交通运输工程学报
JOURNAL OF TRAFFIC AND TRANSPORTATION ENGINEERING
2004 Vol.4 No.4 P.68-71,83


道路网短期交通流预测方法比较

Short-term traffic flow prediction methods comparison of road networks

史其信  郑为中 

摘 要:介绍了用于短期交通流预测的两大类模型:统计预测算法和人工神经网络模型.对其中各种模型的特征进行了比较,将历史平均模型、求和自回归滑动平均模型(ARIMA)、非参数回归模型、径向基函数(RBF)神经网络模型与贝叶斯组合神经网络模型,应用于一个真实路网的短期流量预测,比较了各模型的预测结果.结果表明,组合神经网络模型预测误差最小,可靠性最高,是一种对短期交通流预测的有效方法.
关键词:交通工程;短期交通流;预测;方法;比较
分类号:U491.14  文献标识码:A

文章编号:1671-1637(2004)04-0068-04

作者简介:史其信(1946-),男,北京人,清华大学教授,从事智能交通系统研究.
作者单位:史其信(清华大学,交通研究所,北京,100084) 
     郑为中(清华大学,交通研究所,北京,100084) 

参考文献:

[1]Ben-Akiva M,Koutsopoulos H N,Mukundan A.A dynamic traffic model system for ATMS/ATIS operations[J].IVHS Journal,1994,2(1):1-19.
[2]Cheslow M,Hatcher S G,Patel V M.An initial evaluation of alternative intelligent vehicle highway systems architecture[R].MITRE Report 92w0000063,MITRE Corporation, 1992.
[3]Davis G A,Nihan N L.Nonparametric regression and short term freeway traffic forecasting[J].Journal of Transportation Engineering,1991,117(2):178-188.
[4]Box G E P,Jenkins G M.Time series analysis:forecasting and control[R].San Francisco:Holden-Day,1977.
[5]Kalman R E.A new approach to linear filtering and prediction problems[J].Journal of Basic Engineering,1960,82(1):35-45.
[6]Okutani I,Stephanedes Y J.Dynamic prediction of traffic volume through Kalman filtering theory[J].Transportation Research,Part B,1984,18(1):1-11.
[7]Altman N S.An introduction to kernel and nearest-neighbor nonparametric regression[J].The American Statistician,1992,46(3):175-185.
[8]Dougherty M S.A review of neural networks applied to transport[J].Transportation Research,Part C,1995,3(4):247-260.
[9]Zhang H J,Ritchie S G,Lo Z P.Macroscopic modeling of freeway traffic using an artificial neural network[J].Transportation Research Record,1997,1588:110-119.
[10]Faghri A,Hua J.Evaluation of artificial neural network applications in transportation engineering[J].Transportation Research Record,1992,1358:71-80.
[11]Dougherty M S,Kirby H C.The use of neural networks to recognize and predict traffic congestion[J].Traffic Engineering and Control,1993,34(6):311-314.
[12]Park B,Messer C J,Urbanik T.Short-term freeway traffic volume forecasting using radial basis function neural network[J].Transportation Research Record,1998,1651:39-47.
[13]Abdulhai B,Porwal H,Recker W.Short-term freeway traffic flow prediction using genetically-optimized time-delay-based neural networks[R].Institute of Transportation Studies,University of California,1998.
[14]Dia H.An object-oriented neural network approach to short-term traffic forecasting[J].European Journal of Operational Research,2001,131(2):253-261.
[15]Van D V,Dougherty M,Watson S.Combining kohonen maps with ARIMA time series models to forecast traffic flow[J].Transportation Research,Part C,1996,4(5):307-318.
[16]Park D,Rilett L R.Forecasting multiple-period freeway link travel times using modular neural networks[J].Transportation Research Record,1998,1617:163-170.
[17]Lee D,Zheng W,Shi Q.Short-term freeway traffic flow prediction using a combined neural network model[A].The 83rd Annual Meeting of TRB[C].Washington D C:TRB,2004.


收稿日期:2004年6月7日

出版日期:2004年12月1日