分车型的高速公路短时交通流量预测方法研究  

Research on forecast method of short-term freeway mixed traffic flow

作　　者：周桐[1,2] 杨智勇[1,2] 孙棣华[2] 魏方强 

机构地区：[1]重庆工程职业技术学院信息工程学院,重庆400037 [2]重庆大学自动化学院,重庆400044

出　　处：《计算机应用研究》2015年第7期1996-1999,共4页Application Research of Computers

基　　金：中国工程院重点咨询项目(2012-ZX-22);重庆市自然科学基金重点资助项目(cstc2012jj B40002);国家教育部博士点基金资助项目(20120191110047);重庆市教委科学技术研究项目(KJ1403208;KJ1403209)

摘　　要：针对混合交通流中车辆类型的不确定性和随机性,导致了直接对总车流量进行预测时难以获得较高的预测精度问题,提出一种分车型的流量预测方法。依据各种车型的车流量变化规律不同的特点,选用改进的时间序列算法对大型车和拖挂车的流量进行预测,选用二次指数平滑法对小客车和中型车的流量进行预测;然后通过车辆折算系数将各车型的流量预测值进行加权求和,从而得到总车流量预测值;最后利用渝武高速公路上微波车检器的实测数据对提出的预测方法进行了实验验证,并与非参数回归预测方法和卡尔曼滤波预测方法进行了对比。实验结果表明,无论在工作日还是节假日,分车型的流量预测方法均具有更高的预测精度,该结果为进一步提高高速公路管控能力建立了基础。Mixed traffic flows behave uncertainty and random feature, which lead to traditional forecast method has low prediction precision. This paper proposed a new multi-type vehicles forecast method of the short-term freeway traffic flow. Based on the change law of traffic flow of the various type vehicles was different, it used improved time series method to forecast the flow value of large type car and trailer, and used second exponential smoothing method to forecast the flow value of small type car and middle type car, then obtained the prediction value of the mixed traffic flow by weight average method on the basic of vehicle conversion factor. Finally, compared with nonparametric regression model and traditional time series model, the results of experiment shows that the new method can increase the forecasting accuracy of short-term freeway traffic flow on weekdays or holidays, and the results can supply the foundation to further improve the ability of highway management and control.

关 键 词：交通流 短时预测 分车型 时间序列 二次指数平滑 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]