1,742 | 121 | 441 |
下载次数 | 被引频次 | 阅读次数 |
实时准确高效的交通流预测是实现交通流诱导和交通控制的关键技术之一,近年来它在智能运输领域受到广泛关注。本文首先介绍了短时交通流的属性和预测要求,接着将现有预测方法分成4类:基于线性理论的方法、基于非线性理论的方法、基于混合理论的方法和基于交通流理论的方法,并且总结评述了现有各种预测模型的优缺点,之后探讨了当今短时交通流预测领域的研究热点,最后指出了其未来研究方向。
Abstract:Real-time,accurate and efficiency short term traffic flow prediction is one of the key technologies to realize traffic flow guidance and traffic control,which has being widely concerned in the domain of ITS during recent years.Firstly,the attributes and requirements of traffic flow were introduced in this paper.Then,the prediction methods were fallen into 4 categories:linear,nonlinear,hybrid,and traffic flow based.The present forecasting models' advantages and disadvantages were summarized and commented at the same time.Subsequently,the hot topics in the field of traffic flow prediction were also discussed.Finally,the future research direction is pointed out.
[1]高慧,赵建玉,贾磊.短时交通流预测方法综述[J].济南大学学报(自然科学版),2008,22(1):88-94.
[2]刘静,关伟.交通流预测方法综述[J].公路交通科技,2004,21(3):82-85.
[3]王进,史其信.短时交通流预测模型综述[J].中国公共安全.学术卷,2005,1(1):92-98。
[4]袁振洲.交通流量短时预测方法研究[D].北京:北京交通大学,2006.
[5]贺国光,李宇,马寿峰.基于数学模型的短时交通流预测方法探讨[J].系统工程理论与实践,2000,20(12):51-56.
[6]姚智胜.基于实时数据的道路网短时交通流预测理论与方法研究[D].北京:北京交通大学,2006.
[7]Smith B.L.,Demetsky M.J.Traffic flow forecasting:Comparison of modeling approaches.Journal of Transportation Engineering[J].American Society of Civil Engineers,1997,123(4),ASCE:261-266.
[8]Lingras Pawan,Sharma Satish C.,Subramanian Gopalakrishnan.Short-term traffic volume forecasts:existing and future research[C].Canadian Society for Civil Engineering-1999Annual Conference.Montreal,Canada:Canadian Society for Civil Engineering,1999:429-438.
[9]Vlahogianni Eleni I.,Golias John C.,Karlaftis Matthew G.Short-term traffic forecasting:Overviewof objectives and methods[J].Transport Reviews,2004,24(5):533-557.
[10]Smith B.L.,Williams B.M.,Oswald R.K.Comparison of parametric and nonparametric models for traffic flow forecasting[J].Transportation Research Part C,2002,10:303-321.
[11]Stephanedes Y.J.,Michalopoulos P.G.,Plum R.A.Improved estimation of traffic flow for real-time control[J].Transportation Research Record795,1981:28-39.
[12]Ahmaed Mohamed S.,Cook Allen R.Analysis of freeway traffic time-series data by using Box-Jenkins technique[J].Transportation Research Record722,1979:l-9.
[13]Nihan N.L.,Holmesland K.O.Use of the box and jenkins time series technique in traffic forecasting[J].Transportation Research Record,1980,9(2):125-143.
[14]Williams B.M,Durvasula P.K.,Brown D.E.Urban freeway traffic flow Prediction:application of seasonal autoregressive integrated moving average and exponential smoothing models[J].Transportation Research Record1644,1998:132-141.
[15]朱顺应,王红,李关寿.路段上短时间区段内交通量预测ARIMA模型[J].重庆交通学院学报,2003,22(l):76-77.
[16]OkutaniI wao,Stephanedes Yorgos J.DynamicPrediction of traffic volume through Kalman filtering theory[J].Transportation Research Part B:Methodological,1984,18(l):l-11.
[17]Ye Zhirui,Zhang Yunlong,Middleton Dan R.Unscented Kalman filter method for speed Estimation using single loop detector data[J].Transportation Research Record1968,2006:117-125.
[18]杨兆升,朱中.基于卡尔曼滤波理论的交通流量实时预测模型[J].中国公路学报,1999,12(3):63-67.
[19]杭明升,杨晓光,彭国雄.基于卡尔曼滤波的高速道路行程时间动态预测[J].同济大学学报,2002,30(9):1068-1072.
[20]Stathopoulos Anthony,Karlaftis Matthew G.A multivariate state space approach for urban traffic flow modeling and prediction[J].Transportation Research part C,2003,11(2):121-135.
[21]Williams Billy M..Multivariate vehicular traffic flow prediction-evaluation of ARIMAX Modeling[J].Transportation Research Record1776,2001:194-200.
[22]Kamarianakis Yiannis,Prastacos Poulicos.Forecasting traffic flow conditions in an urban Network-comparison of multivariate and univariate approaches[J].Transportation Research Record1857,2003:74-84.
[23]Karnarianakis Yiannis,Prastacos Poulicos.Space-time modeling of traffic flow[J].Computers&Geosciences,2005,31(2):119-133.
[24]Smith B.L.,Demetsky M.J.Short-term traffic flow prediction:neural network approach[J].Transportation Research Record1453,1994:98-104.
[25]Doughetry M.S.and Cobbett M.R.Short-term inter-urban traffic forecasts using neural networks[J].International Journal of Forecasting,1997,13(l):21-31.
[26]Park B.,Messer C.J.,Urban II Thomas.Short-term freeway traffic volume forecasting using Radial basis function neural network[J].Transportation Research Record1651,1998:39-41.
[27]朱中,杨兆升.实时交通流量人工神经网络预测模型[J].中国公路学报,1998,11(4):89-92.
[28]Chang E.C-P.Traffic estimation for proactive freeway traffic control[J].Transportation Research Record1679,1999:81-86.
[29]Yin Honghin,Wong S.C.,Xu Jianmin,Wong C.K.Urban traffic flow prediction using a Fuzzy-neural approach[J].Transportation Research Part C,2002,10(2):85-98.
[30]Ishak S.,Kotha P.,Alecsandru C.Optimization of dynamic neural network performance for Short-term traffic prediction[J].Transportation Research Record1836,2003:45-56.
[31]杨立才,贾磊.粗神经网络及其在交通流预测中的应用[J].公路交通科技,2004,21(10):95-98.
[32]Davis Gary A.,Nihan Nancy L.Nonparametric regression and short-term freeway traffic forecasting[J].Journal of Transportation Engineering,1991,117(2):178-188.
[33]Smith Brian L.,Williams Billy M.,Oswald R.Keith.Comparison of parametric and nonparametric models for traffic flow forecasting[J].Transportation Research Part C:Emerging Technologies,2002,10(4):303-321.
[34]Clark Stephen.Traffic prediction using multivariate nonparametric regression[J].Journal of Transportation Engineering,2003,129(2):161-165.
[35]宫晓燕,汤淑明.基于非参数回归的短时交通流量预测与事件检测综合算法[J].中国公路学报,2003,16(l):52-56.
[36]徐启华,杨瑞.支持向量机在交通流量实时预测中的应用[J].公路交通科技,2005,22(12):131-134.
[37]姚智胜,邵春福,高永亮.基于支持向量回归机的交通状态短时预测方法研究[J].北京交通大学学报(自然科学版),2006,30(3):19-22.
[38]杨兆升,王媛,管青.基于支持向量机方法的短时交通流量预测方法[J].吉林大学学报(工学版).2006.36(6):881-884.
[39]张学工.关于统计学习理论与支持向量机[J].自动化学报,2000,26(l):32-42.
[40]Maschavan Der Voort,Dougherty Mark,Watson Susan.Combining kohonen maps with ARIMA time series models to forecast traffic flow[J].Transportation Research Part C,1996,4(5):307-318.
[41]Kirby Howard R.,Watson Susan M.,Dougherty Mark S.Should we use neural networks or statistical models for short-term motorway traffic forecasting[J].International Journal of Forecasting,1997,13:43-50.
[42]Park D.,Rilett L.R.Forecasting multiple-period freeway link travel times using modular neural networks[J].Transportation Research Record,1998,1617:163-170.
[43]Park B.Hybrid neuro-fuzzy application in short-term freeway traffic volume forecasting[J].Transportation Research Record1802,2002:190-196.
[44]贺国光,马寿峰,李宇.基于小波分解与重构的交通流短时预测法[J].系统工程理论与实践,2002,(9):101-106.
[45]李存军,杨儒贵,张家树.基于小波分析的交通流量预测方法[J].计算机应用,2003,23(12):7-8.
[46]杨立才,贾磊,何立琴,等.基于混沌小波网络的交通流预测算法研究[J].山东大学学报(工学版),2005,35(2):46-50.
[47]王晓原,吴磊,张开旺,等.非参数小波算法的交通流预测方法[J].系统工程,2005,23(10):44-47.
[48]杨芳明,朱顺应,基于小波的短时交通流预测[J].重庆交通学院学报,2006,25(3):99-103.
[49]姜桂艳.道路交通状态判别技术与应用[M].北京:人民交通出版社,2004:28-227.
[50]郑为中,史其信.基于贝叶斯组合模型的短期交通量预测研究[J].中国公路学报,2005,18(1):85-89.
[51]聂佩林,余志,何兆成.基于约束卡尔曼滤波的短时交通流量组合预测模型[J].交通运输工程学报,2008,8(5):86-90.
[52]Guo Jianhua.Adaptive estimation and prediction of univariate vehicular Traffic condition series[D].North Carolina State University,2005.
基本信息:
DOI:
中图分类号:U491.112
引用信息:
[1]陆海亭,张宁,黄卫等.短时交通流预测方法研究进展[J],2009,7(04):84-91.
基金信息: