城市道路短期交通流预测VHSSA模型

doi:10.3969/j.issn.1002-0268.2014.05.021

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摘要 A short-term traffic prediction model VHSSA (prediction model based on vertical and horizontal sequence similarity algorithm) is proposed for accurate traffic prediction and dynamic route planning. The model is based on the similarity of vertical and horizontal sequences and analyzes historical traffic time series data and cyclic similarity characteristics of traffic volume in urban roads. The model can overcome the deficiency of the traditional model VSSA (prediction model based on vertical sequence similarity algorithm), which focuses only on vertical cyclic sequence similarity. Complete data are transformed into basic sequences that reflect basic characteristics and fluctuant sequences as well as variation characteristics by utilizing the wavelet transformation function. This transformation can achieve both basic and complete sequence prediction. For complete sequence prediction, the paper corrected the fluctuant sequence based on confidence interval and overlapped it with the basic sequence. Verification experiments are conducted to compare the basic and complete sequences of VHSSA and VSSA. Results show that VHSSA prediction is better than VSSA prediction, and the error probability of VHSSA is lower than that of VSSA; the prediction error can meet the actual requirement.

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	袁健
	范炳全

关键词 ： traffic engineering, VHSSA model, similarity of time cycle, short-term traffic flow prediction, wavelet analysis

Abstract：A short-term traffic prediction model VHSSA (prediction model based on vertical and horizontal sequence similarity algorithm) is proposed for accurate traffic prediction and dynamic route planning. The model is based on the similarity of vertical and horizontal sequences and analyzes historical traffic time series data and cyclic similarity characteristics of traffic volume in urban roads. The model can overcome the deficiency of the traditional model VSSA (prediction model based on vertical sequence similarity algorithm), which focuses only on vertical cyclic sequence similarity. Complete data are transformed into basic sequences that reflect basic characteristics and fluctuant sequences as well as variation characteristics by utilizing the wavelet transformation function. This transformation can achieve both basic and complete sequence prediction. For complete sequence prediction, the paper corrected the fluctuant sequence based on confidence interval and overlapped it with the basic sequence. Verification experiments are conducted to compare the basic and complete sequences of VHSSA and VSSA. Results show that VHSSA prediction is better than VSSA prediction, and the error probability of VHSSA is lower than that of VSSA; the prediction error can meet the actual requirement.

Key words： traffic engineering VHSSA model similarity of time cycle short-term traffic flow prediction wavelet analysis

收稿日期: 2014-07-19

基金资助:Supported by the National Natural Science Foundation of China (No.51008196);the Shanghai Leading Academic Discipline Project (No.S30504)

通讯作者: YUAN Jian, yuanjianwq@163.com E-mail: yuanjianwq@163.com

引用本文:

袁健, 范炳全. 城市道路短期交通流预测VHSSA模型[J]. Journal of Highway and Transportation Research and Development, 2014, 8(4): 90-96.
YUAN Jian, FAN Bing-quan. VHSSA Model for Predicting Short-term Traffic Flow of Urban Road. Journal of Highway and Transportation Research and Development, 2014, 8(4): 90-96.

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http://manu27.magtech.com.cn/Jwk_gljtkj_en/CN/10.3969/j.issn.1002-0268.2014.05.021 或 http://manu27.magtech.com.cn/Jwk_gljtkj_en/CN/Y2014/V8/I4/90

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