本文關(guān)鍵詞：短時(shí)交通流復(fù)雜動(dòng)力學(xué)特性分析及預(yù)測(cè)，，由筆耕文化傳播整理發(fā)布。

摘要

為揭示短時(shí)交通流的內(nèi)在動(dòng)態(tài)特性，利用非線性方法對(duì)交通流混沌特性進(jìn)行識(shí)別，為短時(shí)交通流的預(yù)測(cè)提供基礎(chǔ). 基于混沌理論對(duì)交通流時(shí)間序列進(jìn)行相空間重構(gòu)，利用C-C算法計(jì)算時(shí)間延遲和嵌入維數(shù)，采用Grassberger-Procaccia算法計(jì)算吸引子關(guān)聯(lián)維數(shù)，通過改進(jìn)小數(shù)據(jù)量法計(jì)算最大Lyapunov指數(shù)來判別交通流時(shí)間序列的混沌特性. 針對(duì)局域自適應(yīng)預(yù)測(cè)方法在交通流多步預(yù)測(cè)中預(yù)測(cè)器系數(shù)無法調(diào)節(jié)的問題，提出了交通流多步自適應(yīng)預(yù)測(cè)方法. 通過實(shí)測(cè)數(shù)據(jù)計(jì)算，結(jié)果表明: 2，4和5min三種統(tǒng)計(jì)尺度的交通流時(shí)間序列均具有混沌特性；改進(jìn)的小數(shù)據(jù)量法能夠準(zhǔn)確地計(jì)算出最大Lyapunov指數(shù)；構(gòu)建的交通流多步自適應(yīng)預(yù)測(cè)模型能夠有效地預(yù)測(cè)交通流量的變化. 為智能交通系統(tǒng)誘導(dǎo)和控制提供了依據(jù).

In order to reveal the internal dynamic property of short-term traffic flow, the nonlinear analysis method is used to identify the chaotic property of traffic flow which is the basis for the prediction of the traffic flow time series. Traffic flow time series is reconstructed in phase-space based on chaos theory. The embedding dimension and delay time are first calculated via the C-C method. The correlative dimension of attractor is then calculated with the Grassberger-Procaccia method. The largest Lyapunov exponent of traffic flow set is calculated on the basis of the improved small data set method to verify the presence of the chaos in traffic flow time series. A novel multi-step adaptive prediction method is proposed to solve the problem of adjusting the filter parameters of the chaos local adaptive prediction method during traffic flow multi-step prediction. The traffic flow time series are found to have chaotic properties in different statistical scales of 2, 4, and 5 min and show that the improved small data set method can accurately evaluate the chaotic property for traffic flow time series, and that the multi-step adaptive prediction method is capable of effectively predicting its fluctuation, which provides a useful reference for traffic guidance and control.

收稿日期:2013-07-29

國(guó)家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃（批準(zhǔn)號(hào)：2012CB723303）和國(guó)家自然科學(xué)基金青年科學(xué)基金（批準(zhǔn)號(hào)：51308058）資助的課題.

Project supported by the National Basic Research Program of China (Grant No. 2012CB723303) and the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 51308058).

[中文] 張洪賓, 孫小端, 賀玉龍. 短時(shí)交通流復(fù)雜動(dòng)力學(xué)特性分析及預(yù)測(cè)[J]. 物理學(xué)報(bào), 2014, 63(4): 040505. [英文] Zhang Hong-Bin, Sun Xiao-Duan, He Yu-Long. Analysis and prediction of complex dynamical characteristics of short-term traffic flow[J]. Acta Phys. Sin., 2014, 63(4): 040505.

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  本文關(guān)鍵詞：短時(shí)交通流復(fù)雜動(dòng)力學(xué)特性分析及預(yù)測(cè)，由筆耕文化傳播整理發(fā)布。