Study on GPS real-time data on-line filtration and complementation
基于GPS实时数据的在线过滤与补遗研究*

Global positioning system(GPS)technique effectively helps to forecast traffic flow accurately in intelligent traffic management system(ITMS) development. But GPS crude data presented random or system error inevitably during traffic data acquisition by GPS.Thus,it was meaningful to research on how to effectively filter GPS crude data for accurate forecasting of traffic flow, which could further help to realize traffic guidance.Based on GPS historical data,set up GPS data filtering model according to the principle of minimization of coefficient of variance,and two complementation models when data missing.And then combined on-line filtration and complementation to be an integrative program based on dymic GPS real-time data. Finally,provided an application based on Hangzhou GPS data.Results show that the filtering model based on simple arithmetic mean is the best alternative, and the quick complementation model based on time series is well fit for the real-time forecasting.