省自然科学基金(20011707)

摘　　要：通过分析公交车辆的行驶特性,利用卡尔曼滤波算法建立行程时间预测模型,并用该模型预测未来时段的公交车辆路段行程时间。预测结果表明,该方法预测精度较高,可有效地改善公交车辆动态调度效果,提高交通资源利用率,因此该方法具有推广意义。Through analysis on the running characteristics of the public transport vehicles, and then using Kalman filtering algorithm establish the prediction model for the travel time of the public transport vehicles. The result of using this model to predict the travel time in the future based on the detected traffic volume shows that this model has high accuracy, and the method can effectively improve the effect of operation on dynamic dispatching for public transport vehicles and the utilization of the traffic resource. So, the method has much vale to application.

关 键 词：智能交通系统 行程时间 卡尔曼滤波算法 预测 公交车辆 

分 类 号：U491.14[交通运输工程—交通运输规划与管理]